Study on land cover change detection method based on NDVI time series batasets: Change detection indexes design

Abstract

The Normalized Difference Vegetation Index (NDVI) time-series database, derived from NOAA/AVHRR, SPOT/VGT etc., is increasingly being recognized as a valuable data source for extracting land cover and its change information at global, continental and large regional scale. However, existing approaches present considerable difficulties in taking full advantage the NDVI dataset for land cover change detection. Based on the assumptions that different land cover types have different NDVI temporal profiles, we analyze the existing change detection indexes and develop a new land cover change detection method based on Lance distance and a cross correlogram spectral matching (CCSM) technique. The new method takes the shape and value features of NDVI profile curve into consideration. From the simulation experiment results, we have demonstrated that : (1) the new method can reduce the effects of "false" changes inducted by vegetation phenology changes, climate events, atmospheric variability and sensor noise in different years, and (2) it is similarly sensitive to all kinds of land cover changes no matter where the changes have occurred. © 2005 IEEE.