|Table of Contents|

Ｒetrieving Soybean Leaf Area Index Based on High Imaging Spectrometer(PDF)

《大豆科学》[ISSN:1000-9841/CN:23-1227/S]

Issue:
2016年04期
Page:
599-608
Research Field:
Publishing date:

Info

Title:
Ｒetrieving Soybean Leaf Area Index Based on High Imaging Spectrometer
Author(s):
LU Guo-zheng1; 2; 3; LI Chang-chun1; YANG Gui-jun2; YU Hai-yang2; ZHAO Xiao-qing2; ZHANG Xiao-yan3
1. School of Surveying and Land Information Engineering，Henan Polytechnic University，Jiaozuo 454000，China; 2. National Engineering ＲesearchCenter for Agricultural Information Technology，Beijing 100097，China; 3. Nanjing Agricultural University，The National Center for Soybeans，Nanjing210095，China
Keywords:
Unmanned aerial vehicle ( UAV) ;  Ｒemote sensing;  Digital;  High imaging spectrometer;  Vegetation index;  Leafarea index
PACS:
TP79
DOI:
10.11861/j.issn.1000-9841.2016.04.0599
Abstract:
Hyperspectral remote sensing can continuous access to a spectral image，this technology can greatly improve the estimationof leaf area index level. Using unmanned aerial vehicle ( UAV) with high imaging spectrometer for crop spectral informationinversion of leaf area index of precision agriculture production and management is of great significance. This articlechose the triangle ratio vegetation index ( TVI) ，vegetation index ( ＲVI) ，NDVI705，NDVI and ＲDVI using the grey correlationdegree sorting，red pool information criteria and partial least squares ( GＲA-PLS-AIC) ，being combined with the fieldmeasured leaf area index data，the empirical model was used to construct multiple index inversion model. By unmanned aerialvehicle UAV for high platform synchronization with a digital camera and imaging spectrometer，gained the soybean throughoutthe reproductive period of remote sensing image in Jinghang canal area，at the same time used LAI-2200c plant canopy analyzerfor determination of leaf area index，took the measurement data of remote sensing image and the ground inversion of leaf areaindex. Ｒesults showed that many exponential model were builded in the whole soybean reproductive period，the modelingresults Ｒ2 and ＲMSE of the predicted and the measured values were 0. 701 and 0. 672 respectively，the verification results Ｒ2and ＲMSE were 0. 695 and 0. 534 respectively，forecasting model had higher precision and reliability using the model to theinversion of LAI was accurate，the generated soybean LAI distribution reflected the reality of the local soybean was growing.Platform for multiple UAV rotorcraft synchronization，an high-definition digital camera and a high imaging spectrometer madethe large soybean leaf area index inversion feasible，and build more index model for the whole growth period.

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Last Update: 2016-08-22