Estimating proportional change in forest cover as a continuous variable from multi-year MODIS data

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• 作者：Daniel J. Hayes ; Warren B. Cohen ; Steven A. Sader ; Daniel E. Irwin
• 关键词：MODIS ; Regression models ; Tropical forests ; Land cover and land use change
• 刊名：Remote Sensing of Environment
• 出版年：2008
• 期刊代码：79_00344257
• 类别：ear
• 出版时间：18 March 2008
• 卷：112
• 期：3
• 页码：735-749
• 文件大小：720 K

摘要

This article describes a series of fundamental analyses designed to test and compare the utility of various MODIS data and products for detecting land cover change over a large area of the tropics. The approach for estimating proportional forest cover change as a continuous variable was based on a reduced major axis regression model. The model relates multispectral and multi-temporal MODIS data, transformed to optimize the spectral detection of vegetation changes, to reference change data sets derived from a Landsat data record for several study sites across the Central American region. Three MODIS data sets with diverse attributes were evaluated on model consistency, prediction accuracy and practical utility in estimating change in forest cover over multiple time intervals and spatial extents.