Estimating double cropping plantations in the Brazilian Cerrado through PlanetScope monthly mosaics.

• Autor(a) principal: SANO, E. E.
• Data de Publicação: 2023
• Outros Autores: BOLFE, E. L., PARREIRAS, T. C., BETTIOL, G. M., VICENTE, L. E., DEL'ARCO SANCHES, I., VICTORIA, D. de C.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152103; https://doi.org/10.3390/land12030581
• topic: Floresta aleatória; Mapeamento do uso da terra; Mapeamento de cobertura da terra; Cobertura da terra; Constelação de satélites; Matriz de coocorrência em nível de cinza; Savana tropical; Random forest; Gray-level co-occurrence matrix; GRNDI; Land use and land cover mapping; Satellite constellation; Tropical savanna; Uso da Terra; Land use; Land cover

Abstract: Farmers in the Brazilian Cerrado are increasing grain production by cultivating second crops during the same crop growing season. The release of PlanetScope (PS) satellite images represents an innovative opportunity to monitor double cropping production. In this study, we analyzed the potential of six PS monthly mosaics from the 2021/2022 crop growing season to discriminate double cropping areas in the municipality of Goiatuba, Goiás State, Brazil. The four multispectral bands of the PS images were converted into normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), green-red normalized difference index (GRNDI), and textural features derived from the gray-level co-occurrence matrix (GLCM). The ten most important combinations of these attributes were used to map double cropping systems and other land use and land cover classes (cultivated pasture, sugarcane, and native vegetation) of the municipality through the Random Forest classifier. Training and validation samples were obtained from field campaigns conducted in October 2021 and April 2022. PS mosaic from February 2022 was the most relevant data. The overall accuracy and Kappa index of the final map were 92.2% and 0.892, respectively, with an accuracy confidence of 81%. This approach can be expanded for mapping and monitoring other agricultural frontiers in the Cerrado biome.