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normalizing landsat and aster data using modis data products for forest change detectionMonitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.
Document ID
20110015249
Document Type
Conference Paper
Authors
Gao, Feng
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Masek, Jeffrey G.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Wolfe, Robert E.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Tan, Bin
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 25, 2013
Publication Date
July 25, 2010
Subject Category
Earth Resources and Remote Sensing
Report/Patent Number
GSFC.CPR.4776.2011
Meeting Information
International Geoscience and Remote Sensing Symposium (IGARSS)(Honolulu, HI)
Distribution Limits
Public
Copyright
Other