Fire Perimeter Research Articles

A power series formulation for two-dimensional wildfire shapes

Computational simulations of wildfires require a model for the two-dimensional expansion of a fire perimeter. Although many expressions exist for the one-dimensional rate of spread of a fire front, there are currently no agreed mathematical expressions for the two-dimensional outward speed of a fire perimeter. Multiple two-dimensional shapes such as elliptical and oval-shaped perimeters have been observed and reported in the literature, and several studies have attempted to classify these shapes using geometric approximations. Here we show that a two-dimensional outward speed based on a power series results in a perimeter that can match many of these observed shapes. The power series is based on the dot product between the vector normal to the perimeter and a fixed wind vector. The formulation allows the evolution and shape of a fire perimeter to be expressed using a small set of scalar coefficients. The formulation is implemented using the level set method, and computed perimeters are shown to provide a good match to perimeters of small-scale experimental fires. The method could provide a framework for statistical matching of wildfire shapes or be used to improve current wildfire prediction systems.

Curvature effects in the dynamic propagation of wildfires

The behaviour and spread of a wildfire are driven by a range of processes including convection, radiation and the transport of burning material. The combination of these processes and their interactions with environmental conditions govern the evolution of a fire’s perimeter, which can include dynamic variation in the shape and the rate of spread of the fire. It is difficult to fully parametrise the complex interactions between these processes in order to predict a fire’s behaviour. We investigate whether the local curvature of a fire perimeter, defined as the interface between burnt and unburnt regions, can be used to model the dynamic evolution of a wildfire’s progression. We find that incorporation of curvature dependence in an empirical fire propagation model provides closer agreement with the observed evolution of field-based experimental fires than without curvature dependence. The local curvature parameter may represent compounded radiation and convective effects near the flame zone of a fire. Our findings provide a means to incorporate these effects in a computationally efficient way and may lead to improved prediction capability for empirical models of rate of spread and other fire behaviour characteristics.

Historical reconstructions of California wildfires vary by data source

Historical data are essential for understanding how fire activity responds to different drivers. It is important that the source of data is commensurate with the spatial and temporal scale of the question addressed, but fire history databases are derived from different sources with different restrictions. In California, a frequently used fire history dataset is the State of California Fire and Resource Assessment Program (FRAP) fire history database, which circumscribes fire perimeters at a relatively fine scale. It includes large fires on both state and federal lands but only covers fires that were mapped or had other spatially explicit data. A different database is the state and federal governments’ annual reports of all fires. They are more complete than the FRAP database but are only spatially explicit to the level of county (California Department of Forestry and Fire Protection – Cal Fire) or forest (United States Forest Service – USFS). We found substantial differences between the FRAP database and the annual summaries, with the largest and most consistent discrepancy being in fire frequency. The FRAP database missed the majority of fires and is thus a poor indicator of fire frequency or indicators of ignition sources. The FRAP database is also deficient in area burned, especially before 1950. Even in contemporary records, the huge number of smaller fires not included in the FRAP database account for substantial cumulative differences in area burned. Wildfires in California account for nearly half of the western United States fire suppression budget. Therefore, the conclusions about data discrepancies and the implications for fire research are of broad importance.

A growing importance of large fires in conterminous United States during 1984–2012

AbstractFire frequency, extent, and size exhibit a strong linkage with climate conditions and play a vital role in the climate system. Previous studies have shown that the frequency of large fires in the western United States increased significantly since the mid‐1980s due to climate warming and frequent droughts. However, less work has been conducted to examine burned area and fire emissions of large fires at a national scale, and the underlying mechanisms accounting for the increases in the frequency of large fires are far from clear. In this study, we integrated remote‐sensed fire perimeter and burn severity data sets into the Dynamic Land Ecosystem Model to estimate carbon emissions from large fires (i.e., fires with size larger than 1000 acres or 4.05 km2) in conterminous United States from 1984 to 2012. The results show that average area burned by large fires was 1.44 × 104 km2 yr−1 and carbon emissions from large fires were 17.65 Tg C yr−1 during the study period. According to the Mann‐Kendall trend test, annual burned area and pyrogenic carbon emissions presented significant upward trends at the rates of 810 km2 yr−1 and 0.87 Tg C yr−1, respectively. Characteristic fire size (fire size with the largest contribution to the total burned area) in the period of 2004–2012 increased by 176.1% compared to the period of 1984–1993. We further found that the larger fires were associated with higher burn severity and occurred more frequently in the warmer and drier conditions. This finding implies that the continued warming and drying trends in the 21st century would enhance the total burned area and fire emissions due to the contributions of larger and more severe wildfires.

Identification of two distinct fire regimes in Southern California: implications for economic impact and future change

The area burned by Southern California wildfires has increased in recent decades, with implications for human health, infrastructure, and ecosystem management. Meteorology and fuel structure are universally recognized controllers of wildfire, but their relative importance, and hence the efficacy of abatement and suppression efforts, remains controversial. Southern California’s wildfires can be partitioned by meteorology: fires typically occur either during Santa Ana winds (SA fires) in October through April, or warm and dry periods in June through September (non-SA fires). Previous work has not quantitatively distinguished between these fire regimes when assessing economic impacts or climate change influence. Here we separate five decades of fire perimeters into those coinciding with and without SA winds. The two fire types contributed almost equally to burned area, yet SA fires were responsible for 80% of cumulative 1990–2009 economic losses ($3.1 Billion). The damage disparity was driven by fire characteristics: SA fires spread three times faster, occurred closer to urban areas, and burned into areas with greater housing values. Non-SA fires were comparatively more sensitive to age-dependent fuels, often occurred in higher elevation forests, lasted for extended periods, and accounted for 70% of total suppression costs. An improved distinction of fire type has implications for future projections and management. The area burned in non-SA fires is projected to increase 77% (±43%) by the mid-21st century with warmer and drier summers, and the SA area burned is projected to increase 64% (±76%), underscoring the need to evaluate the allocation and effectiveness of suppression investments.

The relative impacts of vegetation, topography and spatial arrangement on building loss to wildfires in case studies of California and Colorado

Wildfires destroy thousands of buildings every year in the wildland urban interface. However, fire typically only destroys a fraction of the buildings within a given fire perimeter, suggesting more could be done to mitigate risk if we understood how to configure residential landscapes so that both people and buildings could survive fire. Our goal was to understand the relative importance of vegetation, topography and spatial arrangement of buildings on building loss, within the fire’s landscape context. We analyzed two fires: one in San Diego, CA and another in Boulder, CO. We analyzed Google Earth historical imagery to digitize buildings exposed to the fires, a geographic information system to measure some of the explanatory variables, and FRAGSTATS to quantify landscape metrics. Using logistic regression we conducted an exhaustive model search to select the best models. The type of variables that were important varied across communities. We found complex spatial effects and no single model explained building loss everywhere, but topography and the spatial arrangement of buildings explained most of the variability in building losses. Vegetation connectivity was more important than vegetation type. Location and spatial arrangement of buildings affect which buildings burn in a wildfire, which is important for urban planning, building siting, landscape design of future development, and to target fire prevention, fuel reduction, and homeowner education efforts in existing communities. Landscape context of buildings and communities is an important aspect of building loss, and if taken into consideration, could help communities adapt to fire.

Integrating Pixel- and Polygon-Based Approaches to Wildfire Risk Assessment: Application to a High-Value Watershed on the Pike and San Isabel National Forests, Colorado, USA

We develop a novel risk assessment approach that integrates complementary, yet distinct, spatial modeling approaches currently used in wildfire risk assessment. Motivation for this work stems largely from limitations of existing stochastic wildfire simulation systems, which can generate pixel-based outputs of fire behavior as well as polygon-based outputs of simulated final fire perimeters, but due to storage and processing limitations do not retain spatially resolved information on intensity within a given fire perimeter. Our approach surmounts this limitation by merging pixel- and polygon-based modeling results to portray a fuller picture of potential wildfire impacts to highly valued resources and assets (HVRAs). The approach is premised on using fire perimeters to calculate fire-level impacts while explicitly capturing spatial variation of wildfire intensity and HVRA susceptibility within the perimeter. Relative to earlier work that generated statistical expectations of risk, this new approach can better account for the range of possible fire-level or season-level outcomes, providing far more comprehensive information on wildfire risk. To illustrate the utility of this new approach, we focus on a municipal watershed on the Pike and San Isabel National Forests in Colorado, USA. We demonstrate a variety of useful modeling outputs, including exceedance probability charts, conditional distributions of watershed area burned and watershed impacts, and transmission of risk to the watershed based on ignition location. These types of results can provide more information than is otherwise available using existing assessment frameworks, with significant implications for decision support in pre-fire planning, fuel treatment design, and wildfire incident response.

A new model of landscape-scale fire connectivity applied to resource and fire management in the Sonoran Desert, USA.

Understanding where and when on the landscape fire is likely to burn (fire likelihood) and the predicted responses of valued resources (fire effects) will lead to more effective management of wildfire risk in multiple ecosystem types. Fire is a contagious and highly unpredictable process, and an analysis of fire connectivity that incorporates stochasticity may help predict fire likelihood across large extents. We developed a model of fire connectivity based on electrical circuit theory, which is a probabilistic approach to modeling ecological flows. We first parameterized our model to reflect the synergistic influences of fuels, landscape properties, and winds on fire spread in the lower Sonoran Desert of southwestern Arizona, and then defined this landscape as an interconnected network through which to model flow (i.e., fire spread). We interpreted the mapped outputs as fire likelihood and used historical burned area data to evaluate our results. Expected fire effects were characterized based on the degree to which future fire exposure might negatively impact native plant community recovery, taking into account the impact of repeated fire and major vegetation associations. We explored fire effects within habitat for the endangered Sonoran pronghorn antelope and designated wilderness. Model results indicated that fire likelihood was higher in lower elevations, and in areas with lower slopes and topographic roughness. Fire likelihood and effects were predicted to be high in 21% of the currently occupied range of the Sonoran pronghorn and 15% of the additional habitat considered suitable. Across 16 designated wilderness areas, highest predicted fire likelihood and effects fell within low elevation wilderness areas that overlapped large fire perimeters that occurred in 2005. As ongoing changes in climate and land cover are poised to alter the fire regime across extensive and ecologically important areas in the lower Sonoran Desert, an analysis of fire likelihood and effects can contribute new and important information to fire and fuels management. Our novel approach to modeling fire connectivity addresses challenges in quantifying and communicating wildfire risk and is applicable to other ecosystems and management issues globally.

Sequential Disturbance Effects of Hailstorm and Fire on Vegetation in a Mediterranean-Type Ecosystem

Frequency and intensity of disturbance is projected to increase for many ecosystems globally, with uncertain consequences, particularly when disturbances occur in rapid succession. We quantified community response (52 shrub species and the tree Eucalyptus todtiana) to a severe hailstorm followed 2 months later by prescribed fire for a Mediterranean-type shrubland in southwestern Australia. Partial overlap of hailstorm path and fire perimeter provided a unique opportunity to compare storm and fire effects along a storm severity gradient (high–moderate–none) with and without fire. We quantified disturbance severity (bark and canopy removal, scorch height) and subsequent response (resprouting type, quantity and quality, and seedling regeneration) to evaluate evidence for disturbance interactions and implications for ecosystem recovery. Canopy loss, litter deposition, and tree bark removal increased significantly with hailstorm severity. Scorch heights in hailstorm + burn were significantly higher than fire alone, suggesting one disturbance conditioned the effect of the next. Hailstorm severity interacted with fire such that severely storm-affected shrubs and trees displayed reduced resprouting quantity and quality (length) after fire, implying resource depletion. Seedling regeneration was highest in fire-only plots for soil-stored seed species, while for serotinous species it was significantly reduced by the combination of storm and fire. Overall, our results show strong resilience of this Mediterranean-type ecosystem to storm or fire alone, whereas successive storm and fire reduced resprouting quantity and quality and selectively filtered recruitment of serotinous species, potentially altering species composition and structure. These results underscore the complex effects of linked and compound disturbances and reveal an important knowledge gap requiring future research.

Seasonal reversal of the influence of El Niño–Southern Oscillation on very large wildfire occurrence in the interior northwestern United States

AbstractSatellite‐mapped fire perimeters and the multivariate El Niño–Southern Oscillation index were used to examine the impact of concurrent El Niño–Southern Oscillation (ENSO) phase on very large fire (VLF) occurrences over the intermountain northwestern United States (U.S.) from 1984 to 2012. While the warm phase of ENSO promotes drier and warmer than normal conditions across the region during winter and spring that favor widespread fire activity the following summer, a reduction in VLFs was found during the warm phase of ENSO during summer concurrent with the fire season. This paradox is primarily tied to an anomalous upper level trough over the western U.S. and positive anomalies in integrated water vapor that extend over the northwestern U.S. during summers when the warm phase of ENSO is present. Collectively, these features result in widespread increases in precipitation amount during the summer and a curtailment of periods of critically low‐fuel moistures that can carry wildfire.

Toward an integrated system for fire, smoke and air quality simulations

In this study, WRF-Sfire is coupled with WRF-Chem to construct WRFSC, an integrated forecast system for wildfire behaviour and smoke prediction. WRF-Sfire directly predicts wildfire spread, plume and plume-top heights, providing comprehensive meteorology and fire emissions to chemical transport model WRF-Chem, eliminating the need for an external plume-rise model. Evaluation of WRFSC was based on comparisons between available observations of fire perimeter and fire intensity, smoke spread, PM2.5 (particulate matter less than 2.5 μm in diameter), NO and ozone concentrations, and plume-top heights with the results of two WRFSC simulations, a 48-h simulation of the 2007 Witch–Guejito Santa Ana fires and a 96-h WRF-Sfire simulation with passive tracers of the 2012 Barker Canyon fire. The study found overall good agreement between forecast and observed local- and long-range fire spread and smoke transport for the Witch–Guejito fire. However, ozone, PM2.5 and NO concentrations were generally underestimated and peaks mistimed in the simulations. This study found overall good agreement between simulated and observed plume-top heights, with slight underestimation by the simulations. Two promising results were the agreement between plume-top heights for the Barker Canyon fire and faster than real-time execution, making WRFSC a possible operational tool.

Global burned area mapping from ENVISAT-MERIS and MODIS active fire data

We present the development of a global burned area (BA) algorithm based on MERIS imagery along with the assessment of the global BA results for three years (2006–2008). This work was developed within the Fire Disturbance project under the European Space Agency Climate Change Initiative programme, which aimed to generate long-term BA information for climate models. Our algorithm combined temporal series of MERIS reflectances with thermal information from MODIS HS (hotspot) product. The algorithm included two-steps. Firstly, cumulative distribution functions were computed to discriminate the most clearly burned pixels using regionally-oriented near infrared reflectance thresholds. Secondly, a contextual criterion improved the spatial detection of the burned patches from the seed pixels. BA estimates for the three target years range from 3.6 to 3.8million km2. Results were validated from a statistically designed sample of fire perimeters generated from Landsat multi-temporal imagery. Intercomparison with existing BA products was also carried out. Results from global validation datasets provided an average overall accuracy higher than 0.95. The accuracy of the BA category was lower than the accuracy of the unburned one. Within the former, average omission and commission errors were lower for areas where the proportion of burned area was higher (for pixel-based error matrices, commission error (CE) was 0.52 and omission error (OE) was 0.51), than for those areas with very low BA proportion (CE=0.60 and OE=0.74). In terms of total BA estimation, errors were generally well balanced, with a tendency towards underestimation (34%). Relevant impact of temporal reporting accuracy was found for these validation datasets. Intercomparison with other existing BA datasets pointed out similar spatial and temporal trends, with high correlation with GFED v4 BA estimations for the three years (r2>0.974).

A Chance-Constrained Programming Model to Allocate Wildfire Initial Attack Resources for a Fire Season

This research developed a chance-constrained two-stage stochastic programming model to support wildfire initial attack resource acquisition and location on a planning unit for a fire season. Fire growth constraints account for the interaction between fire perimeter growth and construction to prevent overestimation of resource requirements. We used this model to examine daily resource stationing budget requirements and suppression resource types and deployments within a fire planning unit. A chance constraint ensures the conditional probability of one or more fire escapes on days with ignitions below a predefined threshold. This chance-constrained approach recognizes that funding for local resources is unlikely to be sufficient for containing all fires in initial attack. For test cases, we used 1,655 fires occurring over 935 historical fire days from the Black Hills Fire Planning Unit in South Dakota. We tested our model under a variety of fire suppression assumptions to estimate appropriate daily stationing budget levels and resource allocations.

Disturbance response across a productivity gradient: postfire vegetation in serpentine and nonserpentine forests

Disturbances such as wildfire play a major role in the diversity, structure and composition of plant communities, however, little is known about the differential impacts of fire across landscapes that vary in characteristics such as soil nutrients and site productivity. Theory predicts that productivity can mediate the impacts of fire for reasons related to broad ecological processes and differential selective forces. For instance, ecosystems with lower site productivity are less limited by space and light and consequently experience less pronounced changes in these resources following a disturbance. Moreover, resource availability related to disturbance and productivity can affect the proportion of plants with competitive versus stress‐tolerant life history strategies. In this study, we utilized a model system for testing predictions about productivity and disturbance that included a mixed conifer forest across a gradient of edaphically harsh, ultramafic “serpentine” soils and “nonserpentine” soils in the northern Sierra Nevada (California, USA). We predicted that the magnitude of fire effects on plant diversity from a 2008 wildfire would be positively related to productivity (higher on nonserpentine soils) and that these factors would interact as environmental filters driving post‐fire species assemblage. In summer 2013 we established 90 vegetation plots in burned areas and 40 plots outside the fire perimeter as a proxy for pre‐fire conditions. We found a unimodal relationship between species diversity and fire severity (peaking at low/moderate severity), and mild evidence post‐fire changes were more pronounced on nonserpentine soils. In contrast, we found strong evidence that productivity and fire severity interact as drivers of species composition and functional traits with a higher proportion of resprouting shrubs on nonserpentine soils and, contrary to our prediction, more invaders on serpentine soils. We hypothesize that differences in biomass between serpentine and nonserpentine forests were not substantial enough to elicit a differential diversity response, possibly deriving from a weaker serpentine syndrome in this region that has been previously noted. Our study reveals that differences in productivity can mediate the outcome of disturbances in ways that cannot be detected through standard community diversity metrics, and that consideration of life history trait variation is necessary.

Calibration of FARSITE simulator in northern Iranian forests

Abstract. Wildfire simulators based on empirical or physical models need to be locally calibrated and validated when used under conditions that differ from those where the simulators were originally developed. This study aims to calibrate the FARSITE fire spread model considering a set of recent wildfires that occurred in northern Iranian forests. Site-specific fuel models in the study areas were selected by sampling the main natural vegetation type complexes and assigning standard fuel models. Overall, simulated fires presented reliable outputs that accurately replicated the observed fire perimeters and behavior. Standard fuel models of Scott and Burgan (2005) afforded better accuracy in the simulated fire perimeters than the standard fuel models of Anderson (1982). The best match between observed and modeled burned areas was observed on herbaceous fuel models. Fire modeling showed a high potential for estimating spatial variability in fire spread and behavior in the study areas. This work represents a first step in the application of fire spread modeling in northern Iran for wildfire risk monitoring and management.

Detection of burned areas from mega-fires using daily and historical MODIS surface reflectance

The detection and mapping of burned areas from wildland fires is one of the most important approaches for evaluating the impacts of fire events. In this study, a novel burned area detection algorithm for rapid response applications using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m surface reflectance data was developed. Spectra from bands 5 and 6, the composite indices of the Normalized Burn Ratio, and the Normalized Difference Vegetation Index were employed as indicators to discover burned pixels. Historical statistical data were used to provide pre-fire baseline information. Differences in the current (post-fire) and historical (pre-fire) data were input into a support vector machine classifier, and the fire-affected pixels were detected and mapped by the support vector machine classification process. Compared with the existing MODIS level 3 monthly burned area product MCD45, the new algorithm is able to generate burned area maps on a daily basis when new data become available, which is more applicable to rapid response scenarios when major fire incidents occur. The algorithm was tested in three mega-fire cases that occurred in the continental USA. The experimental results were validated against the fire perimeter database generated by the Geospatial Multi-Agency Coordination Group and were compared with the MCD45 product. The validation results indicated that the algorithm was effective in detecting burned areas caused by mega-fires.

Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread

Environmental conditions, such as fuel load and moisture levels, can influence the behaviour of wildfires. These factors are subject to natural small-scale variation which is usually spatially or temporally averaged for modelling fire propagation. The effect of including this variation in propagation models has not previously been fully examined or quantified. We investigate the effects of incorporating three types of variation on the shape and rate of propagation of a fire perimeter: variation in combustion conditions, wind direction and wind speed. We find that increasing the variation of combustion condition decreases the overall rate of propagation. An analytical model, based on the harmonic mean, is presented to explain this behaviour. Variation in wind direction is found to cause the development of rounded flanks due to cumulative chance of outward fluctuations at the sides of the perimeter. Our findings may be used to develop improved models for fire spread prediction.

Impacts of Forest Fires and Climate Variability on the Hydrology of an Alpine Medium Sized Catchment in the Canadian Rocky Mountains

This study investigates the hydrology of Castle River in the southern Canadian Rocky Mountains. Temperature and precipitation data are analyzed regarding a climate trend between 1960 and 2010 and a general warming is identified. Observed streamflow has been declining in reaction to a decreasing snow cover and increasing evapotranspiration. To simulate the hydrological processes in the watershed, the physically based hydrological model WaSiM (Water Balance Simulation Model) is applied. Calibration and validation provide very accurate results and also the observed declining runoff trend can be reproduced with a slightly differing inclination. Besides climate change induced runoff variations, the impact of a vast wildfire in 2003 is analyzed. To determine burned areas a remote sensing method of differenced burn ratios is applied using Landsat data. The results show good agreement compared to observed fire perimeter areas. The impacts of the wildfires are evident in observed runoff data. They also result in a distinct decrease in model efficiency if not considered via an adapted model parameterization, taking into account the modified land cover characteristics for the burned area. Results in this study reveal (i) the necessity to establish specific land cover classes for burned areas; (ii) the relevance of climate and land cover change on the hydrological response of the Castle River watershed; and (iii) the sensitivity of the hydrological model to accurately simulate the hydrological behavior under varying boundary conditions. By these means, the presented methodological approach is considered robust to implement a scenario simulations framework for projecting the impacts of future climate and land cover change in the vulnerable region of Alberta’s Rocky Mountains.

Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation

The accuracies of six global burned area (BA) products for year 2008 were compared using the same validation methods and reference data to quantify accuracy of each product. The selected products include MCD64, MCD45 and Geoland2, and three products developed within the Fire Disturbance project (fire_cci), which is part of the European Space Agency's (ESA) Climate Change Initiative (CCI) program. The latter three products were derived from MERIS and VEGETATION sensors (one product from each sensor separately, and a third one from the merging of MERIS and VGT products). The reference fire perimeters were mapped from two multi-temporal Landsat TM/ETM+ images at 103 non-overlapping Thiessen scene areas (TSA) selected with a stratified random sampling design. The validation results were based on cross tabulated error matrices from which six accuracy measures were computed following the requirements of end-users of burned area products. While overall accuracy (OA) exceeded 99% for all products, overall accuracy was lower for the burned class. Burned area commission error ratio was above 40% for all products and omission error ratio was above 65% for all products. The statistical significance of differences in accuracy between pairs of products was evaluated based on theory of the stratified combined ratio estimator. Statistical tests identified the MCD64 as the most accurate product, followed by MCD45 and the MERIS product.

Integration of Optical and SAR Data for Burned Area Mapping in Mediterranean Regions

The aim of this paper is to investigate how optical and Synthetic Aperture Radar (SAR) data can be combined in an integrated multi-source framework to identify burned areas at the regional scale. The proposed approach is based on the use of fuzzy sets theory and a region-growing algorithm. Landsat TM and (C-band) ENVISAT Advanced Synthetic Aperture Radar (ASAR) images acquired for the year 2003 have been processed to extract burned area maps over Portugal. Pre-post fire SAR backscatter temporal difference has been integrated with optical spectral indices to the aim of reducing confusion between burned areas and low-albedo surfaces. The output fuzzy score maps have been compared with reference fire perimeters provided by the Fire Atlas of Portugal. Results show that commission and omission errors in the output burned area maps are a function of the threshold applied to the fuzzy score maps; between the two extremes of the greatest producer’s accuracy (omission error < 10%) and user’s accuracy (commission error < 5%), an intermediate threshold value provides errors of about 20% over the study area. The integration of SAR backscatter allowed reducing local commission errors from 65.4% (using optical data, only) to 11.4%, showing to significantly mitigate local errors due to the presence of cloud shadows and wetland areas. Overall, the proposed method is flexible and open to further developments; also in the perspective of the European Space Agency (ESA) Sentinel missions operationally providing SAR and optical datasets.