Data/hora: 03/06/2024 15:59:05

Biblioteca(s): 	Embrapa Agricultura Digital; Embrapa Cerrados; Embrapa Meio Ambiente.	
Data corrente: 	01/03/2023	
Data da última atualização: 	06/03/2023	
Autoria: 	SANO, E. E.; BOLFE, E. L.; PARREIRAS, T. C.; BETTIOL, G. M.; VICENTE, L. E.; DEL'ARCO SANCHES, I.; VICTORIA, D. de C.	
Afiliação: 	EDSON EYJI SANO, CPAC; EDSON LUIS BOLFE, CNPTIA; TAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; GIOVANA MARANHAO BETTIOL, CPAC; LUIZ EDUARDO VICENTE, CNPMA; IARA DEL´ARCO SANCHES, INSTITUTO DE PESQUISAS ESPACIAIS; DANIEL DE CASTRO VICTORIA, CNPTIA.	
Título: 	Estimating double cropping plantations in the Brazilian Cerrado through PlanetScope monthly mosaics.	
Ano de publicação: 	2023	
Fonte/Imprenta: 	Land, v. 12, n. 3, 581, 2023.	
DOI: 	https://doi.org/10.3390/land12030581	
Idioma: 	Inglês	
Conteúdo: 	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.	
Palavras-Chave: 	Cobertura da terra; Constelação de satélites; Floresta aleatória; Gray-level co-occurrence matrix; GRNDI; Land use and land cover mapping; Mapeamento de cobertura da terra; Mapeamento do uso da terra; Matriz de coocorrência em nível de cinza; Random forest; Satellite constellation; Savana tropical; Tropical savanna.	
Thesagro: 	Cobertura do Solo; Uso da Terra.	
Thesaurus Nal: 	Land cover; Land use.	
Categoria do assunto: 	--
P Recursos Naturais, Ciências Ambientais e da Terra	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1152103/1/land-12-00581-v2.pdf	
Registro original: 	Embrapa Cerrados (CPAC)	
Exemplares: 	CNPTIA - (21623-1) - UPC - AP - DD -  -  -  - DIS
CNPMA - (17376-1) - UPC - AP - DD -  -  -  - DIS
CPAC - (37498-1) - UPC - AP - DD - DIGITAL -  -  - DIS