Justine Sarrau

GISFire is a free map, accessible without registration, that displays active wildfires around the world in real time. It relies on NASA satellite detections and geostationary satellites, and tracks firefighting aircraft live (call sign, aircraft type, speed, altitude), with automatic detection of water drops, scooping, takeoffs, and landings. The map also overlays wind, smoke plumes, and a news feed whose AI-assisted analysis helps confirm fires' existence and location. A replay of up to seven days back, with daily satellite imagery, makes it easier to follow how an incident unfolds. It also covers industrial fires and lightning strikes, and the interface is available in French, English, Spanish and German. Born from a volunteer, public-service approach, SARO runs the project in association with Gistin and consistently reminds users it does not replace official guidance. During the summer 2026 fires, it reached over 450,000 website views and 2.6 million views on Instagram, and was cited in the press as one of the best platforms for tracking aerial resources in real time. A professional offering, GISFire Pro, complements it with area monitoring and alerts on fire detections, lightning, smoke, and press reports.

Fire list and historic burned fires extents: https://firemap.saro.app/

Presented in 2025 at the ISPRS Geospatial Week in Dubai by Justine Sarrau and M.M. Yagoub, this article documents for the first time the history of major forest fires in Gironde and Les Landes, in southwest France. The authors identified fires of more than 100 hectares that occurred between 1989 and 2022 using press coverage and official reports, then verified their outlines on free satellite images (Landsat and Sentinel-2). From this, they built a map of the most exposed areas, combining vegetation moisture, tree type, and terrain, along with roads and waterways, which slow the spread of fire. The results show that the vast majority of fires start in spring (March to April) and summer (July to August), that Gironde is the most affected in number of fires, and that nearly the whole of both departments is vulnerable because of the extent of pine forests and dryness. Supervised classification of Sentinel-2 images proved to be the most reliable method for measuring burned areas, with nearly 97% overall accuracy. For a decision-maker, a planner, or a local stakeholder, the value is concrete: a database that did not exist before, a risk map available online for free, and a method that can be replicated elsewhere using public data.

Sarrau, J., & Yagoub, M. M. (2025). Documentation of Historical Forest Fires and Hazard: Case of Gironde and Les Landes, France. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 771-778.

Published in 2025 in Transportation Research Interdisciplinary Perspectives by Khaula Alkaabi and Justine Sarrau, this article asks what would happen to an autonomous taxi service if sea levels rise. The study focuses on TXAI, the first service of its kind in the UAE, which connects Yas Island and Saadiyat Island in Abu Dhabi. By simulating rises of 1 to 4 meters, it shows that the road network would remain largely functional in the first three scenarios, and that the bridge linking the two islands would never be affected. Only the extreme 4-meter scenario would hit key areas, including about half of the drop-off stations. The takeaway for decision-makers is twofold. Data quality completely changes the diagnosis: with less precise elevation data (30 m), the bridge appears almost entirely submerged, whereas it is not with finer data (11 m). Such analyses make it possible to act early, by relocating stations or adapting routes, before investing in costly protections.

Alkaabi, K., & Sarrau, J. (2025). Modeling sea level rise scenarios and their effects on smart mobility infrastructure using GIS. Transportation Research Interdisciplinary Perspectives, 34, 101667.

Published in 2025 in Frontiers in Remote Sensing by Justine Sarrau, Khameis Al Abdouli and Abdelgadir Abuelgasim, this article shows how the coastline of the United Arab Emirates changed over thirty years, from 1991 to 2021. The team designed an algorithm that automatically detects the shoreline on Landsat satellite images, with no manual tracing, and applied it to the country's roughly 770 km of coast. The finding is clear: most changes come from human activity, notably ports, artificial islands, and urban expansion into the sea in Abu Dhabi and Dubai. Most of these transformations took place before 2013, and the coastline has largely stabilized since. Outside developed areas, the coast has remained relatively stable, with slight erosion in the west of the country and sandbanks that have grown around cities. For a decision-maker or an investor, the value is twofold: the method is fast, replicable in other regions, and relies on public satellite archives, and it provides a quantified baseline for planning coastal development and measuring the environmental effect of large projects.

Sarrau, J., Al Abdouli, K., & Abuelgasim, A. (2025). Spatiotemporal variations of the United Arab Emirates coastline each decade from 1991 to 2021. Frontiers in Remote Sensing, 6, 1468918.

Published in 2024 in Sustainability by Justine Sarrau, Khaula Alkaabi, and Saif Obaid Bin Hdhaiba, this article reviews 200 studies since 1992 on sea level rise and how geographic information systems (GIS) are used to analyze it. It shows that highly precise elevation data from LiDAR gives the most reliable results, while many studies still rely on data that is too coarse. It also highlights major gaps: real-time data is rarely used, connecting GIS with 3D engines such as Unity is complex, and exposed regions like the Gulf are under-studied. The message for decision-makers is clear: local scenarios and precise data are essential, and 3D simulation is a promising but still underused avenue.

Sarrau, J., Alkaabi, K., & Bin Hdhaiba, S. O. (2024). Exploring GIS techniques in sea level change studies: a comprehensive review. Sustainability, 16(7), 2861.

Published in 2025 in the Journal of Geographical Sciences by Justine Sarrau and Ferréol Salomon, this study shows that the ground in the Tiber Delta, near Rome, is sinking mainly in its central part, including beneath the international airport. By combining LiDAR data, old maps and geological data, the authors identify the areas with the highest risk of flooding and coastal submersion, especially as rising sea levels add to the sinking. For a decision-maker, the message is concrete: understanding a coastline's history makes it possible to spot fragile areas before investing or building there, particularly when they are heavily urbanized.

Sarrau, J., & Salomon, F. (2025). Morphometric analyses of a deltaic strandplain inferred from LiDAR data and old maps: A contribution to the coastal risk mapping of the Tiber Delta (Italy). Journal of Geographical Sciences, 35(10), 2229-2247.