112. Assessing within-field soybean yield variability using texture measures of a Sentinel-2 image
Author:
Affiliation:
1. School of Agricultural Engineering, University of Campinas – UNICAMP, 13083-875, Campinas, São Paulo, Brazil.
Publisher
Wageningen Academic Publishers
Link
https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-947-3_112
Reference22 articles.
1. Baptista, G. M. M. 2015. Aplicação do Índice de Vegetação por Profundidade de Feição Espectral (SFDVI – Spectral Feature Depth Vegetation Index) em dados RapidEye. (Application of Spectral Feature Depth Vegetation Index (SFDVI) to RapidEye data). In: Simpósio Brasileiro de Sensoriamento Remoto, 17. (SBSR), 2015, João Pessoa. Anais. São José dos Campos: INPE, 2015. 2277-2284.
2. Blasch, G., Li, Z. & Taylor, J. A. (2020). Multi-temporal yield pattern analysis method for deriving yield zones in crop production systems. Precision Agriculture, 21(6), 1263-1290. https://doi.org/10.1007/s11119-02009719-1
3. SMOTE: Synthetic Minority Over-sampling Technique
4. Yield Prediction in Soybean Crop Grown under Different Levels of Water Availability Using Reflectance Spectroscopy and Partial Least Squares Regression
5. Efficient k NN classification algorithm for big data
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