A Method for Estimating Soybean Sowing, Beginning Seed, and Harvesting Dates in Brazil Using NDVI-MODIS Data

Author:

Carneiro de Santana Cleverton Tiago12,Del’Arco Sanches Ieda13ORCID,Marques Caldas Marcellus4ORCID,Adami Marcos13ORCID

Affiliation:

1. Remote Sensing Graduate Program (PGSER), Coordination of Teaching, Research and Extension (COEPE), National Institute for Space Research (INPE), Av. dos Astronautas, 1.758, São José dos Campos 12227-010, SP, Brazil

2. Management of Crop Monitoring (GEASA), Superintendence of Agricultural Information (SUINF), Directorate of Agricultural Policy and Information (DIPAI), National Food Supply Company (CONAB), SGAS I Setor de Grandes Áreas Sul 901 s/n, Asa Sul, Brasília 70390-010, DF, Brazil

3. Earth Observation and Geoinformatics Division (DIOTG), General Coordination of Earth Science (CG-CT), National Institute for Space Research (INPE), Av. dos Astronautas, 1.758, São José dos Campos 12227-010, SP, Brazil

4. Department of Geography and Geospatial Sciences, Kansas State University, 1001 Seaton Hall, Manhattan, KS 66506-1111, USA

Abstract

Brazil, as a global player in soybean production, contributes about 35% to the world’s supply and over half of its agricultural exports. Therefore, reliable information about its development becomes imperative to those who follow the market. Thus, this study estimates three phenological stages of soybean crops (sowing, beginning seed, and harvesting dates), identifying spatial–temporal patterns of soybean phenology using phenological metric extraction techniques from Normalized Difference Vegetation Index (NDVI) time-series data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Focused on the state of Paraná, this study validates the methodology using reference data from the Department of Rural Economics (DERAL). Subsequently, the model was applied to the major Brazilian soybean area cultivation. The results demonstrate strong agreement between the phenological estimates and reference data, showcasing the reliability of phenological metrics in capturing the stages of the soybean cycle. This study represents the first attempt, to the best of our knowledge, to correlate the vegetative peak of soybeans with the beginning seed stage at a large scale within Brazilian territory. Amidst the urgent need for the accurate estimation of agricultural crop phenological stages, particularly considering extreme weather events threatening global food security, this research emphasizes the continual importance of advancing techniques for soybean monitoring.

Funder

Coordenação de Aperfeicoamento de Pessoal de Nível Superior

Publisher

MDPI AG

Reference87 articles.

1. FAO—Food and Agriculture Organization of the United Nations (2023, October 26). Faostat. Available online: http://www.fao.org/faostat/en/#data.

2. (2023, October 26). CEPEA—Centro de Estudos Avançados em Economia Aplicada—CEPEA-Esalq/USP. Available online: https://www.cepea.esalq.usp.br/br/mercado-de-trabalho-do-agronegocio.aspx.

3. Patterns of land use, extensification, and intensification of Brazilian agriculture;Dias;Glob. Chang. Biol.,2016

4. CONAB—Companhia Nacional de Abastecimento (2023, October 26). Calendário de Plantio e Colheita de Grãos no Brasil, Available online: https://www.conab.gov.br/institucional/publicacoes/outras-publicacoes.

5. Paschal, H., Berger, G., and Nari, C. (2000, January 7–10). Soybean breeding in South America. Proceedings of the American Seed Trade Association Conference, 30th ASTA, Chicago, IL, USA.

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