PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Integrated Geomatics and Remote Sensing Analysis of Forest Fire Propagation and Land Cover Change in Berkane, Morocco

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
By combining geomatics techniques and remote sensing data, this paper gives a thorough investigation of the forest fires that occurred close to Berkane, Morocco, from July 16 to July 18, 2023. The goals of the study included spatiotemporally tracking the propagation of active forest fires during the fire season, and to accurately map the burned area and detect changes in vegetation cover caused by the fire. A detailed fire severity mapping of the impact of the fire on the forest was made by this integrated approach. We used remote sensing data from various sources, including NASA FIRMS data for the fire period and Sentinel-2 satellite imagery acquired two days before and one day after the fire, to accomplish these goals. In terms of estimating the burned area, our study produced important findings. We were able to estimate 3508.12 hectares, 3517.98 hectares, and 3113.63 hectares using satellite imagery with dNBR, dNDVI, and supervised classification, respectively. These results offer considerable potential for directing post-fire management plans and preserving this critically important forest area. The integration of FIRMS data, Sentinel-2 images, and GIS in our research highlights the need of using this coordinated strategy to conduct an accurate and thorough evaluation of forest fires in the area. In addition to improving our understanding of forest fire dynamics, this study emphasizes the value of using cutting-edge geospatial and remote sensing techniques in attempts to manage wildfires and save the environment. The findings of this study will contribute significantly to guiding post-fire management strategies, thus promoting the conservation of the vital forest area.
Twórcy
  • Geophysics and Natural Hazards Laboratory, GEOPAC Research Center, Scientific Institute, Mohammed V University in Rabat, Rabat, Morocco
  • Majal Berkane., N 2, Siége Social de la SDL Majal Berkane, Route Oujda, Berkane, 63300, Morocco
  • Geophysics and Natural Hazards Laboratory, GEOPAC Research Center, Scientific Institute, Mohammed V University in Rabat, Rabat, Morocco
  • GREPOM/BirdLife Morocco, Salé, 11160, Morocco
Bibliografia
  • 1. Arjasakusuma, S., Kusuma, S.S., Vetrita, Y., Prasasti, I., Arief, R. 2022. Monthly Burned-Area Mapping using Multi-Sensor Integration of Sentinel-1 and Sentinel-2 and machine learning: Case Study of 2019’s fire events in South Sumatra Province, Indonesia. Remote Sensing Applications: Society and Environment, 27, 100790.
  • 2. Brean W. Duncan, Guofan Shao, Frederic W. Adrian. 2009. Delineating a managed fire regime and exploring its relationship to the natural fire regime in East Central Florida, USA: A remote sensing and GIS approach, Forest Ecology and Management, 258(2), 132-145.
  • 3. Collins, L., McCarthy, G., Mellor, A., Newell, G., Smith, L. 2020. Training data requirements for fire severity mapping using Landsat imagery and random forest. Remote Sensing of Environment, 245, 111839.
  • 4. Fisher, R.A. 1922. On the mathematical foundations of theoretical statistics. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 222, 309–368.
  • 5. Ghali R., Akhloufi M.A. Deep Learning Approaches for Wildland Fires Remote Sensing: Classification, Detection, and Segmentation. Remote Sensing. 2023, 15(7), 1821.
  • 6. Kala, C.P. (2023). Environmental and socioeconomic impacts of forest fires: A call for multilateral cooperation and management interventions. Natural Hazards Research.
  • 7. Key, C.H., Benson, N.C. 2005. Landscape assessment (LA): Sampling and analysis methods. In Entwistle, P.G., DeBano, L.F., Neary, D.G. (Tech. Coords.), Proceedings: Restoration of American Southwest Ponderosa Pine Forests, General Technical Report. RMRS-GTR-150, 73–84. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.
  • 8. Maffei, C., Lindenbergh, R., Menenti, M. 2021. Combining multi-spectral and thermal remote sensing to predict forest fire characteristics. ISPRS Journal of Photogrammetry and Remote Sensing, 181, 400–412.
  • 9. Melissa B. Jenkins, Anna W. Schoettle, Jessica W. Wright, Karl A. Anderson, Joseph Fortier, Linh Hoang, Tony Incashola Jr., Robert E. Keane, Jodie Krakowski, Dawn M. LaFleur, Sabine Mellmann-Brown, Elliott D. Meyer, ShiNaasha Pete, Katherine Renwick, Robert A. 2022. Sissons, Restoring a forest keystone species: A plan for the restoration of whitebark pine (Pinus albicaulis Engelm.) in the Crown of the Continent Ecosystem, Forest Ecology and Management, 522, 120282.
  • 10. Nolè, A., Rita, A., Spatola, M.F., Borghetti, M. 2022. Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics. Science of The Total Environment, 823, 153807.
  • 11. Payra, S., Sharma, A., Verma, S. 2023. Application of remote sensing to study forest fires. In Atmospheric Remote Sensing, Elsevier, pp. 239-260.
  • 12. Rouse Jr., J.W., Haas, R.H., Schell, J.A., Deering, D.W. 1973. Monitoring vegetation systems in the Great Plains with ERTS. In Third Earth Resources Technology Satellite-1 Symposium, 10–14 December 1973, Greenbelt, Maryland, NASA, 1, pp. 309-317.
  • 13. Ryan M. Perkl. 2016. Geodesigning landscape linkages: Coupling GIS with wildlife corridor design in conservation planning, Landscape and Urban Planning, 156, 44-58.
  • 14. Viana-Soto A., Aguado I., Salas J., García M. Identifying Post-Fire Recovery Trajectories and Driving Factors Using Landsat Time Series in Fire-Prone Mediterranean Pine Forests. Remote Sensing, 2020, 12(9), 1499.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2a9c53ef-8acb-46f7-8978-e66110fc2ab9
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.