RT info:eu-repo/semantics/article
T1 FIREMAP: Cloud-based software to automate the estimation of wildfire-induced ecological impacts and recovery processes using remote sensing techniques
A1 Fernández Guisuraga, José Manuel
A1 Fernández Manso, Alfonso
A1 Quintano Pastor, María del Carmen
A1 Fernández García, Victor
A1 Cerrillo, Alberto
A1 Marqués, Guillermo
A1 Cascallana, Gaspar
A1 Calvo, Leonor
AB The formulation and planning of integrated fire management strategies must be strengthened by decision support systems about fire-induced ecological impacts and ecosystem recovery processes, particularly in the context of extreme wildfire events that challenge land management initiatives. Wildfire data collection and analysis through remote sensing earth observations is of utmost importance for this purpose. However, the needs of land managers are not always met because the exploitation of the full potential of remote sensing techniques requires a high level of technical expertise. In addition, data acquisition and storage, database management, networking, and computing requirements may present technical difficulties. Here, we present FIREMAP software, which leverages the potential of Google Earth Engine (GEE) cloud-based platform, an intuitive graphical user interface (GUI), and the European Forest Fire Information System (EFFIS) wildfire database for wildfire analyses through remote sensing techniques and data collections. FIREMAP software allows automatic computing of (i) machine learning-based burned area (BA) detection algorithms to facilitate the mapping of (historical) fire perimeters, (ii) fire severity spectral indices, and (iii) post-fire recovery trajectories through the inversion of physically-based radiative transfer models. We introduce (i) the FIREMAP platform architecture and the GUI, (ii) the implementation of well-established algorithms for wildfire science and management in GEE, (iii) the validation of the algorithm implementation in fifteen case-study wildfires across the western Mediterranean Basin, and (iv) the near-future and long-term planned expansion of FIREMAP features.
PB Elsevier
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/72439
UL https://uvadoc.uva.es/handle/10324/72439
LA spa
NO Ecological Informatics, 2024, 81, 102591
DS UVaDOC
RD 22-dic-2024