基于遥感阴影与财产密度的城市房屋滑坡灾害风险评估方法——以广西梧州市为例

发布时间：2018-02-26 16:50

本文关键词： 高分遥感影像城市居民区阴影密度函数财产风险　出处：《桂林理工大学学报》2017年01期 　论文类型：期刊论文

【摘要】：针对我国西部山地城市居民区滑坡灾害的空间分布特点,从高分遥感角度探讨了滑坡灾害损失发生的承灾体物质基础,提出一种基于遥感阴影与承灾体财产密度的城市居民区房屋滑坡风险评估方法。与以往方法不同,该方法利用了高分影像上的建筑物的落影信息,通过遥感落影成像模型反演建筑物的高度、楼层数和建筑面积,结合实地勘测和危险性区划完成滑坡风险评估。以广西梧州市为研究区进行风险区划研究,获得区划结果。结果显示:建筑物样本的楼层数反演结果与实地量测建筑物样本楼层数基本相符;与样方估计法相比,核密度函数法便于进行建筑物的财产密度分析,该方法更适合我国西部山地城市房屋的滑坡易损性与风险评估。
[Abstract]:In view of the spatial distribution characteristics of landslide disaster in mountainous cities and residential areas in western China, the material basis of disaster bearing body for landslide disaster loss is discussed from the perspective of high score remote sensing. This paper presents a landslide risk assessment method for urban residential buildings based on remote sensing shadow and property density of disaster bearing bodies. Different from the previous methods, this method utilizes the falling image information of buildings on high score images. The height, the number of floors and the area of buildings were retrieved by remote sensing imaging model, and the landslide risk assessment was completed by combining with field survey and dangerous regionalization. The risk zoning was carried out in Wuzhou City, Guangxi, as the study area. The results show that the inversion results of building samples are basically consistent with the number of floor samples measured in the field, and the kernel density function method is convenient for the analysis of building property density compared with the method of sample square estimation. This method is more suitable for landslide vulnerability and risk assessment of houses in mountainous cities in western China.
【作者单位】：桂林理工大学测绘地理信息学院;桂林理工大学广西空间信息与测绘重点实验室;
【基金】：广西自然科学基金项目(2016GXNSFAA380013) 广西自然科学基金重点项目(2014GXNSFDA118038) 桂林市科学研究与技术开发计划项目(2016012601) 广西空间信息与测绘重点实验室基金项目(15-140-07-17;15-140-07-18) 重庆基础科学与前沿技术研究重点项目(cstc2015jcyj B028)
【分类号】：P237;P642.22

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