Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil

Willyan Ronaldo Becker, Jonathan Richetti, Erivelto Mercante, Júlio César Dalla Mora Esquerdo, Carlos Antonio da Silva Junior, Alex Paludo, Jerry Adriani Johann

Abstract


Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the SD, the difference in the maturation cycles of the cultivars, and regional climatic variation, the HD of soybean varied greatly during the studied crop years, ranging from mid-February to late March. The SD of corn is before that of soybean, and mainly occurs in late September to mid-October. The DMVD mainly occurs during December, and the HD is distributed throughout January to March in Paraná. When comparing the estimated dates with observed dates the mean error (ME) varied from 0.2 days earlier to 3.3 days after the observed date for soybean with root mean square error (RMSE) from 1.93 to 14.73 days. For corn, the ME varied from 10.3 days to 18.5 days after the observed date with RMSE from 18.02 to 27.82 days.

Keywords


Enhanced Vegetation Index; Timesat; Sowing Date; Harvest Date.

Full Text:

PDF

References


Aparecido, L. E. de O., Rolim, G. de S., Richetti, J., Souza, P. S. de, & Johann, J. A. (2016). Köppen, Thornthwaite and Camargo climate classifications for climatic zoning in the State of Paraná, Brazil. Ciência e Agrotecnologia, 40(4), 405-417. doi: 10.1590/1413-70542016404003916

Becker, W. R., Johann, J. A., Richetti, J., & Silva, L. C. de A. (2017). Data mining techniques for separation of summer crop based on satellite images. Engenharia Agrícola, 37(4), 750-759. doi: 10.1590/1809-4430-eng.agric.v37n4p750-759/2017

Cima, E. G., Uribe-Opazo, M. A., Johann, J. A., Rocha, W. F. da, Jr., & Dalposso, G. H. (2018). Analysis of spatial autocorrelation of grain production and agricultural storage in Paraná. Engenharia Agrícola, 38(3), 395-402. doi: 10.1590/1809-4430-eng.agric.v38n3p395-402/2018

Companhia Nacional de Abastecimento (2019). Acompanhamento da Safra Brasileira de Grãos - Safra 2019/20 - Terceiro Levantamento. Brasília. Recuperado de http//www.conab.gov.br/info-agro/safras/ grãos/boletim-da-safra-de-graos/item/download/29866_571b1bb20d986efd905ef7f 689141329

Eklundh, L., & Jönsson, P. (2015). TIMESAT: a software package for time-series processing and assessment of vegetation dynamics. In C. Kuenzer, S. Dech, & W. Wagner (Eds.), Remote sensing time series - revealing land surface dynamics (pp. 141-158). Lund: Springer International Publishing.

Grzegozewski, D. M., Johann, J. A., Uribe-Opazo, M. A., Mercante, E., & Coutinho, A. C. (2016). Mapping soya bean and corn crops in the State of Paraná, Brazil, using EVI images from the MODIS sensor. International Journal of Remote Sensing, 37(6), 1257-1275. doi: 10.1080/01431161.2016.1148285

Instituto Brasileiro de Geografia e Estatística. (2002). Pesquisa Agropecuária. (Vol. 6). Recuperado de ftp://ftp.ibge.gov.br/Producao_Agricola/Producao_da_Extracao_Vegetal_e_da_Silvicultura_[anual]/ Metodologia_da_Pesquisa/PesquisasAgropecuarias. pdf

Johann, J. A., Becker, W. R., Uribe-Opazo, M. A., & Mercante, E. (2016). Estimating soybean development stages in Paraná State - Brazil through orbital modis images. Engenharia Agrícola, 36(1), 126-142. doi: 10.1590/1809-4430-Eng.Agric.v36n1p126-142/2016

Johann, J. A., Rocha, J. V., Duft, D. G., & Lamparelli, R. A. C. (2012). Estimation of Summer Crop Areas in the State of Paraná, Brazil, Using Multitemporal EVI/Modis Images. Pesquisa Agropecuária Brasileira, 47(9), 1295–1306. doi: 10.1590/S0100-204X2012000900015

Mathison, C., Deva, C., Falloon, P., & Challinor, A. J. (2018). Estimating sowing and harvest dates based on the Asian summer monsoon. Earth System Dynamics, 9(2), 563-592. doi: 10.5194/esd-9-563-2018

Ren, J., Campbell, J., & Shao, Y. (2017). Estimation of SOS and EOS for Midwestern US corn and soybean crops. Remote Sensing, 9(7), 722. doi: 10.3390/rs9070722

Richetti, J., Judge, J., Boote, K. J., Johann, J. A., Uribe-Opazo, M. A., Becker, W. R.,… Silva, L. C. de A. (2018). Using phenology-based enhanced vegetation index and machine learning for soybean yield estimation in Paraná State, Brazil. Journal of Applied Remote Sensing, 12(02), 1. doi: 10.1117/1. JRS.12.026029

Secretaria da Agricultura e do Abastecimento/Departamento de Economia Rural (2019). Divisão de Estatísticas Básicas - DEB. Recuperado de http://www.agricultura.pr.gov.br/deral/safras

Souza, C. H. W. de, Mercante, E., Johann, J. A., Lamparelli, R. A. C., & Uribe-Opazo, M. A. (2015). Mapping and discrimination of soya bean and corn crops using spectro-temporal profiles of vegetation indices. International Journal of Remote Sensing, 36(7), 1809-1824. doi: 10.1080/01431161.2015. 1026956

Terler, G., Gruber, L., & Knaus, W. F. (2017). Effect of variety and harvest date on nutritive value and ruminal degradability of ensiled maize ears. Archives of Animal Nutrition, 71(5), 333-346. doi: 10.1080/ 1745039X.2017.1358537

United States Departament of Agriculture. (2019). World Agricultural Production. 19(12). Retrieved from https://apps.fas.usda.gov/psdonline/circulars/production.pdf.

Wardlow, B. D., Kastens, J. H., & Egbert, S. L. (2006). Using USDA crop progress data for the evaluation of greenup onset date calculated from MODIS 250-Meter Data. Photogrammetric Engineering & Remote Sensing, 72(11), 1225-1234. doi: 10.14358/PERS.72.11.1225




DOI: http://dx.doi.org/10.5433/1679-0359.2020v41n5supl1p2419

Semina: Ciênc. Agrár.
Londrina - PR
E-ISSN 1679-0359
DOI: 10.5433 / 1679-0359
E-mail:  semina.agrarias@uel.br
Este obra está licenciado com uma Licença  Creative Commons Atribuição-NãoComercial 4.0 Internacional .