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基于IDL语言的植被指数UNVI软件插件

Universal Normalized Vegetation Index(UNVI) and UNVI software based on IDL
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摘要 植被指数是地球陆表植被覆盖度和植被活力的指示因子,对环境监测、植被理化参量估算等应用研究有重要的意义。基于植被的反射光谱特征,通过遥感数据波段的组合,可以计算得到遥感植被指数。传统的植被指数如NDVI、EVI等仅利用有限波段信息的线性或非线性组合构建而成,没有充分利用遥感传感器所提供的多波段遥感信息,通用归一化植被指数UNVI(Universal Normalized Vegetation Index)充分利用了遥感传感器提供的多波段植被光谱信息,因此在反演植被叶绿素、生物量等植被理化参量上较其他传统植被指数更具优势。为方便UNVI指数的计算,本文基于IDL语言开发了UNVI软件插件,可直接作为ENVI商业遥感软件进行调用,并可满足多个传感器的UNVI计算需求。为了验证UNVI的应用效果,以植被总初级生产力GPP(Gross Primary Productivity)估算为例,比较了不同植被指数估算GPP的效果,结果表明:基于UNVI估算的GPP与通量站点获得的GPP具有较高的相关性(相关系数R2为0.79),验证了UNVI在GPP估算方面的优势。本文提供的UNVI软件插件可为遥感研究和应用人员提供便捷的计算工具。 The Universal Normalized Vegetation Index(UNVI)is an improved Vegetation Index(VI)based on the Universal Pattern Decomposition Method(UPDM).However,UPDM-based UNVI involves the calculation of a complex coefficient matrix,which is inconvenient for users.We reformulated the computation of the coefficients of the UPDM without changing its main mathematical formulation to generalize the UNVI in a user friendly manner.We derived new matrices and developed a UNVI software using IDL to facilitate the convenient calculation of the UNVI based on data from MODIS and Lands at TM,ETM,and OLI satellite sensors.Vegetation information derived from satellite data is highly significant to the operational monitoring of the Earth’s land cover.VIs are determined traditionally by calculating directly the algebraic combinations of the reflectance at different bands,that is,from the visible to the SWIR spectral range.These VIs(e.g.,NDVI and EVI)were calculated by limited reflectance bands and might cause loss of information.All available data are considered as input variables in UPDM-based UNVI in the calculation of VIs.We provided the code and the coefficient matrices in this study to make UNVI usable for all users and multiple sensors.For the UPDM-based UNVI,the spectrum of each pixel is expressed as the linear sum of three fixed standard spectral patterns(i.e.,water,vegetation,and soil),along with a supplementary one(i.e.,yellow leaves),associated with particular objects found on land.The goal of UPDM is to transform the reflectance values of the n bands of a target pixel into three standard coefficients,along with a supplementary one,using standard spectral decomposition patterns.We derived the matrices to facilitate the convenient calculation of the UNVI based on data from the MODIS and Lands at TM,ETM,and OLI satellite sensors.We also provided the software and coefficient matrices of UNVI.We assessed the capabilities of the UNVI to evaluate the Gross Primary Production(GPP)of vegetation compared with the GPP data derived from t
作者 胡顺石 张辰璐 乔娜 孙雪剑 钟涛 HU Shunshi;ZHANG Chenlu;QIAO Na;SUN Xuejian;ZHONG Tao(College of Resources and Environmental Sciences,Hunan Normal University,Changsha410081,China;Key Laboratory of Geospatial Big Data Mining and Application,Hunan Province,Changsha410081,China;State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Science,Beijing100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing100049,China)
出处 《遥感学报》 EI CSCD 北大核心 2019年第5期952-958,共7页 Journal of Remote Sensing
基金 湖南省自然科学基金(编号:2018JJ3348) 湖南省大学生研究性学习和创新性实验计划项目(编号:201710542032) 国家自然科学基金(编号:41830108) 中国国家留学基金(编号:201806725009) 湖南省教育厅科学研究项目(编号:17C0952).
关键词 LANDSAT MODIS 植被指数 UNVI IDL语言 GPP Landsat MODIS vegetation index UNVI IDL GPP
作者简介 第一作者:胡顺石,1984年生,男,讲师,研究方向为资源环境遥感与灾害遥感、遥感大数据应用。E-mail:hufrank@163.com;通信作者:孙雪剑,1987年生,男,助理研究员,研究方向为高光谱数据融合。E-mail:sunxj@radi.ac.cn
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