长江科学院院报 ›› 2015, Vol. 32 ›› Issue (11): 130-135.

• 信息技术应用 • 上一篇    下一篇

快鸟影像在典型古滑坡识别应用的研究

张雅莉, 马金珠, 张鹏, 顾春杰   

  1. 兰州大学 西部环境教育部重点实验室,兰州 730000
  • 收稿日期:2014-05-19 修回日期:2014-07-03 出版日期:2015-11-20 发布日期:2015-11-05
  • 作者简介:张雅莉(1987-),女,山西朔州人,硕士研究生,主要从事水文过程与环境遥感方面的研究,(电话)13313493645(电子信箱) zhangyali12@lzu.edu.cn。
  • 基金资助:
    国家科技支撑计划项目(2011BAK12B05)

Recognition of Typical Old Landslide Based on Quick Bird Image

ZHANG Ya-li, MA Jin-zhu, ZHANG Peng, GU Chun-jie   

  1. Key Laboratory of Western China's Environmental Systems of Ministry of Education,Lanzhou University, Lanzhou 730000,China
  • Received:2014-05-19 Revised:2014-07-03 Online:2015-11-20 Published:2015-11-05

摘要: 为了对甘肃南部典型古滑坡的滑坡灾害空间分布及其特征进行微观分析,采用高分辨率快鸟影像(Quick Bird Image)及已有地质灾害调查资料和实测资料,并合理选用滑坡体、滑坡后壁、后缘、裂缝、冲沟、滑坡台阶、鼓丘等作为滑坡识别标志,从而判定甘肃省舟曲县大川乡泄流坡滑坡的具体位置、边界及规模等基础特征信息。提取滑坡地表细节情况,经与实地查勘情况对比,结果表明遥感图像初步解译的成果中泄流坡滑坡位置是准确的,滑坡识别所选用的典型解译标志也基本正确。基于上述方法,借鉴对泄流坡滑坡的解译经验,对舟曲县其他2个大型古滑坡即锁儿头滑坡和龙江新村滑坡进行了解译分析,其成果为研究区滑坡灾害防治及预测提供了理论依据。由此表明,针对研究区建立的这种高精度滑坡识别方法在实际工作应用中是可行的。

Abstract: In order to analyze the spatial distribution and characteristics of typical old landslides in the south of Gansu province, a typical large landslide called Xieliupo landslide in Zhouqu county of Gansu province was selected as an example. Rational interpretation marks such as landslide mass, back wall of landslide, trailing edge of landslide, fissure, gulch, step and drumlin were established by making use of Quick Bird high resolution remote sensing images in association with geological data and measured data obtained from field survey. On the basis of this, the location, boundary, scale and other basic characteristics of Xieliupo landslide was confirmed. We extracted surface conditions of the landslide and compared them with in-situ investigation conditions. Results show that, the position of Xieliupo landslide is correct in the initiatory interpretation result, and the proposed typical interpretation signs for landslide recognition has been proved to be basically right. The method and experiences from Xieliupo landslide were applied to the recognition of other two landslides, namely Suoertou landslide and Longjiangxincun landslide. This research provides theoretical basis for the subsequent research of landslides prevention, treatment and prediction in the study area. In the same time, the proposed method of high resolution landslide recognition established for the study area has been proved to be feasible in practical projects.

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