基于高光谱影像的玉米LAI反演模型研究

以吉林省长春西部地区合心与合隆镇为研究区,利用高光谱Hyperion遥感影像,结合与其同步实测LAI数据,分别建立影像波段与玉米LAI线性及非线性统计回归模型,最终选出以SAVI为自变量的指数函数模型y=1.717e1.064x为最优反演模型,其估测精度高达96.8%。经实验证实,高光谱遥感可以实现大范围、快速、较精确地获取玉米叶面积指数。...

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Bibliographic Details
Published in江西农业学报 Vol. 27; no. 10; pp. 58 - 61
Main Author 翟羽娟 张艳红 刘兆礼 刘宝江
Format Journal Article
LanguageChinese
Published 吉林建筑大学城建学院,吉林长春,130111%吉林大学地球探测科学与技术学院,吉林长春,130026%中国科学院东北地理与农业生态研究所,吉林长春,130012 2015
Subjects
Hyperion影像
反演建模
玉米叶面积指数
Maize leaf area index
反演建模
Hyperion image
Hyperion影像
Inversion model
玉米叶面积指数
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ISSN1001-8581

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Summary:以吉林省长春西部地区合心与合隆镇为研究区,利用高光谱Hyperion遥感影像,结合与其同步实测LAI数据,分别建立影像波段与玉米LAI线性及非线性统计回归模型,最终选出以SAVI为自变量的指数函数模型y=1.717e1.064x为最优反演模型,其估测精度高达96.8%。经实验证实,高光谱遥感可以实现大范围、快速、较精确地获取玉米叶面积指数。
Bibliography:36-1124/S
In this paper, Hexin and Helong towns of western Changchun city in Jilin province were taken as the research re- gions. According to the hyperspectral remote-sensing Hyperion images and synchronously-measured maize LAI （ Leaf Area Index） data, the linear and nonlinear statistical regressive models describing the relationship between maize LAI and image band were built respectively. The exponential function model y= 1.717e^1.064x, which used SAV1 as independent variable, was finally selected as the optimum inversion model, and its estimative accuracy was as high as 96.8%. This experiment confirmed that the hyperspectral re- mote-sensing could quickly and accurately acquire the LAI of large-area maize.
Hyperion image; Maize leaf area index; Inversion model
ZHAI Yu-juan, ZHANG Yan-hong , LIU Zhao-li, LIU Bao-jiang （ 1. City College, Jilin Jianzhu University, Changchun 130111, China; 2. College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China; 3. Northeast Institute of G
ISSN:1001-8581