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 fi res is very important in tropical countries like
India where 55 percent of the total forest covers is prone to
fi res annually causing adverse ecological, economic and
social impacts. Studies on the impacts of tropical wildfi res
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
fi rst compare pixel values with different threshold and
convert pixels as dry. Apply watershed algorithm for the
modifi ed 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.