Overview
DOI | https://doi.org/10.3334/ORNLDAAC/1035 |
---|---|
Version | 1 |
Project | |
Published | 2011-08-22 |
Updated | 2017-07-06 |
Usage | 1712 downloads |
Description
This data set, LBA-ECO LC-15 Vegetation Cover Types from MODIS, 1-km, Amazon Basin: 2000-2001, contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Earth Observing System,Terra (AM-1) satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin.
Science Keywords
- LAND SURFACE
- LAND USE/LAND COVER
- LAND USE/LAND COVER CLASSIFICATION
- LAND SURFACE
- LAND USE/LAND COVER
- LAND USE CLASSES
- BIOSPHERE
- VEGETATION
- VEGETATION COVER
Data Use and Citation
This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use Policy. See our Data Use and Citation Policy for more information.
Data Files
Sign in to download files.
Companion Files
Sign in to download files.
Dataset Companion Files
Dataset has 1 companion files.
- LC15_MODIS_TreeCover.pdf
Visualize and Subset Data
Download customized subsets in user-selected projection and format using the Spatial Data Access Tool.