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Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and ChallengesThe compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 m. In this article, we describe the methods to create global products of forest cover and cover change at Landsat resolutions. Nevertheless, there are many challenges in ensuring the creation of high-quality products. And we propose various ways in which the challenges can be overcome. Among the challenges are the need for atmospheric correction, incorrect calibration coefficients in some of the data-sets, the different phenologies between compilations, the need for terrain correction, the lack of consistent reference data for training and accuracy assessment, and the need for highly automated characterization and change detection. We propose and evaluate the creation and use of surface reflectance products, improved selection of scenes to reduce phenological differences, terrain illumination correction, automated training selection, and the use of information extraction procedures robust to errors in training data along with several other issues. At several stages we use Moderate Resolution Spectroradiometer data and products to assist our analysis. A global working prototype product of forest cover and forest cover change is included.
Document ID
20140013402
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Townshend, John R.
(Maryland Univ. College Park, MD, United States)
Masek, Jeffrey G.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Huang, ChengQuan
(Maryland Univ. College Park, MD, United States)
Vermote, Eric F.
(Maryland Univ. College Park, MD, United States)
Gao, Feng
(Department of Agriculture Beltsville, MD, United States)
Channan, Saurabh
(Maryland Univ. College Park, MD, United States)
Sexton, Joseph O.
(Maryland Univ. College Park, MD, United States)
Feng, Min
(Maryland Univ. College Park, MD, United States)
Narasimhan, Ramghuram
(Maryland Univ. College Park, MD, United States)
Kim, Dohyung
(Maryland Univ. College Park, MD, United States)
Song, Kuan
(Maryland Univ. College Park, MD, United States)
Song, Danxia
(Maryland Univ. College Park, MD, United States)
Song, Xiao-Peng
(Maryland Univ. College Park, MD, United States)
Noojipady, Praveen
(Maryland Univ. College Park, MD, United States)
Tan, Bin
(Earth Resources Technology, Inc. Laruel, MD, United States)
Hansen, Matthew C.
(Maryland Univ. College Park, MD, United States)
Li, Mengxue
(Maryland Univ. College Park, MD, United States)
Wolfe, Robert E.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
November 6, 2014
Publication Date
August 23, 2012
Publication Information
Publication: International Journal of Digital Earth
Volume: 5
Issue: 5
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN11586
Funding Number(s)
CONTRACT_GRANT: NNX08AP33A
CONTRACT_GRANT: NNG09HP10C
CONTRACT_GRANT: NNX08AN72G
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Global
forest
Characterization
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