Assessment of sparse forest and fire detection using threshold watershed algorithm

Fire, a natural disaster, has significant effects on ecosystems and plays a major role in deforestation, and it is a major source of trace gases, aerosol etc,. Remote sensing is a valuable data source to investigate different phases of fire management. Monitoring and management of forest fires is very important in tropical countries like India where 55 percent of the total forest covers is prone to fires annually causing adverse ecological, economic and social impacts. Studies on the impacts of tropical wildfires on the environment indicated Satellite remote sensing plays a key role in estimating loss of the forest cover and land cover change. in the existing watershed algorithm it encounters many problems such as over segmentation, poor detection of segmented areas. In the proposed system first compare pixel values with different threshold and convert pixels as dry. Apply watershed algorithm for the modified data. It is able to provide the information about sparse and high dry regions accurately and up-to-date, over wide areas, and repeatedly over the time.