首页> 外文会议>Asian conference on remote sensing >APPLICATION OF INTEGRATED REMOTE SENSING AND GEOGRAPHICAL INFORMATION SYSTEM TECHNIQUES IN ASSESSMENT OF COASTAL EROSION VULNERABILITY
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APPLICATION OF INTEGRATED REMOTE SENSING AND GEOGRAPHICAL INFORMATION SYSTEM TECHNIQUES IN ASSESSMENT OF COASTAL EROSION VULNERABILITY

机译:集成遥感和地理信息系统技术在沿海侵蚀脆弱性评估中​​的应用

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The primary objective of this study was to attempt an assessment of coastal erosion vulnerability of a coast using integrated remote sensing and geographical information system techniques. A quantitative measure, 'coastal erosion vulnerability index (CEVI)', was evaluated by integrating multiple data, viz., erosion-accretion, landuse / landcover and population density on a geographical information system (GIS) platform. The CEVI value was calculated over a 65 km long coastal stretch, located between Rasulpur in Midnapuir district of West Bengal and Subamarekha in Balasore district of Orissa, on the eastern coast of India. The area includes both erosional and accretionary beaches. Since the study area lies over a tourism site, several man-made structures, such as seawall, groin and pylon, had been constructed at different periods for possible prevention of erosion. Multi-resolution Landsat satellite imagery of 1972, 1980, 1990, 2000 and 2010 were used for identifying shoreline positions at ten year intervals. Shoreline changes show accretion up-drift of artificial structures and erosion along down-drift of structures. These changes were divided into four categories, from 'high erosion' to 'high accretion'. Satellite data were also used to map landuse / landcover, which were categorized into four divisions, 'very high capital' to 'no capital' land use. Population density maps of coastal villages in the study area were prepared using Census data, and divided into four categories, from 'high density area' to 'very low density area'. Finally, coastal erosion vulnerability index (CEVI) was calculated by integrating shoreline retreat with land use type and population density. Zones of vulnerabilities of different magnitudes, namely, 'very high', 'high', 'moderate' and 'low', had been identified. The result indicates that maximum vulnerability values are around artificial structures. The coastal erosion vulnerability index map prepared from this study can be suitably used for proper planning and management of this coastal region.
机译:本研究的主要目标是尝试使用集成遥感和地理信息系统技术进行沿海侵蚀脆弱性的评估。通过集成多个数据,侵蚀 - 吸收,土地使用,土地使用,土地利用,土地利用,土地利用,土地利用和人口密度,评估了定量措施,“沿海侵蚀漏洞指数(CEVI)”进行了评估了地理信息系统(GIS)平台。 CEVI价值计算在65公里长的沿海拉伸,位于印度奥斯塔州兰萨雷地区西孟加拉邦和萨拉莫雷萨·萨拉玛雷萨郡的Rasulpur之间。该地区包括侵蚀性和侵蚀性海滩。由于研究区域位于旅游部位,因此在不同的时期构建了几个人造的结构,例如海堤,腹股沟和塔架,以便可能预防侵蚀。 1972年,1980年,1990年,2000年和2010年的多分辨率Landsat卫星图像用于识别十年间隔的海岸线职位。海岸线变化显示人工结构和沿着结构的下漂流的吸收浮动。这些变化分为四类,从“高侵蚀”到“高侵蚀”。卫星数据也用于映射土地利用/地图,分为四个部门,“非常高的资本”到“无资本”的土地使用。使用人口普查数据制备研究区域沿海村庄的人口密度图,并分为四类,从“高密度区域”到“非常低密度”。最后,通过将海岸线撤退与土地利用类型和人口密度集成来计算沿海侵蚀脆弱性指数(CEVI)。已经确定了不同大小的漏洞,即“非常高”,“高”,“中等”和“低”。结果表明最大漏洞值是人工结构。本研究准备的沿海侵蚀脆弱性指数地图可以适用于此沿海地区的适当规划和管理。

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