ASSESSMENTS OF SENTINEL-2 VEGETATION RED-EDGE SPECTRAL BANDS FOR IMPROVING LAND COVER CLASSIFICATION

10 citations as recorded by crossref.

1. Winter remote sensing images are more suitable for forest mapping in Jiangxi Province R. Wang et al. 10.1080/22797254.2023.2237655
2. Total Stem Biomass Estimation Using Sentinel-1 and -2 Data in a Dense Coniferous Forest of Complex Structure and Terrain N. Georgopoulos et al. 10.3390/f13122157
3. A Multi Sensor Approach to Forest Type Mapping for Advancing Monitoring of Sustainable Development Goals (SDG) in Myanmar S. Biswas et al. 10.3390/rs12193220
4. Integrating Sentinel-2 Derivatives to Map Land Use/Land Cover in an Avocado Agro-Ecological System in Kenya E. King’ori et al. 10.1007/s41976-023-00090-z
5. Improved Mapping of Mountain Shrublands Using the Sentinel-2 Red-Edge Band A. Bayle et al. 10.3390/rs11232807
6. Crop Classification Based on Red Edge Features Analysis of GF-6 WFV Data Y. Kang et al. 10.3390/s21134328
7. A Comparison of Multi-Temporal RGB and Multispectral UAS Imagery for Tree Species Classification in Heterogeneous New Hampshire Forests H. Grybas & R. Congalton 10.3390/rs13132631
8. Forest Land Cover Mapping at a Regional Scale Using Multi-Temporal Sentinel-2 Imagery and RF Models L. Alonso et al. 10.3390/rs13122237
9. Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data L. Suarez et al. 10.1007/s11119-020-09722-6
10. Selecting Relevant Biological Variables Derived from Sentinel-2 Data for Mapping Changes from Grassland to Arable Land Using Random Forest Classifier J. Šandera & P. Štych 10.3390/land9110420