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The Sundarban, covering about one million ha in the delta of the rivers Ganga, Brahmaputra and Meghna at the point where it merges with the Bay of Bengal, is the single largest block of tidal halophytic mangrove forest in the world shared between Bangladesh (62%) and India (38%), which supports a large, biodiversity-rich unique ecosystem. The larger part (62%) is situated in the southwest corner of Bangladesh located between 21°30 ‘ N to 22°30 ‘N and longitude 89° E to 90° E. The forest has a unique biodiversity comprising 334 species of plants.

The mangroves of the Sundarban are unique when compared to non-deltaic coastal mangrove forest, the prime species are sundri Heritiera fames and gewa Excoecaria agallocha. The Sundarban can be classified as moist tropical seral forest, comprising a mosaic of beach forest and tidal forest. Of the latter, there are four types: low mangrove forests, tree mangrove forests, salt-water Heritiera forests and freshwater Heritiera forests. Sundarban West occurs within the salt-water zone, which supports sparse Ecoecaria agallocha, a dense understory of Ceriops, and dense patches of hantal palm Phoenixpaludosa on drier soils.

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Dhundal and passur Xylocalpus spp. , and Bruguiera occur sporadically throughout the area. Sundri and gewa cover most of the Sundarban but Oryza coarctata, Nypa fruticans and Imperata cylindrica are prevalent on mud flats. Large stands of keora Sonneratia apetala are found on newly accreted mudbanks and provide important wildlife habitat. (MS Rahman). The main objective of this study is to develop an appropriate classification map to represent the biomass content/forest cover in this area, to evaluate the forest cover change ( sundori, gewa and others ) in study area for the period of 1980- 2012 .

This paper quantifies biomass content /mangrove forest cover change in Sundarban area . The mangrove forests in this area are intermixed with a complex network of tidal rivers and tributaries. We measured biomass content/forest cover change using several different image processing methods. Satellite image processing and spatial analysis have been shown to be effective methods for quantifying mangrove forest cover (Ramsey and Jensen, 1995; Long and Skewes, 1996; Blasco et al. , 1998; Davis and Jensen, 1998). Describing the reasons for changes in the spatial distribution of a angrove ecosystem over time is an extremely complex task. Changes in mangrove forests are multi dimensional; therefore we must consider biotic, geomorphic, and anthropogenic influences. Remote sensing could play an important and effective role in the assessment and monitoring of biomass content/mangrove forest cover dynamics. The use of remotely sensed data offers many advantages including synoptic coverage, availability of low cost or free satellite data, availability of historical satellite data. The methods mainly used in our study include interpretation and analysis of satellite images and geographic information system (GIS).

Image analysis and GIS techniques have been used extensively, and a site specific geospatial database would be developed accordingly. Initial temporal changes can captured from visual interpretation of two time series satellite images. This study quantifies forest cover change from 1972 to 2012 using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper plus. Here we will use Normalize Differential Vegetation Index (NDVI) techniques and Maxium Likelyhood Classifier. Key Word: Remote sensing, Biomass content, change detection, NDVI, Landsat TM

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