WILDFIRE DAMAGE ASSESSMENT USING MULTI-TEMPORAL SENTINEL-2 DATA

8 citations as recorded by crossref.

1. Initial post-fire vegetation recovery in temperate coastal dunes: evidence from remote sensing and field surveys T. Hosokawa et al. https://doi.org/10.1016/j.pyro.2026.100024
2. Yanmış Alanların Sentinel-2 MSI ve Landsat-8 OLI ile Tespiti ve Analizi: Çanakkale/Gelibolu Orman Yangını B. YILMAZ et al. https://doi.org/10.21324/dacd.941456
3. Analysis of the forest fire in the ‘Bohemian Switzerland’ National Park using Landsat-8 and Sentinel-5P in Google Earth Engine F. Yilgan et al. https://doi.org/10.1007/s11069-024-07052-8
4. Machine Learning in Water Resources Management: Paddy Rice Irrigation Case Study Ü. KIZIL & H. ALTINBİLEK https://doi.org/10.33202/comuagri.1245421
5. Assessment of environmental and atmospheric impacts of stubble burning in Mardin-Diyarbakır (Southeastern of Türkiye): a remote sensing approach T. Çınar et al. https://doi.org/10.1007/s11069-025-07496-6
6. Geospatial technologies for estimating post-wildfire severity through satellite imagery and vegetation types: a case study of the Gangneung Wildfire, South Korea L. Widya & C. Lee https://doi.org/10.1007/s12303-023-0045-2
7. Satellite-Based Analysis of Forest Fires in the Bolivian Chiquitania and Amazon Region: Case 2019 N. Vargas-Cuentas & A. Roman-Gonzalez https://doi.org/10.1109/MAES.2020.3033392
8. SENTINEL-2 MSI VE LANDSAT-9 OLI UYDU GÖRÜNTÜLERİYLE YANMIŞ ALANLARIN TESPİTİ: 2022 MUĞLA/MARMARİS ORMAN YANGINI E. YÜCER https://doi.org/10.17780/ksujes.1303299