Weighted Linear Combination Procedures with GIS and Remote Sensing in Flood Vulnerability Analysis of Abeokuta Metropolis in Nigeria

J. Oyedepo, J. Adegboyega, D. E. Oluyege, E. Babajide
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引用次数: 1

Abstract

The study offered the opportunity for an evaluation of the role of Remote Sensing and Geospatial techniques in flood disaster risk management and development of spatial decision support system for flood risk assessment and management in Abeokuta metropolis. Datasets used includes cloud free high resolution satellite images and Shuttle Radar Topographic Mission (SRTM) data downloaded from earth explorer site. Soil data used was obtained from Food and Agriculture Organization (FAO’s) Harmonised World Soil Database, while rainfall data was obtained from the Climate Hazards Group InfraRed Precipitation Station. Maps of flood enhancing factors namely: soil types, rainfall intensity, drainage density and topography were created in Geographic Information Systems using same scale of 1: 50,000 and Geographic coordinate system (WGS 1984). All maps were produced in raster format with the same cell grid cell size of 0.0028 mm. They were then subjected to weighting by ranking and Multi-Criteria Analysis (MCA) using the Weighted Linear Combination. The study identified topography and land use as key factors contributing to flooding within Abeokuta metropolis. Obstruction of natural drainage channels by buildings aggravates disasters from flash flood events.
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基于GIS和遥感的尼日利亚阿贝奥库塔大都市洪水脆弱性加权线性组合分析
该研究为评价遥感和地理空间技术在洪水灾害风险管理中的作用以及开发阿贝奥库塔大都市洪水风险评估和管理的空间决策支持系统提供了机会。使用的数据集包括从地球探测器站点下载的无云高分辨率卫星图像和航天飞机雷达地形任务(SRTM)数据。所使用的土壤数据来自联合国粮食及农业组织(FAO)世界土壤统一数据库,而降雨数据来自气候灾害组织红外降水站。在地理信息系统中使用相同的1:5万比例尺和地理坐标系统(WGS 1984)绘制了洪水增强因子图,即土壤类型、降雨强度、排水密度和地形。所有地图均采用栅格格式,单元格尺寸相同,为0.0028 mm。然后使用加权线性组合对它们进行排序和多标准分析(MCA)加权。该研究确定地形和土地利用是导致阿贝奥库塔大都市洪水的关键因素。建筑物对自然排水渠道的阻塞加剧了山洪灾害。
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