基于光谱混合分析的干旱荒漠区植被遥感信息提取研究——以古尔班通古特沙漠西缘为例

摘要/Abstract

摘要： 干旱荒漠区植被的盖度和空间分布特征是评判该区生态环境状况及荒漠化程度的重要指标。以Landsat TM影像为数据源,利用归一化植被指数（NDVI）和线性光谱混合分析模型（LSMM）两种方法对研究区——古尔班通古特沙漠西缘进行分析。在运用LSMM过程中,通过多种方法选择出最佳端元,并利用实测数据对混合像元分解结果进行验证。结果表明:①NDVI提取植被的方法受到很多限制,不适合在干旱荒漠区应用;②基于最小法非受限光谱混合分解结果较为理想,植被、盐碱地、裸沙和黑色砂粒等4种端元地物被选取出来;③LSMM提取的植被分量与实测植被盖度显著相关,线性相关系数为0.858,表明干旱荒漠区的植被盖度可以通过遥感影像提取的植被分量间接得到。

关键词: 光谱混合分析, 端元, 干旱荒漠区, NDVI, 古尔班通古特沙漠

Abstract: The coverage and spatial distribution of vegetation is a fundamental index to estimate the ecological environment and desertification in arid desert area. Comparison among deserts in the same latitude region, Gurbantunggut Desert is the unique which teems with lots of plant species, although the distribution of vegetation is more sparse than that of some typical desert steppe. In this paper, vegetation coverage of the western Gurbantunggut Desert was selected as the target indicator, which was extracted using normalized difference vegetation index (NDVI) and linear spectral mixture model (LSMM), based on Landsat TM images. In order to get better result, we chose the best endmember in the LSMM process through different methods, and utilized the measured vegetation coverage data to validate the vegetation fraction that came from remote sensing images. The results showed that: the NDVI method was subjected to many restrictions, and wasnt suitable for application in the arid desert area. While, the LSMM showed a better result, thus vegetation, alkaline soil, bare sand and dark sand had been successfully selected for further analyses. A significant linear relationship also was found between vegetation fraction and vegetation coverage, with a correlation coefficient of 0.858. All those reflected that vegetation coverage in the arid desert area can be extracted indirectly through remote sensing images.
Keywords: spectral mixture analysis; endmember; arid desert area; normalized

Key words: vegetation index, Gurbantunggut Desert

中图分类号:

崔耀平;王让会;刘彤;张惠芝. 基于光谱混合分析的干旱荒漠区植被遥感信息提取研究——以古尔班通古特沙漠西缘为例[J]. 中国沙漠, 2010, 30(2): 334-341.

CUI Yao-ping;WANG Rang-hui;LIU Tong;ZHANG Hui-zhi. Extraction of Vegetation Information in Arid Desert Area based on Spectral Mixture Analysis——a Case in the Western Gurbantunggut Desert[J]. JOURNAL OF DESERT RESEARCH, 2010, 30(2): 334-341.

参考文献

[1]王让会,张慧芝,赵振勇,等.MODS耦合关系的界面过程及其特征[J].干旱区地理,2004,27(3):388-392.
[2]Raich J W,Schilesinger W H.The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate[J].Tellus B,1992,44(2):81-99.
[3]池宏康,陈维英.遥感数据的裸沙土壤线校正方法[J].地理学报,1999,54(005):454-461.
[4]Myneni R B,Hall F G,Sellers P J,et al.The interpretation of spectral vegetation indexes[J].IEEE Transactions on Geoscience and Remote Sensing,1995,33(2):481-486.
[5]郄妍飞,颜长珍,宋翔,等.近30 a黄河源地区荒漠遥感动态监测[J].中国沙漠,2008,28(3):405-409.
[6]高志海,李增元,魏怀东,等.干旱地区植被指数(VI)的适宜性研究[J].中国沙漠,2006,26(2):243-248.
[7]王澄海,惠小英.以植被指数0.12为指标看我国的荒漠化与草原界限的变化[J].中国沙漠,2005,25(1):88-92.
[8]Jiang Z,Huete A R,Chen J,et al.Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction[J].Remote Sensing of Environment,2006,101(3):366-378.
[9]宋怡,马明国.基于SPOT VEGETATION数据的中国西北植被覆盖变化分析[J].中国沙漠,2007,27(1):89-93.
[10]Gitelson A A,Stark R,Grits U,et al.Vegetation and soil lines in visible spectral space: a concept and technique for remote estimation of vegetation fraction[J].International Journal of Remote Sensing,2002,23(13):2537-2562.
[11]王强.Hyperion高光谱数据进行混合像元分解研究[D].黑龙江:东北林业大学,2006.
[12]吴柯,张良培,李平湘.一种端元变化的神经网络混合像元分解方法[J].遥感学报,2007,11(1):20-26.
[13]Ichoku C,Karnieli A.A review of mixture modeling techniques for sub-pixel land cover estimation[J].Remote Sensing Reviews,1996,13(16):1-1.
[14]Wu C.Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery[J].Remote Sensing of Environment,2004,93(4):480-492.
[15]Small C,Lu J W.Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis[J].Remote Sensing of Environment,2006,100(4):441-456.
[16]Elmore A J,Mustard J F,Manning S J,et al.Quantifying vegetation change in semiarid environments: Precision and accuracy of spectral mixture analysis and the normalized difference vegetation index[J].Remote Sensing of Environment,2000,73(1):87-102.
[17]陈荣毅,张元明,潘伯荣,等.古尔班通古特沙漠土壤养分空间分异与干扰的关系[J].中国沙漠,2007,27(2):257-265.
[18]张立运,陈昌笃.论古尔班通古特沙漠植物多样性的一般特点[J].生态学报,2002,22(11):1923-1932.
[19]贾亚敏,刘彤,骆郴,等.新疆莫索湾南缘沙漠四种灌木空间异质性的对比[J].干旱区研究,2008,25(2):225-230.
[20]Chavez P,Mackinnon D.Image-based atmospheric corrections-Revisited and Improved[J].Photogrammetric Engineering and Remote Sensing,1996,62(9):1025-1036.
[21]刘卫国,吕光辉,高炜,等.阜康绿洲生态系统生物量空间格局分析[J].中国沙漠,2006,26(5):809-813.
[22]Small C.Estimation of urban vegetation abundance by spectral mixture analysis[J].International Journal of Remote Sensing,2001,22(7):1305-1334.
[23]Collado A D,Chuvieco E,Camarasa A.Satellite remote sensing analysis to monitor desertification processes in the crop-rangeland boundary of Argentina[J].Journal of Arid Environments,2002,52(1):121-133.
[24]Gilabert M,Gonzalez-piqueras J,Garcia-haro F J,et al.A generalized soil-adjusted vegetation index[J].Remote Sensing of Environment,2002,82(2):303-310.
[25]岳文泽,徐建华,武佳卫,等.基于线性光谱分析的城市旧城改造空间格局遥感研究:以1997—2000年上海中心城区为例[J].科学通报,2006,51(8):966-974.
[26]李晓松,吴波,范文义,等.基于光谱混合分析的毛乌素沙地油蒿群落覆盖度提取[J].遥感学报,2007,11(6):923-930.