论文

基于高分辨率遥感影象的城市泥石流灾害损失评估

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  • 1. 成都理工大学地质灾害防治与地质环境保护国家专业实验室, 四川 成都 610059;
    2. 云南大学资源环境与地球科学学院, 云南 昆明 650223

收稿日期: 2004-11-15

  修回日期: 2005-02-05

  网络出版日期: 2006-05-20

基金资助

国家自然科学基金(40371018)和云南省"十五"科技攻关项目(2001NG44)资助。

Loss Evaluation of Urban Debris Flow Hazard Using High Spatial Resolution Satellite Imagery

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  • 1. National Professional Laboratory for Geo-hazard Prevention and Ge-environment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059;
    2. College of Resource, Environment and Earth Science, Yunnan University, Kunming, Yunnan 650223

Received date: 2004-11-15

  Revised date: 2005-02-05

  Online published: 2006-05-20

摘要

文章探讨了城市泥石流灾害损失评估的系统方法,该方法包括了泥石流堆积泛滥区危险区划、城市土地覆盖类型遥感解译、损失评估模型构建和价值核算4个主要内容。以美国高分辨率的"快鸟"卫星影象为数据源完成了研究区的土地覆盖类型遥感解译,根据泥石流危险程度和土地覆盖类型特征,构建了城市泥石流灾害的损失评估模型。最后,应用GIS提供的分析工具完成了研究区不同土地覆盖类型的泥石流灾害损失计算和评价。

本文引用格式

唐川, 张军, 万石云, 周春花 . 基于高分辨率遥感影象的城市泥石流灾害损失评估[J]. 地理科学, 2006 , 26(3) : 358 -363 . DOI: 10.13249/j.cnki.sgs.2006.03.358

Abstract

This paper approached an integrated methodology for urban debris flow loss estimation.Procedure of the methodology involved debris flow hazard zonation, image interpretation of urban land cover, model establishment for loss estimation, and property value calculation.Debris flow hazard zonation on the alluvial fan of the study area are created by overlaying distributed flow depth and velocity maps, which are produced through the numerical simulation.The possible loss estimation model is formulated based on stage-damage relationships between different debris flow hazard level and land-use features.Nowadays, earth observation techniques can contribute toward more accurate urban debris flow hazard modelling and they can be used to assess damage to residential properties, infrastructure and agricultural crops.For this study, detailed land cover information was derived by using the Quickbird high spatial resolution satellite imagery.Based on detail interpretation for the Quickbird image, the land cover of the study city was classified into 5 first level types, 10 second level types and 16 third level types.We calculated and evaluated the economic loss to different land-use features based on a GIS statistical tool.

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