Prognosis for Brazilian Agricultural Production: The Impact of Drought-Sensitive Crops on the Climate

The northern part of the state of Mato Grosso is located at the intersection of large-scale agricultural production and the Amazon, a tropical biome of great importance for ecosystem services and biodiversity. Agricultural production activities interact with natural capital, among other factors, in land use and in biogeochemical cycles of water and carbon. In this study, we sought to use remote sensing at the regional level to diagnose and spatialize the contribution of agricultural activity to dry areas. Using carbon dioxide orbital models, land use classification techniques, the Standardized Precipitation Index (SPI), and Pettitt and Mann–Kendall statistics, the variables were compared spatially for the biogeographic boundary of the Amazon in Mato Grosso in two distinct time frames: (i) over the crop years of the CO2 efflux model (2020 to 2023), and (ii) over the years 2008 to 2023, with consolidated data from the MODIS sensor system. The hot and cold spots analysis reinforces the correlation of carbon variables to land use; the drought index suggests a spatial correlation to forest loss, where more intense agricultural activity favors drought and inhibits moderate rainfall, and in turn is linked to the amount of forest in the context of intense continentality. Temporally, the statistical diagnosis highlights abrupt changes in 2011, 2013, and 2019, restate the complex relation of tropical forest and biogeochemical cycles, above all with carbon dioxide.

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Publication Details

Journal
Climate
Published
2026-04-20
DOI
https://doi.org/10.3390/cli14040087
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Prognosis for Brazilian Agricultural Production: The Impact of Drought-Sensitive Crops on the Climate

Damien Arvor, Tatiane Deoti Pelissari, João Lucas Della-Silva, Fernando Saragosa Rossi et al.
Climate
Remote Sensing in Agriculture
article

Prognosis for Brazilian Agricultural Production: The Impact of Drought-Sensitive Crops on the Climate

Damien Arvor, Tatiane Deoti Pelissari, João Lucas Della-Silva, Fernando Saragosa Rossi, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro, Carlos Antônio da Silva, Gabriela Souza de Oliveira, Wendel Bueno Morinigo
article en

Abstract

The northern part of the state of Mato Grosso is located at the intersection of large-scale agricultural production and the Amazon, a tropical biome of great importance for ecosystem services and biodiversity. Agricultural production activities interact with natural capital, among other factors, in land use and in biogeochemical cycles of water and carbon. In this study, we sought to use remote sensing at the regional level to diagnose and spatialize the contribution of agricultural activity to dry areas. Using carbon dioxide orbital models, land use classification techniques, the Standardized Precipitation Index (SPI), and Pettitt and Mann–Kendall statistics, the variables were compared spatially for the biogeographic boundary of the Amazon in Mato Grosso in two distinct time frames: (i) over the crop years of the CO2 efflux model (2020 to 2023), and (ii) over the years 2008 to 2023, with consolidated data from the MODIS sensor system. The hot and cold spots analysis reinforces the correlation of carbon variables to land use; the drought index suggests a spatial correlation to forest loss, where more intense agricultural activity favors drought and inhibits moderate rainfall, and in turn is linked to the amount of forest in the context of intense continentality. Temporally, the statistical diagnosis highlights abrupt changes in 2011, 2013, and 2019, restate the complex relation of tropical forest and biogeochemical cycles, above all with carbon dioxide.

ClimateVol. 14(4)
Universidade Federal de Mato Grosso do Sul (BR), Universidade do Estado de Mato Grosso (BR), Université Rennes 2 (FR), Littoral, Environnement, Télédétection, Géomatique (FR), Université de Rennes (FR)
Universidade do Estado de Mato Grosso, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Centre National de la Recherche Scientifique, Universidade Federal de Mato Grosso do Sul
Zero hunger
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
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