A change detection experiment using vegetation indices.

Abstract

Vegetation indices [m) have long been used in remote sens-ing for monitoring temporal changes associated with vegeta-tion. In this study, seven vegetation indices were compared for their value in vegetation and land-cover change detection in part of the State of Chiapas, Mexico. VI values were devel-oped from three different dates of Landsat Multispectral Scanner [MSS) data. The study suggested that (1) if normali-zation techniques were used, then all seven vegetation indi-ces could be grouped into three categories according to their computational procedures; (2) vegetation indices in different categories had significantly different statistical characteris-tics, and only NDVI showed normal distribution histograms; and [3), of the three vegetation index groups, the NDVI group was least affected b y topographic factors i n this study. Com-parisons of these techniques found that the NDVI difference technique demonstrated the best vegetation change detection as judged b y laboratory and field results.