@book{6139,
	author = {Sebastian Joy (91717007)},
	title = {Assessment and monitoring of long-term changes in mangroves of sundarbans using remote sensing data and GIS},
	note = {Mangroves are undergoing constant short term and long-term changes due to its dynamic
nature and to a greater extent through various natural and anthropogenic influences.
Sundarbans is the largest contiguous mangrove forest in the world. Mangroves show
conspicuous tone and texture in different band combinations in optical satellite remote
sensing data. Multi-temporal remote sensing data along with the GIS supports mapping,
change analysis and monitoring of mangroves. The present study assesses vegetation
dynamics in the mangroves over the last four decades in the Sundarbans, using Landsat MSS,
TM, ETM+ and OLI images. Hybrid classification technique was used to map mangroves.
There were inter-period variations (1975-1990-2000-2010-2017), both positive and negative,
those are related mainly to the dynamics of the mangrove vegetation structure, afforestation,
accretion, erosion, aquaculture and agriculture. Over the 42 years, the net change was
negative, which was estimated as about 6% of mangrove area. The annual net rate of
deforestation in mangroves has been estimated as 0.2% from 1975 to 2010. The mangroves of
Sundarbans have not changed significantly from 2010 to 2017 indicates increased
conservation measures. Validation of distribution of mangroves has been carried out based on
historical Google earth images and with other existing regional classified datasets. This
measure was helped to evaluate the map qualitatively and improve the overall classification
accuracy. This study has developed a spatially explicit database would stand as baseline for
subsequent monitoring and assessment. 
The study also focused on characterization and identifying the spatial distribution of
mangroves on the basis of ALOS-PALSAR mosaic 25 m resolution. Methodology includes
primarily the collection of ALOS-PALSAR data, preprocessing of converting DN to NRCS,
filtering, collecting region of interest that distributed over Sundarbans region,
characterization and classification. The result indicates that the mangroves are having an
average of HH values between -12.27 dB and -3.55 dB and average of HV values between    
-17.84 dB and -11.17 dB also within this range it is covering other vegetations along with the
mangroves. HV. Mangrove has significant HV value, that makes it separately identifiable
from other vegetation, on comparing with HH values. The microwave remote sensing data
can be used as a complementary source for the analysis of vegetation along with optical data. }
}