干旱区生态环境知识资源中心(Arid): 基于Landsat 8 OLI影像的塔里木河下游河岸林叶面积指数反演

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	基于Landsat 8 OLI影像的塔里木河下游河岸林叶面积指数反演
其他题名	Leaf area index inversion of riparian forest in the lower basin of Tarim River based on Landsat 8 OLI images
	朱绪超 1; 袁国富 1; 易小波 2; 杜涛 1
来源期刊	干旱区地理
ISSN	1000-6060
出版年	2014
卷号	37 期号:6 页码:1248-1256
中文摘要	叶面积指数(Leaf Area Index, LAI)是描述植物冠层结构特征的重要参数,也是研究植物冠层表面物质和能量交换必不可少的参数。根据在塔里木河下游河岸林地利用LAI- 2250实测的LAI数据,比较Landsat 8 OLI遥感数据提取的几种常规植被指数估算LAI的能力,建立LAI估算模型,并利用实测数据对模拟结果进行精度验证,生成塔里木河下游LAI分布图。结果表明:(1)各植被指数(Vegetation Indexes, VIs)与LAI均具有一定的相关性,对于不同的植被指数,二次多项式回归模型相关性均最高;(2)在不区分植被类型的样本分析中,大气阻抗植被指数(Atmospherically Resistant Vegetation Index,)与实测LAI具有最高的相关性;(3)分别针对柽柳林和胡杨林样本分析,判定系数R~2和反演精度均具有不同程度的提高,对应的最适植被指数分别为归一化植被指数(Normalized Differential Vegetation Index, NDVI)和ARVI; (4)塔里木河下游河岸植被 LAI有3个高值区:大西海子水库附近、下游中部和尾闾湖台特玛湖附近。全区LAI值主要分布在0~1.5之间,均值为0.361。该研究结果为遥感提取塔里木河下游河岸林带高空间分辨率的叶面积指数数据提供了数据支持和方法支撑。
英文摘要	Leaf area index ( LAI) is an important parameter for describing structural characteristics of plant canopy and also an essential parameter for researching the exchange information of mass and energy associated with canopy surface. In this study, we use the VIs (Vegetation Indexes) -LAI method to inverse LAI value of the riparian forests of the lower reaches of the Tarim River. The modeling data is comprised of LAI and VIs,which were acquired by field measurements by LAI - 2250 and indoor processing work of Landsat 8 OLI remote sensing image respectively. Three optimal models were built separately for the whole samples,the Tamarix forests samples and the Populus euphratica Oliv forests samples,and made precision tests by comparing with the measured LAI values which were not used in building the models previously. Then the LAI distribution map was acquired by using the whole samples VIs - LAI inversion model. The results showed as follows : (1) In the three different samples analyses,all vegetation indexes have good relevance with LAI, and among different vegetation indexes,quadratic polynomial regression model has the highest goodness of fit. (2)ln the whole samples analysis which does not distinguish vegetation types, ARVI (atmospherically resistant vegetation index) has the best correlation with measured LAI, y= 10.714x2+ 2.324x + 0.157,R~2 = 0.632. In the Tamarix forests samples analysis, NDVI (normalized difference vegetation index) has the best correlation with measured LAI, y= -0.216 x2 + 5.744x - 0.356,R~2 = 0.689,and in the Populus euphratica Oliv forests samples analysis,ARVI has the best correlation with measured LAI, y = 8.ll9x2 + 2.036x2 + 0.095,R~2 = 0.816. (3) All the three models have relatively high overall precision which could meet the demand of LAI inv-er-sion in this arid region. And the fitting precision of Tamarix forests samples and the Populus euphratica Oliv forests samples have improved by 4.7% and 0.2% respectively compared with the whole samples fitting precision. (4) There are three relatively high value areas in the distribution map of LAI, the Daxihaizi reservoir area, the middle part of the reach and the Taitema Lake area,due to relative high water content for vegetation. And the LAI values were mainly in a range of 0-1.5 with a mean value of 0.361. In this study, we estimated the LAI distribution of the riparian vegetation of the lower Tarim River. The results provided data support for studying riparian plant and desert ecology of the Tarim River, and also provided method support for acquiring the high spatial resolution LAI data in the riparian forests in the lower Tarim River.
中文关键词	叶面积指数 ; 植被指数 ; 塔里木河下游 ; 遥感反演 ; Landsat 8 OLI影像
英文关键词	leaf area index vegetation index the lower Tarim River remote sensing inversion Landsat 8 OLI image
语种	中文
国家	中国
收录类别	CSCD
WOS类目	GEOSCIENCES MULTIDISCIPLINARY
WOS研究方向	Geology
CSCD记录号	CSCD:5321751
来源机构	中国科学院地理科学与资源研究所 ; 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/2XILL650/231145
作者单位	1.中国科学院地理科学与资源研究所, 中国科学院生态系统网络观测与模拟重点实验室, 北京 100101, 中国; 2.西北农林科技大学资源与环境学院, 杨陵, 陕西 712100, 中国
推荐引用方式 GB/T 7714	朱绪超,袁国富,易小波,等. 基于Landsat 8 OLI影像的塔里木河下游河岸林叶面积指数反演[J]. 中国科学院地理科学与资源研究所, 西北农林科技大学,2014,37(6):1248-1256.
APA	朱绪超,袁国富,易小波,&杜涛.(2014).基于Landsat 8 OLI影像的塔里木河下游河岸林叶面积指数反演.干旱区地理,37(6),1248-1256.
MLA	朱绪超,et al."基于Landsat 8 OLI影像的塔里木河下游河岸林叶面积指数反演".干旱区地理 37.6(2014):1248-1256.