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Determining date or time Feature Class was created in File Geodatabase?

Determining date or time Feature Class was created in File Geodatabase?


I had a script running at the office over the last 5 days and tried to remote on unsuccessfully since the 3rd day. I got here and it appears there was a power outage. Is there a way to find out the time a feature class was created? That would very much help me figure out how long the script took to run.


Actually, if I open the recent History .xml file,

C:UsersUSERNAMEAppDataRoamingESRIDesktop10.1ArcToolboxHistory

The most recent will have parameters & env. settings & time. It gives all the geoprocessing tools used (if w/in arcpy) and all the settings and environment settings and time started and finished.


Prepare your data in ArcGIS Desktop

A new Collector app is available on Android and iOS. For help with the new app, see Prepare your layer.

In this exercise, you'll build a copy of the Damage Assessments feature layer. You'll create a geodatabase in ArcMap, create domains, add a feature class, and add the correct field types and configure them to meet the requirements of the data collection form. Once you have configured the information model, you will build a map in ArcMap and publish a feature service to your organization. In the next exercise in this series, the service will be leveraged as a layer in a map and used by your mobile workforce to collect information in the field.

Completing this exercise requires an ArcGIS organizational account with the ability to publish hosted feature services. This includes publishers and administrators.


Geospatial Data

This spreadsheet lists all of the post fire aerial photography projects flown by the Southwestern Region. With projects dating back to 1972, this imagery serves as an important record of fire extent and damage. Geospatial features describing the photo centers and footprints for these projects can be accessed in the Historical Aerial Photography feature service above, and the imagery can be requested from the Aerial Photography Field Office

Constructed Features (Southwestern Region)

Ecological Response Units (Southwestern Region)

Ecological Response Units (Version 5.3)

Ecological Response Units - The purpose of this feature class is to be an ecosystem mapping tool across all of Arizona and New Mexico.

Ecological Response Units (ERUs) facilitate landscape analyses and planning. The framework represents all major ecosystem types of the southwest region, and represents a stratification of biophysical themes. ERUs are used to define historic/reference conditions within a mapping unit by integrating site potential (soil physical and chemical properties, geology, geomorphology, aspect, slope, climate variables, and geographic location), fire regime (historic and contemporary), neighboring vegetation communities, and seral state sequence.

The shapefile data is tiled into four tiles: Arizona North, Arizona South, New Mexico North, New Mexico South. View a sample image of the tile locations

Climate Change Vulnerability Assessment

Forest Health - Insect Disease (Southwestern Region)

Forest Orders (Southwestern Region)

Posted as a map service Daily

Forest order map. Forest orders are areas of the forest where entry or use is restricted for safety and or resource protection.

Title 36, Code of Federal Regulations, Chapter II, Subpart B, may close an area to entry or may restrict the use of an area by applying any or all of the prohibitions authorized by the code of regulations.

Forest Planning (Individual Forest)

Apache Sitgreaves Management Area 2015

The purpose of this feature class is to depict and label a spatially contiguous land area identified within a planning area (the administrative boundary). The feature class will be used to provide planning information for any necessary analysis.

General Terrestrial Ecosystem Survey (Southwestern Region)

General Terrestrial Ecosystem Survey

General Terrestrial Ecosystem Survey - (United States Forest Service Southwest Region)

The data set is composed of polygon features denoting soil condition, erosion hazard, revegetation potential and vegetation cover. The scale is 1:250000. This data set was created for the USFS General Terrestrial Ecosystem Survey. It's purpose is to delineate the locations and areas of varying GTES characteristics.

Invasive (Southwestern Region)

The Invasive Plants, Invertebrate, Pathogen, and Vertebrate (Invasive) feature class contains all the Invasive Infestation polygons collected by the National Invasive Plant Inventory Protocol. Includes most recent as well as historic observations. Includes Site ID, Plant code, status etc. for the infesting species, date, area and other basic data.

This dataset at this time is mostly Plants.

Land (Southwestern Region)

Other National Designated Area

PLSS - Public Land Survey System

Section - An area defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township.

Township - An area defined by the Public Lands Survey System grid that is referenced by its tier and range numbers, and is normally a rectangle approximately 6 miles on a side with boundaries conforming to meridians and parallels.

Special Interest Management Area

Surface Ownership Dissolve

Recreation (Southwestern Region)

Recreation Site Point and Recreation Site Polygon

Depicts developed recreation sites, trailhead, fishing, picnic area, campground

Recreation Opportunity Settings

Depicts the spatial location of areas showing the type of Recreation Opportunity Settings that exist (Existing Condition) either without over-snow travel or uses (summer season) or year-round when no seasonal variation exists.

RMU - Range Management Units (Southwestern Region)

RMU_Unit, RMU_SubUnit, RMU_WHB

RMU_Unit (Allotments) - Depicts the gross grazing management area (allotment) boundaries, range general resource area boundaries, and wild horse territories boundaries.

RMU_SubUnit (Pastures) - Depicts grazing implementation monitoring area boundaries within each Pasture.

RMU_WHB (Wild Horse and Burro Areas) - Depicts Wild Horse and Burro Areas

Terrestrial Ecological Unit Inventory (Southwestern Region)

TEU, Terrestrial Ecological Unit

Terrestrial Ecological Unit Inventory. Potential Natural Vegetation and Soil Class. The Land Type Map Component Vegetation, Soil, Geology (LT_MapCompVegSoilGeology) feature class has classification information for Vegetation (potential and existing), soil, geology, geomorphology, ecological types and miscellaneous classifications. Classifications are displayed in order of dominance for each type (PNV, Soil, etc) along with the percentage based on aggregating component actual percents (null values are treated as 0). If there are multiple classifications per component, that component percent is divided by the number of classifications that are attached to that component, and then that percent is aggregated up to the map unit. Map Symbol Comp Pct Vegetation Class 22 1 45 VegClass1 22 2 30 Vegclass2 22 3 25 Vegclass1 Aggregated Vegetation class Vegclass1 - 70 pct Vegclass2 - 30 pct

Transportation (Southwestern Region)

MVUM (Motor Vehicle Use Map) Data

Motorized Vehicle Use Maps (MVUM) Data, These MVUM maps are valid in as of the publication date which have been designated as open to motorized vehicles under the Travel Management Rule (36 CFR 212, Subpart B, Designation of Roads, Trails, and Areas for Motor Vehicle Use). Routes not designated for motor vehicle use (such as non-motorized trails, single-purpose roads and trails, unauthorized roads and trails, and temporary roads and trails) are not included.

Specific types of motorized vehicles allowed on the designated roads/trails and their seasons of use. These data represent the following symbol classes of roads and trails: Open to All Vehicles, Open to Highway Legal Vehicles and Roads with Seasonal Designations.

MVUM (Motor Vehicle Use Map) Downloadable Maps

Vegetation (Southwestern Region)

INREV (OSU Institute Natural Resources Existing Vegetation)

Existing vegetation mapping provides basic information on the current condition of vegetation structure and composition. Beginning in 2004 the Southwestern Region developed Mid-Scale Existing Vegetation Mapping on all National Forests and Grasslands (Mellin et al. 2008). The Southwestern Region collaborated with OSU&rsquos Institute of Natural Resources to develop new mid-scale mapping with the INREV project. Mid-scale mapping is compliant with agency technical guidance for existing vegetation (Brohman and Bryant 2005, Nelson et al. 2015). For business needs of natural resource organizations, existing vegetation mapping represents an important component in an overall inventory, monitoring, and analysis framework.

Mid-Scale Existing Vegetation Canopy Cover Map Units

Canopy cover map units of trees for tree life form polygons or shrubs for shrub life form polygons. The Southwestern Region existing vegetation mapping program (R3-EVP) is intended to meet the needs of forest plan revisions, national fire planning, and other landscape-level analyses by providing a consistent, region-wide dataset that depicts existing vegetation at the mid-scale level.

Mid-Scale Existing Vegetation Dominance Type Map Units

Polygons of dominance type in the map units. Dominance types are defined by the species or genera of greatest abundance, usually of the uppermost canopy of the plant community. The Southwestern Region existing vegetation mapping program (R3-EVP) is intended to meet the needs of forest plan revisions, national fire planning, and other landscape-level analyses by providing a consistent, region-wide dataset that depicts existing vegetation at the mid-scale level.

Mid-Scale Existing Vegetation Life Form

Polygons representing the dominant life form. The Southwestern Region existing vegetation mapping program (R3-EVP) is intended to meet the needs of forest plan revisions, national fire planning, and other landscape-level analyses by providing a consistent, region-wide dataset that depicts existing vegetation at the mid-scale level.

Mid-Scale Existing Vegetation Size Map Units

Diameter class map unit of dominant trees for tree life form polygons or shrub height class for shrub life form polygons. The Southwestern Region existing vegetation mapping program (R3-EVP) is intended to meet the needs of forest plan revisions, national fire planning, and other landscape-level analyses by providing a consistent, region-wide dataset that depicts existing vegetation at the mid-scale level.

Riparian Existing Vegetation​

    (10x) 16.8 MB (10x) 8.9 MB (10x) 10.0 MB (10x) 6.5 MB (10x) 8.8 MB (10x) 25.1 MB (10x) 5.5 MB (10x) 3.3 MB (10x) 10.9 MB (10x) 8.4 MB (10x) 16.6 MB

This feature class contains attribute information from four different vegetation maps (Lifeform Type, Leaf Retention Type, Canopy Cover, and Size Class) and statistics on NDVI and lidar.

For this project canopy height and cover data were derived from lidar data found within the Prescott National Forest and used in mapping tree size. The lidar and other predictor variables from imagery were used to segment the study area into objects with similar characteristics for use in vegetation mapping. Vegetation mapping attributes were then added to each segment as classified by Random Decision Forest classifier. A 20 meter buffer from the RMAP boundary was created as a study area. Two final products are presented, this product that has been clipped to the RMAP boundary with map features designed to meet a minimum size of .25 hectares and a second that includes the 20 meter buffer and has no minimum map unit.

Riparian Potential Vegetation​

Riparian Potential Vegetation - Potential Riparian plant communities across Forests and Grasslands of the US Forest Service Southwestern Region. Riparian Potential Vegetation is derived from the Ecological Response Units (ERUs) layer.

Ecological Response Units (ERUs) facilitate landscape analyses and planning. The framework represents all major ecosystem types of the southwest region, and represents a stratification of biophysical themes. ERUs are used to define historic/reference conditions within a mapping unit by integrating site potential (soil physical and chemical properties, geology, geomorphology, aspect, slope, climate variables, and geographic location), fire regime (historic and contemporary), neighboring vegetation communities, and serial state sequence.

Wild Land Fire Perimeters (Southwestern Region)

Fire History Occurrences (Points) and Perimeters (Polygons)

The FireOccurrence point layer represents ignition points from which individual wildland fires started. Data are maintained at the Forest/District level, or their equivalent, to track the occurrence and the origin of individual wildland fires. Records in FireOccurrence include historical fire point records from a variety of sources. Since 1986, FIRESTAT, the Fire Statistics System computer application, has been the authoritative data source for all wildland fire occurrences on National Forest System Lands or National Forest-Protected Lands. FIRESTAT is used by the USFS to enter and maintain information from the Individual Wildland Fire Report (FS-5100-29).

The FirePerimeter polygon layer represents final mapped wildland fire perimeters. Incidents of 10 acres or greater in size are expected. Incidents smaller than 10 acres in size may also be included. Data are maintained at the Forest/District level, or their equivalent, to track the area affected by wildland fire. Records in FirePerimeter include perimeters for wildland fires that have corresponding records in FIRESTAT, which is the authoritative data source for all wildland fire reports. FIRESTAT, the Fire Statistics System computer application, required by the USFS for all wildland fire occurrences on National Forest System Lands or National Forest-protected lands, is used to enter and maintain information from the Individual Fire Report (FS-5100-29).

Wildfire Perimeters > 100 acres

Wildland Urban Interface (WUI) Areas (Southwestern Region)

Wildland Urban Interface (WUI) Areas Adjacent to Forest Service Lands in the South Western Region of the Forest Service

Wildlife (Southwestern Region)

Legacy Forest Datasets

Links to the legacy GIS dataset on the individual Forest web pages. We are in the process of updating our website and transferring data to this Regional page from the Forest pages.


Download National Datasets

Requests for KML/KMZ output
The Enterprise Data Warehouse Team tested exporting out to KML/KMZ files as a deliverable and due to the complexity and size of the datasets this has been unsuccessful. To obtain a KML file for any EDW dataset, go to the Geospatial Data Discovery Tool and search for the dataset. An option to download to KML is available from that website. If you have questions, contact: [email protected]

Activity Range Vegetation Improvement

Date of last refresh: Jun 23, 2021

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The RngVegImprove feature class depicts the area planned and accomplished areas treated as a part of the Range Vegetation Improvement program of work, funded through the budget allocation process and reported through the Forest Service Activity Tracking System (FACTS) database within the Natural Resource Manager (NRM) suite of

Activity Silviculture Timber Stand Improvement

Date of last refresh: Jun 23, 2021

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The SilvTSI (Silviculture Timber Stand Improvement) feature class represents activities associated with the following performance measure: Forest Vegetation Improved (Release, Weeding, and Cleaning, Precommercial Thinning, Pruning and Fertilization). The Activities data set portrays the areas where activities are accomplished

Activity SilvicultureReforestation

Date of last refresh: Jun 23, 2021

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The SilvReforestation feature class represents activities associated with the following performance measure: Forest Vegetation Establishment (Planting, Seeding, Site Preparation for Natural Regeneration and Certification of Natural Regeneration without Site Preparation). The Activities data set portrays the areas where

Hazardous Fuel Treatment Reduction: Line

Date of last refresh: Jun 23, 2021

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HazFuelTrt_LN (Hazardous Fuel Treatments - Line) represents activities of hazardous fuel treatment reduction. All accomplishments toward the unified hazardous fuels reduction target must meet the following definition: "Vegetative manipulation designed to create and maintain resilient and sustainable landscapes, including

Hazardous Fuel Treatment Reduction: Polygon

Date of last refresh: Jun 23, 2021

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HazFuelTrt_PL (Hazardous Fuel Treatments - Polygon) represents activities of hazardous fuel treatment reduction that are polygons. All accomplishments toward the unified hazardous fuels reduction target must meet the following definition: "Vegetative manipulation designed to create and maintain resilient and sustainable

Timber Harvests

Date of last refresh: Jun 23, 2021

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The TimeberHarvest feature class depicts the area planned and accomplished acres treated as a part of the Timber Harvest program of work, funded through the budget allocation process and reported through the Forest Service Activity Tracking System (FACTS) database within the Natural Resource Manager (NRM) suite of

Activity Monarch Butterfly Habitat Restoration (MBHR)

Date of last refresh: Oct 29, 2020

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Activities meeting the Monarch Butterfly Habitat Restoration initiative are a subset of activities that benefit native plants, and in doing so, benefit pollinators. Activities such as thinning, prescribed fire and other methods of fuel removal, treating invasive species and acres of native plantings can benefit Monarchs.

Collaborative Forest Landscape Restoration Program: Line

Date of last refresh: Jun 23, 2021

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CFLRP_LN represents Collaborative Forest Landscape Restoration (CFLR) Program project activities in polyline vector format. Also included are other High Priority Restoration projects that are funded outside of CFLR. It is important to note that this layer does not contain all of the approved project activities. Instead, these

Collaborative Forest Landscape Restoration Program: Point

Date of last refresh: Jun 23, 2021

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CFLRP_PL represents Collaborative Forest Landscape Restoration (CFLR) Program project activities in the format of a polygon vector. Also included are other High Priority Restoration projects that are funded outside of CFLR. It is important to note that this layer does not contain all of the approved project activities.

Collaborative Forest Landscape Restoration Program: Polygon

Date of last refresh: Jun 23, 2021

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CFLRP_PL represents Collaborative Forest Landscape Restoration (CFLR) Program project activities in the format of a polygon vector. Also included are other High Priority Restoration projects that are funded outside of CFLR. It is important to note that this layer does not contain all of the approved project activities.

Integrated Resource Restoration (IRR): Line

Date of last refresh: Jun 23, 2021

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IRR_LN (Integrated Resource Restoration (IRR): Line) depicts the location of activities funded through the NFRR (National Forest Resource Restoration) Budget Line Item and reported through the FACTS (Forest Service Activity Tracking System) database. The activities fall under number of acres treated annually to sustain or

Integrated Resource Restoration (IRR): Point

Date of last refresh: Jun 23, 2021

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Activity_IRR_PT (Integrated Resource Restoration (IRR): Line) depicts the location of activities funded through the NFRR (National Budget Line Item and reported through the FACTS (Forest Service Activity Tracking System) database. The activities fall under number of acres treated annually to sustain or restore watershed

Integrated Resource Restoration (IRR): Polygon

Date of last refresh: Jun 23, 2021

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IRR_PL (Integrated Resource Restoration (IRR): Polygon) depicts the location of activities funded through the NFRR (National Budget Line Item and reported through the FACTS database. The activities fall under number of acres treated annually to sustain or restore watershed function: acres of forestlands treated using timber

Stewardship Contracting: Line

Date of last refresh: Jun 23, 2021

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StwrdCntrctng_LN (Stewardship Contracting: Line) depicts the linear activities within Stewardship Contracting Project Boundary. Activities are implemented through stewardship contracts or agreements and are self-reported by Forest Service Units through the FACTS (Forest Service Activity Tracking System) database. This feature

Stewardship Contracting: Point

Date of last refresh: Jun 23, 2021

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StwrdshpCntrctng_PT (Stewardship Contracting: Point) depicts the locations of activities within Stewardship Contracting Project Boundary. Activities are implemented through stewardship contracts or agreements and are self-reported by Forest Service Units through the FACTS Service Activity Tracking System) database. This

Stewardship Contracting: Polygon

Date of last refresh: Jun 23, 2021

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map service
StwrdshpCntrctng_PL (Stewardship Contracting: Polygon) depicts the area of activities within Stewardship Contracting Project Boundary. Activities are implemented through stewardship contracts or agreements and are self-reported by Forest Service Units through the FACTS Service Activity Tracking System) database. This feature

Western Bark Beetle Strategy: Line

Date of last refresh: Jun 23, 2021

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WBBS_LN depicts the area of activities to implement the Western Bark Beetle Strategy. Activities were self-reported by field units, and center around three main objectives: increasing safety to ensure that people and community infrastructure are protected from the hazards of falling bark beetle-killed trees and elevated

Western Bark Beetle Strategy: Point

Date of last refresh: Jun 23, 2021

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map service
WBBS_PT depicts the location of activities to implement the Western Bark Beetle Strategy. Activities were self-reported by field units, and center around three main objectives: increasing safety to ensure that people and community infrastructure are protected from the hazards of falling bark beetle-killed trees and elevated

Western Bark Beetle Strategy: Polygon

Date of last refresh: Jun 23, 2021

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map service
WBBS_PL depicts the area of activities to implement the Western Bark Beetle Strategy. Activities were self-reported by field units, and center around three main objectives: increasing safety to ensure that people and community infrastructure are protected from the hazards of falling bark beetle-killed trees and elevated

Activity Knutson-Vandenberg

Date of last refresh: Jun 23, 2021

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The Knutson-Vandenberg Act (K-V) of June 9, 1930 (16 U.S.C. 576-576b 46 Stat. 527), as amended by the National Forest Management Act of October 22, 1976 (16 U.S.C. 1600 et seq.) authorized collection of deposits from federal timber purchasers for prompt and efficient use of funds to reestablish, protect, and improve the

Brush Disposal Funded Activities

Date of last refresh: Jun 23, 2021

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The Brush Disposal Program (BD) was established in 1916. It requires all purchasers of National Forest timber to make deposits to the United States for the estimated cost of disposing of brush and other unwanted debris (slash) resulting from its cutting operations on timber sale contracts, stewardship contracts and permits,

Administrative Forest Boundaries

Date of last refresh: Jun 23, 2021

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An area encompassing all the National Forest System lands administered by an administrative unit. The area encompasses private lands, other governmental agency lands, and may contain National Forest System lands within the proclaimed boundaries of another administrative unit. All National Forest System lands fall within one

Forest Service Regional Boundaries

Date of last refresh: Jun 23, 2021

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An area encompassing all the National Forest System lands administered by a Region. The area encompasses private lands, other governmental agency lands. All National Forest System lands fall within one and only one Administrative Region Area.

Ranger District Boundaries

Date of last refresh: Jun 23, 2021

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A depiction of the boundary that encompasses a Ranger District.

Ecological Provinces

Date of last refresh: May 4, 2017

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The EcoMap Provinces feature class contains ecological province polygons attributed with names and descriptions. The EcomapSections 2007 data set describes the ecological sections within the conterminous United States. It contains regional geographic delineations for analysis of ecological relationships across ecological

Ecological Section: Kuchler Mapping

Date of last refresh: Jul 1, 2019

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The Potential Natural Vegetation (PNV) Kuchler Sections feature class contains polygons for ecological sections, attributed with Kuchler's PNV type to show the relationships between ECOMAP 2007 and Kuchler's (1975, second edition) map of potential natural vegetation. A list of Kuchler's PNV groups can be accessed at

Ecological Section: Potential Natural Vegetation

Date of last refresh: May 4, 2017

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The Potential Natural Vegetation (PNV) 2000 feature class contains ecological section polygons attributed with PNV group to show the relationships between ECOMAP 2007 and potential natural vegetation groups developed through coarse-scale mapping for wildland fire and fuel management (USDA-FS, 2002). The EcomapSections 2007

Ecological Section: Soils

Date of last refresh: May 4, 2017

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The Soil Section feature class contains ecological section polygons attributed with soil characteristics to show relationships between ECOMAP 2007 and soil data from STATSGO, 2005. The EcomapSections 2007 data set describes the ecological sections within the conterminous United States. It contains regional geographic

Ecological Sections

Date of last refresh: May 4, 2017

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map service
The Ecomap Sections feature class contains ecological section polygons attributed with section names and descriptions. The EcomapSections 2007 data set describes the ecological sections within the conterminous United States. It contains regional geographic delineations for analysis of ecological relationships across ecological

Ecological Sections by Climate

Date of last refresh: May 4, 2017

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map service
The Climate Sections feature class contains ecological section polygons attributed with climate information to show the relationships between ECOMAP 2007 and various climate data from the PRISM climate mapping system. The EcomapSections 2007 data set describes the ecological sections within the conterminous United States. It

Ecological Sections: Landcover

Date of last refresh: May 4, 2017

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The National Land Cover Sections feature class contains ecological section polygons attributed with land cover types to show the relationships between ECOMAP 2007 and National Landcover mapping (USGS, 1992). The EcomapSections 2007 data set describes the ecological sections within the conterminous United States. It contains

Fenneman-Johnson Physiographic Sections

Date of last refresh: May 4, 2017

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map service
The Fenneman-Johnson Physiographic Sections feature class contains ecological section polygons attributed with physiographic types to show the relationships between ECOMAP 2007 and Fenneman-Johnson physiographic mapping from USGS (1946). The EcomapSections 2007 data set contains polygons for ecological sections within the

Ecological Subsection: Kuchler Mapping

Date of last refresh: Jul 1, 2019

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map service
The Potential Natural Vegetation (PNV) Kuchler Subsections feature class contains polygons for ecological subsections, attributed with Kuchler's PNV type to show the relationships between ECOMAP 2007 and Kuchler's (1975, second edition) map of potential natural vegetation. A list of Kuchler's PNV groups can be accessed at

Ecological Subsection: Potential Natural Vegetation

Date of last refresh: May 4, 2017

metadata
map service
The Potential Natural Vegetation (PNV) 2000 feature class contains ecological subsection polygons attributed with PNV group to show the relationships between ECOMAP 2007 and potential natural vegetation groups developed through coarse-scale mapping for wildland fire and fuel management (USDA-FS, 2002). The EcomapSubsections

Ecological Subsection: Soils

Date of last refresh: May 4, 2017

metadata
map service
The Soil Subsections feature class contains ecological subsection polygons attributed with soil characteristics to show relationships between ECOMAP 2007 and soil data from STATSGO, 2005. The EcomapSubsections 2007 data set describes the ecological sections within the conterminous United States. It contains regional geographic

Ecological Subsections

Date of last refresh: May 4, 2017

metadata
map service
The Ecomap Subsections feature class contains ecological subsection polygons attributed with subsection names and descriptions. The EcomapSubsections 2007 data set describes the ecological subsections within the conterminous United States. It contains regional geographic delineations for analysis of ecological relationships

Ecological Subsections by Climate

Date of last refresh: May 4, 2017

metadata
map service
The Climate Subsections feature class contains ecological subsection polygons attributed with climate information to show the relationships between ECOMAP 2007 and various climate data from the PRISM climate mapping system. The EcomapSubections 2007 data set describes the ecological subsections within the conterminous United

Ecological Subsections: Landcover

Date of last refresh: May 4, 2017

metadata
map service
The National Land Cover Subsections feature class contains ecological subsection polygons attributed with land cover types to show the relationships between ECOMAP 2007 and National Landcover mapping (USGS, 1992). The EcomapSubsections 2007 data set describes the ecological subsections within the conterminous United States. It

Fenneman-Johnson Physiographic Subsections

Date of last refresh: May 4, 2017

metadata
map service
The Fenneman-Johnson Physiographic Subsections feature class contains ecological subsection polygons attributed with physiographic types to show the relationships between ECOMAP 2007 and Fenneman-Johnson physiographic mapping from USGS (1946). The EcomapSubsections 2007 data set contains polygons for ecological subsections

Healthy Forest Restoration Act Activities

Date of last refresh: May 22, 2017

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The Healthy Forest Restoration Act feature class depicts National Forest System (NFS) Lands within 37 States designated under section 602 and 603 of the Healthy Forest Restoration Act. Designated areas were selected based on a set of eligibility criteria regarding forest health and do not include any areas coinciding with

Healthy Forest Restoration Act Activities 2015

Date of last refresh: May 22, 2017

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The Healthy Forest Restoration Act feature class depicts National Forest System (NFS) Lands within 37 States designated under section 602 and 603 of the Healthy Forest Restoration Act. Designated areas were selected based on a set of eligibility criteria regarding forest health and do not include any areas coinciding with

Healthy Forest Restoration Act Activities 2016

Date of last refresh: May 22, 2017

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The Healthy Forest Restoration Act feature class depicts National Forest System (NFS) Lands within 37 States designated under section 602 and 603 of the Healthy Forest Restoration Act. Designated areas were selected based on a set of eligibility criteria regarding forest health and do not include any areas coinciding with

Collaborative Forest Landscape Restoration Project Boundaries

Date of last refresh: Jun 23, 2021

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Depicts the boundaries for the Collaborative Forest Landscape Restoration (CFLR). Three of these projects were formerly "High Priority Restoration Projects" (HPRP): Northeastern Washington Vision 2020 Ozark Highlands and Longleaf Pine Ecosystem Restoration and Hazardous Fuels Reduction. These projects received CFLR

Current Invasive Plants

Date of last refresh: Jun 23, 2021

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The Current Invasive Plants (InvasivePlantCurrent) feature class contains only the most recent or latest invasive Plant Infestation polygons collected by the National Invasive Plant Inventory Protocol. Includes most recent and excludes historic observations. Includes Site ID, Plant code, status etc. for the infesting species,

Forest Service developed sites subject to regulation

Date of last refresh: Jun 23, 2021

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An area having regulations and/or restrictions related to existing buildings, structures, or resource activities such as a constructed fuel breaks.

Geopolitical Units adjusted within Administrative Forest Boundaries

Date of last refresh: Jun 23, 2021

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This dataset includes States, Counties or Boroughs, Congressional Districts, Alaska Recording Districts, County Subdivisions, and Places boundaries that are derived from the latest official Census Bureau and Alaska Department of Natural Resources datasets. Features within Forest Service Administrative Forest boundaries may

Hazardous sites

Date of last refresh: Jun 23, 2021

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Polygons representing Forest Service land areas with a regulated use specification authorized by the Comprehensive Environmental Response, Compensation, and Liability Act of 1980. These areas generally contain hazardous waste considerations.

Land Management Planning Unit (LMPU)

Date of last refresh: Jun 23, 2021

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The Land Management Planning Unit (LMPU) feature class displays the plan revision status for FS land management planning units, their boundaries, FS Region, planning phase milestone and associated date, and link to a related planning website. A land management plan provides a framework for integrated resource management and

Land Utilization

Date of last refresh: Jun 23, 2021

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A unit designated by the Secretary of Agriculture for conservation and utilization under Title III of the Bankhead-Jones Farm Tenant Act.

Mineral Rights

Date of last refresh: Jun 23, 2021

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An area depicting ownership parcels of the subsurface estate, representing mineral rights it is collected only if the subsurface estate is different than the overlying surface estate.

National Forest Lands with Nationally Designated Management or Use Limitations

Date of last refresh: Jun 23, 2021

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A boundary within which National Forest System land parcels have managment or use limits placed on them by legal authority. Examples are: National Recreation Area, National Monument, and National Game Refuge.

National Forest Lands with Nationally Designated Management or Use Limitations: Legal Status

Date of last refresh: Jun 23, 2021

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A boundary of an area designation within which National Forest System land parcels have management or use limits placed on them by legal authority above the Agency level (e.g. Congress and/or President). Areas that have been designated by Congress, Executive Order, Presidential Proclamation, or an Executive branch Department,

National Forest System Land Units

Date of last refresh: Jun 23, 2021

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An NFS Land Unit is nationally significant classification of Federally owned forest, range, and related lands that are administered by the USDA Forest Service or designated for administration through the Forest Service. NFS Land Unit types include proclaimed national forest, purchase unit, national grassland, land utilization

National Grassland Units

Date of last refresh: Jun 23, 2021

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A National Grassland unit designated by the Secretary of Agriculture and permanently held by the Department of Agriculture under Title III of the Bankhead-Jones Farm Tenant Act.

National Wild and Scenic River Lines

Date of last refresh: Jun 23, 2021

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This polyline feature class depicts the river corridors of each Wild and Scenic River designated by Congress or the Secretary of the Interior for the United States and Puerto Rico. This GIS data layer was created from a multi-agency effort by the US Forest Service, National Park Service, Bureau of Land Management, and the US

National Wild and Scenic River Segments

Date of last refresh: Jun 23, 2021

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This polyline feature class depicts the classification of each wild and scenic river segment designated by Congress and the Secretary of the Interior for the United States and Puerto Rico. This layer was created by a multi-agency effort including the US Forest Service, National Park Service, Bureau of Land Management and the

National Wild and Scenic Rivers

Date of last refresh: Jun 23, 2021

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A boundary depicting an area that has been designated as a National Wild, Scenic or Recreational River in the National Wild and Scenic River System.

National Wilderness Areas

Date of last refresh: Jun 23, 2021

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A boundary depicting an area that has been designated as a National Wilderness in the National Wilderness Preservation System.

Original Proclaimed National Forests

Date of last refresh: Jun 23, 2021

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The FS National Forests Dataset (US Forest Service Proclaimed Forests) is a depiction of the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with subsequent Executive Orders, Proclamations, Public Laws, Public Land Orders, Secretary of Agriculture Orders,

Original Proclaimed National Forests and National Grasslands

Date of last refresh: Jun 23, 2021

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This layer includes both Proclaimed Forest and National Grassland boundary areas. A Proclaimed Forest boundary is the boundary encompassing National Forest System land within a national forest that is set aside and reserved from the public domain by executive order or proclamation congressional action is required to terminate

Other Sub Surface Right

Date of last refresh: Jun 23, 2021

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An area depicting ownership parcels of the subsurface estate, excluding mineral rights it is collected only if the subsurface estate is different than the overlying surface estate.

Other Surface Right

Date of last refresh: Jun 23, 2021

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An area depicting a right to a surface resource, excluding rights of way.

Parcels withdrawn from settlement, sale, mineral location, and/or entry

Date of last refresh: Jun 23, 2021

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Federal land parcels that are withdrawn from settlement, sale, location, or entry under some or all of the general land and mineral laws in order to maintain other public values or purposes. A withdrawal area has one or more associated segregations. A segregation is a specific activity from which the area has been withdrawn

Public Land Survey Corner

Date of last refresh: Jun 23, 2021

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A land survey point from a GCDB LX file, survey plat, or captured from a CFF land net coverage. Includes points generated by calculating an aliquot breakdown of a section.

Public Land Survey Monument

Date of last refresh: Jun 23, 2021

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A land survey point from a GCDB LX file, survey plat, or captured from a CFF land net coverage. Includes points generated by calculating an aliquot breakdown of a section.

Public Land Survey System Quarter Section

Date of last refresh: Jun 23, 2021

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This Quarter Section feature class depicts PLSS Second Divisions . PLSS townships are subdivided in a spatial hierarchy of first, second, and third division. These divisions are typically aliquot parts ranging in size from 640 acres to 160 to 40 acres, and subsequently all the way down to 2.5 acres. The data in this feature

Public Land Survey System Sections

Date of last refresh: Jun 23, 2021

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An area defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township.

Public Land Survey System Townships

Date of last refresh: Jun 23, 2021

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An area defined by the Public Lands Survey System grid that is referenced by its tier and range numbers, and is normally a rectangle approximately 6 miles on a side with boundaries conforming to meridians and parallels.

Purchase Units under the Weeks Law

Date of last refresh: Jun 23, 2021

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A unit designated by the Secretary of Agriculture or previously approved by the National Forest Reservation Commission for purposes of Weeks Law acquisition.

Right of Way

Date of last refresh: Jun 23, 2021

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An area depicting a privilege to pass over the land of another in some particular path usually an easement over the land of another a strip of land used in this way for railroad and highway purposes, for pipelines or pole lines and for private and public passage.

Special Interest Management Areas

Date of last refresh: Jun 23, 2021

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A boundary within which National Forest System land parcels have management or use limits placed on them by the Forest Service. Examples include: Archaeological Area, Research Natural Area, and Scenic Area.

Special Status Areas

Date of last refresh: Jun 23, 2021

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A land area that has distinct management/use authorities or agreements for Forest Service action. Includes: Cost Share Agreement Areas, Exchange Authority Areas, Land Adjustment Plan Areas, Forest Reserves, and Secretary's Order Areas.

Surface Ownership Parcels

Date of last refresh: Jun 23, 2021

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An area depicted as surface ownership parcels dissolved on the same ownership classification.

Surface Ownership Parcels, detailed

Date of last refresh: Jun 23, 2021

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An area depicting ownership parcels of the surface estate. Each surface ownership parcel is tied to a particular legal transaction. The same individual or organization may currently own many parcels that may or may not have been acquired through the same legal transaction. Therefore, they are captured as separate entities

Survey Boundaries maintained by the US Forest Service

Date of last refresh: Jun 23, 2021

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Surface Management Agency (SMA) lines represent the surveyed boundary lines for which the Forest Service is responsible for marking and posting. These include the boundaries between NFS lands and non-NFS lands and the boundaries of congressionally designated areas such as National Wilderness.

Survey parcels described by metes and bounds

Date of last refresh: Jun 23, 2021

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A depiction of a survey parcel described by a metes and bounds description. Examples include: land lots, housing subdivision lots, mineral surveys, and homestead entry surveys.

Wild and Scenic Rivers: Legal Status

Date of last refresh: Jun 23, 2021

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A boundary of an area designation that comprises all or a portion of a National Wild, Scenic or Recreational River in the Wild and Scenic River System. Each area designation is characterized by a date, boundary status, and authority and may be just one of several designations that comprise a single National Wild and Scenic

Wilderness Areas: Legal Status

Date of last refresh: Jun 23, 2021

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A boundary of an area designation that comprises all or a portion of a National Wilderness in the National Wilderness Preservation System. Each area designation is characterized by a date, boundary status, and authority and may be just one of several designations that comprise a single National Wilderness.

PADUS FS Managed Surface Ownership Parcels

Date of last refresh: Jun 23, 2021

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An area depicting National Forest System (NFS) ownership parcels of the surface estate.

PADUS FS National Designated Areas

Date of last refresh: Jun 23, 2021

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An area depicting designated National Forest System (NFS) land boundaries, excluding boundaries designated by proclamation.

PADUS FS Proclaimed NF and National Grassland Boundaries

Date of last refresh: Jun 23, 2021

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An area depicting designated National Forest System (NFS) land boundaries which are designated by proclamation.

PADUS FS Scenic and Conservation Easement Areas

Date of last refresh: Jun 23, 2021

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An area depicting a type of special use authorization (usually granted for linear rights-of-way) that is utilized in those situations where a conveyance of a limited and transferable interest in National Forest System (NFS) land is necessary or desirable to serve or facilitate authorized long-term uses, and that may be

Range: Allotment

Date of last refresh: Jun 23, 2021

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Allotment is a feature class in the Range Management Unit (RMU) data set. It represents the area boundaries of livestock grazing allotments.

Range: Pasture

Date of last refresh: Jun 23, 2021

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Pasture is a feature class in the Range Management Unit (RMU) data set. It represents the area boundaries of pastures within livestock grazing allotments.

Range: Wild Horse and Burro Territory

Date of last refresh: Jun 23, 2021

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WildHorseBurro is a feature class in the Range Management Unit (RMU) data set. It represents area boundaries of wild horse and burro territories.

Recreation Area Activities

Date of last refresh: Jun 23, 2021

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This dataset contains the recreation opportunity information that the Forest Service collects through the Recreation Portal and shares with the public on http://www.recreation.gov, the Forest Service World Wide Web pages (http://www.fs.fed.us/) and the Interactive Visitor Map. This recreation data contains detailed

Recreation Opportunities

Date of last refresh: Jun 23, 2021

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This dataset contains the recreation site opportunity information that the Forest Service collects through the Recreation Portal and shares with the public on the Forest Service World Wide Web pages (http://www.fs.fed.us/), the Recreation Information Database (RIDB), the Enterprise Data Warehouse (EDW), and the Interactive

Roadless Areas: 2001 Roadless Rule

Date of last refresh: Jun 23, 2021

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This dataset is the official data for the 2001 Roadless Area Conservation Rule (36 CFR 294, Subpart B). It contains the Inventoried Roadless Areas (IRAs) designated by the 2001 Roadless Area Conservation Rule and used in the associated Final Environmental Impact Statement. The EIS analysis team used this spatial data to assess

Roadless Areas: 2001, Idaho, and Colorado Rules Combined

Date of last refresh: Jun 23, 2021

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The RoadlessArea_2001_ID_CO feature class describes the boundaries of all Roadless Areas managed by the U.S. Forest Service. These roadless areas were designated by administrative rule making to provide management direction for their conservation and management. The RoadlessArea Conservation Rule of 2001 designated roadless

Roadless Areas: Colorado Roadless Rule

Date of last refresh: Jun 23, 2021

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This feature class describes the boundaries of Roadless Areas designated by the Colorado Roadless Rule of 2012 and managed by the U.S. Forest Service. These roadless areas were designated by administrative rulemaking to provide management direction for conservation of roadless area characteristics while addressing Colorado

Roadless Areas: Idaho Roadless Rule

Date of last refresh: Jun 23, 2021

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The RoadlessArea_ID_2008 feature class describes the boundaries of Roadless Areas designated by the Idaho Roadless Rule of 2008 and managed by the U.S. Forest Service. The final rule reflects the views and concerns of thousands of people who expressed interest during the rule-making process, which ran from October 2006 to

Motor Vehicle Use Map: Roads

Date of last refresh: Jun 23, 2021

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The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the Motor Vehicle Use Map (MVUM). Only roads with a SYMBOL attribute value of 1, 2, 3, 4, 11, and 12 are Forest Service System roads and contain

Motor Vehicle Use Map: Trails

Date of last refresh: Jun 23, 2021

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This feature class depicts Forest Service trails where motorized use is allowed. It contains information on the specific type of motor vehicle and their seasons of use. The feature class is consistent with the appropriate National Forest's Motor Vehicle Use Map (MVUM). Non-motorized trails are not included in this data. Trails

National Forest System Roads

Date of last refresh: Jun 23, 2021

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Existing Forest Service roads with attributes representing their characteristics. Each feature represents a segment of road where the attributes are the same. Attributes apply either to the entire road or to some measured distance along the road.

National Forest System Trails

Date of last refresh: Jun 23, 2021

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The TrailNFS_Publish Layer is designed to provide information about National Forest System trail locations and characteristics to the public. It describes trail locations, basic characteristics of the trail, and where and when various trail uses are prohibited, allowed and encouraged. Because the data readiness varies between

Watershed Condition Classification

Date of last refresh: Jun 23, 2021

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The Watershed Condition Classification feature class represents data on Watershed Condition on Forest Service lands in HUC12 (from the Watershed Boundary Dataset) watersheds that contain more than 5% USFS ownership. The feature class also includes data on high priority watersheds identified in the Watershed Condition Framework

Active Periodical Cicada Broods of the United States

Date of last refresh: Apr 7, 2017

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Active Periodical Cicada Broods of the United States. The periodical cicada emerges in massive groups once every 13 or 17 years and is completely unique to North America. There are 15 of these mass groups, called broods, of periodical cicadas in the United States. This county-based data, complied by USFS Northern Research

Aerial Fire Retardant Avoidance Areas: Terrestrial

Date of last refresh: Jun 23, 2021

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This layer contains features of aerial fire retardant avoidance areas delivered as part of the 2011 Nationwide Aerial Application of Fire Retardant on National Forest System Land Environmental Impact Statement. This Feature Class shows areas, provided by each National Forest who used aerial fire retardant from 2000-2010, where

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 1

Date of last refresh: Apr 1, 2021

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Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 10

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 2

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 3

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 4

Date of last refresh: Mar 31, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 5

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 6

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 8

Date of last refresh: Mar 31, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

Aerial Fire Retardant Hydrographic Avoidance Areas: Aquatic - Region 9

Date of last refresh: Apr 1, 2021

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map service
Aerial retardant avoidance area for hydrographic feature data are based on high resolution National Hydrographic Dataset (NHD) produced by USGS and available from the USFS. Forests and/or regions have had the opportunity to modify the default NHD water representation (300ft buffer from all water features) for their areas of

CALVEG Zones - Ecoregions

Date of last refresh: Mar 22, 2018

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This polygon layer consists of boundaries for the ecological tile units and CALVEG (Classification and Assessment with Landsat of Visible Ecological Groupings) zone units currently being used to tile the EVEG (existing vegetation) dataset. Selected lines were added from the CalWater watershed layer where finer tile divisions

Climate Shield - Bull Trout, 1980

Date of last refresh: Jul 10, 2018

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This feature class represents the historic (1980) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and

Climate Shield - Bull Trout, 2040

Date of last refresh: Jul 10, 2018

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This feature class represents the future (2040) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and

Climate Shield - Bull Trout, 2080

Date of last refresh: Jul 10, 2018

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map service
This feature class represents the future (2080) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and

Climate Shield - Cutthroat Trout, 1980

Date of last refresh: Jul 10, 2018

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map service
This feature class represents the historic (1980) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate

Climate Shield - Cutthroat Trout, 2040

Date of last refresh: Jul 10, 2018

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map service
This feature class represents the future (2040) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change

Climate Shield - Cutthroat Trout, 2080

Date of last refresh: Jul 10, 2018

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map service
This feature class represents the future (2080) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change

Communications Sites - Special Use Authorizations

Date of last refresh: Feb 12, 2020

Existing Vegetation: Region 5 - Central Coast

Date of last refresh: Jan 18, 2018

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map service
This Existing Vegetation (EVeg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails the northeastern portion of CALVEG Zone 6, Central Coast. Source imagery for this layer ranges from the

Existing Vegetation: Region 5 - Central Valley

Date of last refresh: Oct 15, 2019

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map service
This Existing Vegetation (EVeg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000 for CALVEG Zone 5, Central Valley. Source imagery for this layer ranges from the year 1998 to 2015. The CALVEG classification system

Existing Vegetation: Region 5 - Great Basin

Date of last refresh: Jan 18, 2018

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This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000 for CALVEG Zone 9, the Great Basin. Source imagery for this layer ranges from the year 1999 to 2009. The CALVEG classification system

Existing Vegetation: Region 5 - North Coast East

Date of last refresh: Jan 18, 2018

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails the northeastern portion of CALVEG Zone 1 (North Coast), Ecoregion Section M261A. Source imagery for

Existing Vegetation: Region 5 - North Coast Mid

Date of last refresh: Jan 18, 2018

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails the middle portion of CALVEG Zone 1 (North Coast), Ecoregion Section M261B. Source imagery for this

Existing Vegetation: Region 5 - North Coast West

Date of last refresh: Jan 18, 2018

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails the western portion of CALVEG Zone 1 (North Coast), Ecoregion Section 263A. Source imagery for this

Existing Vegetation: Region 5 - North Interior

Date of last refresh: Oct 15, 2019

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails CALVEG Zone 2, North Interior. Source imagery for this layer ranges from the year 1999 to 2016. The

Existing Vegetation: Region 5 - North Sierra

Date of last refresh: Oct 15, 2019

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This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails CALVEG Zone3, the North Sierra. Source imagery for this layer ranges from the year 2000 - 2014. The

Existing Vegetation: Region 5 - South Coast

Date of last refresh: Jan 18, 2018

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000 for CALVEG Zone 7, the South Coast. Source imagery for this layer ranges from the year 2002 to 2010. The CALVEG classification system

Existing Vegetation: Region 5 - South Interior

Date of last refresh: Feb 18, 2021

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map service
This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000 for CALVEG Zone 8, the South Interior. Source imagery for this layer ranges from the year 2000 to 2008. The CALVEG classification

Existing Vegetation: Region 5 - South Sierra

Date of last refresh: Oct 24, 2018

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This Existing Vegetation (Eveg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000 for CALVEG Zone 4, the South Sierra. Source imagery for this layer ranges from the year 1995 - 2016. The CALVEG classification system

Experimental Forest and Range Areas

Date of last refresh: Jan 4, 2018

Experimental Forest and Range Locations

Date of last refresh: Jan 4, 2018

FIA Landcover County Estimates 2015

Date of last refresh: Jun 23, 2021

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map service
This feature class represents forest area estimates (and percent sampling error) by county for the year 2015. The data was generated from the Forest Inventory Analysis (FIA) using the EVALIDator web tool (http://apps.fs.fed.us/Evalidator/evalidator.jsp-
). The areas were calculated within county limits using the US Census

FIA Landcover County Estimates 2016

Date of last refresh: Jun 23, 2021

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map service
This feature class represents forest area estimates (and percent sampling error) by county for the year 2016. The data was generated from the Forest Inventory Analysis (FIA) using the EVALIDator web tool (http://apps.fs.fed.us/Evalidator/evalidator.jsp-
). The areas were calculated within county limits using the US Census

FIA Landcover County Estimates 2017

Date of last refresh: Jun 23, 2021

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map service
This feature class represents forest area estimates (and percent sampling error) by county for the year 2017. The data was generated from the Forest Inventory Analysis (FIA) using the EVALIDator web tool (http://apps.fs.fed.us/Evalidator/evalidator.jsp-
). The areas were calculated within county limits using the US Census

FIRESTAT Fire Occurrence - Yearly Update

Date of last refresh: Jun 23, 2021

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The FIRESTAT (Fire Statistics System) Fire Occurrence point layer represents ignition points, or points of origin, from which individual wildland fires started on National Forest System lands. The source is the FIRESTAT database, which contains records of fire occurrence, related fire behavior conditions, and the suppression

FSTopo Airfield Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Airfield_LN portrays Heliports, Seaplane Bases, Landing Strips, Airport Outlines, etc. This feature class was derived from the Cartographic Feature File (CFF). Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the

FSTopo Airfield Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Airfield_PT portrays Helipads, Helispots, Seaplane Anchorages or Bases. This feature class was derived from the Cartographic Feature File (CFF). Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

FSTopo Arrow Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Arrows_LN contains Variable length arrow, used to point to feature where labeling would otherwise be unclear. Example: Road number symbol pointing to a road. Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic

FSTopo Boundary Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Boundary_LN portrays boundaries. This feature class was derived from the Cartographic Feature File (CFF). The boundary line feature class complements the boundary polygon feature class (FSTopo_Boundary_PL) the two feature classes create a complete boundary coverage of the FSTopo area of interest.Within the FSTopo

FSTopo Boundary Ownership Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Ownership_PL portrays land that is not owned by the Forest Service within the Proclaimed Forest boundary. The line feature class was derived from the Cartographic Feature File (CFF). The source for updates is the BasicOwnership feature class from the Automated Lands Program (ALP).Within the FSTopo database, features are

FSTopo Boundary Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Boundary_PL portrays boundaries. The source for updates is data from the Automated Lands Project (ALP). The boundary polygon feature class complements the boundary lines (FSTopo_Boundary_LN) feature class the two feature classes create a complete boundary coverage of the FSTopo area of interest.Within the FSTopo

FSTopo Building Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Building_PT portrays small buildings are portrayed as point features. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

FSTopo Building Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Building_PL portrays large building footprints greater than 100 feet along the longest axis are displayed as polygon features. The polygon feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype

FSTopo BuiltupArea Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_BuiltupArea_PL portrays Urban areas where only landmark buildings are portrayed. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic

FSTopo ContourFSAK Annotation

Date of last refresh: Oct 29, 2020

metadata FSTopo_TextAK_A (Annotation): Alaska-Stand alone map text collected at scale of PBS (1:63,360). Text is categorized by annotation subclasses Boundary, Civil Township, Culture, Landforms, Hydrographic, Trail Numbers, National Trails, Recreation, PLSS, Spot Elevations, Place Names, Control/Monuments. Text layers are separated

FSTopo ContourFSAK Line

Date of last refresh: Jul 24, 2019

metadata FSTopo_Contour_AK_LN portrays elevation contour lines for the Alaska Area of Interest. This feature class was derived from the Cartographic Feature File (CFF). The contour labels for the ContourFS_AK_LN are displayed in the ContourFSAK_A (Alaska). The elevation contours for the conterminous USA was obtained from the USGS and

FSTopo ContourFSPR Annotation

Date of last refresh: Oct 29, 2020

FSTopo ContourFSPR Line

Date of last refresh: Jul 24, 2019

metadata FSTopo_Contour_PR_LN portrays elevation contour lines for the Puerto Rico Area of Interest. This feature class was derived from the Cartographic Feature File (CFF). The contour labels for the CotourFS_PR_LN are displayed in the ContourFSPR_A (Puerto Rico). The elevation contours for the conterminous USA was obtained from the

FSTopo ContourUSGS Annotation

Date of last refresh: Oct 29, 2020

FSTopo Culture Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Culture_LN portrays manmade features such as Pipelines, Power Lines, Ski Lifts, Fences, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the

FSTopo Culture Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Culture_PT portrays manmade features such as Mines, Lighthouses, Located Objects, Prospects, Drill Holes, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to

FSTopo Culture Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Culture_PL portrays Manmade features such as Fish Hatcheries, Pools, Piers, Sewage Disposal, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the

FSTopo Drainage Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Drainage_LN portrays features associated with water lines such as Rivers, Streams, Shorelines, Canals, Dams, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached

FSTopo Drainage Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Drainage_PT portrays features associated with water such as Springs, Wells, Boat Access, Gaging Stations, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to

FSTopo Drainage Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Drainage_PL portrays features associated with water bodies such as Open Water, Swamps, Glaciers, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe

FSTopo GeodeticControl Point

Date of last refresh: Oct 29, 2020

metadata GeodeticControl_X contains Vertical and Horizontal control locations. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

FSTopo Landform Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Landform_LN portrays surface features that have geographic significance such as Continental Divides, Levees and Spoil Banks. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes

FSTopo Landform Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_Landform_PL portrays surface features that have geographic significance such as Glacial Moraines, Gravel or Lava Areas, Dry Lakes or Ponds, Mines, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with

FSTopo LargeTank Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_LargeTank_PT portrays variable size point features, where the 'tank_radius' field defines the size. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the

FSTopo Offshore Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Offshore_LN portrays Offshore features, such as exposed Rock, Wreck, Shoal, Pile, Coral Reef, and Large Area Outline. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes

FSTopo Offshore Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Offshore_PT portrays Offshore features, such as Exposed or Sunken Rocks, Wreck, and Pile.Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology characteristics of features. Annotation features are

FSTopo PBSText48 Annotation

Date of last refresh: Oct 29, 2020

metadata FSTopo_Text48_A (Annotation): Coterminous United States-Stand alone map text collected at scale of PBS (1:24,000). Text is categorized by annotation subclasses Boundary, Civil Township, Culture, Landforms, Hydrographic, Trail Numbers, National Trails, Recreation, PLSS, Spot Elevations, Place Names, Control/Monuments. Text

FSTopo PBSTextAK Annotation

Date of last refresh: Oct 29, 2020

FSTopo PBSTextPR Annotation

Date of last refresh: Oct 29, 2020

metadata FSTopo_TextPR_A (Annotation): Coterminous United States-Stand alone map text collected at scale of PBS (1:24,000). Text is categorized by annotation subclasses Boundary, Civil Township, Culture, Landforms, Hydrographic, Trail Numbers, National Trails, Recreation, PLSS, Spot Elevations, Place Names, Control/Monuments. Text

FSTopo PLSS Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_PLSS_LN portrays Public Land Survey System (PLSS). The line feature class was derived from the Cartographic Feature File (CFF). The PLSS line feature class (FSTopo_PLSS_LN) complements the PLSS polygon layer (FSTopo_PLSS_PL) the two feature classes create a complete PLSS coverage of the FSTopo area of interest.Within

FSTopo PLSS Polygon

Date of last refresh: Oct 29, 2020

metadata FSTopo_PLSS_PL portrays Public Land Survey System (PLSS). The source for updates is data from the Township and Section feature classes from the Automated Lands Program (ALP) and the BLM CAD-NSDI. The PLSS_polygon feature class complements the PLSS_line layer (FSTopo_PLSS_LN) the two feature classes create a complete PLSS

FSTopo Railroad Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Railroad_LN portrays features associated with Railroad Tracks. This feature class was derived from the Cartographic Feature File (CFF). Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

FSTopo RecFacility Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_RecFacilities_PT portrays Recreational locations, such as Campgrounds, Picnic Areas, Trailheads. The layer also contains Forest Service Offices and Facilities. This feature class was derived from the Cartographic Feature File (CFF). The source for the Recreation facility feature class is the Infra database, which is the

FSTopo RoadShield48 Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_RoadShield48_PT contains Interstate, U.S., State, County route marker, vertical and horizontal Forest Service road box. The name field is used to label the point symbol. Conterminous US and Puerto Rico 1:24,000. Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype

FSTopo RoadShieldAK Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_RoadShieldAK_PT contains Interstate, U.S., State, County route marker, vertical and horizontal Forest Service road box. The name field is used to label the point symbol. Alaska, 1:63,360.Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached

FSTopo RoadShieldPR Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_RoadShieldPR_PT contains Interstate, U.S., State, County route marker, vertical and horizontal Forest Service road box. The name field is used to label the point symbol. Conterminous US and Puerto Rico 1:24,000. Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype

FSTopo SpotElevation Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_SpotElev_PT marks the location of spot elevations. Elevation values are displayed in the PBS Text layers. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to

FSTopo Survey Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Survey_LN portrays Public Land Survey System (PLSS) Land Grants, Survey Lines, Tract lines. The line feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the

FSTopo Survey Point

Date of last refresh: Oct 29, 2020

metadata FSTopo_Survey_PT contains monuments, land grants, and non Public Land Survey System (PLSS) survey points. The point feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe

FSTopo Transportation Line

Date of last refresh: Oct 29, 2020

metadata FSTopo_Transport_LN contains transportation features ranging from Trails to Highways. This feature class was derived from the Cartographic Feature File (CFF). The source for this feature class is local, county, and state data as well as the Infra database, which is the USFS authoritative database for manmade features.Within

FSTopo Transportation Point

Date of last refresh: Oct 29, 2020

metadata FSTopo Transport PT contains features such as Gates, Berms, Bridge Abutments, etc. This feature class was derived from the Cartographic Feature File (CFF).Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

Forest Common Names

Date of last refresh: Jun 23, 2021

metadata
map service
Basic Description: The FSCommonNames dataset contains the common names of the national forests and grasslands and their respective FS WWW URL information that is used for both display of the national forest and national grassland boundaries on any map product and for dynamic interactivity of the map. This published dataset

Forest Service Office Locations

metadata
map service
This data includes offices where Forest Service employees work or where IT equipment is housed. There is no Personally Identifiable Information (PII) data in this dataset, nor telework locations. It includes owned, leased and shared offices. Shared offices are buildings owned or leased by another entity (i.e. a university,

Fraction of Runoff from Forest Service Lands

Date of last refresh: Apr 3, 2019

metadata
map service
This feature class contains water runoff metrics from Forest Service lands. Note: 'Forest Service Lands' are here defined as those lands within the Forest Service administrative boundaries these include some inholdings and other non-USFS lands enclosed within these boundaries. This feature class was generated from the

Historical Woodland Density of the Conterminous U.S., 1873

Date of last refresh: Mar 31, 2017

metadata
map service
This dataset includes polygons with a minimum of 40 acres of woodlands per square mile as depicted in William H. Brewer’s 1873 map of woodland density and covers the conterminous United States. Each polygon has been labeled with the density category (1-5) depicted on the original map. This dataset was created by

Hydro Flow Metrics West 2040

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents modeled streamflow metrics from the mid-21st century time period (2030-2059) in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August), flood levels associated with 1.5 year, 10-year, 25-year,

Hydro Flow Metrics West 2080

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents modeled streamflow metrics from the late-21st century time period (2070-2099) in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August), flood levels associated with 1.5 year, 10-year, 25-year,

Hydro Flow Metrics West Absolute Change 2040

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents the absolute change in modeled streamflow metrics between the historical (1997-2006) and mid 21st century (2030-2059) time periods in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August),

Hydro Flow Metrics West Absolute Change 2080

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents the absolute change in modeled streamflow metrics between the historical (1997-2006) and late 21st century (2070-2099) time periods in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August),

Hydro Flow Metrics West Historical

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents modeled streamflow metrics from the historical time period (1977-2006) in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August), flood levels associated with 1.5 year, 10-year, 25-year, and

Hydro Flow Metrics West Percent Change 2040

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents the percent change in modeled streamflow metrics between the historical (1997-2006) and mid 21st century (2030-2059) time periods in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August), flood

Hydro Flow Metrics West Percent Change 2080

Date of last refresh: Feb 5, 2020

metadata
map service
This feature class represents the percent change in modeled streamflow metrics between the historical (1997-2006) and late 21st century (2070-2099) time periods in the western United States. In addition to standard NHD attributes, the streamflow dataset includes metrics on mean daily flow (year-round, summer, and August),

Land and Water Conservation Fund Projects

Date of last refresh: Jun 23, 2021

Land and Water Conservation Fund: Proposed Land Purchases

Date of last refresh: Jun 23, 2021

metadata
map service
This dataset contains parcels proposed for purchase by the Forest Service under the Land and Water Conservation Fund (LWCF) Program. Also, some polygons in this dataset are meant to provide supporting information or historical context for parcels proposed by the Forest Service for purchase under the Land and Water Conservation

MTBS Burn Area Boundary

Date of last refresh: May 7, 2021

metadata
map service
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. All fires reported as

MTBS Fire Occurrence Points

Date of last refresh: May 7, 2021

metadata
map service
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. All fires reported as

NEPA Project Area Boundaries

Date of last refresh: Jun 23, 2021

metadata
map service
Actv_ProjectArea_NEPA represents an area (polygon) within which one or more activities related to the National Environmental Policy Act (NEPA) are aggregated or organized. The data comes from the Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS), which is the agency standard for managing

National USFS Final Fire Perimeter

Date of last refresh: Jun 23, 2021

metadata
map service
The FinalFirePerimeter polygon layer represents final mapped wildland fire perimeters. This feature class is a subset of the FirePerimeters feature class. Incidents of 10 acres or greater in size are expected. Incidents smaller than 10 acres in size may also be included. Data are maintained at the Forest/District level, or

National USFS Fire Occurrence Point

Date of last refresh: Jun 23, 2021

metadata
map service
The FireOccurrence point layer represents ignition points, or points of origin, from which individual USFS wildland fires started. Data are maintained at the Forest/District level, or their equivalent, to track the occurrence and the origin of individual USFS wildland fires. Forests are working to include historical data,

National USFS Fire Perimeter

Date of last refresh: Jun 23, 2021

metadata
map service
The FirePerimeter polygon layer represents daily and final mapped wildland fire perimeters. Incidents of 10 acres or greater in size are expected. Incidents smaller than 10 acres in size may also be included. Data are maintained at the Forest/District level, or their equivalent, to track the area affected by wildland fire.

NorWeST Observed Temperature Points

Date of last refresh: Jul 10, 2018

metadata
map service
This layer indicates the location of the observed stream temperature records used for the NorWeST database summaries. NorWeST summer stream temperature scenarios were developed for all rivers and streams in the western U.S. from the > 20,000 stream sites in the NorWeST database where mean August stream temperatures were

NorWeST Predicted Stream Temperature Lines

Date of last refresh: Jul 10, 2018

metadata
map service
This layer represents modeled stream temperatures derived from the NorWeST point feature class (NorWest_TemperaturePoints). NorWeST summer stream temperature scenarios were developed for all rivers and streams in the western U.S. from the > 20,000 stream sites in the NorWeST database where mean August stream temperatures were

PBS Reference Quadrangle

Date of last refresh: Oct 29, 2020

metadata
map service
FSTopo_Quadrangle_PL portrays the FSTopo quad footprint. Quadrangles with a Vintage > 0 (greater than zero) make up the FSTopo area of interest.Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology

Payments in Lieu of Taxes and All Service Receipts Forest Lands

Date of last refresh: Apr 30, 2021

metadata
map service
This data is intended for read-only use. Payments In Lieu of Taxes (PILT) and All Service Receipts (ASR) are combined into a base layer that is used in Forest Service business functions, as well as by other entities such as states and counties. This layer depicts Forest Service lands that qualify for PILT and/or ASR. Payments

RAVG Burn Area Boundaries

Date of last refresh: Jun 25, 2021

metadata
map service
The USDA Forest Service Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program produces geospatial data and maps of post-fire vegetation condition using standardized change detection methods based on Landsat or similar multispectral satellite imagery. RAVG data products characterize vegetation condition within

Research Station Boundaries

Date of last refresh: Jun 23, 2021

Research Station Boundaries (Generalized)

Date of last refresh: Jun 23, 2021

metadata
map service
ResearchStationBoundaries_Gen is a generalized spatial representation of the administrative boundaries of the US Forest Service Research and Development Stations. These territories consist of a collection of states' geographic areas, within which all research and development facilities and lands are managed by a station

Research Station Facilities

Date of last refresh: Jun 23, 2021

Sale Area Improvement Project Boundaries

Date of last refresh: Jun 23, 2021

metadata
map service
Actv_ProjectArea_SAIPlan represents an area (polygon) within which one or more Sale Area Improvement (SAI) related activities are aggregated or organized. The data comes from the Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS), which is the agency standard for managing information about

Spatial Wildfire Occurrence Data for the United States, 1992-2015 (FPA FOD 4th Edition)

Date of last refresh: Jan 2, 2018

metadata
map service
FPA_FOD_4thedition is a point feature class that represents occurrence of wildfires in the United States from 1992 to 2015. This is the third update of a publication originally generated to support the national Fire Program Analysis (FPA) system. The wildfire records were acquired from the reporting systems of federal, state,

Surface Drinking Water Importance

Date of last refresh: Jun 23, 2021

metadata
map service
The Forests to Faucets dataset provides a watershed index of surface drinking water importance, a watershed index of forest importance to surface drinking water, and a watershed index to highlight the extent to which development, fire, and insects and disease threaten forests important for surface drinking water. The Forests

Surface Drinking Water Importance - Forests on the Edge

Date of last refresh: Jun 23, 2021

metadata
map service
The Forests on the Edge feature class is based on the digital hydrologic unit boundary layer to the Subwatershed (12-digit) 6th level for the continental United States. This 2015 data set is an updated version of the 2011 Forests to Faucets data set. America’s private forests provide a vast array of public goods and

Timber Sale Project Area Boundaries

Date of last refresh: Jun 23, 2021

metadata
map service
Actv_ProjectArea_TimberSale represents an area (polygon) within which one or more Timber Sale related activities are aggregated or organized. The data comes from the Forest Service's Natural Resource Manager (NRM) Forest Activity Tracking System (FACTS), which is the agency standard for managing information about activities

Tongass Landslide Areas

Date of last refresh: Aug 13, 2019

metadata This is a once-over landslide inventory of the Tongass National Forest. This inventory includes all mass wasting features--including talus slopes, snow avalanche fields, and snow avalanche chutes. Each of these are coded differently in the attributes. It may be necssary to exclude several polygons in this data set when using

Tongass Landslide Initiation

Date of last refresh: Aug 13, 2019

metadata This is the point feature class for theonce-over landslide inventory of the Tongass National Forest. Most of the landslide polygons were digitized on the 1998 to 2010 ortho photos in GIS. Many of them were age bracketed using air photos back to the 1929 Navy Trimegon photos. It includes both field and photo interpreted

Tribal Ceded Lands

Date of last refresh: May 29, 2018

metadata
map service
Sixty-seven maps from "Indian Land Cessions in the United States," compiled by Charles C. Royce and published as the second part of the two-part Eighteenth Annual Report of the Bureau of American Ethnology to the Secretary of the Smithsonian Institution, 1896-1897 have been scanned, georeferenced in JPEG2000 format, and

Tribal Ceded Lands Table

Date of last refresh: May 29, 2018

metadata This is a table used for joining additional attributes to the feature class called TribalCededLands, which is the result of scanning, georeferencing and digitizing sixty-seven maps from "Indian Land Cessions in the United States," compiled by Charles C. Royce and published as the second part of the two-part Eighteenth Annual

U.S. Forest Service Silviculture Reforestation Needs

Date of last refresh: Jun 23, 2021

metadata
map service
The SilvReforestation feature class represents activities associated with the following performance measure: Forest Vegetation Establishment (Planting, Seeding, Site Preparation for Natural Regeneration and Certification of Natural Regeneration without Site Preparation). The Activities data set portrays the areas where

U.S. Forest Service Silviculture Timber Stand Improvement Needs

Date of last refresh: Jun 23, 2021

metadata
map service
The SilvTSI (Silviculture Timber Stand Improvement) feature class represents activities associated with the following performance measure: Forest Vegetation Improved (Release, Weeding, and Cleaning, Precommercial Thinning, Pruning and Fertilization). The Activities data set portrays the areas where activities are accomplished

Enterprise Data Disclaimer:

The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.


Download National Datasets

Requests for KML/KMZ output
The Enterprise Data Warehouse Team tested exporting out to KML/KMZ files as a deliverable and due to the complexity and size of the datasets this has been unsuccessful. To obtain a KML file for any EDW dataset, go to the Geospatial Data Discovery Tool and search for the dataset. An option to download to KML is available from that website. If you have questions, contact: [email protected]

Existing Vegetation: Region 5 - Central Coast

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - Central Valley

Date of last refresh: Oct 15, 2019

Existing Vegetation: Region 5 - Great Basin

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - North Coast East

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - North Coast Mid

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - North Coast West

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - North Interior

Date of last refresh: Oct 15, 2019

Existing Vegetation: Region 5 - North Sierra

Date of last refresh: Oct 15, 2019

Existing Vegetation: Region 5 - South Coast

Date of last refresh: Jan 18, 2018

Existing Vegetation: Region 5 - South Interior

Date of last refresh: Feb 18, 2021

Existing Vegetation: Region 5 - South Sierra

Date of last refresh: Oct 24, 2018

Enterprise Data Disclaimer:

The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.


AIS FAQ

Q: Do you have plans to publish LIVE or more recent data?
A: The most current AIS data we have access to is what is published on this website. We also do not have access to any LIVE AIS data or feeds. Every year, the MarineCadastre.gov team prioritizes data development activities based on funding and needs expressed by the user community. Please let us know how you are using the AIS data by emailing [email protected], and if more current data are necessary for your use. Your request will not guarantee that we will be able to provide more current data, but it will help us prioritize and plan future releases.

Q: Do you have AIS data before 2009?
A: No, 2009 is the earliest data we have.

Q: Do you have AIS for [my location]?
A: The AIS data published by MarineCadastre.gov originates from the Nationwide Automatic Identification System (NAIS) by the U.S. Coast Guard. The NAIS is composed of approximately 200 land-based receiving stations located near important navigation routes in the conterminous U.S., Alaska, Hawaii, Guam, and parts of the Caribbean. NAIS data are generally not available for the Arctic, waters beyond 40 to 50 miles of the coast, or foreign waters.

Q: Do you have AIS data collected by satellite?
A: No. All of our data originates from land-based receivers. Commercial providers collect, license, and sell satellite AIS data. Some federal agencies purchase satellite AIS data for specific needs, and they are restricted from distributing the data to the public by the terms of their license agreement.

Q: Are accidents or other types of events removed from the AIS point data?
A: Collisions and accidents are not removed from the data explicitly. The MarineCadastre.gov AIS data represent 16 of the most important fields from the original AIS record. Our data are filtered to a one-minute rate and show all vessels that the land-based antennas received, with the exception of certain law enforcement and military vessels that are excluded.

Q: Do you have tonnage, horsepower, fuel type, and other parameters for vessels?
A: No, these parameters are not part of our database. We have heard about other users finding these parameters in commercial databases, and having success in merging those parameters with the Marine Cadastre AIS records using the MMSI value as a JOIN key.

Q. Do you have a voyage identifier value?
A: Before 2015, we did calculate and insert a voyage ID and included the destination value. Our criteria for defining a voyage can be found in the AIS Data Handler documentation. Since 2015, we have not included a voyage ID or destination because defining the start and end of a voyage is a subjective and complex process dependent on mariner input. The Track Builder tools are now the best option to generate track lines that can be used to define a voyage.

Q: Do you have origination or destination values?
A: We collect the destination values however, most of the entries are incomplete, inconsistent, or null. We will continue to monitor the destination and the origination input and will consider adding them to future products if the values are more complete.

Q: How do I interpret the vessel codes and cargo codes?
A: The vessel type codes are outlined in this PDF document. The cargo codes are part of the vessel type parameter. Please see the detailed documentation available at the U.S. Coast Guard, Navigation Center.

Q: How do the vessel draught field from 2009 to 2014 and the vessel draft field from 2015 to 2017 compare?
A: The 2009-2014 draught parameter is reported in 1/10’s meters, and the value 255 equals 25.5 meters or greater. The 2015-2017 vessel draft parameter is reported in meters. Carriage requirements and instructions to mariners for entering vessel draft values have changed over time. Recent vessel draft values report the “maximum present static draught.”

Q: If I want to group data by vessel type, can I combine vessel type codes? For example, should I combine vessel type 31 (towing) with vessel type 1025 (towing vessel)?
A: In this example, yes.

We have used the U.S. Coast Guard Authoritative Vessel identification Service (AVIS) to populate and improve many of the null values found in the native AIS data. Similar vessel types from both lists can be combined into groups. We usually categorize null values under the “other” group type. We have also found many users have a need to define their own groups of vessel types. The vessel groups defined by MarineCadastre.gov are those frequently used among the ocean planning community.

  • Codes 0 through 255 are original vessel type codes defined by AIS standards
  • Codes 256 through 999 are an empty set added by MarineCadastre.gov
  • Codes 1001 through 1025 are keys to the AVIS vessel type descriptions

Q: Who owns the copyright to these AIS data, and are they available for use and redistribution by commercial entities?
A: Our data are derived from the U.S. Coast Guard NAIS and are free for public use. The MarineCadastre.gov AIS data are intended for coastal and ocean planning. Please see the information at the bottom of the NAIS web page for the terms and conditions of use. If you have additional questions about the terms and conditions, please use the contact email on the NAIS data request page.

Q: Are the AIS data provided by MarineCadastre.gov adequate for regulatory or enforcement purposes?
A: The AIS data provided by Marine Cadastre are intended for marine planning purposes only.

Q: What is the resolution (cell size) of the density grids?
A: The cell size for the kernel density grids (2011 and 2013) is 100 meters. The cell size for the transit count grids (2015, 2016, and 2017) is 100 meters.

Q: Why are there AIS points over land (e.g., like Kansas and Canada in data set 2017_01_Zone14)?
A: Location values are principally derived from on-vessel GPS devices. For a detailed discussion on errors in GPS signals, please search the web or contact a vendor of GPS units. Accurately reported GPS positions from vessels being transported over land can also be seen in the data, as well as vessels transiting very small canals and locks that may be difficult or impossible to see on a web-map.

Q: How do I account for apparent inconsistencies of the AIS timestamp and of an observed vessel’s voyage?
A: The full timestamp is added to the record by the base station, using the time clock of the base station that is reporting in UTC. Be sure to account for your time zone shift to UTC and other offsets such as Daylight Savings Time.

Q: Is there a schema diagram or data dictionary for the new AIS points data?
A: Below is the proposed data dictionary starting in 2018. This expands the 2015, 2016, and 2017 data with the addition of the Transceiver Class designation.

Q: What does a value of “511” in the Heading field represent?
A: The value 511 stands for “not available = default.”

Q: What is represented by Vessel Type code 59, and what is RR Resolution No. 18 referencing?
A: A good place to begin researching the meaning of type codes and resolutions is on the U.S. Coast Guard Navigation Center website (see IMO Resolutions).

Q: How can I calculate the estimated time of arrival (ETA) for vessel tracks?
A: While there are multiple ways one could calculate ETA values, here is just one suggestion:

  1. Filter the points to remove unwanted vessels or vessel types.
  2. Generate vessel tracks, probably using a 24-hour period to segment the tracks.
  3. Generate a polygon defining the arrival port.
  4. Examine track end-time date/times of the remaining tracks.
    Note: Track start and end times are contained within the MarineCadastre.gov trackline data sets
    Note: Track start and end times are contained within trackline products generated by the Track Builder tools

Q: I am failing to create tracklines for points that are very close together (for example, less than 10 meters). How do I create tracklines in these cases?
A: This is due to how the python script handles XY points that are very close together (

10 meters or less) AND are stored in a geographic coordinate system (GCS). If the points are first transformed into a projected coordinate system, the python script runs as intended and will connect the points even when they are in very close proximity to one another.

The TrackBuilder input file should be in a projected coordinate system if there is a need for points closer than

10 meters to be connected. If very near points do not need to be connected, then either projected or geographic coordinate systems can be used for an input file.

Q: Why do I encounter failures or errors when running the Track Builder tool (v3.1)?
A: Error messages that say you have run out of memory while the tool is running could be due to using the 32-bit version of the tool or environment (such as IDLE). The best solution is to use the 64-bit command line version of the program. You will need to have the 64-bit Background Geoprocessing patch installed. The patch will install a 64-bit version of Python for ArcGIS Desktop. If you are running ArcGIS Pro, be sure to use our Track Builder Pro 1.0 tool.

Q: When working AIS data prior to 2015 in the file geodatabase format, clipping the broadcast features to an area of interest causes the link between the features and the voyage attributes to be broken within the Track Builder. How do I retain these voyage attributes?
A: The Track Builder tool looks for specific field names in the Vessel and Voyage tables that match the data model used in the MarineCadastre.gov products. Check during your CLIP process that file or field names are not being modified. Consider using a simple JOIN of the Vessel and Voyage tables using the MMSI as key after you run the Track Builder tool.

Q: I am not an ArcGIS user. How can I access and use the 2009 to 2014 data that are in the file geodatabase format?
A: Consider using the GDAL Python library, which supports a wide range of file format translations and other operations that can be run from the command line. Numerous commercial applications by companies such as SAFE Software and MatLab have a capacity to read the native GDB format. Reference their documentation for which version is supported.

Q: Do you include Class B data?
A: Beginning in 2018, we will include class B data and the class designation for each record.


PAD-US Data Overview

PAD-US is America’s official national inventory of U.S. terrestrial and marine protected areas that are dedicated to the preservation of biological diversity and to other natural, recreation and cultural uses, managed for these purposes through legal or other effective means. PAD-US also includes the best available aggregation of federal land and marine areas provided directly by managing agencies, coordinated through the Federal Geographic Data Committe Federal Lands Working Group.

Lands in PAD-US are mainly open space/resource lands owned in fee by agencies and nonprofits. Conservation easements suitable for distribution in the public domain are also included. The current data set includes the “GAP Status Codes” of these lands, indicating how they are being managed for conservation purposes. A measure of public access for recreation is also included. PAD-US includes all Federal and most State and local lands.

Why are protected areas data important?

Detailed information about the conservation status of our country’s protected areas is crucial to improving our understanding of how well we are protecting the animals and plants that inhabit those areas. Natural resources decision-makers, planners, researchers, private interests and others also use this information in many other ways from locating and siting public resources such as recreation areas and energy facilities, to planning for and mitigating the impacts of climate change.

How GAP protected areas data can be used

Information about the conservation status of common species – a primary purpose of protected area analyses — is important for decision makers, planners, researchers, private interests, and others:

  • Biodiversity: Protected areas (parks, preserves, etc.) have often been set aside without full understanding of their value to species conservation. As a result, many protected areas have little significance in terms of biodiversity, while many biodiversity-rich areas lack protection. Information provided by the PAD-US can help land conservation decision makers better match biodiversity goals to land protection programs and activities.
  • Habitat Loss: Human population in the U.S. is predicted to grow by 25% in the next 50 years. This population increase, coupled with our land consumption patterns, means that there will be significant decreases in habitat for other species. Efforts to target the most effective lands for biodiversity conservation can offset some or many of the effects of habitat loss.
  • Climate: Accelerating climate change is elevating the importance of effectively targeted species protection efforts. For many species, warming climates could push them to the brink of extinction unless habitat migration corridors can be set aside. Protected Areas analysis is critical to understanding where to focus such corridor planning.
  • Energy Siting: Traditional and renewable energy projects such as oil, natural gas, solar and wind are planned and built across the U.S., often aided by governmental incentives. Protected area analysis can inform this planning and siting work, helping energy projects to find the best balance between habitat conservation and much-needed energy production.
  • Management: Agencies and nonprofits that manage protected areas often lack good information about the full range of species that might be present or could be encouraged on their lands. The Gap Analysis Project can provide tools to improve land management practices that support continued biodiversity.
  • Public Access: There is increasing interest and research on the benefits of publicly accessible open space. In the current version of PAD-US, access is fully attributed but primarily assigned categorically instead of through individual unit review. However, this data can be used to view lands open for public recreation, incorporated into web or mobile based recreation apps, and utilized in other analyses on public access. Now with a more complete inventory of city and county data in PAD-US, it may also be useful for local or regional recreation and open space planning.

Description of PAD-US data

How to cite data:

U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2018, Protected Areas Database of the United States (PAD-US): U.S. Geological Survey data release, https://doi.org/10.5066/P955KPLE.

U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2020, Protected Areas Database of the United States (PAD-US) 2.1: U.S. Geological Survey data release, https://doi.org/10.5066/P92QM3NT

Main purpose:

The goals of the USGS Gap Analysis Project (GAP) are to provide landscape (e.g. State, watershed, regional and national) assessments of the conservation status of native vertebrate species and natural land cover types and to facilitate the application of this information to land management activities. The PAD-US geodatabase is required to organize and assess the status (i.e. land ownership and GAP Status Code) of protected areas for biodiversity protection. GAP has committed to develop and maintain PAD-US while implementing recommendations from the PAD-US Design Project (see A Map for the Future report) and expanding its scope to meet the needs of the recreation and public health communities (see Completing America's Inventory of Public Parks and Protected Areas report), to the extent resources allow. The PAD-US geodatabase is built to support landscape analyses by describing all protected areas to illustrate patterns and possible relationships with other factors (e.g. urban areas, migration corridors) across the landscape. Characteristics of protected areas such as land owner, name, location, size, public access, and a measure of biodiversity management intent are compiled and standardized.

Our current objective is to refine the PAD-US Data Manual to facilitate more efficient sharing of authoritative protected areas data between agencies and organizations that ultimately results in a comprehensive and accurate inventory of protected areas for the United States to meet a variety of needs (e.g. conservation, recreation, public health, transportation, energy siting, ecological, or watershed assessments and planning). In cooperation with UNEP-World Conservation Monitoring Centre (WCMC) and the Commission for Environmental Cooperation (CEC), GAP ensures PAD-US also supports continental and global decision making by maintaining World Database on Protected Areas (WDPA) Site Codes and International Union for the Conservation of Nature (IUCN) Categories for linkage to the North American Terrestrial Protected Areas Database and WDPA.

PAD-US data features:

PAD-US is available as a zipped national, DOI Region, or state geodatabase or shapefile. The following are included in PAD-US:

  • Geographic boundaries of public land ownership (primarily Federal and State, with a significant amount of local government data, particularly for urban areas) and voluntarily provided private conservation lands (e.g., Nature Conservancy Preserves or land trust easements) from authoritative data sources.
  • Standardized and original land owner, land manager, management designation and parcel name descriptions, areas and the source of geographic information of each mapped land unit.
  • GAP Status Code – conservation measure of each parcel based on protection level categories that provide a measure of management intent for the long-term protection of biodiversity. More details provided in the following section. – a globally inter operable conservation measure required for a protected area’s inclusion into UNEP-World Conservation Monitoring Centre’s (WCMC) World Database on Protected Areas (WDPA).
  • Reference information – aggregator source and original GIS source and dates.
  • See “Supplemental_Info.txt” and metadata files included in download for more information.

GAP Status Code:

Status 1: An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a natural state within which disturbance events (of natural type, frequency, intensity, and legacy) are allowed to proceed without interference or are mimicked through management. Examples of Status 1: National Parks, Wilderness Areas

Status 2: An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a primarily natural state, but which may receive uses or management practices that degrade the quality of existing natural communities, including suppression of natural disturbance. Examples of Status 2: National Wildlife Refuges, State Parks, The Nature Conservancy Preserves

Status 3: An area having permanent protection from conversion of natural land cover for the majority of the area, but subject to extractive uses of either a broad, low-intensity type (e.g., logging, Off Highway Vehicle recreation) or localized intense type (e.g., mining). It also confers protection to federally listed endangered and threatened species throughout the area. Examples of Status 3: National Forests, BLM Lands, State Forests, some State Parks

Status 4: There are no known public or private institutional mandates or legally recognized easements or deed restrictions held by the managing entity to prevent conversion of natural habitat types to anthropogenic habitat types. The area generally allows conversion to unnatural land cover throughout or management intent is unknown. Examples of Status 4: Unknown areas, private lands, developed or agriculture areas

How these data were aggregated:

Boundaries, and their descriptors, available in spatial databases (i.e. shapefiles or geodatabase feature classes) from land management agencies are the desired and primary data sources in PAD-US. If these authoritative sources are unavailable, or the agency recommends another source, data may be incorporated by other aggregators such as non-governmental organizations. Data sources are tracked for each record in the PAD-US geodatabase (see below).

'Aggregator Source' describes the Aggregator (Organization) credited with data aggregation, version of PAD-US when the update occurred, feature class the data reside in (unless mixed), reference to the original source data file, and a reference to describe the State location to manage boundary inconsistencies between agency datasets (from State data-steward submissions only). 'Aggregator Source' is attributed in the format 'organization name_PADUSversion+featureclass_filename.filetype' (e.g. TNC_PADUS1_4_SecuredAreas2008.shp). State aggregations also include a reference to the State in the format 'organization name_PADUSversion_filename.filetype_StateUSPS'. Aggregators may not always be able to define the geodatabase feature class as data may be mixed (e.g. MNDNR_PADUS2_0_MN2015_PADUS_MN_1.gdb_MN, NJOGIS_PADUS2_0Fee_OSPRI_August2017_NJ). Organization acronyms are used and underscore replaces spaces. A data aggregator submits data in the PAD-US format or includes nonprofit aggregators managing regional or national datasets with required fields for PAD-US translation. USGS is identified as aggregator when data translation is required (e.g. USGS_PADUS2_0Fee_BLM_SMA_ADMU_Union). Information about PAD-US Data Stewards and the Source Data they provide can be found at http://www.protectedlands.net/data-stewards/. This information will be made available on the USGS PAD-US web pages soon.

The 'GIS Source' field in the PAD-US geodatabase identifies the source of spatial data the aggregator obtained (e.g. WYGF_whmas08.shp) for each record. Files names match original source data provided by managing agencies to increase update efficiency and data transparency. This field is in a state of transition to fully meet standards as the original 'GIS Source' is not always provided in aggregated datasets.

The 'GIS Source Date' describes the date (yyyy/mm/dd) GIS data was obtained by the data source for aggregation. This date represents the best available data the GIS source has at the time.


New GIS-Ready Topographic Map Style Template Released

Map Viewer Enhancements: Upgrades to The National Map Viewer increase the platform capabilities and user experience released in time to be highlighted at the Esri UC in San Diego.

A new GIS-ready topographic map style template is now available from the USGS National Geospatial Program. The “Topo TNM Style Template” can be readily used with the Topo Map Vector Data products and other data available for download from The National Map (TNM). The template and TNM data are intended to be used together to quickly provide an advanced Geographic Information Systems user with a fully customizable map in the style of US Topo maps using the most current TNM data available.

Highlights of the Topo TNM Style Template:

  • Mimics US Topo map design for symbology and labeling 24,000-scale
  • Includes data for tailoring to specific 7.5-minute cell
  • Tailorable to any geographic location where data is available for download from TNM
  • Customizable content, extent and design
  • ArcMap Map Document format (v10.0)

Symbolized layers within the template can be linked to data downloaded from TNM and include layers from TNM vector data themes of:

  • Transportation,
  • Hydrography,
  • Elevation Contours,
  • Geographic Names,
  • Governmental Units (Boundaries),
  • Structures, and
  • Woodland polygons.

Web Map Service layers in the template include orthoimagery and shaded relief services produced by the USGS, as well as a National Wetlands Inventory Web Map Service produced by the U.S. Fish and Wildlife Service. An ancillary file geodatabase, provided along with the template, contains a Military Grid Reference System feature class and a data table created by the National Geospatial Technical Operations Center containing 7.5-minute map cell names, UTM zones, and other information for use in tailoring the template to a specific 7.5-minute map. Instructional Documentation is available to help with tailoring the template.

This template may be used with any TNM data source available from the TNM Download Client and can easily be extended with data layers supported by ArcGIS according to end user needs. For best results in symbolization and labeling, it is recommended to be used with the Topo Map Vector Data products, and at scales between 1:18,000- and 1:36,000.

Topo Map Vector Data

The Geographic Names Information System. The GNIS is the official repository of domestic geographic names data the official vehicle for geographic names use by all departments of the Federal Government and the source for applying geographic names to Federal electronic and printed products of all types. TNM Derived Names is a filtered and enriched dataset intended specifically to be used in the Topo TNM Style Template for symbolizing and labeling named features. TNM Derived Names data are provided only in conjunction with Topo Map Vector Data products.

Topo TNM Style Template Disclaimer: Initial styling of this Map Template is provided by the U.S. Geological Survey (USGS). The USGS does not endorse any products created from the template.

To keep current with The National Map downloadable products and map services, visit The National Map launch page.

Questions or feedback regarding any of these changes can be submitted to [email protected]


Predictive Models of Cetacean Densities in the California Current Ecosystem, 2020b

To develop improved species distribution models (SDMs) and to update US West Coast cetacean stock abundance estimates, sighting data from NOAA&rsquos Southwest Fisheries Science Center 2018 California Current Ecosystem Survey were combined with previous line-transect survey data collected within the study area to create a robust modeling database spanning more than 25 years (1991&ndash2018). Habitat models were developed based on previously established methods that allow for the incorporation of segment-specific estimates of detection probability and included dynamic covariates from an ocean model calibrated to the California Current Ecosystem study area. In addition, recently-developed techniques for deriving more comprehensive estimates of uncertainty in SDM predictions were used to provide variance estimates for the model-based abundance estimates. SDMs were developed for short-beaked common dolphin (Delphinus delphis delphis), long-beaked common dolphin (Delphinus delphis bairdii), northern right whale dolphin (Lissodelphis borealis), Pacific white-sided dolphin (Lagenorhynchus obliquidens), striped dolphin (Stenella coeruleoalba), common bottlenose dolphin (Tursiops truncatus), Risso&rsquos dolphin (Grampus griseus), Dall&rsquos porpoise (Phocoenoides dalli), sperm whale (Physeter macrocephalus), blue whale (Balaenoptera musculus), fin whale (B. physalus), humpback whale (Megaptera novaeangliae), Baird&rsquos beaked whale (Berardius bairdii), and a &ldquosmall beaked whale guild&rdquo that included Mesoplodonts (Mesoplodon spp.) and Cuvier&rsquos beaked whale (Ziphius cavirostris). Sample sizes were also sufficient to develop the first model-based density estimates for minke whale (B. acutorostrata) in this study area.


CONCLUSIONS

Based on GIA&rsquos database containing more than 300 Paraíba tourmaline samples with known provenance, geographic origin determinations can be made using a variety of minor/trace element data when collected by highly precise and accurate methods. In the modern gemological laboratory, the weight of the origin determination rests overwhelmingly on trace element analysis by LA-ICP-MS. Paraíba tourmalines from Brazil, Mozambique, and Nigeria can, in most cases, be identified by their unique fingerprints of concentrations of trace elements such as Sr, Cu, Zn, Ga, Sn, and Pb. Additionally, the more recent find of Paraíba tourmaline belonging to the liddicoatite species can be identified through major element analysis. However, in a few cases &ldquoinconclusive&rdquo origin determinations may result when their trace element profiles do not match with any reference samples of known provenance. By improving the database with additional reference samples and conducting further research on analytical methods and statistical analyses, fewer Paraíba tourmalines will require an &ldquoinconclusive&rdquo call.

Dr. Katsurada is a senior staff gemologist at GIA in Tokyo. Mr. Sun is a research associate, and Dr. Breeding is a senior research scientist, at GIA in Carlsbad, California. Dr. Dutrow is the Williams Distinguished Alumni professor at Louisiana State University in Baton Rouge and a GIA governor.

Thorough and thoughtful peer reviews by Professor Darrell Henry at Louisiana State University, Dr. Claudio Milisenda at DSEF German Gem Lab, and an anonymous reviewer greatly improved the manuscript. Dr. Aaron Palke provided timely and important feedback. We thank Bill Barker, William Larson, Hussain Rezayee, Shane McClure, Chico Bank, Blue Sheppard, and the GIA Museum for providing many of the reference samples for this study. This paper benefited from National Science Foundation funding to BD (grant number EAR-1551434).

Abduriyim A., Kitawaki H. (2005) Gem News International: Cu- and Mn-bearing tourmaline&mdashMore production from Mozambique. G&G, Vol. 41, No. 4, pp. 360&ndash361.

Abduriyim A., Kitawaki H., Furuya M., Schwarz D. (2006) &ldquoParaíba&rdquo-type copper-bearing tourmaline from Brazil, Nigeria, and Mozambique: Chemical fingerprinting by LA-ICP-MS. G&G, Vol. 42, No. 1, pp. 4&ndash21, http://dx.doi.org/10.5741/GEMS.42.1.4

Beurlen H., de Moura O.J.M., Soares D.R., Da Silva M.R.R., Rhede D. (2011) Geochemical and geological controls on the genesis of gem-quality &ldquoParaíba tourmaline&rdquo in granitic pegmatites from northeastern Brazil. Canadian Mineralogist, Vol. 49, No. 1, pp. 277&ndash300, http://dx.doi.org/10.3749/canmin.49.1.277

Breeding C.M., Rockwell K., Laurs B.M. (2007) Gem News International: New Cu-bearing tourmaline from Nigeria. G&G, Vol. 43, No. 4, pp. 384&ndash385.

Dutrow B.L., Farnsworth-Pinkerton S., Henry D.J., McMillan N.J., Niepagen N. (2019) Copper-bearing tourmaline sources: Evidence from laser-induced breakdown spectroscopy (LIBS) and electron microprobe analyses (EMP). Geological Society of America Abstracts with Programs, p. 51.

Ertl A., Giester G., Schüssler U., Brätz H., Okrusch M., Tillmanns E., Bank H. (2013) Cu- and Mn-bearing tourmalines from Brazil and Mozambique: Crystal structures, chemistry and correlations. Mineralogy and Petrology, Vol. 107, No. 2, pp. 265&ndash279, http://dx.doi.org/10.1007/s00710-012-0234-6

Faye G.H., Manning P.G., Nickel E.H. (1968) The polarized optical absorption spectra of tourmaline, cordierite, chloritoid and vivianite: Ferrous-ferric electronic interaction as a source of pleochroism. American Mineralogist, Vol. 53, No. 7-8, pp. 1174&ndash1201.

Fritsch E., Shigley J.E., Rossman G.R., Mercer M.E., Muhlmeister S.M., Moon M. (1990) Gem-quality cuprian-elbaite tourmalines from São José da Batalha, Paraíba, Brazil. G&G, Vol. 26, No. 3, pp. 189&ndash205, http://dx.doi.org/10.5741/GEMS.26.3.189

Furuya M. (2007) Copper-bearing tourmalines from new deposits in Paraíba State, Brazil. G&G, Vol. 43, No. 3, pp. 236&ndash239, http://dx.doi.org/10.5741/GEMS.43.3.236

Henry D.J., Novák M., Hawthorne F.C., Ertl A., Dutrow B.L., Uher P., Pezzotta F. (2011) Nomenclature of the tourmaline-supergroup minerals. American Mineralogist, Vol. 96, No. 5&ndash6, pp. 895&ndash913, http://dx.doi.org/10.2138/am.2011.3636

Hsu T. (2018) Paraíba tourmaline from Brazil: The neon-blue burn. InColor, No. 39, pp. 42&ndash50.

Karampelas S., Klemm L. (2010) Gem News International: &ldquoNeon&rdquo blue-to-green Cu- and Mn-bearing liddicoatite tourmaline. G&G, Vol. 46, No. 4, pp. 323&ndash325.

Katsurada Y., Sun Z. (2017) Cuprian liddicoatite tourmaline. G&G, Vol. 53, No. 1, pp. 34&ndash41, http://dx.doi.org/10.5741/GEMS.53.1.34

Koivula J.I., Nagle K., Shen A.H., Owens P. (2009) Solution-generated pink color surrounding growth tubes and cracks in blue to blue-green copper-bearing tourmalines from Mozambique. G&G, Vol. 45, No. 1, pp. 45&ndash47, http://dx.doi.org/10.5741/ GEMS.45.1.44

Kröner A., Stern R.J. (2004) Pan-African orogeny. Encyclopedia of Geology, Vol. 1, Elsevier, Amsterdam, pp. 1&ndash12, http://dx.doi.org/10.1016/B0-12-369396-9/00431-7

Laboratory Manual Harmonisation Committee (LMHC) (2012) LMHC Information Sheet #6: &ldquoParaíba tourmaline&rdquo Version 7, https://static1.squarespace.com/static/5bfbb7e6cc8fed3bb9293bf3/t/5bfe92a90e2e72555d61eec3/1543410345434/LMHC+Information+Sheet_6_V7_2012.pdf

Laurs B.M., Zwaan J.C., Breeding C.M., Simmons W.B., Beaton D., Rijsdijk K.F., Befi R., Falster A.U. (2008) Copper-bearing (Paraíba-type) tourmaline from Mozambique. G&G, Vol. 44, No. 1, pp. 4&ndash30, http://dx.doi.org/10.5741/GEMS.44.1.4

Ludwig T., Marschall H.R., Pogge von Strandmann P.A.E., Shabaga B.M., Fayak M., Hawthorne F.C. (2011) A secondary ion mass spectrometry (SIMS) re-evaluation of B and Li isotopic compositions of Cu-bearing elbaite from three global localities. Mineralogical Magazine, Vol. 75, No. 4, pp. 2485&ndash2494, http://dx.doi.org/10.1180/minmag.2011.075.4.2485

Mattson S.M., Rossman G.R. (1987) Fe 2+ -Fe 3+ interactions in tourmaline. Physics and Chemistry of Minerals, Vol. 14, pp. 163&ndash171, http://dx.doi.org/10.1007/BF00308220

Merkel P.B., Breeding C.M. (2009) Spectral differentiation between copper and iron colorants in gem tourmalines. G&G,Vol. 45, No. 2, pp. 112&ndash119, http://dx.doi.org/10.5741/GEMS.45.2.112

Milisenda C.C. (2018a) Paraíba tourmaline revisited. InColor, No. 39, pp. 34&ndash41.

Milisenda C.C. (2018b) Gemstones and photoluminescence. G&G,Vol. 54, No. 3, p. 258.

Milisenda C.C., Müller S. (2017) REE photoluminescence in Paraíba type tourmaline from Mozambique. Abstract Proceedings, 35th International Gemmological Conference, Windhoek, Namibia, pp. 71&ndash73.

Okrusch M., Ertl A., Schüssler U., Tillmanns E., Brätz H., Bank H. (2016) Major- and trace-element composition of Paraíba-type tourmaline from Brazil, Mozambique and Nigeria. Journal of Gemmology, Vol. 35, No. 2, pp. 120&ndash139.

Peretti A., Bieri W.P., Reusser E., Hametner K., Günther D. (2009) Chemical variations in multicolored &ldquoParaíba-type&rdquo tourmalines from Brazil and Mozambique: Implications for origin and authenticity determination. Contributions to Gemology, Vol. 9, pp. 1&ndash77.

Pezzotta F. (2018) Mozambique Paraíba tourmaline deposits&mdashan update. InColor, No. 39, pp. 52&ndash56.


Watch the video: Retrieval of Gene Expression Profile or DataSets from NCBI GEO