Abstract
Abstract Change-vector analysis in multi-temporal space is a powerful tool to analyse the nature and magnitude of land-cover change. The change vector compares the difference in the time-trajectory of a biophysical indicator for successive time periods. This change detection method is applied to three remotely-sensed indicators of land-surface conditions—vegetation index, surface temperature and spatial structure—in order to improve the capability to detect and categorize subtle forms of land-cover change. It is tested in a region of West Africa, using multi-temporal Local Area Coverage imagery obtained by the Advanced Very-High Resolution Radiometer on NOAA-9 and NOAA-II orbiting platforms. The three indicators show a low degree of redundancy and detect different land-cover change processes, which operate at different time scales. Change vector analysis is being developed for application to the land-cover change product to be produced using NASA's Moderate-Resolution Imaging Spectroradiometer instrument, scheduled for flight in 1998 and 2000on EOS-AM and -PM platforms.
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