Predictive assessment on landscape and coastal erosion of Bangladesh using geospatial techniques

被引:18
作者
Islam, Md Mozahidul [1 ]
Rahman, Md Saifur [2 ]
Kabir, Md Alamgir [3 ]
Islam, Md Nazrul [4 ]
Chowdhury, Ruhul Mohaiman [5 ]
机构
[1] Independent Univ, Dept Environm Management, SESM, Bashundhara R-A, Dhaka 1229, Bangladesh
[2] Patuakhali Sci & Technol Univ, Dept Geoinformat Sci & Earth Observat, Dumki 8602, Patuakhali, Bangladesh
[3] Patuakhali Sci & Technol Univ Dumki, Dept Agroforestry, Patuakhali 8602, Bangladesh
[4] Jahangirnagar Univ, Dept Geog & Environm, Dhaka 1342, Bangladesh
[5] Bangladesh Forest Dept, Sustainable Forests & Livelihoods SUFAL Project, Dhaka 1215, Bangladesh
关键词
LULC; Sub-district; Accretion-erosion; Mangrove forest; Conversion; LAND-COVER CLASSIFICATION; CLIMATE; RIVER;
D O I
10.1016/j.rsase.2019.100277
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Coastal erosion, land use and land cover (LULC) changes analysis using remote sensing is a dynamic, relatively low cost based precise method using now a day. Coastal districts of Bangladesh occupied by naturally grown mangrove forest which are susceptible to rapid land cover (LC) changes and natural erosion. Barguna and Patuakhali districts of Bangladesh deserve special attention for conserving coastal mangrove forest named Tengragiri Wildlife Sanctuary and variety of human forces income. The core objective of this research is to analyze the LULC change along with coastal erosion analysis from 2000 to 2017. Combination of four years Landsat satellite image analysis, primary field data, geo-tag photography, secondary information, utilization of forest carbon inventory 2015 data, and semi-structured questionnaire are the key approaches adopted in the study. K-means cluster based unsupervised and maximum likelihood supervised classification by using ERDAS Imagine 2014 found the total study area is 33,361 ha. Random sampling (40 points/class) based accuracy assessment and verification by google earth pro 7.1 found overall accuracy 88.15% and Kappa coefficient is 0.867. Python coding program and overlay operation tested for conversion analysis any found weighted overlay provide best results. An intensive RS analysis of 33,564 ha mangrove forest and community landscapes generated six (6) distinct land cover class and sub-classes, e.g. Forest, agriculture & grassland, plantation, sandbar, settlement and waterbody. During 2000-2017, agriculture and grassland were decreasing 23 ha/year. Out of 11,831 ha (in 2000) Agri-grass land 9,326 ha remained intact while remaining 2,246 ha converted to settlement mixed with homestead plantation class. This study also presents the landscape erosion-accretion due to natural, quasi-natural and anthropogenic interventions which shows that, along the river flow and at the confluence at the Nishanbaria Union (local name Khouttar Char & Fakir hat) to lower side of the Tengragiri WS locations are susceptible to high trend of land erosion whereas accretions are prominent on the reverse sides named Baliatali Union, Barabagi Union and so on. These results of the study and developed maps will be helpful for the community people, line departments, national and international policy maker and the researchers' community for monitoring coastal geomorphology including erosion and accretion of this landmass.
引用
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页数:10
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