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Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation?

Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation? Tucker and Townshend (2000) conclude that 'wall-to-wall coverage is needed to avoid gross errors in estimations of deforestation rates' because tropical deforestation is concentrated along roads and rivers. They specifically question the reliability of the 10% sample of Landsat sensor scenes used in the global remote sensing survey conducted by the Food and Agricultural Organization (FAO) of the United Nations. They base their conclusion on simulations with data from Bolivia, Columbia and Peru, in which the size of a 10% sample is 4 @ n h 6 Landsat sensor scenes. However, their conclusion is not valid when extrapolated to larger sample sizes (e.g. n S 40), such as those employed by the FAO and the European Commission for global and pantropical assessments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Remote Sensing Taylor & Francis

Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation?

International Journal of Remote Sensing , Volume 24 (6): 4 – Jan 1, 2003
4 pages

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References (6)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1366-5901
DOI
10.1080/0143116021000057135
Publisher site
See Article on Publisher Site

Abstract

Tucker and Townshend (2000) conclude that 'wall-to-wall coverage is needed to avoid gross errors in estimations of deforestation rates' because tropical deforestation is concentrated along roads and rivers. They specifically question the reliability of the 10% sample of Landsat sensor scenes used in the global remote sensing survey conducted by the Food and Agricultural Organization (FAO) of the United Nations. They base their conclusion on simulations with data from Bolivia, Columbia and Peru, in which the size of a 10% sample is 4 @ n h 6 Landsat sensor scenes. However, their conclusion is not valid when extrapolated to larger sample sizes (e.g. n S 40), such as those employed by the FAO and the European Commission for global and pantropical assessments.

Journal

International Journal of Remote SensingTaylor & Francis

Published: Jan 1, 2003

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