Change detection of forest areas using object-based image analysis

In environmental studies the use of remote sensing is becoming frequent. In the 1970s and 1980s satellite images were mostly used in simple interpretations or as a map background. In the past three decades satellite imagery has been used successfully for weather, geographical and geological applications. Deforestation is one of the major contributors to global warming and climate change. An elevation in the greenhouse gases that halo our planet is because of the global warming. The effect of global warming is further exacerbated by deforestation because the removal of densely forested areas decreases the number of the CO2 consuming vegetation. Indirectly, Deforestation disturbs the delicate balance of CO2, consumed by trees and produced by different sources. Change detection from remotely sensed images is a process that utilizes a pair of images acquired over the same geographical area at different times to identify the changes that may have occurred between the considered acquisition dates. Because of insensitiveness to atmosphere (particularly rain and clouds), the SAR system is more suitable for this purpose than other remote sensing devices, employed in change detection for land use and land cover. Hence, in the past decades, it has been successfully used in many applications such as agricultural surveys, environmental monitoring, damage assessment, urban studies, and forest monitoring.