Descriptive Study and Analysis of Forest Change detection techniques using Satellite Images

Forest is considered as an important part in context to the environment. The major purpose is to inhale carbon dioxide and generate oxygen in their cycle of photosynthesis for maintaining a balance and healthy atmosphere. Examination of environmental disasters, such as biodiversity loss, deforestation, depletion of natural resources, etc., necessitates the computation of continuous change detection in the forest. Nowadays, land cover change analysis is performed using satellite images. Several techniques are introduced for forest change detection, but missing data in the satellite images is a serious problem due to artifacts, cloud occlusion, and so on. Thus, techniques handling missing data for forest change detection are essential. As a result, this survey provides a review of unique forest change detection mechanisms. Therefore, this paper presents a complete analysis of 25 papers presenting a forest change detection methods, like Machine learning techniques, Pixel-based techiques. In addition, a detailed investigation are carried out based on the performance measures, images adapted, datasets used, evaluation metrics, and accuracy range. Finally, the issues faced by different forest change detection methods are offered to extend the researchers to form enhanced role in considerable detection methods.