刘珺,庞鑫,李彦荣,杜灵通.夏玉米叶面积指数遥感反演研究[J].农业机械学报,2016,47(9):309-317.
Liu Jun,Pang Xin,Li Yanrong,Du Lingtong.Inversion Study on Leaf Area Index of Summer Maize Using Remote Sensing[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(9):309-317.
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夏玉米叶面积指数遥感反演研究   [下载全文]
Inversion Study on Leaf Area Index of Summer Maize Using Remote Sensing   [Download Pdf][in English]
投稿时间:2015-11-16  
DOI:10.6041/j.issn.1000-1298.2016.09.042
中文关键词:  夏玉米  叶面积指数  反演  植被指数  HJ卫星
基金项目:国家自然科学基金项目(41201438)、山西省青年研究基金项目(2014021032-1)和太原理工大学校基金项目(2013Z016)
作者单位
刘珺 太原理工大学
山西省交通科学研究院博士后科研工作站 
庞鑫 太原理工大学 
李彦荣 太原理工大学 
杜灵通 宁夏大学 
中文摘要:利用LAI-2000的观测数据与基于HJ卫星遥感数据生成的植被指数,结合3种常用的回归模型,构造了夏玉米分别按全生育期、不同生育阶段和阈值分段的叶面积指数(Leaf area index, LAI)反演模型;获取了3种模式下LAI的最优反演模型;在验证和评价各模型可靠性之后,生成了夏玉米在营养生长期、抽雄期和生殖生长期的LAI分布图;并将基于HJ影像反演得到的LAIHJ与MODIS LAI产品(MOD15A2)LAIM进行了对比。研究发现,与各种通用植被指数相比,针对HJ CCD数据构造的环境植被指数HJVI与LAI的相关性在3种反演模式中均为最佳。HJVI与全生育期LAI的相关性达到0.875,在不同生育阶段与LAI的相关性也高于其他植被指数(营养生长期线性模型最佳,〖JP3〗决定系数为0.769;抽雄期对数模型最佳,决定系数为0.783;生殖生长期指数模型最佳,决定系数为0.703)。〖JP〗普适性植被指数中,OSAVI适用于夏玉米生长前中期的LAI反演,NDVI适用于夏玉米生长后期的LAI反演。在夏玉米全生育期内,各植被指数与LAI的相关性整体较高,但最优回归模型出现在按不同生育阶段反演的模式中。LAI小于3时EVI为精度最佳指数(决定系数为0.358),LAI不小于3时OSAVI为精度最佳指数(决定系数为0.515)。在夏玉米3个生育阶段,LAIM与LAIHJ的相关性分别达到0.732、0.761、0.661。HJ遥感数据具有较强的LAI反演能力,其高时间和高空间分辨率的特征可以使其代替传统的中分辨率遥感数据而成为农业遥感研究的重要数据源。
Liu Jun  Pang Xin  Li Yanrong  Du Lingtong
Taiyuan University of Technology;Postdoctoral Research Workstation of Shanxi Transportation Research Institute,Taiyuan University of Technology,Taiyuan University of Technology and Ningxia University
Key Words:summer maize  leaf area index  inversion  vegetation index  HJ satellite
Abstract:The observation data of LAI-2000 and vegetation index was generated by satellite remote sensing data of HJ, combining three kinds of commonly used regression model. LAI (Leaf area index) inversion model was constructed according to growth period, growth stage and threshold boundaries of summer maize, respectively. The optimal LAI inversion model was acquired based on the above three modes. The summer corn LAI scatter grams of the vegetative growth period, the tasseling stage as well as the reproductive stage were generated after verification and evaluation of the model reliability. The productions of MODIS LAI (MOD15A2) were verified by LAIHJ based on the inversion of model HJ image. According to the survey, except HJVI, during the whole growth period of summer maize, a linear model of RVI with LAI was regarded as the best fitting model (R2 = 0.662); during the vegetative growth period, a linear model of OSAVI with LAI was regarded as the best fitting model (R2=0.724); at the tasseling stage, index model of OSAVI with LAI was regarded as the best fitting model(R2=0.749); at the reproductive stage, a linear model of NDVI with LAI was regarded as the best fitting model(R2=0.700). The correlation of HJVI and LAI at the growth period achieved to 0875, and the correlation at different growth stages with LAI is higher than the other vegetation indexes (during the vegetative period, R2=0.769; at the tasseling stage, R2=0.783; at the reproductive stage, R2=0.703). EVI is the best index when LAI is less than 3 (R2=0.358), while OSAVI is the best when LAI is more than 3(R2=0.515). During the three reproductive periods, R2 of LAIM and LAIHJ is 0.732, 0.761 and 0.661. Conclusions were drawn: the inversion method of LAI at different stages is optimal. HJVI shows obvious advantage for LAI inversion ability. The production of MODIS LAI could be used for crop monitoring in special situation. The study not only broadens the mode of inversion LAI using vegetation index, but also confirms the importance of HJ data in agricultural field.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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