Monitoring land-cover change is often done by simple overlay of two classified maps from different dates. However, such analysis tends to overestimate the rate of change. Main error sources are the mis-registration between classified maps and their thematic accuracies. This study proposes a change detection method with morphological post-processing to improve change detection accuracy in comparison with traditional post-classification by taking into account these error sources.

Forest dynamics, such as deforestation, reforestation and afforestation, could be caused by the natural and human-induced disturbances. Traditional methods rarely quantify the history of such disturbances along a continuous temporal trajectory; yet, such disturbance history often determines system course and evolution. We adopted a retrospective perspective to study system history by implementing a newly proposed entropy index.

Satellite imagery with fine spectral and spatial resolution and high temporal resolution provides a unique opportunity to map and monitor biodiversity. The aim of this article is (i) to review the state of the use of high-resolution remote sensing for ecological studies in the Indian Himalayan Region (IHR) and (ii) to suggest further potential avenues of research in the region using this technology.