Regional Model to Predict Sugarcane Yield Using Sentinel-2 Imagery in São Paulo State, Brazil
Author:
Funder
Fundação de Amparo à Pesquisa do Estado de São Paulo
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12355-024-01468-z.pdf
Reference57 articles.
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2. Arnt, W.R. 2016. Desempenho de variedades de cana-de-açúcar no pontal do paranapanema. Universidade Federal da Grande Dourados.
3. Atzberger, C. 2013. Advances in remote sensing of agriculture: Context description, existing operational monitoring systems and major information needs. Remote Sensing 5: 949–981.
4. Bégué, A., V. Lebourgeois, E. Bappel, P. Todoroff, A. Pellegrino, F. Baillarin, and B. Siegmund. 2010. Spatio-temporal variability of sugarcane fields and recommendations for yield forecast using NDVI. International Journal of Remote Sensing 31: 5391–5407.
5. Bordonal, R.O., J.L.N. Carvalho, R. Lal, E.B. Figueiredo, B.G. Oliveira, and N.L. Scala Jr. 2018. Sustainability of sugarcane production in Brazil. A Review. Agronomy for Sustainable Development 38: 13.
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