Journal of Theoretical and Computational Science · 2015 · 10 citations · 38 references
Natural ResourcesEarth SciencesForestryForest ManagementRemote SensingTerrestrial EcologyLand Cover Change DetectionLand Use Change DetectionRemote Sensing Change DetectionVegetation Change DetectionVegetation IndicesVegetation MonitoringForest-cover ChangeLand Cover AnalysisLand Use AnalysisMangrove Change DetectionMangrove Land Cover ChangeMangrove Remote SensingMaximum Likelihood ClassificationSea Level Rise Impacts On Mangroves
This paper quantifies the changes and present status of mangrove forest in Indian part of Sundarban from 1975 to 2014 using Landsat MSS (1975), TM (1990), ETM (2002) and OLM (2014) satellite imageries. The study used two image processing techniques: Maximum Likelihood Classification for the Land use and land cover analysis and NDVI for the vegetation characteristics and their temporal changes. The research found that the area of mangrove gradually decreases from 203752 hector (44%) to 132723 hector (31 %) and the barren land increases from 15078 hector (2.86 %) to 37247 hector (7.12%) due to natural ( sea level rise, salinization etc.) and anthropogenic (livelihood collection and shrimp farming etc.) disturbances and continuous land reclamation. Other land use categories like agriculture, water body, and sand deposition have approximately remained constant. The NDVI values were changed significantly only in 1990 due to the landward migration and defragmentation of mangrove forest. However, the paper signifies that the forest cover is constantly evolving due to deforestation, aggradation, erosion and forest rehabilitation programs in the Indian Sundarban.
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A 20th century acceleration in global sea‐level rise
John Church, Neil J. White · Geophysical Research Letters · 2006 · 1.6K citations · Full text
Organic and Semiorganic Nonlinear Optical Materials
Minhua Jiang, Qi Fang · Advanced Materials · 1999 · 394 citations · Full text