Hierarchical Classification of Soybean in the Brazilian Savanna Based on Harmonized Landsat Sentinel Data

Autor(es)

Parreiras, Taya Cristo ; Bolfe, Edson Luis ; Dantas Chaves, Michel Eustaquio ; Sanches, Ieda Del'Arco ; Sano, Edson Eyji ; Victoria, Daniel de Castro ; Bettiol, Giovana Maranhao ; Vicente, Luiz Eduardo

• Tipo de documento: Artigo Científico
• Fonte: REMOTE SENSING; v. 14, n. 15, p. 22-pg., 2022-08-01.

Resumo

The Brazilian Savanna presents a complex agricultural dynamic and cloud cover issues; therefore, there is a need for new strategies for more detailed agricultural monitoring. Using a hierarchical classification system, we explored the Harmonized Landsat Sentinel-2 (HLS) dataset to detect soybean in western Bahia, Brazil. Multispectral bands (MS) and vegetation indices (VIs) from October 2021 to March 2022 were used as variables to feed Random Forest models, and the performances of the complete HLS time-series, HLSS30 (harmonized Sentinel), HLSL30 (harmonized Landsat), and Landsat 8 OLI (L8) were compared. At Level 1 (agricultural areas x native vegetation), HLS, HLSS30, and L8 produced identical models using MS + VIs, with 0.959 overall accuracies (OA) and Kappa of 0.917. At Level 2 (annual crops x perennial crops x pasturelands), HLS and L8 achieved an OA of 0.935 and Kappa > 0.89 using only VIs. At Level 3 (soybean x other annual crops), the HLS MS + VIs model achieved the best performance, with OA of 0.913 and Kappa of 0.808. Our results demonstrated the potential of the new HLS dataset for medium-resolution mapping initiatives at the crop level, which can impact decision-making processes involving large-scale soybean production and agricultural sustainability. (AU)

• Processo FAPESP: 19/26222-6 - Mapeamento agropecuário no Cerrado via combinação de imagens multisensores
• Beneficiário: Édson Luis Bolfe
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 21/07382-2 - Uso de séries temporais densas Sentinel-2/MSI e algoritmos de aprendizado de máquinas para melhorar o monitoramento agrícola no bioma Cerrado
• Beneficiário: Michel Eustáquio Dantas Chaves
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado