ASSESSMENT OF CLASSIFICATION ACCURACIES OF SENTINEL-2 AND LANDSAT-8 DATA FOR LAND COVER / USE MAPPING

45 citations as recorded by crossref.

1. Evaluation of Accuracy Enhancement in European-Wide Crop Type Mapping by Combining Optical and Microwave Time Series B. Ghassemi et al. https://doi.org/10.3390/land11091397
2. Analysis of Vegetative Cover Vulnerability in Rohingya Refugee Camps of Bangladesh Utilizing Landsat and Per Capita Greening Area (PCGA) Datasets M. Karim & X. Zhang https://doi.org/10.3390/rs13234922
3. Assessing alteration of urban floodplains using remote sensing and GIS: a three decade analysis (1992–2022) Y. Ali et al. https://doi.org/10.1080/24749508.2025.2524209
4. Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery P. Thanh Noi & M. Kappas https://doi.org/10.3390/s18010018
5. Assessing biomass and primary production of microphytobenthos in depositional coastal systems using spectral information P. Jacobs et al. https://doi.org/10.1371/journal.pone.0246012
6. Potential of Landsat-8 and Sentinel-2A composite for land use land cover analysis D. Varade et al. https://doi.org/10.1080/10106049.2018.1497096
7. Evaluating the Influence of Traffic Congestion on Surface Urban Heat Island Intensity J. Lee & M. Berkelhammer https://doi.org/10.1029/2025GL116651
8. Monitoring the operational changes in surface reflectances after logging, based on popular indices over Sentinel-2, Landsat-8, and ASTER imageries Ç. Genç & A. Altunel https://doi.org/10.1007/s10661-024-13526-w
9. Can a Hierarchical Classification of Sentinel-2 Data Improve Land Cover Mapping? A. Waśniewski et al. https://doi.org/10.3390/rs14040989
10. Water Information Extraction Based on Multi-Model RF Algorithm and Sentinel-2 Image Data Z. Jiang et al. https://doi.org/10.3390/su14073797
11. The Monitoring of Macroplastic Waste in Selected Environment with UAV and Multispectral Imaging T. Oberski et al. https://doi.org/10.3390/su17051997
12. Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms M. Aghababaei et al. https://doi.org/10.3390/rs13173433
13. Sentinel-2A MSI Verisinin Makine Öğrenmesi Tabanlı Destek Vektör Makinesi, Rastgele Orman ve En Büyük Olasılık Algoritmalarını Kullanarak Piksel Tabanlı Kontrollü Sınıflandırılmadaki Etkilerinin Araştırılması N. Kaya & O. Dengiz https://doi.org/10.48123/rsgis.1410250
14. Fine-Grained Classification of Urban Functional Zones and Landscape Pattern Analysis Using Hyperspectral Satellite Imagery: A Case Study of Wuhan J. Yuan et al. https://doi.org/10.1109/JSTARS.2022.3174412
15. Surface Soil Moisture Determination of Irrigated and Drained Agricultural Lands with the OPTRAM Method and Sentinel-2 Observations T. Stańczyk et al. https://doi.org/10.3390/rs15235576
16. Machine Learning Approaches for Developing Land Cover Mapping A. Alzahrani et al. https://doi.org/10.1155/2022/5190193
17. Monitoring of phenological stage and yield estimation of sunflower plant using Sentinel-2 satellite images O. Narin & S. Abdikan https://doi.org/10.1080/10106049.2020.1765886
18. Application of Sentinel-2 and EnMAP new satellite data to the mapping of alpine vegetation of the Karkonosze Mountains M. Jędrych et al. https://doi.org/10.1515/pcr-2017-0011
19. Estimation of forest development stage and crown closure using different classification methods and satellite images: A case study from Turkey S. Bulut et al. https://doi.org/10.17221/127/2018-JFS
20. Fire regime attributes shape pre-fire vegetation characteristics controlling extreme fire behavior under different bioregions in Spain D. Beltrán-Marcos et al. https://doi.org/10.1186/s42408-024-00276-w
21. Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data S. Eskandari et al. https://doi.org/10.3390/rs12121912
22. Use of Sentinel-2 and LUCAS Database for the Inventory of Land Use, Land Use Change, and Forestry in Wallonia, Belgium O. Close et al. https://doi.org/10.3390/land7040154
23. Testing the Applicability and Credibility of the High Conservation Value Forest (HCVF) Toolkit: A Systematic Global Review B. Abbasnezhad & J. Abrams https://doi.org/10.1007/s11842-022-09510-2
24. Dynamic Land Degradation Assessment: Integrating Machine Learning with Landsat 8 OLI/TIRS for Enhanced Spectral, Terrain, and Land Cover Indices P. Badapalli et al. https://doi.org/10.1007/s41748-024-00442-9
25. Enhancing Flood Mapping Accuracy in North and West Africa Using Multi-Sensor Satellite Data and Machine Learning in Google Earth Engine Y. Loukili et al. https://doi.org/10.1007/s41748-025-00796-8
26. Land Cover Mapping and Change Analysis Using Optimized Random Forest Classifier Incorporating Fusion of Texture and Gabor Features A. Kumar & R. Garg https://doi.org/10.1007/s42979-023-02111-6
27. Spatio-temporal distribution of Vachellia stuhlmannii (Taub.) in Venetia-Limpopo nature reserve – SPOT-imagery S. Nkosi et al. https://doi.org/10.1080/0035919X.2022.2036263
28. Estimating Reservoir Sedimentation Rates and Storage Capacity Losses Using High‐Resolution Sentinel‐2 Satellite and Water Level Data F. Yao et al. https://doi.org/10.1029/2023GL103524
29. Effect of the Synergetic Use of Sentinel-1, Sentinel-2, LiDAR and Derived Data in Land Cover Classification of a Semiarid Mediterranean Area Using Machine Learning Algorithms C. Valdivieso-Ros et al. https://doi.org/10.3390/rs15020312
30. Landscape Evaluation Based on Gaofen Satellite in the Southern Part of the Nile Delta, Egypt H. El-Hamid et al. https://doi.org/10.4236/gep.2019.77005
31. Effect of Spatial Resolution on Land Cover Mapping in an Agropastoral Area of Niger (Aguié and Mayahi) Using Sentinel-2 and Landsat 8 Imagery Within a Random Forest Regression Framework S. Abdou Amadou et al. https://doi.org/10.3390/rs18050750
32. Land Use/Land Cover Mapping Using Multitemporal Sentinel-2 Imagery and Four Classification Methods—A Case Study from Dak Nong, Vietnam H. Nguyen et al. https://doi.org/10.3390/rs12091367
33. Land cover mapping in mountainous Croatia using Sentinel-2A satellite imagery V. Rossi et al. https://doi.org/10.1007/s12665-025-12510-y
34. Consistent Long-Term Monthly Coastal Wetland Vegetation Monitoring Using a Virtual Satellite Constellation S. Tahsin et al. https://doi.org/10.3390/rs13030438
35. Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset A. Baloloy et al. https://doi.org/10.3389/frsen.2021.730238
36. Development of the spectral forest index in the Khangai region, Mongolia using Sentinel-2 imagery B. Norovsuren et al. https://doi.org/10.1080/21580103.2022.2153928
37. Does building development in Dhaka comply with land use zoning? An analysis using nighttime light and digital building heights M. Rahman et al. https://doi.org/10.1007/s11625-021-00923-0
38. Typological classification of rural-urban continuum regions for an enhanced spatial planning - A case of Kerala, India S. Cyriac & C. Mohammed Firoz https://doi.org/10.1080/23754931.2026.2684313
39. Advancing forest fire prediction: A multi-layer stacking ensemble model approach F. Shahzad et al. https://doi.org/10.1007/s12145-025-01782-4
40. Enhancing GeoAI land cover classification via hyperparameter tuning and cross-validation: A case study in Ravenna, Italy A. Vitale & F. Lamonaca https://doi.org/10.1016/j.measurement.2025.118662
41. Mapping of Sicilian Pocket Beaches Land Use/Land Cover with Sentinel-2 Imagery: A Case Study of Messina Province G. Randazzo et al. https://doi.org/10.3390/land10070678
42. Designing a European-Wide Crop Type Mapping Approach Based on Machine Learning Algorithms Using LUCAS Field Survey and Sentinel-2 Data B. Ghassemi et al. https://doi.org/10.3390/rs14030541
43. Remote Sensing-Enhanced Structural Equation Modeling for Evaluating the Health of Ancient Juglans regia L. in Tibetan Traditional Villages Q. Zhu et al. https://doi.org/10.3390/f17010056
44. Spatiotemporal patterns of water hyacinth dynamics as a response to seasonal climate variability in Lake Tana, Ethiopia T. Abebe et al. https://doi.org/10.1007/s13201-023-01975-6
45. Digitally Mapping the Hydro-Topographical Context for Community Planning: A Case Study for the Upper Choapa River Watershed in Chile G. Moran et al. https://doi.org/10.4236/gep.2017.53019