AEGIS App: Wildfire Information Management for Windows Phone Devices

AbstractNovel technological advances in mobile devices and applications can be exploited in wildfire confrontation, enabling end-users to easily conduct several everyday tasks, such as access to data and information, sharing of intelligence and coordination of personnel and vehicles. This work describes an innovative mobile application for wildfire information management that operates on Windows Phone devices and acts as a complementary tool to the web-based version of the AEGIS platform for wildfire prevention and management. Several tasks can be accomplished from the AEGIS App, such as routing, spatial search for closest facilities and firefighting support infrastructures, access to weather data and visualization of fire management data (water sources, gas refill stations, evacuation sites etc.). An innovative feature of AEGIS App is the support of these tasks by a digital assistant for artificial intelligence named Cortana (developed by Microsoft for Windows Phone devices), that allows information utilization through voice commands. The application is to be used by firefighting personnel in Greece and is potentially expected to contribute towards a more sophisticated transferring of information and knowledge between wildfire confrontation operation centers and firefighting units in the field

Archetypes of Community Wildfire Exposure from National Forests of the Western US

Risk management typologies and their resulting archetypes can structure the many social and biophysical drivers of community wildfire risk into a set number of strategies to build community resilience. Existing typologies omit key factors that determine the scale and mechanism by which exposure from large wildfires occur. These factors are particularly important for land managing agencies like the US Forest Service, which must weigh community wildfire exposure against other management priorities. We analyze community wildfire exposure from national forests by associating conditions that affect exposure in the areas where wildfires ignite to conditions where exposure likely occurs. Linking source and exposure areas defines the scale at which crossboundary exposure from large wildfires occurs and the scale at which mitigation actions need to be planned. We find that the vast majority of wildfire exposure from national forests is concentrated among a fraction of communities that are geographically clustered in discrete pockets. Among these communities, exposure varies primarily based on development patterns and vegetation gradients and secondarily based on social and ecological management constraints. We describe five community exposure archetypes along with their associated risk mitigation strategies. Only some archetypes have conditions that support hazardous fuels programs. Others have conditions where managing community exposure through vegetation management is unlikely to suffice. These archetypes reflect the diversity of development patterns, vegetation types, associated fuels, and management constraints that exist in the western US and provide a framework to guide public investments that improve management of wildfire risk within threatened communities and on the public lands that transmit fires to them

Social Vulnerability to Large Wildfires in the Western USA

Federal land managers in the US can be informed with quantitative assessments of the social conditions of the populations affected by wildfires originating on their administered lands in order to incorporate and adapt their management strategy to achieve a more targeted prioritization of community wildfire protection investments. In addition, these assessments are valuable to socially vulnerable communities for quantifying their exposure to wildfires originating on adjacent land tenures. We assessed fire transmission patterns using fire behavior simulations to understand spatial variations across three diverse study areas (North-central Washington; Central California; and Northern New Mexico) to understand how different land tenures affect highly socially vulnerable populated places. Transboundary wildfire structure exposure was related to populations with limited adaptive capacity to absorb, recover and modify exposure to wildfires, estimated with the Social Vulnerability Index using US Census unit data (block groups). We found geographic heterogeneity in terms of land tenure composition and estimated fire exposure. Although high social vulnerability block groups covered small areas, they had high population and structure density and were disproportionately exposed per area burned by fire. Structure exposure originated primarily from three key land tenures (wildland-urban interface, private lands and national forests). Federal lands proportionately exposed, on an area basis, populated places with high social vulnerability, with fires ignited on Forest Service administered lands mostly affecting north-central Washington and northern New Mexico communities

Application of simulation modeling for wildfire exposure and transmission assessment in Sardinia, Italy

Abstract The development of comprehensive fire management and risk assessment strategies is of prominent concern in Southern Europe, due to the expanding scale of wildfire risk. In this work, we applied simulation modeling to analyze fine-scale (100-m resolution) wildfire exposure and risk transmission in the 24,000 km2 island of Sardinia (Italy). Sardinia contains a variety of ecological, cultural, anthropic and touristic resources that each summer are threatened by wildfires, and represents well the Mediterranean Basin environments and conditions. Wildfire simulations based on the minimum travel time algorithm were used to characterize wildfire exposure and risk transmission in terms of annual burn probability, flame length, structures exposed and type and amount of transmission. We focused on the historical conditions associated with large (>50 ha) and very large (>200 ha) wildfires that occurred in Sardinia in the period 1998–2016, and combined outputs from wildfire simulation modeling with land uses, building footprint locations, weather, and historical ignition data. The outputs were summarized for weather zones, main wind scenarios and land uses. Our study characterized spatial variations in wildfire spread, exposure and risk transmission among and within weather zones and the main winds associated with large events. This work provides a novel quantitative approach to inform wildfire risk management and planning in Mediterranean areas. The proposed methodology can serve as reference for wildfire risk assessment and can be replicated elsewhere. Findings can be used to better understand the spatial dynamics and patterns of wildfire risk and evaluate expected wildfire behavior or transmission potential in Sardinia and neighboring regions

Spatial wildland fire analysis scheme and evaluation of wildfire effects for Greece with geoinformatics

The primary research goal was the design and application of a methodology that will enable the conduction of fire behavior simulations and estimation of forest fire effects by using tools and methods of geoinformatics in Greece. For the first time, geoinformatics tools were combined for two case study areas (Lesvos Island and Evros) in order to conduct an overall assessment of the wildfire aftermath. Results will aid on gaining knowledge on which are the best practices for the implementation of similar analysis for other wildfire events of Greece. In particular, we quantified and mapped fire-related characteristics of forest structure through field inventories, statistics, remote sensing, and geographical information systems. Then, fire behavior modeling was applied on Lesvos Island by simulating wildfires with state-of-the art software (FARSITE, FlamMap and Minimum Travel Time). Finally, the research was focused on analyzing the effects and impacts of the large 2011 Lefkimi Evrou wildfire, by using geoinformatics, aided by field measurements conducted immediately after the fire.A secondary goal aimed at creating a context for the evaluation of each wildfire of Greece, based on the effects it has caused on society, economy and the environment. A scientific approach is missing based on wildfire classification and overall assessment of wildfire effects. This prompted our research thoughts about the need for introducing a new ranking method that will be based on expert judgment, with scientific evaluation of what has happened and what it is expected to occur based on several fire related aspects and parameters. Towards this goal, this research is to contribute with a methodology that it is relatively easy to use; based on thorough study and knowledge of local conditions; with small variations, if it is applied by different users; and using widely implemented tools and processes. The backbone of the proposed Fire Ranking and Effects Index (FIRE Index) is the Analytical Hierarchical Process that is used to combine the scores of 7 categories and 56 wildfire effects criteria that comprise them. These categories form two groups of wildfire effects: Environmental Fire Effects with three categories and Socioeconomic Fire Effects with four categories. End-users are able to estimate the FIRE Index in a user-friendly, web-based platform that runs all the necessary calculations in the background.Το θέμα της διδακτορικής διατριβής είναι ο σχεδιασμός πρόβλεψης συμπεριφοράς και η αξιολόγηση των επιπτώσεων δασικών πυρκαγιών με χρήση της γεωπληροφορικής. Για το πρώτο τμήμα της έρευνας έγιναν εκτεταμένες δειγματοληψίες στα δάση της Λέσβου ώστε να καταγραφούν δασικοί–οικολογικοί παράγοντες που σχετίζονται με το φαινόμενο των δασικών πυρκαγιών. Ακολούθησε στατιστική ανάλυση και χαρτογράφηση βασικών παραμέτρων που μετρήθηκαν στο πεδίο και αφορούν την κόμη των δασικών συστάδων, κυρίως για τα δάση κωνοφόρων, ώστε να επιτευχθεί η χαρτογράφηση τους με απώτερο σκοπό την χρήση τους σε λογισμικά προσομοίωσης συμπεριφοράς πυρκαγιών. Στη συνέχεια, διεξήχθησαν αναλύσεις γνωστών ιστορικών περιστατικών πυρκαγιάς που εκδηλώθηκαν στη νήσο Λέσβο για την εκτίμηση της ακρίβειας προσομοίωσης. Έπειτα, διεξήχθη ενδελεχής εκτίμηση των επιπτώσεων πυρκαγιών πρώτης τάξης καθώς και της συμπεριφοράς της πυρκαγιάς που εκδηλώθηκε στην Λευκίμμη Έβρου το 2011. Διενεργήθηκαν δειγματοληψίες εντός της καμένης περιοχής για τη μέτρηση και εκτίμηση των αμέσων συνεπειών που προέκυψαν από την δράση της πυρκαγιάς. Οι μετρήσεις διεξήχθησαν με εφαρμογή των πρωτοκόλλων δειγματοληψιών του FIREMON. Οι μετρήσεις συσχετίστηκαν με αποτελέσματα που προέκυψαν από την ανάλυση δορυφορικών εικόνων Landsat, με κύριο αποτέλεσμα την εκτίμηση και χαρτογράφηση της σφοδρότητας καύσης και της περιμέτρου της πυρκαγιάς. Ακολούθησε η χαρτογράφηση της μεταπυρικής κατάστασης της βλάστησης με δορυφορικές εικόνες υψηλής χωρικής διακριτικής ικανότητας. Έπειτα, διενεργήθηκαν χωρικές προσομοιώσεις της συμπεριφοράς της πυρκαγιάς με τα λογισμικά FARSITE και FlamMap και διενεργήθηκε χωρική εκτίμηση των επιπτώσεων πρώτης τάξης της πυρκαγιάς. Τέλος, διεξήχθη έρευνα για τον σχεδιασμό ενός δείκτη εκτίμησης επιπτώσεων δασικών πυρκαγιών. Συγκεκριμένα, καθορίστηκαν κατηγορίες επιπτώσεων, κάθε μια με τα δικά της κριτήρια, ενώ το κάθε κριτήριο είχε τις δικές του προκαθορισμένες επιλογές σε μια κλίμακα από 0 (καμία επίπτωση) έως και 100 (υψηλή επίπτωση). Οι βαθμολογίες των κριτηρίων σταθμίζονται με συντελεστές βαρύτητας που προέκυψαν από την εφαρμογή της μεθόδου Analytic Hierarchy Process, ενώ στη συνέχεια συνδυάζονται για να αποδοθεί η συνολική βαθμολογία της κατηγορίας. Οι επιμέρους βαθμολογίες των κατηγοριών συνδυάζονται για να προκύψει η τελική βαθμολογία του δείκτη. Η προτεινόμενη μέθοδος δοκιμάστηκε για την πυρκαγιά της Λευκίμμης, ενώ σχεδιάστηκε και διαδικτυακό λογισμικό που επιτρέπει την αυτοματοποίηση της όλης διαδικασίας

Forest mapping by geoinformatics for landscape fire behaviour modelling in coastal forests, Greece

This study aims at quantifying and mapping fire-related characteristics of forest structure through field inventories, statistics, remote sensing, and geographical information systems in the island of Lesvos, northeast Aegean Sea, Greece. Simulation of fire behaviour requires forest biomass inputs that describe surface fuel types/models along with canopy fuel properties, such as canopy cover, stand height, crown base height, and crown bulk density, to accurately predict surface and crown fire spread and spotting potential. Forest canopy characteristics and other vegetation attributes were sampled and derived in over 100 field plots, the majority of which were located in coastal pine forest stands. Regression models involving four dependent forest stand variables (stand height, canopy cover, crown base height, and crown bulk density) were developed using generalized additive models. The values of adjusted R2 were 0.72 for stand height, 0.68 for canopy cover, 0.51 for crown base height, and 0.33 for crown bulk density. These regression models were used to create forest fuel characteristics layers, which can be used as inputs to fire management applications and state-of-the-art landscape-scale fire behaviour mode

Using Transboundary Wildfire Exposure Assessments to Improve Fire Management Programs: a Case Study in Greece

Numerous catastrophic wildfires in Greece have demonstrated that relying on fire suppression as the primary risk-management strategy is inadequate and that existing wildfire-risk governance needs to be re-examined. In this research, we used simulation modelling to assess the spatial scale of wildfire exposure to communities and cultural monuments in Chalkidiki, Greece. The study area typifies many areas in Greece in terms of fire regimes, ownership patterns and fire-risk mitigation. Fire-transmission networks were built to quantify connectivity among land tenures and populated places. We found that agricultural and unmanaged wildlands are key land categories that transmit fire exposure to other land tenures. In addition, fires ignited within protected lands and community boundaries are major sources of structure exposure. Important cultural monuments in the study area had fairly low exposure but higher potential for fires with moderate to high intensity. The results show how the spatial diversity of vegetation and fuels, in combination with vegetation management practices on private and public tracts of land, contribute to transboundary risk. We use the results to motivate a discussion of integrating transboundary risk assessments to improve the current wildfire-risk rating system and begin the process of reforming risk governance in Greece

Optimizing Fuel Treatments Allocation to Protect the Wildland–Urban Interface from Large-Scale Wildfires in Greece

A crucial risk governance priority of the Greek forest managers is to reduce damages in the wildland–urban interface (WUI) by controlling wildfire behavior through fuel management practices. To support decisions for where management should be applied and how, this study experimented with new methods for fuel treatments allocation over a typical Mediterranean fire-prone landscape in the peninsula of Kassandra (an area of 350 km2), northern Greece. The Minimum Travel Time (MTT) fire simulation algorithm and the Treatment Optimization Model were used to produce eight spatial exclusionary and non-exclusionary datasets that were used as criteria for the spatial optimization of fuel management interventions. We used the Multicriteria Decisions Analysis method with Geographical Information Systems to cartographically intersect the criteria to produce two priority maps for two forest management scenarios (i.e., a control and a realistic one). The results revealed that 48 km2 of the study area was characterized as high-priority locations in the control scenario (i.e., with equally weighted management priorities), while 60 km2 was assigned to the high-priority class in the realistic scenario (i.e., with different weighted management priorities). Further analysis showed a substantial variation in treatment priority among the four major forest land cover types (broadleaves, sparse Mediterranean shrublands, conifers, and dense Mediterranean shrublands), revealing that the latter two had the highest selection values. Our methodological framework has already been operationally used by the Greek Forest Service branch of Kassandra to decide the most effective landscape fuel treatment allocation

Mapping burn severity and uncovering spread patterns of the 2021 Varibopi wildfire

This work unveils how the wildfire of August 3rd, 2021 that initiated at the northeastern part of Attica (Varibopi), spread and burned during the four days of its active propagation. This fire is a characteristic large-scale event that affected the wildland-urban interface of Athens, revealing weaknesses of both pillars of fire management: prevention and suppression. Initially, we provide a short description of how and under which conditions (vegetation and weather) the fire initiated and propagated after debriefing reports, news articles and satellite data. Then, we applied the difference Normalized Burn Ratio on a pair of Sentinel 2A satellite images (one right before and another taken one year later) to map the extended burn severity and delineate the fire perimeter. Finally, using the Minimum Travel Time Algorithm, we simulated major spread vectors and rate of spread to answer how the fire would have been evolved in the absence of active fire suppression. We found that from the 8,445-ha included in the final delineated perimeter, 1,000 ha were unburned, 4,715 ha experienced low or moderate-low burn severity, and 2,730 moderate-high or high burn severity. Without suppression, the fire could have escaped from three directions to the west with high spread rate, potentially affecting the Parnitha National Park. The most imminent post-fire issue is not whether the conifer vegetation will recover, but if during the next decade vegetation management measures are not applied in selected locations, then a new ignition can spread faster and burn a more extended area compared to the 2021 fire

Neural-Network Time-Series Analysis of MODIS EVI for Post-Fire Vegetation Regrowth

The time-series analysis of multi-temporal satellite data is widely used for vegetation regrowth after a wildfire event. Comparisons between pre- and post-fire conditions are the main method used to monitor ecosystem recovery. In the present study, we estimated wildfire disturbance by comparing actual post-fire time series of Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and simulated MODIS EVI based on an artificial neural network assuming no wildfire occurrence. Then, we calculated the similarity of these responses for all sampling sites by applying a dynamic time warping technique. Finally, we applied multidimensional scaling to the warping distances and an optimal fuzzy clustering to identify unique patterns in vegetation recovery. According to the results, artificial neural networks performed adequately, while dynamic time warping and the proposed multidimensional scaling along with the optimal fuzzy clustering provided consistent results regarding vegetation response. For the first two years after the wildfire, medium-high- to high-severity burnt sites were dominated by oaks at elevations greater than 200 m, and presented a clustered (predominant) response of revegetation compared to other sites