1. Model for soybean production forecast based on prevailing physical conditions
- Author
-
Aníbal Gusso, Jorge Ricardo Ducati, Damien Arvor, Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Université de Caen Normandie (UNICAEN), and Université de Nantes (UN)-Université de Nantes (UN)
- Subjects
Official statistics ,Coefficient of determination ,010504 meteorology & atmospheric sciences ,Agriculture (General) ,satellite ,01 natural sciences ,S1-972 ,remote sensing ,Statistics ,Production (economics) ,Reliability (statistics) ,ComputingMilieux_MISCELLANEOUS ,0105 earth and related environmental sciences ,agriculture ,2. Zero hunger ,Amazon rainforest ,Crop yield ,04 agricultural and veterinary sciences ,Enhanced vegetation index ,[SHS.GEO]Humanities and Social Sciences/Geography ,15. Life on land ,EVI ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Environmental science ,Animal Science and Zoology ,Moderate-resolution imaging spectroradiometer ,Modis ,Agronomy and Crop Science - Abstract
The objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p≤0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast.
- Published
- 2017
- Full Text
- View/download PDF