Steven A. Sader

TL;DR: In this paper, a simple and relatively accurate technique for classifying time-series Landsat Thematic Mapper (TM) imagery to detect levels of forest harvest is the topic of this research.

TL;DR: In this paper, the authors compared multitemporal normalized difference moisture index (NDMI) and tasseled cap wetness (TCW) data sets and compared their statistical relationships and relative efficiencies in detecting forest disturbances associated with forest type and harvest intensity at five, two and one year Landsat acquisition intervals.

TL;DR: Forest area change associated with life zones, slope gradients, and transportation networks was examined within the framework of a geographically referenced data base for Costa Rica between 1940 and 1983 to quantitatively assess forest change dynamics.

TL;DR: In this article, three change detection methods were evaluated: normalized difference vegetation index (NDVI) image differencing, principal component analysis, and RGB-NDVI change detection.

TL;DR: In this article, the feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated and it was shown that NDVI differences were not detectable for successional forests older than approximately 15-20 years.