DISCRIMINATION OF SUGARCANE CROP AND CANE YIELD ESTIMATION USING LANDSAT AND IRS RESOURCESAT SATELLITE DATA

6 citations as recorded by crossref.

1. Mapping of sugarcane crop types from multi-date IRS-Resourcesat satellite data by various classification methods and field-level GPS survey R. Singh et al. 10.1016/j.rsase.2020.100340
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3. Sugarcane Crop Type Discrimination and Area Mapping at Field Scale Using Sentinel Images and Machine Learning Methods A. Nihar et al. 10.1007/s12524-021-01444-0
4. Deriving Phenological Metrics from Landsat-OLI for Sugarcane Crop Type Mapping: A Case Study in North India R. Singh et al. 10.1007/s12524-022-01515-w
5. Satellite-Based Light Use Efficiency Model for Sugarcane Yield Estimation at Field Scale A. Nihar et al. 10.1007/s12524-023-01712-1
6. Integration of RGB-based vegetation index, crop surface model and object-based image analysis approach for sugarcane yield estimation using unmanned aerial vehicle S. K.C. et al. 10.1016/j.compag.2020.105903