Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο:
https://hdl.handle.net/20.500.14279/34743| Τίτλος: | Multimodal Dataset for Wildfire Risk Prediction in Cyprus | Συγγραφείς: | Prodromou, Maria Girtsou, Stella Leventis, Georgios Koumoulidis, Dimitrios Tzouvaras, Marios Mettas, Christodoulos Apostolakis, Alexis Kaskara, Mariza Kontoes, Haris Hadjimitsis, Diofantos G. |
Major Field of Science: | Natural Sciences;Engineering and Technology | Field Category: | NATURAL SCIENCES;ENGINEERING AND TECHNOLOGY;Civil Engineering | Λέξεις-κλειδιά: | Data cube;Wildfires;Cyprus;Fire management | Ημερομηνία Έκδοσης: | 5-Σεπ-2024 | Πηγή: | International Geoscience and Remote Sensing Symposium (IGARSS), 2024, vol.1 no.5 | Start page: | 1 | End page: | 5 | Project: | EXCELSIOR: ERATOSTHENES Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment | Περιοδικό: | International Geoscience and Remote Sensing Symposium (IGARSS) | Περίληψη: | Wildfires detection is a major issue for authorities. There are various causes of fire events with the most common being human influence. A fire risk prediction model through the analysis of geo-environmental and climate data is important for early warning and fire management. In this work, a dataset from multiple modalities, including road density, travelers, forest-agriculture interface, burned areas from historical fire events, metrological data, land cover, vegetation indices from data cube, is generated. Artificial intelligence and machine learning models can use this multimodal dataset to improve forest fire management. | URI: | https://hdl.handle.net/20.500.14279/34743 | ISBN: | 979-8-3503-6032-5 | DOI: | 10.1109/IGARSS53475.2024.10642963 | Rights: | Attribution 4.0 International | Type: | Article | Affiliation: | ERATOSTHENES Centre of Excellence Cyprus University of Technology National Observatory of Athens |
Funding: | The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. | Publication Type: | Peer Reviewed |
| Εμφανίζεται στις συλλογές: | EXCELSIOR H2020 Teaming Project Publications |
Αρχεία σε αυτό το τεκμήριο:
| Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
|---|---|---|---|---|
| Multimodal_Dataset_for_Wildfire_Risk_Prediction_in_Cyprus.pdf | 1.14 MB | Adobe PDF | Δείτε/ Ανοίξτε |
CORE Recommender
Page view(s)
170
Last Week
2
2
Last month
11
11
checked on 4 Ιουν 2026
Download(s)
234
checked on 4 Ιουν 2026
Google ScholarTM
Check
Altmetric
Αυτό το τεκμήριο προστατεύεται από άδεια Άδεια Creative Commons
