本期要文(可全文下载)

滑坡图像自动识别浅议

展开
  • 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室, 北京 100101
王治华(1942-),女,研究员,主要从事地质灾害遥感和数字滑坡等方面的研究。E-mail:577027159@qq.com

收稿日期: 2013-05-20

  修回日期: 2013-08-01

  网络出版日期: 2013-09-29

A Preliminary Discussion on Landslide Pattern Recognition

Expand
  • Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101

Received date: 2013-05-20

  Revised date: 2013-08-01

  Online published: 2013-09-29

摘要

识别滑坡须先了解什么是滑坡,广义滑坡包括崩塌、滑坡、碎屑流、泥石流等所有斜坡重力侵蚀现象;狭义滑坡指部分斜坡沿着斜坡内的一个或数个面在重力的作用下作剪切运动的现象。各类滑坡有自已特殊的地表形态特征,发育的基本地质环境条件和触发因素,据这些特征识别滑坡。利用数字滑坡技术进行滑坡识别大致分为2步:(1)通过RS和GIS技术将不同时间的调查区地物现场以不同分辨率展现在数字图像上,并与地理控制及地质环境信息配准、组合,建立解译基础;(2)在滑坡地学理论指导下,通过人机交互方式进行解译和时空分析,获取减灾防灾需要的信息。该方法尚未达到遥感自动识别滑坡的程度,但建立解译基础的过程已可由计算机通过多种程序软件完成,故认为滑坡模式识别的前2个步骤:数字化及预处理已由计算机实现。现需探索的是用计算机实现基于滑坡地学理论知识,以人机交互方式进行的滑坡识别及分析过程。就狭义滑坡而言,基于DEM的滑坡地形识别已可由计算机实现。如能确定地面滑坡壁及滑体与地下滑面、滑床的关系,了解它们的光谱特征并建立计算模型,便可构建遥感技术的滑坡模式识别。

本文引用格式

王治华 . 滑坡图像自动识别浅议[J]. 地球信息科学学报, 2013 , 15(5) : 726 -733,782 . DOI: 10.3724/SP.J.1047.2013.00726

Abstract

Identification of landslide should first understand what it is. Broad sense of landslide means all the slope gravitational erosion phenomena including rock fall, landslide, clastic flow and debris flow and so on; narrow sense of landslide means the phenomenon that parts of slope move searing along one or several surfaces internal the slope under the function of the gravitation. Each type of landslide has own special morphological characteristics on the ground and basic geological environmental conditions and trigger factors for growing. According to the special characteristics the landslide can be identified. Digital Landslide Technique suggested based on the research and practice of RS+GIS for landslide at home and abroad identification of the landslide can be divided into 2 steps roughly. First, with RS+GIS technique, ground features at different time were showed on digital images with different solutions. Through registration and combination with geological structure and geographic information, the base for remote sensing interpretation is established. Second, under the guide of theory of landslide, by means of men-PC interactive mode, the remote sensing interpretation and time-space analysis are carried out and the key elements information of landslide for disaster prevention then are obtained. That methods has not been reached automatic identification of landslide, but the process of establishing the base for remote sensing interpretation has been accomplished with several soft program procedure by PC, so it is considered that the first two steps, digitalization and preprocess for landslide pattern recognition have already realized by PC. Now we should explore the methods of landslide recognition and analysis procedure with computer calculation instead of men-PC interactive mode. For the narrow landslide sense, the landslide topography recognition has already been conducted by computer based on DEM. If the relation between landslide scarp, deposit body on the ground and landslide surface, bed under the ground could be found, their spectral property could be determined and the calculating mode could be established, the landslide pattern recognition based on the remote sensing technique then could be realized.

参考文献

[1] 王治华.滑坡遥感[M].北京:科学出版社,2012,104-105.

[2] 王猛,王军,江煜,等.汶川地震地质灾害遥感调查与空间特征分析[J].地球信息科学学报,2010,12(4):480-486.

[3] 黄润秋等.汶川地震地质灾害研究[M].北京:科学出版社, 2009,171-198.

[4] 张茂省,雷学武,校培喜,等.遥感技术在黄土高原区地质灾害详细调查中的应用[J].西北地质,2007,40(3):92-97.

[5] 马瑛,田望学.高分辨遥感图像在黄土高原滑坡解译中的应用[J].资源环境与工程,2007, 21(2):167-169.

[6] 王治华,徐起德,徐斌,等. 5.12 汶川地震航空遥感应急调 查[J].中国科学E辑,2009,39(7):1304-1311.

[7] 王治华.青藏公路和铁路沿线的滑坡研究[J].现代地质, 2003,17(4):355-362.

[8] Mondini A C, Guzzetti F, Reichenbach P, Rossia M, et al. Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images[J]. Remote Sensing of Environment, 2011(115):1743-1757.

[9] Nichol J, and Wong M S. Satellite remote sensing for detailed landslide inventories using change detection and image fusion[J]. International Journal of Remote Sensing, 2005,26(9):1913-1926.

[10] Keefer D, Larsen M. Assessing landslide hazards[J]. Science, 2007(316):1136-1138.

[11] Chung C F, Fabbri A G. Probabilistic prediction models for landslide hazard mapping[J]. Photogrammetric Engineering & Remote Sensing (PE&RS), 1999, 65(12): 1388-1399.

[12] 单新建,叶洪,李焯芬,等.基于GIS 的区域滑坡危险性预测方法与初步应用[J].岩石力学与工程学报, 2002,21 (10):1507-1514.

[13] 兰恒星,王苓涓,周成虎.地理信息系统支持下的滑坡灾害分析模型研究[J].工程地质学报,2002,10(4):421-427.

[14] 王治华,郭兆成,杜明亮,等.基于数字滑坡技术的暴雨滑坡、泥石流预警预测模型研究[J].地学前缘,2011,18(5): 303-309.

[15] 冯振,殷跃平,李滨,等.重庆武隆鸡尾山滑坡视向机制分析[J].岩土力学,2012(9):2704-2712.

[16] 西奥多里德斯等著,李晶皎等译.模式识别[M].北京:电 子工业出版社,2006.

[17] 王润生,杨苏明,阎柏琨.成像光谱矿物识别方法与识别模型评述[J].国土资源遥感,2007(1):1-9.

[18] 姚佛军,杨建民,张玉君,等.光谱角制图法与谱线平行分类法若干问题的探讨——以ETM数据为例[J].遥感信息,2009(1):20-26.

文章导航

/