LBA-ECO LC-22 Land Cover from MODIS Vegetation Indices, Mato Grosso, Brazil

Description

This data set, LBA-ECO LC-22 Land Cover from MODIS Vegetation Indices, Mato Grosso, Brazil, provides land cover classifications for Mato Grosso, Brazil, for the years 2000-2001 and 2003-2004. The classifications were derived from annual vegetation phenology information from a time series of Collection 4, 16-day MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI) vegetation data, at 250-m resolution. A decision tree classifier was trained using field observations and Landsat TM data of land cover from 2003-2004 to identify seven land-cover classes. The classifier was applied to the 2000-2001 and 2003-2004 MODIS ENVI and EVI data. There are two GeoTIFF (.tif) files with this data set.

Resources

Name Format Description Link
21 ORNL DAAC Data Set Documentation https://daac.ornl.gov/LBA/guides/LC22_MODIS_Phenology_Mato_Grosso.html
33 White paper about this data set. https://data.ornldaac.earthdata.nasa.gov/public/lba/land_use_land_cover_change/LC22_MODIS_Phenology_Mato_Grosso/comp/LC22_MODIS_Phenology_Mato_Grosso.pdf
34 Browse Image https://daac.ornl.gov/graphics/browse/sdat-tds/1185_1_fit.png
21 Search results for publications that cite this dataset by its DOI. https://scholar.google.com/scholar?q=10.3334%2FORNLDAAC%2F1185
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/daacdata/lba/land_use_land_cover_change/LC22_MODIS_Phenology_Mato_Grosso/
21 Data set Landing Page DOI URL https://doi.org/10.3334/ORNLDAAC/1185
33 Data set documentation PDF. https://data.ornldaac.earthdata.nasa.gov/public/lba/land_use_land_cover_change/LC22_MODIS_Phenology_Mato_Grosso/comp/morton_mato_grosso_land_cover_chapter_lba_archive.pdf
21 Web Coverage Service for this collection. https://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=1185

Tags

  • land-use-land-cover
  • land-surface
  • national-geospatial-data-asset
  • ngda
  • earth-science

Topics

Categories