Garamszegi B, Jung C, Schindler D (2022).
Multispectral Spaceborne Proxies of Predisposing Forest Structure Attributes to Storm Disturbance A Case Study from Germany
Forests 13 (12): 2114
Dalponte M, Solano-Correa YT, Marinelli D, Gianelle D (2023).
Windthrows Detection With Satellite Remote Sensing Data: A Comparison Among Sentinel-2, Planet, And Cosmo Sky-Med Data
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 6752
Einzmann K, Immitzer M, Böck S, Bauer O, Schmitt A, Atzberger C (2017).
Windthrow Detection in European Forests with Very High-Resolution Optical Data
Forests 8 (1): 21
Bonanomi G, Incerti G, Abd El-Gawad AM, Sarker TC, Stinca A, Motti R, Cesarano G, Teobaldelli M, Saulino L, Cona F, Chirico GB, Mazzoleni S, Saracino A (2018).
Windstorm disturbance triggers multiple species invasion in an urban Mediterranean forest
iForest - Biogeosciences and Forestry 11 (1): 64
Haidu I, Furtuna PR, Lebaut S (2019).
Detection of old scattered windthrow using low cost resources. The case of Storm Xynthia in the Vosges Mountains, 28 February 2010
Open Geosciences 11 (1): 492
Dalponte M, Marzini S, Solano-Correa YT, Tonon G, Vescovo L, Gianelle D (2020).
Mapping forest windthrows using high spatial resolution multispectral satellite images
International Journal of Applied Earth Observation and Geoinformation 93: 102206
Idbella M, Stinca A, Abd El-Gawad AM, Motti R, Mazzoleni S, Bonanomi G (2023).
Windstorm disturbance sets off plant species invasion, microbiota shift, and soilborne pathogens spread in an urban Mediterranean forest
Forest Ecology and Management 540: 121058
Dalponte M, Solano-Correa YT, Marinelli D, Liu S, Yokoya N, Gianelle D (2023).
Detection of forest windthrows with bitemporal COSMO-SkyMed and Sentinel-1 SAR data
Remote Sensing of Environment 297: 113787
Dimou V, Demertzis K, Kantartzis A (2024).
Harvesting wind damaged trees: a study of prediction of windthrow damage in mixed-broadleaf stands via a machine learning model
International Journal of Forest Engineering 35 (1): 43
Vaglio Laurin G, Francini S, Luti T, Chirici G, Pirotti F, Papale D (2021).
Satellite open data to monitor forest damage caused by extreme climate-induced events: a case study of the Vaia storm in Northern Italy
Forestry: An International Journal of Forest Research 94 (3): 407
Renaud J-P, Vega C, Durrieu S, Lisein J, Magnussen S, Lejeune P, Fournier M (2017).
Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models
Annals of Forest Science 74 (4)
Hamdi ZM, Brandmeier M, Straub C (2019).
Forest Damage Assessment Using Deep Learning on High Resolution Remote Sensing Data
Remote Sensing 11 (17): 1976
Zupan M, Oštir K, Potočnik Buhvald A (2025).
Windthrow Mapping with Sentinel-2 and PlanetScope in Triglav National Park: A Regional Case Study
Remote Sensing 17 (21): 3568
Klemmt H-J, Seitz R, Straub C (2020).
Application of Haralick’s Texture Features for Rapid Detection of Windthrow Hotspots in Orthophotos
Forests 11 (7): 763
Ghosh S, Dawn A, Kour S, Mallick A, Chowdhury A, Kundu K, De Sarkar K, Rahman MR, Sharma P, Rajakaruna P, Rahman MM, Nath AJ, Shaw R (2025).
Climate extremes walking together: Evidence from recent compounding climate hazards after Remal
International Journal of Disaster Risk Reduction 118: 104974
Rüetschi M, Small D, Waser LT (2019).
Rapid Detection of Windthrows Using Sentinel-1 C-Band SAR Data
Remote Sensing 11 (2): 115
Chehata N, Orny C, Boukir S, Guyon D, Wigneron JP (2014).
Object-based change detection in wind storm-damaged forest using high-resolution multispectral images
International Journal of Remote Sensing 35 (13): 4758
Ritter T, Gollob C, Kraßnitzer R, Stampfer K, Nothdurft A (2022).
A Robust Method for Detecting Wind-Fallen Stems from Aerial RGB Images Using a Line Segment Detection Algorithm
Forests 13 (1): 90