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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| Published in | 江西农业学报 Vol. 27; no. 10; pp. 58 - 61 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| 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
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-8581 |
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| Abstract | 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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| AbstractList | 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。 TP79; 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=1.717e1064x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. |
| Author | 翟羽娟 张艳红 刘兆礼 刘宝江 |
| AuthorAffiliation | 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 |
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| Author_FL | LIU Bao-jiang LIU Zhao-li ZHAI Yu-juan ZHANG Yan-hong |
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| DocumentTitleAlternate | Study on Inversion Model of Maize LAI Based on Hyperspectral Images |
| DocumentTitle_FL | Study on Inversion Model of Maize LAI Based on Hyperspectral Images |
| EndPage | 61 |
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| Keywords | 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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| Notes | 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 |
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| PublicationTitle | 江西农业学报 |
| PublicationTitleAlternate | Acta Agriculturae Jiangxi |
| PublicationTitle_FL | Acta Agriculturae Jiangxi |
| PublicationYear | 2015 |
| Publisher | 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 |
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| SubjectTerms | Hyperion影像 反演建模 玉米叶面积指数 |
| Title | 基于高光谱影像的玉米LAI反演模型研究 |
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