Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction

被引:25
|
作者
Venancio, Luan Peroni [1 ]
Mantovani, Everardo Chartuni [1 ]
do Amaral, Cibele Hummel [2 ]
Usher Neale, Christopher Michael [3 ]
Goncalves, Ivo Zution [3 ]
Filgueiras, Roberto [1 ]
Eugenio, Fernando Coelho [4 ]
机构
[1] Fed Univ Vicosa UFV, Agr Engn Dept, Ave Peter Henry Rolfs, BR-36570900 Vicosa, MG, Brazil
[2] Fed Univ Vicosa UFV, Forest Engn Dept, Ave Peter Henry Rolfs, BR-36570900 Vicosa, MG, Brazil
[3] Univ Nebraska UNL, Daugherty Water Food Global Inst, Nebraska Innovat Campus,2021 Transformat Dr Ste 3, Lincoln, NE 68588 USA
[4] Fed Univ Santa Maria UFSM, Forest Engn Dept, St Ernesto Barros, BR-96506322 Cachoeira Do Sul, RS, Brazil
关键词
Zea maysL; spectral unmixing; above-ground green biomass; yield; LEAF-AREA INDEX; MIXTURE ANALYSIS; PHYTOMASS PRODUCTION; YIELD RESPONSE; USE EFFICIENCY; HARVEST INDEX; MAIZE; COVER; RADIATION; MODEL;
D O I
10.1016/j.agwat.2020.106155
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Crop biomass (Bio) is one of the most important parameters of a crop, and knowledge of it before harvest is essential to help farmers in their decision making. Both green and dry Bio can be estimated from vegetation spectral indices (VIs) because they have a close relationship with accumulated absorbed photosynthetically active radiation (APAR), which is proportional to total Bio. The aims of this study were to analyze the potential capacity of spectral vegetation indices in estimating corn green biomass based on their relationship with the photosynthetic vegetation sub-pixel fraction derived from spectral mixture analysis and to analyze the best interval of VI accumulation (days) for corn grain yield estimation. Field data of center pivots cultivated with corn during the irrigation seasons of 2015 and 2018 and Landsat 8 and Sentinel 2 images were used. The EVI produced the best results; Pearson's correlation coefficient, RMSE and Willmott's index reached 0.99, 6.5%, and 0.948, respectively. Among the nine potential VIs analyzed, the EVI, SAVI and OSAVI were considered the first, second and third best performing for corn green Bio estimation, respectively, based on their comparison to the photosynthetic vegetation sub-pixel fraction (fPV), and the time intervals that extended until 120 days after sowing showed the best results for corn grain yield estimation.
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页数:14
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