Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Geospatial data for the Vegetation Mapping Inventory Project of Canyon De Chelly National Monument

Metadata Updated: October 23, 2025

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes, 53 base map classes, which consist of associations and park specials classified with the quantitative analysis, additional associations noted during photointerpretation, non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date September 12, 2025
Metadata Updated Date October 23, 2025

Metadata Source

Harvested from DOI NPS DCAT-US

Additional Metadata

Resource Type Dataset
Metadata Created Date September 12, 2025
Metadata Updated Date October 23, 2025
Publisher National Park Service
Maintainer
Identifier http://datainventory.doi.gov/id/dataset/nps-datastore-2233252
Data First Published 2010-04-01T00:00:00Z
Data Last Modified 2010-04-01T00:00:00Z
Category geospatial
Public Access Level public
Bureau Code 010:24
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://ddi.doi.gov/nps-data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id c949ecd5-08b8-481f-8b36-6d599555473a
Harvest Source Id d917c1a9-26b7-43ea-b8c5-c77ec750a850
Harvest Source Title DOI NPS DCAT-US
Homepage URL https://irma.nps.gov/DataStore/Reference/Profile/2233252
Metadata Type geospatial
Old Spatial -113.9792,33.3451653,-104.875839,38.553688
Program Code 010:119, 010:118
Source Datajson Identifier True
Source Hash 403d192bd0a9118bd8d52d78ccc1a395f570950c138c5a82747de02f49d7c504
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -113.9792, 33.3451653, -113.9792, 38.553688, -104.875839, 38.553688, -104.875839, 33.3451653, -113.9792, 33.3451653}

Didn't find what you're looking for? Suggest a dataset here.