LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA

R. O. Ulakpa, Vera Okwu, K. Chukwu, M. Eyankware
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引用次数: 3

Abstract

Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation. From the processed landsat 8 imagery, landslide susceptibility map was produced, and landslide was category into various class; low, medium and high. From the study, it was observed that Enugu and Anambra state ranges from high to medium in terms of landslide susceptibility, Imo state ranges from medium to low.
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全国选定州滑坡敏感性模型。尼日利亚
滑坡的识别和测绘是滑坡危险性和危害评价的重要内容。本文提供了利用陆地卫星图像绘制从安全区域到高度易发区域大小不等的滑坡区域的信息。滑坡缓解在很大程度上取决于对因素性质的理解,即:坡度、土壤类型、地形、地形密度、高程、降雨量和植被。这些因素对滑坡的发生有直接的影响。确定这些因素对制订适当及策略性的控制山泥倾泻措施至为重要。本研究采用landsat 8 ETM遥感下载图像,采用ArcGIS 10.7和Surfer 8软件下载航拍照片,采用Digital Elevation Model (DEM)和Google EarthPro TM生成坡度、排水、地貌和高程。利用处理后的landsat 8影像,绘制了滑坡易感性图,并对滑坡进行了分类;低、中、高。研究发现,埃努古州和阿南布拉州的滑坡易感性从高到中,伊莫州的滑坡易感性从中到低。
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