ANALYSIS ON THE EFFECT OF SPATIAL AND SPECTRAL RESOLUTION OF DIFFERENT REMOTE SENSING DATA IN SUGARCANE CROP YIELD STUDY

8 citations as recorded by crossref.

1. Integrating Remote Sensing and Crop Simulation Models for Rice Yield Estimation: A Comprehensive Review C. Lokesh et al. https://doi.org/10.3390/agriengineering8030088
2. Use of Vegetation Activity Index for Evaluation of L-Alpha Amino Acid Treatment in Sugarcane A. Ferraz Dias Neto et al. https://doi.org/10.3390/agriculture14111877
3. Use of Unmanned Aerial Vehicle in Sugarcane Cultivation in Brazil: A Review L. Cardoso et al. https://doi.org/10.1007/s12355-022-01149-9
4. Sugarcane yields prediction at the row level using a novel cross-validation approach to multi-year multispectral images S. Akbarian et al. https://doi.org/10.1016/j.compag.2022.107024
5. Rice yield prediction using UAV-mounted RGB sensors and machine learning algorithms R. Tripathi et al. https://doi.org/10.1007/s43538-025-00479-y
6. Remote Sensing Monitoring of Rice Fields: Towards Assessing Water Saving Irrigation Management Practices I. de Lima et al. https://doi.org/10.3389/frsen.2021.762093
7. Drought-induced damage detection in Iberian Scots pine forests through satellite remote sensing M. Rodes-Blanco et al. https://doi.org/10.1016/j.srs.2026.100398
8. Analysis of NDVI and NDRE Indices Using Satellite Images for Crop Identification at Kelantan N. Naguib & S. Daliman https://doi.org/10.1088/1755-1315/1102/1/012054