基于SPOT5图像的泥石流自动提取方法
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摘要
在前人研究基础上,提出了一种基于SPOT5图像和DEM数据自动提取泥石流的方法。首先利用归一化差值植被指数(NDVI)、归一化差值土壤亮度指数(NDSI)和图像经主成分变换得到的第一主成分(PC1)等3种遥感指数获取新的主成分变换图像,进而利用阈值自动选取算法提取包含泥石流的裸地信息;然后基于1∶10 000的DEM数据,利用改进的沟谷中心线提取算法提取沟谷中心线,并利用数学形态学滤波算法生成沟谷范围;最后将提取的疑似泥石流图斑与沟谷范围匹配,并对矢量化后的结果进行面积、坡度和顺坡性等筛选,得到泥石流或潜在泥石流信息。实验表明,本文构建的泥石流提取模型具有较高的提取精度和效率。
Based on achievements obtained by previous researchers,the authors put forward a method for automatically extracting debris flow based on SPOT5 image and DEM data.Firstly,this method uses integrated computing of three indices of remote sensing,i.e.,the index of vegetation,the soil brightness index and the first principal component of the image after KL transformation,for the acquisition of a new principal component transformed image,and then extracts the bare land information containing debris flow by using automatic threshold selection algorithm.Secondly,on the basis of the DEM data at the scale of 1:10 000,the valley central lines are extracted by using the improved valley line extraction algorithm,and the valley range is figured out by using the mathematical morphology filtering algorithm.Finally,the suspicious debris flow pattern is matched with the valley range pattern,and the vectorized result is screened in the aspects of area and slope.On such a basis,the information of existing or potential debris flows is obtained.The experimental results show that the extraction model of debris information from SPOT5 image can accurately and effectively extract the debris flow information.
Based on achievements obtained by previous researchers,the authors put forward a method for automatically extracting debris flow based on SPOT5 image and DEM data.Firstly,this method uses integrated computing of three indices of remote sensing,i.e.,the index of vegetation,the soil brightness index and the first principal component of the image after KL transformation,for the acquisition of a new principal component transformed image,and then extracts the bare land information containing debris flow by using automatic threshold selection algorithm.Secondly,on the basis of the DEM data at the scale of 1:10 000,the valley central lines are extracted by using the improved valley line extraction algorithm,and the valley range is figured out by using the mathematical morphology filtering algorithm.Finally,the suspicious debris flow pattern is matched with the valley range pattern,and the vectorized result is screened in the aspects of area and slope.On such a basis,the information of existing or potential debris flows is obtained.The experimental results show that the extraction model of debris information from SPOT5 image can accurately and effectively extract the debris flow information.
引文
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[11]李洪义,史舟,沙晋明,等.基于人工神经网络的生态环境质量遥感评价[J].应用生态学报,2006,17(8):1475-1480.Li H Y,Shi Z,Sha J M,et al.Evaluation of Eco-environmental Quality Based on Artificial Neural Network and Remote Sensing Technique[J].Chinese Journal of Applied Ecology,2006,17(8):1475-1480(in Chinese with English Abstract).
[12]江振蓝,沙晋明.植被生态环境遥感本底值研究——以福州市为例[J].福建师范大学学报:自然科学版,2008,24(4):80-85.Jiang Z L,Sha J M.Research into RS Background Value of Vegeta-tion Eco-environment:with Fuzhou Taken as an Example[J].Journal of Fujian Normal University:Natural Science Edition,2008,24(4):80-85(in Chinese with English Abstract).
[13]Rouse J W,Hass R H,Schell J A,et al.Monitoring Vegetation Systems in the Great Plans with ERTS[C]//Proceedings of the Third ERTS Symposium NASA:SP351I,1973:309-317.
[14]Tsai D M.A Fast Thresholding Selection Procedure for Multimodal and Unimodal Histograms[J].Pattern Recognition Letters,1995,16:653-666.
[2]余斌,杨永红,苏永超,等.甘肃省舟曲8.7特大泥石流调查研究[J].工程地质学报,2010,18(4):437-444.Yu B,Yang Y H,Su Y C,et al.Research on the Giant Debris Flow Hazards in Zhouqu County,Gansu Province on August7,2010[J].Journal of Engineering Geology,2010,18(4):437-444(in Chinese with English Abstract).
[3]王一川,秦军.基于DEM自动提取泥石流沟谷边缘线算法的试验[J].四川测绘,2006,29(1):28-31.Wang Y C,Qin J.The Test of Auto Extract Debris Flow Channels’Edge Arithmetic by DEM[J].Surveying and Mapping of Sichuan,2006,29(1):28-31(in Chinese with English Abstract).
[4]白志勇.陆地卫星SPOT、TM数据复合影象在泥石流调查中的应用[J].水土保持学报,2001,15(1):116-119.Bai Z Y.Application of Synthetic Satellite Image of SPOT and TM Data in Debris Flow Investigation[J].Journal of Soil and Water Conservation,2001,15(1):116-119(in Chinese with English Abstract).
[5]苏凤环,刘洪江,韩用顺.汶川地震山地灾害遥感快速提取及其分布特点分析[J].遥感学报,2008,12(6):956-963.Su F H,Liu H J,Han Y S.The Extraction of Mountain Hazard Induced by Wenchuan Earthquake and Analysis of Its Distributing Characteristic[J].Journal of Remote Sensing,2008,12(6):956-963(in Chinese with English Abstract).
[6]唐川,丁军,梁京涛.汶川震区北川县城泥石流源地特征的遥感动态分析[J].工程地质学报,2010,18(1):1-7.Tang C,Ding J,Liang J T.Remote Sensing Images Based Observa-tional Analysis on Characters of Debris Flow Source Areas in Beichuan County of Wenchuan Earthquake Epicenter Region[J].Journal of Engineering Geology,2010,18(1):1-7(in Chinese with English Abstract).
[7]唐小明,冯杭建,赵建康.基于虚拟GIS和空间分析的小流域泥石流地质灾害遥感解译——以嵊州市为例[J].地质科技情报,2008,27(2):12-16.Tang X M,Feng H J,Zhao J K.Remote Sensing Interpretation of Small-water-basin Debris Flow Based on Virtual GIS and Spatial Analysis:Example from Shengzhou County[J].Geological Science and Technology Information,2008,27(2):12-16(in Chinese with English Abstract).
[8]潘仲仁,曹林英.遥感技术在成昆铁路泥石流沟调查中的应用[J].铁道工程学报,2006(增刊):237-242.Pan Z R,Cao L Y.Application of Remote Sensing Technology in Surveying Debris Flow of Chengdu-Kunming Railway[J].Journal of Railway Engineering Society,2006(Supplement):237-242(in Chinese with English Abstract).
[9]陈振民.环境本底值背景值基线值概念的商榷[J].河南地质,2000,18(2):158-160.Chen Z M.Discussion on the Conception of the Environmental Original Value and the Environmental Background Value and the Environmental Baseline Value[J].Henan Geology,2000,18(2):158-160(in Chinese with English Abstract).
[10]江振蓝,沙晋明,杨武年.基于GIS的福州市生态环境遥感综合评价模型[J].国土资源遥感,2004(3):46-48,60.Jiang Z L,Sha J M,Yang W N.Multiple Factors-based Remote Sensing Evaluation of Ecological Environment in Fuzhou[J].Remote Sensing for Land and Resources,2004(3):46-48,60(in Chinese with English Abstract).
[11]李洪义,史舟,沙晋明,等.基于人工神经网络的生态环境质量遥感评价[J].应用生态学报,2006,17(8):1475-1480.Li H Y,Shi Z,Sha J M,et al.Evaluation of Eco-environmental Quality Based on Artificial Neural Network and Remote Sensing Technique[J].Chinese Journal of Applied Ecology,2006,17(8):1475-1480(in Chinese with English Abstract).
[12]江振蓝,沙晋明.植被生态环境遥感本底值研究——以福州市为例[J].福建师范大学学报:自然科学版,2008,24(4):80-85.Jiang Z L,Sha J M.Research into RS Background Value of Vegeta-tion Eco-environment:with Fuzhou Taken as an Example[J].Journal of Fujian Normal University:Natural Science Edition,2008,24(4):80-85(in Chinese with English Abstract).
[13]Rouse J W,Hass R H,Schell J A,et al.Monitoring Vegetation Systems in the Great Plans with ERTS[C]//Proceedings of the Third ERTS Symposium NASA:SP351I,1973:309-317.
[14]Tsai D M.A Fast Thresholding Selection Procedure for Multimodal and Unimodal Histograms[J].Pattern Recognition Letters,1995,16:653-666.
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