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CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/1783
Version1
Project
Published2020-09-17
Updated2020-09-17
Usage11 downloads

Description

This dataset provides annual maps of land cover classes for the Colombian Amazon from 2001 through 2016 that were created by classifying time segments detected by the Continuous Change Detection and Classification (CCDC) algorithm. The CCDC algorithm detected changes in Landsat pixel surface reflectance across the time series, and the time segments were classified into land cover types using a Random Forest classifier and manually collected training data. Annual maps of land cover were created for each Landsat scene and then post-processed and mosaicked. Land cover types include unclassified, forest, natural grasslands, urban, pastures, secondary forest, water, or highly reflective surfaces. The training data are not included with this dataset.

Science Keywords

  • HUMAN DIMENSIONS
  • HABITAT CONVERSION/FRAGMENTATION
  • DEFORESTATION
  • LAND SURFACE
  • LAND USE/LAND COVER
  • LAND USE/LAND COVER CLASSIFICATION
  • LAND SURFACE
  • SURFACE RADIATIVE PROPERTIES
  • REFLECTANCE

Data Use and Citation

This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use Policy.

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Crosscite Citation Formatter
Arévalo, P. 2020. CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1783

See our Data Use and Citation Policy for more information.

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Dataset has 1 companion files.

  • Landcover_Colombian_Amazon.pdf