Inversion of Leaf Area Index of Silage Corn Based on PROSAIL Model
Abstract
Accurately and efficiently estimating corn LAI data within a region is of crucial importance for field management decisions, predicting land yield, and implementing precision agriculture. In response to the problems of scale effect, low accuracy, and poor universality in multi-scale and large-scale remote sensing inversion, taking the silage corn experimental field in Minle County, Zhangye City as the research area, silage corn was selected as the research object, based on Landsat-8 hyperspectral and Modis multispectral remote sensing images, combined with ground measured data. Through local and global sensitivity analysis of the input parameters of the PROSAIL model,the lookup table of canopy reflectance-LAI of silage corn in multiple growth periods and the inversion strategy of the minimum optimization cost function were constructed, and the optimal LAI inversion model for the study area was determined. The accuracy verification and linear fitting of the inversion results were completed by using the measured values in different growth periods of silage corn. The results showed that the inversion results of LAI were generally good, with high fitting accuracy and strong correlation with the measured values. The optimal determination coefficients R2 for the jointing stage, tasseling stage, and maturity stage were 0.85, 0.91, and 0.90, respectively. The root mean square error (RMSE) were 0.35, 0.58, and 0.51, respectively. Therefore, the inversion strategy based on multi-source hyperspectral remote sensing data combined with the PROSAIL model can provide scientific basis and methods for crop parameter inversion.
Keywords:silage corn;LAI;PROSAIL model;inversion strategy;hyperspectral data
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TANG Defu, CHEN Zhigang, LI Fei, et al. Construction of near-infrared prediction model for nutrient content in different parts (tissues) of silage maize J . Prataeultural Science, 2021 ,38 (9) ; 1753 -1761. (in Chinese)
DARVISHZADEH R, WANG T, SKIDMORE К A, et al. Analysis of Sentinel—2 and rapideye for retrieval of leaf area index in a saltmarsh using a radiative transfer model [ J]. Remote Sensing ,2019 ,1 1 ( 6 ) : 67 1.
WANG Baoshui, LIU Xu, YANG Hongjun. A vegetation LAI inversion algorithm based on hyperspectral remote sensing data [J] . Geospatial Information, 2016,14 (11): 72 -73. (in Chinese)
LIU Shuaibing, JIN Xiuliang, FENG Ilaikuan, et al. Analysis of effect of disease stress on maize LAI remote sensing estimation J. Transactions of the Chinese Society for Agricultural Machinery ,2023 ,54( 3) *.246 -258. (in Chinese)
HE Xiaohui, FENG Kun, GUO Hengliang, et al. Comparison of leaf area index inversion of different soybean populations based on BP neural network model optimized by PROSAIL model and genetic algorithm[ J]. Journal of Henan Agricultural University, 2021 ,55(4) :698 -706. (in Chinese)
SHAO Yajie, TANG Qiuxiang, GUI Jianping, et al. Cotton leaf area index estimation using UAV spectral information and texture characteristics [ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(6) : 186 - 196. (in Chinese)
LUO Shezhou, CHENG Feng, W ANG Fangjian, et al. Inversion of leaf area index in Nyingchi region of Tibet based on TM remote sensing data [J] . Remote Sensing Technology and Application ,2012 ,27(5 ) :740 -745. (in Chinese)
BAI Landong, GOU Yepei, SHAO Wenwen, et al. Linear relationship between vegetation index and leaf area index based on multi-angle remote sensing [ J ]. Engineering of Surveying and Mapping,2016 ,25( 1 ) : 1 -4. ( in Chinese)
LIU Jun, PANG Xin, LI Yanrong, et al. Study on remote sensing retrieval of leaf area index of summer maize [J ]. Transactions of the Chinese Society for Agricultural Machinery ,2016 ,47 ( 9) :309 -317. (in Chinese)
WANG Jun, JIANG Yun. Leaf area index inversion of soybean based on UAV' multispectral remote sensing [ J ]. China Agriculture Bulletin, 2021 ,37( 19): 134 -142. (in Chinese)
GUO Hengliang, LI Xiao, FU Yu, et al. The PROSAIL model based on nuclear ridge regression algorithm the high spatial resolution leaf area index [J . Acta Prataculturae Siniea, 2022,31 ( 12) ; 41 -51. (in Chinese)
ZHANG Mingzheng, SU Wei, ZHU Dehai. Research on leaf area index and leaf chlorophyll content based on PROSAIL model [J]. Geography and Geographic Information Science, 2019,35(5) : 28 -33. (in Chinese)
DU Yuzhang, JIANG Xiaoguang, ZHANG Yuze, et al. Invert the leaf area index based on the Landsat — 8 remote sensing data and the PROSAIL radiative transmission model [J] . Geography of Arid Region, 2016,39(5) ; 1096 - 1 103. ( in Chinese)
SU Wei, WU Jiayu, WANG Xinsheng, et al. LAI inversion of maize canopy based on Sentinel —2 image and PROSAIL model parameter calibration [J]. Spectroscopy and Spectral Analysis, 2021 ,41 (6) ; 1891 - 1897. (in Chinese)
ZENG Qi, YU Kunyong, YAO Xiong, et al. Simulation of canopy reflectance of Phyllostachys phyllostachys based on PROSAIL radiative transfer model[ J], Chinese Journal of Plant Sciences ,2017 ,35 (5 ) :699 -707. (in Chinese)
GU Chengvan, DU Huaqiang, ZHOU Cuomo, et al. Remote sensing retrieval of leaf area index of bamboo forest based on PROSAIL radiative transfer model [j]. Chinese Journal of Applied Ecology ,2013 ,24( 8) :2248 -2256. (in Chinese)
SU Wei, GUO Hao, ZHAO Dongling, et al. LAI inversion method for maize based on optimization of PROSAIL leaf inclination distribution function [ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47 ( 3 ) ; 234 - 241. (in Chinese)
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