Editorial Type:
Article
Article Type:
Research Article

Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm

M. C. Hansen Department of Geography, University of Maryland, College Park, Maryland

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R. S. DeFries Department of Geography, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland

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J. R. G. Townshend Department of Geography, and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland

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M. Carroll Department of Geography, University of Maryland, College Park, Maryland

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C. Dimiceli Department of Geography, University of Maryland, College Park, Maryland

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R. A. Sohlberg Department of Geography, University of Maryland, College Park, Maryland

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Print Publication:
01 Oct 2003
DOI:
https://doi.org/10.1175/1087-3562(2003)007<0001:GPTCAA>2.0.CO;2
Page(s):
1–15
Restricted access

Abstract

The first results of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field algorithm's global percent tree cover are presented. Percent tree cover per 500-m MODIS pixel is estimated using a supervised regression tree algorithm. Data derived from the MODIS visible bands contribute the most to discriminating tree cover. The results show that MODIS data yield greater spatial detail in the characterization of tree cover compared to past efforts using AVHRR data. This finer-scale depiction should allow for using successive tree cover maps in change detection studies at the global scale. Initial validation efforts show a reasonable relationship between the MODIS-estimated tree cover and tree cover from validation sites.

* Corresponding author address: Dr. M. C. Hansen, Department of Geography, University of Maryland, College Park, College Park, MD 20742.mhansen@Glue.umd.edu

Abstract

The first results of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field algorithm's global percent tree cover are presented. Percent tree cover per 500-m MODIS pixel is estimated using a supervised regression tree algorithm. Data derived from the MODIS visible bands contribute the most to discriminating tree cover. The results show that MODIS data yield greater spatial detail in the characterization of tree cover compared to past efforts using AVHRR data. This finer-scale depiction should allow for using successive tree cover maps in change detection studies at the global scale. Initial validation efforts show a reasonable relationship between the MODIS-estimated tree cover and tree cover from validation sites.

* Corresponding author address: Dr. M. C. Hansen, Department of Geography, University of Maryland, College Park, College Park, MD 20742.mhansen@Glue.umd.edu

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