干旱区生态环境知识资源中心(Arid): 新疆荒漠稀疏植被覆盖度信息遥感提取方法比较

Arid

	新疆荒漠稀疏植被覆盖度信息遥感提取方法比较
其他题名	Comparison of methods based on MODIS for estimating sparse vegetation fraction across desert in Xinjiang
	李向婷 1; 白洁 2; 李光录 1; 罗格平2 ; 古丽·加帕尔 2; 李均力 2
来源期刊	干旱区地理
ISSN	1000-6060
出版年	2013
卷号	36 期号:3 页码:502-511
中文摘要	植被覆盖度信息是荒漠生态环境表征的重要指标之一。荒漠区地表植被稀疏,在遥感光谱信息中表现较弱,通用的植被覆盖度遥感提取方法应用于干旱荒漠区存在一定的局限性,为了探寻一种满足大尺度荒漠地区的植被覆盖度信息的提取方法,必须对比和分析现有的遥感方法在干旱荒漠区的应用效果。以新疆荒漠区为例,利用MODIS遥感影像和野外植被覆盖度实测数据,对常用的6种遥感植被覆盖度提取方法(改进的三波段梯度差法、像元二分法、线型混合像元分解法、归一化植被指数法、增强型植被指数法和修正型土壤调整植被指数法)的结果进行精度验证和对比分析。结果表明:MODIS影像上较难提取纯荒漠植被像元,用农作物的像元值代替会降低像元二分法和线性混合像元分解模型的模拟精度;植被指数法对地面实测数据依赖性较大,模拟的精度差异很大,仅考虑红光和近红外的归一化植被指数法模拟精度最低,而综合考虑土壤和大气因素的增强型植被指数法的模拟结果精度最高;改进的三波段最大梯度差法虽然模拟精度稍次之(R~=.74;RMSE=13.46),但依据光谱的物理特性,能显著地反映南、北疆荒漠植被覆盖度的差异,是目前大尺度的荒漠区覆盖植被信息提取较为适宜的方法之一。
英文摘要	Vegetation coverage information is one of the significant indexes to represent desert eco-environment. Vegetation information of remote sensing spectral information is normally weaker due to the sparse vegetation in desert areas. There are various extraction methods of vegetation coverage using remote sensing data, which are limited in the application of arid desert. From this perspective, the comparison of different methods in desert areas will be essential way to find one feasible and suitable method of desert vegetation coverage information extraction at the larger scale within remote sensing. Taking desert areas in Xinjiang for example, six extraction methods of remote sensing (Modified maximal gradient difference model (Modified TGDVI), Pixel dichotomy model (PDM), Linear Spectral Unmixing (LSU) and vegetation index model (NDVI, EVI, MSAVI2)) were used to extract the vegetation fraction from MODIS images and the results were tested by observed data at field. It indicated that methods of vegetation index were mostly depends on the amount of observed values, so had different results. EVI which considered the factors of atmosphere and soil had the highest simulation accuracy while NDVI had the lowest accuracy of results as it only considered red and near-infrared radiation. Because it is difficult to extract pure desert vegetation pixel from MODIS images, using pixel values of crops instead of desert vegetation pixel could decreased the accuracy of PDM and LSU. With the better accuracy(R~2 =0.74; RMSE =13.46), modified TGDVI could dramatically reflect the vegetation fraction differences between the northern and southern desert in Xinjiang, and was the appropriate vegetation coverage information extraction method in such large scale of desert areas.
中文关键词	新疆荒漠区 ; 遥感 ; 稀疏植被覆盖度
英文关键词	MODIS desert of Xinjiang remote sensing fraction of sparse vegetation MODIS images
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:4865030
来源机构	中国科学院新疆生态与地理研究所 ; 西北农林科技大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/229525
作者单位	1.西北农林科技大学, 杨凌, 陕西 712100, 中国; 2.中国科学院新疆生态与地理研究所, 荒漠与绿洲国家重点实验室, 乌鲁木齐, 新疆 830011, 中国
推荐引用方式 GB/T 7714	李向婷,白洁,李光录,等. 新疆荒漠稀疏植被覆盖度信息遥感提取方法比较[J]. 中国科学院新疆生态与地理研究所, 西北农林科技大学,2013,36(3):502-511.
APA	李向婷,白洁,李光录,罗格平,古丽·加帕尔,&李均力.(2013).新疆荒漠稀疏植被覆盖度信息遥感提取方法比较.干旱区地理,36(3),502-511.
MLA	李向婷,et al."新疆荒漠稀疏植被覆盖度信息遥感提取方法比较".干旱区地理 36.3(2013):502-511.