[1]陆广勇,杨勤科,张少伟,等.基于线性光谱混合模型分解MODIS多光谱影像的研究[J].水土保持研究,2011,18(03):10-14.
　LU Guang-yong,YANG Qin-ke,ZHANG Shao-wei,et al.Classification of MODIS Multispectral Images Based on Line Spectral Mixture Model[J].Research of Soil and Water Conservation,2011,18(03):10-14.
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基于线性光谱混合模型分解MODIS多光谱影像的研究

《水土保持研究》[ISSN:1005-3409/CN:61-1272/P] 卷: 18 期数: 2011年03期 页码: 10-14 栏目: 出版日期: 2011-06-20
Title:
Classification of MODIS Multispectral Images Based on Line Spectral Mixture Model
作者:
陆广勇1,3, 杨勤科2,1, 张少伟1,3, 王海江1,3
1. 中国科学院 水利部 水土保持研究所, 陕西 杨凌 712100;
2. 西北大学, 西安 710127;
3. 中国科学院研究生院, 北京 100039
Author(s):
LU Guang-yong1,3, YANG Qin-ke2,1, ZHANG Shao-wei1,3, WANG Hai-jiang1,3
1. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China;
2. Northwest University, Xi’an 710069, China;
3. Graduate University of Chinese Academy of Sciences, Beijing 100039, China
关键词:
线性混合像元分解; 土地覆盖类型分类; MODIS; 精度评价
Keywords:
linear spectral mixture analysis; land cover classification; MODIS; accuracy assessment
分类号:
F205;TP79
摘要:
为了获取多时相的土地覆盖基础数据以支持区域土壤侵蚀定量评价，基于线性光谱混合模型分解MODIS多光谱影像，并对分解结果进行了定性、定量评价。结果表明，结合像元年内植被指数变化特征，基于线性混合像元分解，可解译出耕地、林地、草地、裸地、水体、居民地等类型。分类结果与2006年TM分类结果的总体一致性为64.46%，Kappa系数为0.519 9，土地覆盖类型分类结果可靠；各类端元估算误差基本小于20%，且与对应TM分类结果具有相关性，总体精度较好；林地端元能够较好地反映植被盖度信息。基于LSMM分解MODIS影像可为区域环境研究提供可靠的土地覆盖类型图和植被覆盖信息。
Abstract:
Soil erosion monitoring works require multi-temporal land cover data on a regional scale.This paper estimated the abundance of land cover components using MODIS09GA multispectral images based on linear spectral mixture model(LSMM) and assessed the accuracy.The results showed the overall accuracy of the final land cover map was 64.46%,and the Kappa coefficient was 0.519 9;the estimation error of the endmember fraction is less than 20% for most of land cover components.There is fine linear correlation between the abundance of land cover components and the classification of Landsat image.For the forest endmember,the linear correlation coefficient is 0.79.It is suggested that,for MODIS image,applying LSMM in land cover classification is feasible and is promising to extracting vegetation fraction.

参考文献/References:

[1] 赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[2] Ichoku C,Karnieli A.A review of mixture modeling techniques for sub-pixel land cover estimation[J].Remote Sensing Reviews,1996,13(3):161-186.
[3] Adams J B,Sabol D E,Kapos V,et al.Classification of multispectral images based on fractions of end-members:application to land-cover change in the Brazilian Amazon[J].Remote Sensing of Environment,1995,52(2):137-154.
[4] Roberts D A,Gardner M,Church R,et al.Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models[J].Remote Sensing of Environment,1998,65(3):267-279.
[5] Small C.A global analysis of urban reflectance[J].International Journal of Remote Sensing,2005,26(4):661-681.
[6] Ridd M K.Exploring a V-I-S(Vegetation-Impervious Surface-Soil) model for urban ecosystem analysis through remote-sensing-comparative anatomy for cities[J].International Journal of Remote Sensing,1995,16(12):2165-2185.
[7] Small C.Estimation of urban vegetation abundance by spectral mixture analysis[J].International Journal of Remote Sensing,2001,22(7):1305-1334.
[8] Tooke T R,Coops N C,Goodwin N R,et al.Extracting urban vegetation characteristics using spectral mixture analysis and decision tree classifications[J].Remote Sensing of Environment,2009,113(2):398-407.
[9] 胡健波,陈玮,李小玉,等.基于线性混合像元分解的沈阳市三环内城市植被盖度变化[J].应用生态学报,2009,20(5):1140-1146.
[10] Jimenez-Munoz J C,Sobrino J A,Plaza A,et al.Comparison between fractional vegetation cover retrievals from vegetation indices and spectral mixture analysis:a case study of PROBA/CHRIS data over an agricultural area[J].Sensors,2009,9(2):768-793.
[11] Kumar U,Kerle N,Ramachandra T V.Constrained linear spectral unmixing technique for regional land cover mapping using MODIS data[C]//Innovations and Advanced Techniques in Systems,Computing Sciences and Software Engineering.Netherlands:Springer,2008:416-423.
[12] 李正国,王仰麟,吴健生,等.不同土地利用方式对黄土高原植被覆盖季节变化的影响:以陕北延河流域为例[J].第四纪研究,2005(6):762-769.
[13] 谢红霞.延河流域土壤侵蚀时空变化及水土保持环境效应评价研究[D].西安:陕西师范大学,2008.
[14] U.S.Department of the Interior/U.S.Geological Survey.Surface Reflectance Daily L2G Global 1km and 500m[EB/OL].[2010-12-20].https://lpdaac.usgs.gov/lpdaac/products/modis_products_table/surface_reflectance/daily_l2g_global_1km_and_500m/mod09ga.
[15] Roerink G,Menenti M,Verhoef W.Reconstructing cloudfree NDVI composites using Fourier analysis of time series[J].International Journal of Remote Sensing,2000,21(9):1911-1917.
[16] 左丽君,张增祥,董婷婷,等.MODIS/NDVI和MODIS/EVI在耕地信息提取中的应用及对比分析[J].农业工程学报,2008,24(3):167-172.
[17] 赵英时.美国中西部沙山地区环境变化的遥感研究[J].地理研究,2001(2):210-219.
[18] 宋现锋,段峥,牛海山,等.土壤侵蚀模型中植被管理因子的遥感估算[J].北京林业大学学报,2009,31(3):58-63.
[19] Boardman J,Kruse F,Green R.Mapping target signatures via partial unmixing of AVIRIS data[C]//Citeseer.5th Annual JPL Airborne Earth science Workshop Jet Propulsion Laboratory.Pasadena,CA:JPL Pub.,1995.
[20] De Asis A M,Omasa K.Estimation of vegetation parameter for modeling soil erosion using linear spectral mixture analysis of landsat ETM data[J].Isprs Journal of Photogrammetry and Remote Sensing,2007,62(4):309-324.
[21] De Asis A M,Omasa K,Oki K,et al.Accuracy and applicability of linear spectral unmixing in delineating potential erosion areas in tropical watersheds[J].International Journal of Remote Sensing,2008,29(14):4151-4171.

备注/Memo

收稿日期:2011-2-28;改回日期:2011-3-18。
基金项目:黄土高原水土流失数学模型（第一期）研发（黄水保200651-08）
作者简介:陆广勇（1985- ），男（壮族），广西贵港市人，在读硕士研究生，主要从事GIS应用和区域土壤侵蚀研究。E-mail：luguangyong16@163.com
通讯作者:杨勤科（1962- ），男，陕西省陇县人，博士，教授，主要从事区域水土流失与GIS应用研究。E-mail：qkyang@nwu.edu.cn

更新日期/Last Update: 1900-01-01