ESTIMATION OF LEAF AREA INDEX BY USING MULTI-ANGULAR HYPERSPECTRAL IMAGING DATA BASED ON THE TWO-LAYER CANOPY REFLECTANCE MODEL

文献类型： 外文期刊

第一作者： Liao, Qinhong

作者： Liao, Qinhong;Zhao, Chunjiang;Yang, Guijun;Wang, Jihua;Zhang, Dongyan;Liao, Qinhong;Zhang, Dongyan;Coburn, Craig;Wang, Zhijie

作者机构：

关键词： Leaf Area Index;Multi-Angular Hyperspectral Image;Canopy Reflectance Model;Vegetation Index;Partial Least Square Regression

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2013 年 19 卷 3 期

页码：

收录情况： SCI

摘要： This study aims to investigate the effects of observation angle on the estimation of leaf area index (LAI) by using multi-angular hyperspectral imaging data. First, the bidirectional reflectance was simulated with a two-layer canopy reflectance model (ACRM), the obvious bell-shaped and bowl-shaped pattern can be found in the blue, red and NIR wavebands. Subsequently, the three most commonly used vegetation indexes, the normalized difference vegetation index (NDVI), the simple ratio index (SRI) and enhanced vegetation index (EVI) were used to exploit the effect of different observation angles. Through the analysis of simulated data, SRI and EVI displayed a greater potential for estimating LAI due to the fact that they are more sensitive to the variation of observation angle, thus the partial least square regression (PLS) based on the cross validation was applied both to the single observation angle and to various combinations of multiple observation angles. The result shows that SRI has obtained the highest estimation accuracy (R-2 = 0.47, RMSE = 0.30) by the combination of six observation angles, which agreed well with the simulated result, indicating that multi-angular observation can improve the estimation accuracy of LAI.

分类号：

  • 相关文献

[1]Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions. Xie, Qiaoyun,Huang, Wenjiang,Xie, Qiaoyun,Dash, Jadunandan,Song, Xiaoyu,Wang, Renhong,Huang, Linsheng,Zhao, Jinling.

[2]Winter wheat biomass estimation based on canopy spectra. Zheng Ling,Zhu Dazhou,Zhang Baohua,Wang Cheng,Zhao Chunjiang,Zheng Ling,Liang Dong. 2015

[3]Spectroscopic Leaf Level Detection of Powdery Mildew for Winter Wheat Using Continuous Wavelet Analysis. Zhang Jing-cheng,Yuan Lin,Wang Ji-hua,Huang Wen-jiang,Chen Li-ping,Zhang Dong-yan,Zhang Jing-cheng,Yuan Lin,Wang Ji-hua,Zhang Dong-yan,Huang Wen-jiang. 2012

[4]Determination of Cr, Zn, As and Pb in Soil by X-Ray Fluorescence Spectrometry Based on a Partial Least Square Regression Model. Lu, Anxiang,Wang, Jihua,Pan, Ligang,Lu, Anxiang,Qin, Xiangyang,Wang, Jihua,Zhu, Dazhou,Sun, Jiang. 2011

[5]Band Depth Analysis and Partial Least Square Regression Based Winter Wheat Biomass Estimation Using Hyperspectral Measurements. Fu Yuan-yuan,Wang Ji-hua,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan,Fu Yuan-yuan,Wang Ji-hua,Yang Gui-jun,Song Xiao-yu,Xu Xin-gang,Feng Hai-kuan. 2013

[6]Determination of Soil Parameters in Apple-Growing Regions by Near- and Mid-Infrared Spectroscopy. Dong Yi-Wei,Xu Chun-Ying,Li Yu-Zhong,Li Qiao-Zhen,Dong Yi-Wei,Yang Shi-Qi,Fan Zhong-Nan,Wang Ya-Nan,Bai Wei. 2011

[7]Estimation of carotenoid content at the canopy scale using the carotenoid triangle ratio index from in situ and simulated hyperspectral data. Kong, Weiping,Huang, Wenjiang,Zhou, Xianfeng,Kong, Weiping,Zhou, Xianfeng,Song, Xiaoyu,Casa, Raffaele. 2016

[8]Estimation of Grain Protein Content in Winter Wheat by Using Three Methods with Hyperspectral Data. Xiu-liang Jin,Wang, Ji-hua,Xiu-liang Jin,Xin-gang Xu,Hai-kuan Feng,Xiao-yu Song,Qian Wang,Xiu-liang Jin,Xin-gang Xu,Hai-kuan Feng,Xiao-yu Song,Qian Wang,Xiu-liang Jin,Wang, Ji-hua,Guo, Wen-shan. 2014

[9]Development and implementation of a multiscale biomass model using hyperspectral vegetation indices for winter wheat in the North China Plain. Bareth, Georg,Lenz-Wiedemann, Victoria I. S.,Koppe, Wolfgang,Gnyp, Martin L.,Bareth, Georg,Li, Fei,Lenz-Wiedemann, Victoria I. S.,Chen, Xinping,Gnyp, Martin L.,Li, Fei,Miao, Yuxin,Jia, Liangliang,Koppe, Wolfgang,Hennig, Simon D.,Jia, Liangliang,Chen, Xinping,Zhang, Fusuo,Laudien, Rainer. 2014

[10]Mapping paddy biomass with multiple vegetation indexes by using multispectral remotely sensed image. Gu, Xiaohe,Wang, Yancang,Song, Xiaoyu,Xu, Xingang. 2016

[11]Assessment of Aerial Agrichemical Spraying Effect Using Moderate-Resolution Satellite Imagery. Zhang Dong-Yan,Wang Xiu,Chen Li-ping,Ma Wei,Zhang Dong-Yan,Zhang Dong-Yan,Wang Xiu,Chen Li-ping,Li Bin,Ma Wei,Lan Yu-bin,Lan Yu-bin,Zhou Xin-gen. 2016

[12]Estimation of crop LAI using hyperspectral vegetation indices and a hybrid inversion method. Liang, Liang,Zhang, Lianpeng,Lin, Hui,Liang, Liang,Zhao, Shuhe,Liang, Liang,Di, Liping,Deng, Meixia,Qin, Zhihao.

[13]REMOTE SENSING OF THE SEASONAL NAKED CROPLANDS USING SERIES OF NDVI IMAGES AND PHENOLOGICAL FEATURE. Shan, Zhengying,Xu, Qingyen. 2013

[14]Assessment of Chlorophyll Content Using a New Vegetation Index Based on Multi-Angular Hyperspectral Image Data. Liao Qin-hong,Zhang Dong-yan,Liao Qin-hong,Zhang Dong-yan,Wang Ji-hua,Yang Gui-jun,Yang Hao,Liao Qin-hong,Zhang Dong-yan,Wang Da-cheng,Craig, Coburn,Wong Zhijie. 2014

[15]Crop growth condition monitoring and analyzing in county scale by time series MODIS medium-resolution data. Yu, Kun,Wang, Zhiming,Sun, Ling,Shan, Jie,Mao, Liangjun. 2013

[16]Exploring new spectral bands and vegetation indices for estimating nitrogen nutrition index of summer maize. Zhao, Ben,Duan, Aiwang,Liu, Zhandong,Chen, Zhifang,Zhang, Jiyang,Xiao, Junfu,Liu, Zugui,Qin, Anzhen,Ning, Dongfeng,Ata-Ul-Karim, Syed Tahir,Gong, Zhihong. 2018

[17]Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring. Peng, D.,Hu, Y.,Li, Z..

[18]Comparison of two methods for monitoring leaf total chlorophyll content (LTCC) of wheat using field spectrometer data. Jin, X.,Wang, K.,Li, S.,Jin, X.,Diao, W.,Xiao, C.,Wang, K.,Li, S.,Wang, F.,Chen, B..

[19]Effects of vegetation indices to the spatial changes of desert environment using EOS/MODIS data: A case study to Sangong inland arid ecosystem. Lu, Liping,Qin, Zhihao,Qin, Zhihao,Gao, Maofang,Zhao, Chengyi,Li, Wenjuan. 2006

[20]Comparison of vegetation indices and red-edge parameters for estimating grassland cover from canopy reflectance data. Liu, Zhan-Yu,Huang, Jing-Feng,Wu, Xin-Hong,Dong, Yong-Ping. 2007

作者其他论文 更多>>

微信小程序