Fire severity and soil erosion susceptibility mapping using multi-temporal Earth Observation data: The case of Mati fatal wildfire in Eastern Attica, Greece

The Impacts of Burn Severity and Frequency on Erosion in Western Arnhem Land, Australia

Wildfires are pivotal to the functioning of many ecosystems globally, including the magnitude of surface erosion rates. This study aims to investigate the relationships between surface erosion rates and wildfire intensity in the tropical north savanna of Australia. The occurrence of fires in western Arnhem Land, Northern Territory, Australia was determined with remotely sensed digital datasets as well as analogue erosion measurement methods. Analysis was performed using satellite imagery to quantify burn severity via a monthly delta normalised burn ratio (dNBR). This was compared and correlated against on-ground erosion measurements (erosion pins) for 13 years. The dNBR for each year (up to +0.4) displayed no relationship with subsequent erosion (up to ±4 mm of erosion/deposition per year). Poor correlation was attributed to low fire severity, patchy burning, significant time between fires and erosion-inducing rainfall. Other influences included surface roughness from disturbances from feral pigs and cyclone impacts. The findings here oppose many other studies that have found that fires increase surface erosion. This accentuates the unique ecosystem characteristics and fire regime properties found in the tropical Northern Territory. Scenarios of late dry season fires with high severity were not observed in this study and require more investigations. Ecosystems such as the one examined here require specialised management practices acknowledging the specific ecosystem functions and processes. The methods employed here combine both analogue and digital sensors to improve understandings of a unique environmental system.

Study and evaluation of the effects of vegetation cover destruction on soil degradation in Middle Guinea through the application of remote sensing and and geotechnics

Soil degradation in Middle Guinea is increasing over the years. While it's good to have precautions to deal with it, it's even more important to go back to the source of the scourge in order to lessen its effects over time, or even eradicate it. At the center of the factors that are often mentioned is the destruction of the vegetation cover, and the aim of this study is to clear it (in all its forms: trees, grass, savannah, etc.) by following its variation in time [1982 and 2021] and in space. The present study was conducted by combining the remote sensing and GIS results, developed with data from geotechnical survey data and laboratory tests. On the Mali Labé Linsan axis, between [1982 and 1992], 63 % of the territory explored was occupied by fresh vegetation cover, compared to 13 % of dry vegetation, as well as 12 % of sterile soil and 12 % of sand mineral soil. For the periods [1992-2002] and [2002-2012], these same parameters increased to: 67 %; 11 %; 11 % and 11 %. The period [2012-2021] was marked by changes of 73 %; 10 %; 9 % and 9 %, respectively. The bearing capacity of soils varies from one point to another. In all six boreholes presented, their maximum values are greater than or equal to 400 Kpa (≥400 Kpa). The minimum values calculated for 2.1 ≤ B(m)≤7.3 fluctuate between 291 Kpa and 806 Kpa. The investigations carried out on this subject show that the overall movement of the positive variation of the vegetation cover in time (63 % < 67 % < 73 %) and very contrasted in space, would not be responsible for the degradations (which are local and mainly caused by erosion: wind and water). In addition, they open up to a (geoscientific and geotechnical) approach of a deep analysis, the purpose of which suggests the adoption of slab/concrete/grating foundations (depth of anchorage specific to each soil analyzed).

Seven decades of Atlantic rainforest conversion to slash-and-burn agriculture: Effects on soil's physical properties

Slash-and-burn agriculture is a millennia-old no-till farming technique that is still widely practiced in developing tropical countries. This practice is currently employed in Brazil by subsistence family farms, Indigenous groups, and maroons, in a primitive manner, using only cutting, fire, and fallow as soil preparation techniques for food production. In recent years, this practice has been drastically reduced. However, the fallow periods have become even shorter. Therefore, there is a need to understand how the recurrence of fire with the reduction of fallow time affects the soil. This study aims to evaluate the cumulative effects of fire recurrence in slash-and-burn agriculture for seven decades on the physical properties of the soil and the minimum fallow times for post-burn resilience. Using a chronosequence approach, different fallow periods: a) native forest (control); b) recently burned (30 days after fire); c) 2-year fallow; d) 5-year fallow; e) 7-year fallow; f) 12-year fallow were considered. In each area, six disturbed and six undisturbed samples were randomly collected at 0-5 cm and 5-10 cm depths each to estimate: soil bulk density, soil total porosity, penetration resistance, aggregate stability, mean weight diameter, and soil water retention capacity. The results show that the seven decades of slash-and-burn agriculture affected the topsoil (0-5 cm deep) more prominently. Curiously, soil bulk density and total porosity were not affected at any time between the areas. The fire increased penetration resistance immediately after burning in the 0-5 cm layer by 162.5%, showing resilience after five years of fallow. Soil aggregate stability showed a delayed effect, with a significant increase in two years after the fire by 64.2%, remaining high after 12 years of fallow, indicating the influence of other mechanisms and reactions in the soil after the fire. The mean weight diameter did not change at any time while soil water retention increased immediately after burning by 25.2% with resilience after a two-year fallow. Most physical properties were not directly affected by fire heating but by post-fire environmental conditions and the interaction of various mechanisms during the fallow period. In general, most physical parameters showed good resilience over an average of five years of fallow, with cumulative effects only for aggregate stability.

Can Satellites Predict Yield? Ensemble Machine Learning and Statistical Analysis of Sentinel-2 Imagery for Processing Tomato Yield Prediction

In this paper, we propose an innovative approach for robust prediction of processing tomato yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite imagery was deployed to obtain values of five (5) selected vegetation indices (VIs) during the growing season of 2021 (April to September) at 5-day intervals. Actual recorded yields were collected across 108 fields, corresponding to a total area of 410.10 ha of processing tomato in central Greece, to assess the performance of Vis at different temporal scales. In addition, VIs were connected with the crop phenology to establish the annual dynamics of the crop. The highest Pearson coefficient (r) values occurred during a period of 80 to 90 days, indicating the strong relationship between the VIs and the yield. Specifically, RVI presented the highest correlation values of the growing season at 80 (r = 0.72) and 90 days (r = 0.75), while NDVI performed better at 85 days (r = 0.72). This output was confirmed by the AutoML technique, which also indicated the highest performance of the VIs during the same period, with the values of the adjusted R² ranging from 0.60 to 0.72. The most precise results were obtained with the combination of ARD regression and SVR, which was the most successful combination for building an ensemble (adj. R² = 0.67 ± 0.02).

Rehabilitation of eroded trails and gullies on quartzite rock outcrops with native species in a high-altitude grassland

The quartzite rock outcrops and the native vegetation of grasslands located at the Serra da Calçada Mountain in Minas Gerais State (Brazil) have been severely degraded by extreme sports activities such as motocross and off-road vehicles, greatly damaging the abundant headwaters. The main consequences thereof were hilly and gully erosion processes with soil loss and the deviation of the water from its original paths. However, currently, there is no report of successful restoration efforts in severely eroded outcrops in Brazilian high-altitude grasslands (campo rupestre). Through the Universal Soil Loss Equation (USLE), we found a high general erosion rate in the study site (669.91 t·ha^-1·year^-1), and the specific soil loss provoked by off-road vehicles on trails was significantly greater (49 m³ per 100 m²) than that caused by mountain bikes and trekking (5.8 m³ per 100 m²). We performed the physical reconstruction of eroded outcrops and surface water flow paths by allocating locally available quartzite rocks. These rocks were inoculated with different species of bryophytes and planted with native species under two treatments: un-inoculated and inoculated with arbuscular mycorrhizal fungi (AMF) spores of the Rhizophagus irregularis species. After 2 years, the bryophyte communities showed a similar pattern to the preserved site, and the AMF inoculation favoured plant establishment of most species, especially of the Asteraceae, Cyperaceae, Fabaceae, Malpighiaceae, Orchidaceae and Poaceae families. The AMF also improved the soil fertility, highlighting soil P, SOM, CEC, NH₄⁺-N as well as soil water content and water retention capacity. Poaceae family species showed an outstanding occupation, which was considered a functional indicator of rehabilitation success, functioning as a "hydraulic carpet" for water exportation, conduction and drainage across the outcrops. This study provides an eco-technology to restore severely eroded outcrops over headwaters using native species in the Brazilian high-altitude grasslands.

Mapping burn severity and monitoring CO content in Türkiye's 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform

This study investigated forest fires in the Mediterranean of Türkiye between July 28, 2021, and August 11, 2021. Burn severity maps were produced with the difference normalised burned ratio index (dNBR) and difference normalised difference vegetation index (dNDVI) using Sentinel-2 images on the Google Earth Engine (GEE) cloud platform. The burned areas were estimated based on the determined burning severity degrees. Vegetation density losses in burned areas were analysed using the normalised difference vegetation index (NDVI) time series. At the same time, the post-fire Carbon Monoxide (CO) column number densities were determined using the Sentinel-5P satellite data. According to the burn severity maps obtained with dNBR, the sum of high and moderate severity areas constitutes 34.64%, 20.57%, 46.43%, 51.50% and 18.88% of the entire area in Manavgat, Gündoğmuş, Marmaris, Bodrum and Köyceğiz districts, respectively. Likewise, according to the burn severity maps obtained with dNDVI, the sum of the areas of very high severity and high severity constitutes 41.17%, 30.16%, 30.50%, 42.35%, and 10.40% of the entire region, respectively. In post-fire NDVI time series analyses, sharp decreases were observed in NDVI values from 0.8 to 0.1 in all burned areas. While the Tropospheric CO column number density was 0.03 mol/m² in all regions burned before the fire, it was observed that this value increased to 0.14 mol/m² after the fire. Moreover, when the area was examined more broadly with Sentinel 5P data, it was observed that the amount of CO increased up to a maximum value of 0.333 mol/m². The results of this study present significant information in terms of determining the severity of forest fires in the Mediterranean region in 2021 and the determination of the CO column number density after the fire. In addition, monitoring polluting gases with RS techniques after forest fires is essential in understanding the extent of the damage they can cause to the environment.

Estimation of mercury emissions from the forest floor of a pine plantation during a wildfire in central Portugal

Mercury (Hg) concentrations in soils and Hg releases from soils during wildfires are not well characterised in Portugal, even though wildfire activity continues to increase around the Mediterranean. This study focused on the low to moderate severity wildfire in Pombal (Portugal) in 2019, which consumed 12.5 ha of maritime pine (Pinus pinaster Ait.). We evaluated Hg concentrations in soil profiles and Hg pools in organic horizons to assess the fire-induced Hg emissions. Moreover, impacts of the fire on forest floor properties were estimated. Four soil profiles were sampled, two at the burned area and two at a nearby unburned area. The soil profiles displayed a typical Hg distribution, with higher Hg concentrations (156 µg kg^-1) in the organic horizons with a sharp decrease in the mineral layers. The bond between organic matter and Hg was evident along the profiles, with a strong correlation between TOC and Hg. Ratios of Hg/TOC in the surface layers of the soil were similar in all profiles. The mean organic Hg pool at the studied site was calculated at 10.6 g ha^-1. The fire did not seem to affect the topsoil properties based on visual indicators and the lack of statistical differences (p > 0.05) among measured fire-sensitive chemical soil properties (pH, CEC, TOC, TS) between the topsoils of the burned and unburned areas. If we consider a hypothetical complete combustion of the organic layer (743 Mg) and unaffected topsoil, we estimated a release of 133 g of Hg from the burned area. The study emphasised the importance of the forest floor for Hg retention and its crucial role in Hg emissions during wildfires in a country increasingly affected by climate change.

Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed

A large wildfire occurred due to strong winds and dry climates in the Gangwon province of South Korea. Thereafter, floods and sediment damage were caused by Typhoon Mitag in the burned areas. This study was an attempt to quantitatively evaluate the risk of soil erosion in wildfire areas using the Soil Erosion Model for Mountain Areas (SEMMA) based on GIS, which was developed in South Korea. The model required the integration of maps of the main factors involved, i.e., rainfall erosivity, vegetation index, soil erodibility, and slope length and steepness. According to the model simulation results, high erosion rates of over 100 t/ha were concentrated within the wildfire areas. Sediment yields from the study watershed, including the wildfire areas, were estimated to be 40.33 t/ha for the 30-year frequency of rainfall, which is similar to those of the typhoon. The high risk of erosion was predominantly observed in the upper mountains, which are characterized by steep slopes, silt loam, and shallow soil depths within the wildfire areas. Urgent and excessive logging of burned trees further increased the risk of erosion. However, various treatment strategies were implemented to control soil erosion and sediment transport from the post-fire watershed. This study confirmed that temporal and spatial BMPs should be selected and enforced to reduce sediment disasters in wildfire areas.

Insect Outbreak and Long-Term Post-Fire Effects on Soil Erosion in Mediterranean Suburban Forest

Our study was conducted in the suburban forest of Thessaloniki (Seich Sou), which constitutes one of the most significant suburban forests of Greece and is located northeast of Thessaloniki. In 1997, more than the half of the forest area was destroyed by a wildfire, while recently (May 2019), a significant insect outbreak by the bark beetle Tomicus piniperda was detected. The insect action still goes on, while the infestation has destroyed so far more than 300 ha of forest area. Extensive selective logging and removal of infected trees from the forest were carried out in order to mitigate and restrict the outbreak spread. In the current study, silt-fenced erosion plots were installed on representative locations of disturbed (by fire and insect action) and undisturbed areas, in order to quantify the effect of the above-mentioned forest disturbances on soil erosion and correlate the height and intensity of precipitation with the soil erosion rate. The results show that there was no statistically significant increase in soil erosion in the areas of insect outbreak compared with the control plots. However, there was a statistically significant increase in soil erosion in areas where logging works had been applied as an infestation preventive measure. In addition, the study revealed that 25 years after the forest fire, the erosion rate is still at higher level compared with the undisturbed forest areas. This study could be considered as one of the first attempts to evaluate the impact of an insect outbreak infestation on soil erosion, while there is also a great lack of information concerning the assessment of long-term post-fire effects on the soil erosion of a forest ecosystem.

A wildfire vulnerability index for buildings

Recent wildfire events (e.g. Mediterranean region, USA, and Australia) showed that this hazard poses a serious threat for wildland–urban interface (WUI) areas around the globe. Furthermore, recent events in regions where wildfire does not constitute a frequent hazard (e.g. Siberia, Scandinavia) indicated that the spatial pattern of wildfire risk might have significantly changed. To prepare for upcoming extreme events, it is critical for decision-makers to have a thorough understanding of the vulnerability of the built environment to wildfire. Building quality and design standards are important not only because building loss is costly but also because robust buildings may offer shelter when evacuation is not possible. However, studies aiming at the analysis of wildfire vulnerability for the built environment are limited. This paper presents an innovative solution for the vulnerability assessment to wildfires, making use of an all-relevant feature selection algorithm established on statistical relationships to develop a physical vulnerability index for buildings subject to wildfire. Data from a recent and systematically documented wildfire event in Greece (Mati, 2018) are used to select and weight the relevant indicators using a permutation-based automated feature selection based on random forests. Building characteristics including the structural type, the roof type, material and shape, the inclination of the ground, the surrounding vegetation, the material of the shutters and the ground covering were selected and formed into the index. The index may be used in other places in Europe and beyond, especially where no empirical data are available supporting decision-making and risk reduction of an emerging hazard amplified by climate change.

Comparing Fire Extent and Severity Mapping between Sentinel 2 and Landsat 8 Satellite Sensors

Mapping of fire extent and severity across broad landscapes and timeframes using remote sensing approaches is valuable to inform ecological research, biodiversity conservation and fire management. Compiling imagery from various satellite sensors can assist in long-term fire history mapping; however, inherent sensor differences need to be considered. The New South Wales Fire Extent and Severity Mapping (FESM) program uses imagery from Sentinel and Landsat satellites, along with supervised classification algorithms, to produce state-wide fire maps over recent decades. In this study, we compared FESM outputs from Sentinel 2 and Landsat 8 sensors, which have different spatial and spectral resolutions. We undertook independent accuracy assessments of both Sentinel 2 and Landsat 8 sensor algorithms using high-resolution aerial imagery from eight training fires. We also compared the FESM outputs from both sensors across 27 case study fires. We compared the mapped areas of fire severity classes between outputs and assessed the classification agreement at random sampling points. Our independent accuracy assessment demonstrated very similar levels of accuracy for both sensor algorithms. We also found that there was substantial agreement between the outputs from the two sensors. Agreement on the extent of burnt versus unburnt areas was very high, and the severity classification of burnt areas was typically either in agreement between the sensors or in disagreement by only one severity class (e.g., low and moderate severity or high and extreme severity). Differences between outputs are likely partly due to differences in sensor resolution (10 m and 30 m pixel sizes for Sentinel 2 and Landsat 8, respectively) and may be influenced by landscape complexity, such as terrain roughness and foliage cover. Overall, this study supports the combined use of both sensors in remote sensing applications for fire extent and severity mapping.

Investigation of near-surface chemical explosions effects using seismo-acoustic and synthetic aperture radar analyses

Chemical explosions are ground truth events that provide data, which, in turn, can enhance the understanding of wave propagation, damage assessment, and yield estimation. On 4 August 2020, Beirut, Lebanon was shocked by a catastrophic explosion, which caused devastating damage to the Mediterranean city. A second strong chemical explosion took place at the Xiangshui, China chemical plant on 21 March 2019. Both events generated shock waves that transitioned to infrasound waves, seismic waves, as well as hydroacoustic signals with accompanying T-phases in the case of the Beirut event. In this work, the seismo-acoustic signatures, yields, and associated damage of the two events are investigated. The differentiainterferometry synthetic aperture radar analysis quantified the surface damage and the estimated yield range, equivalent to 2,4,6-trinitrotoluene [C7H5(NO2)3] (TNT), through a "boom" relation of the peak overpressure was evaluated. Infrasound propagation modeling identified a strong duct in the stratosphere with the propagation to the west in the case of the Beirut-Port explosion. In the case of the Xiangshui explosion, the modeling supports the tropospheric propagation toward the Kochi University of Technology (KUT) sensor network in Japan. Although the Beirut yield (202-270 ± 100 tons) was slightly larger than the Xiangshui yield (201 ± 83.5 tons), the near-source damage areas are almost the same based on the distribution of damaged buildings surrounding the explosions.

Assessing the Accuracy of MODIS MCD64A1 C6 and FireCCI51 Burned Area Products in Mediterranean Ecosystems

The catastrophic impact of wildfires on the economy and ecosystems of Mediterranean countries in recent years, along with insufficient policies that favor disproportionally high funding for fire suppression, demand a more comprehensive understanding of fire regimes. Satellite remote sensing products support the generation of relevant burned-area (BA) information, since they provide the means for the systematic monitoring of large areas worldwide at low cost. This research study assesses the accuracy of the two publicly available MODIS BA products, MCD64A1 C6 and FireCCI51, at a national scale in a Mediterranean country. The research period covered four fire seasons, and a comparison was conducted against a higher-resolution Sentinel-2 dataset. The specific objectives were to assess their performance in detecting fire events occurring primarily in forest and semi-natural lands and to investigate their spatial and temporal uncertainties. Monthly fire observations were processed and analyzed to derive a comprehensive set of accuracy metrics. We found that fire size has an impact on their detection accuracy, with higher detection occurring in fires larger than 100 ha. Detection of smaller (<100 ha) fires was favored by the 250 m FireCCI51 product, but not from MCD64A1 C6, which exhibited less than 50% detection probability in the same range. Their spatial estimates of burned area exhibited a fairly satisfactory agreement with the reference data, reaching an average of 78% in detection rate. MCD64A1 C6 exhibited a more consistent spatial performance overall and better temporal accuracy, whereas FireCCI51 did not substantially outperform the former despite its finer resolution. Additional research is required for a more rigorous assessment of the variability of these burned area products, yet this research provides further insight and has implications for their use in fire-related applications at the local to the national scale.

Land Degradation, Overland Flow, Soil Erosion, and Nutrient Loss in the Eastern Himalayas, India

Studies on the assessment of land degradation, overland flow, soil loss, and nutrient loss have emerged as paramount importance for food security and rural livelihood in the mountains. The present study dealt with similar issues in the Eastern Himalayas, for which the primary data were collected from the field during 2017–18. Quantitative and qualitative methods were used to collect data on soil erosion and information on overland flow, soil loss, and nutrient loss was assessed through field experiments in the watershed of Sikkim, Eastern Himalayas. The first section of the methodology deals with the experimental analysis from different land use categories to quantify soil loss. In the second section, detailed qualitative analyses of farmers’ perceptions of soil erosion indicators were recorded through field surveys, i.e., key informant interviews (KEIs) and focus group discussions (FDGs). The results showed that the highest overland flow was in barren land (8.63%) followed by large cardamom-based agroforestry system (7.02%), and mixed cropping (4.84%), and the lowest overland flow was in terrace cultivation (4.69%). Soil loss was estimated to be the highest for barren land (7.73 Mg/ha/year (megagram/hectare/year)) followed by mixed cropping (4.32 Mg/ha/year), and terrace cultivation (3.75 Mg/ha/year), with the least soil loss estimated to be in cardamom-based agroforestry (3.23 Mg/ha/year). Loss of nitrogen (N) (4.49 kg/ha/year) and phosphorous (P) (2.43 kg/ha/year) were highest in barren land, while potassium (K) loss was highest (4.30 kg/ha/year) in mixed farming. The lowest N loss rate (3.34 kg/ha/year) was in terrace cultivation, the lowest P loss rate (8.19 kg/ha/year) was in mixed farming, and the lowest potassium loss rate (3.28 kg/ha/year) was in cardamom-based agroforestry. Approximately 33% of the farmers acknowledged light or no soil losses, while 17% of the farmers accepted moderate soil erosion. The results of field survey indicated that only 15–19% of the farmers reported high or extreme soil loss in the fields. Farmers in the watershed are practicing multiple measures to control land degradation; however, marginal farmers are still vulnerable and need strong support from the government to safeguard their land.

Long and Short-Term Coastal Changes Assessment Using Earth Observation Data and GIS Analysis: The Case of Sperchios River Delta

The present study provides information about the evolution of the Sperchios River deltaic area over the last 6500 years. Coastal changes, due to natural phenomena and anthropogenic activities, were analyzed utilizing a variety of geospatial data such as historic records, topographic maps, aerial photos, and satellite images, covering a period from 4500 BC to 2020. A qualitative approach for the period, from 4500 BC to 1852, and a quantitative analysis, from 1852 to the present day, were employed. Considering their scale and overall quality, the data were processed and georeferenced in detail based on the very high-resolution orthophoto datasets of the area. Then, the multitemporal shorelines were delineated in a geographical information system platform. Two different methods were utilized for the estimation of the shoreline changes and trends, namely the coastal change area method and the cross-section analysis, by implementing the digital shoreline analysis system with two statistical approaches, the end point rate and the linear regression rate. Significant river flow and coastline changes were observed with the overall increase in the delta area throughout the study period reaching 135 km2 (mean annual growth of 0.02 km2/yr) and the higher accretion rates to be detected during the periods 1805–1852, 1908–1945 and 1960–1986, especially at the central and north part of the gulf. During the last three decades, the coastline has remained relatively stable with a decreasing tendency, which, along with the expected sea-level rise due to climate change, can infer significant threats for the coastal zone in the near future.

Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and Advanced Erosion Modeling in Malesina, Central Greece

Earth’s ecosystems are extremely valuable to humanity, playing a key role ecologically, economically, and socially. Wildfires constitute a significant threat to the environment, especially in vulnerable ecosystems, such as those that are commonly found in the Mediterranean. Due to their strong impact on the environment, they provide a crucial factor in managing ecosystems behavior, causing dramatic modifications to land surface processes dynamics leading to land degradation. The soil erosion phenomenon downgrades soil quality in ecosystems and reduces land productivity. Thus, it is imperative to implement advanced erosion prediction models to assess fire effects on soil characteristics. This study focuses on examining the wildfire case that burned 30 km2 in Malesina of Central Greece in 2014. The added value of remote sensing today, such as the high accuracy of satellite data, has contributed to visualizing the burned area concerning the severity of the event. Additional data from local weather stations were used to quantify soil loss on a seasonal basis using RUSLE modeling before and after the wildfire. Results of this study revealed that there is a remarkable variety of high soil loss values, especially in winter periods. More particularly, there was a 30% soil loss rise one year after the wildfire, while five years after the event, an almost double reduction was observed. In specific areas with high soil erosion values, infrastructure works were carried out validating the applied methodology. The approach adopted in this study underlines the significance of using remote sensing and geoinformation techniques to assess the post-fire effects of identifying vulnerable areas based on soil erosion parameters on a local scale.

How far spatial resolution affects the ensemble machine learning based flood susceptibility prediction in data sparse region

Although the effect of digital elevation model (DEM) and its spatial resolution on flood simulation modeling has been well studied, the effect of coarse and finer resolution image and DEM data on machine learning ensemble flood susceptibility prediction has not been investigated, particularly in data sparse conditions. The present work was, therefore, to investigate the performance of the resolution effects, such as coarse (Landsat and SRTM) and high (Sentinel-2 and ALOS PALSAR) resolution data on the flood susceptible models. Another motive of this study was to construct very high precision and robust flood susceptible models using standalone and ensemble machine learning algorithms. In the present study, fifteen flood conditioning parameters were generated from both coarse and high resolution datasets. Then, the ANN-multilayer perceptron (MLP), random forest (RF), bagging (B)-MLP, B-gaussian processes (B-GP) and B-SMOreg algorithms were used to integrate the flood conditioning parameters for generating the flood susceptible models. Furthermore, the influence of flood conditioning parameters on the modelling of flood susceptibility was investigated by proposing an ROC based sensitivity analysis. The validation of flood susceptibility models is also another challenge. In the present study, we proposed an index of flood vulnerability model to validate flood susceptibility models along with conventional statistical techniques, such as the ROC curve. Results showed that the coarse resolution based flood susceptibility MLP model has appeared as the best model (area under curve: 0.94) and it has predicted 11.65 % of the area as very high flood susceptible zones (FSz), followed by RF, B-MLP, B-GP, and B-SMOreg. Similarly, the high resolution based flood susceptibility model using MLP has predicted 19.34 % of areas as very high flood susceptible zones, followed by RF (14.32 %),B-MLP (14.88 %), B-GP, and B-SMOreg. On the other hand, ROC based sensitivity analysis showed that elevation influences flood susceptibility largely for coarse and high resolution based models, followed by drainage densityand flow accumulation. In addition, the accuracy assessment using the IFV model revealed that the MLP model outperformed all other models in the case of a high resolution imageThe coarser resolution image's performance level is acceptable but quite low. So, the study recommended the use of high resolution images for developing a machine learning algorithm based flood susceptibility model. As the study has clearly identified the areas of higher flood susceptibility and the dominant influencing factors for flooding, this could be used as a good database for flood management.

Combining Methods to Estimate Post-Fire Soil Erosion Using Remote Sensing Data

The increasing number of wildfires in southern Europe is making our ecosystem more vulnerable to water erosion; i.e., the loss of vegetation and subsequent runoff increase cause a shift in large quantities of sediment. Fire severity has been recognized as one of the most important parameters controlling the magnitude of post-fire soil erosion. In this paper, we adopted a combination of methods to easily assess post-fire erosion and prevent potential risk in subsequent rain events. The model presented is structured into three modules that were implemented in a GIS environment. The first module estimates fire severity with the Monitoring Trends in Burn Severity (MTBS) method; the second estimates runoff with rainfall depth–duration curves and the Soil Conservation Service Curve Number (SCS-CN) method; and the third estimates pre- and post-fire soil erosion. In addition, two post-fire scenarios were analyzed to assess the influence of fire severity on soil erosion: the former based on the Normalized Difference Vegetation Index (NDVI) and the latter on the Relative differenced Normalized Burn Index (RdNBR). The results obtained in both scenarios are quite similar and demonstrate that transitional areas, such as rangelands and rangelands with bush, are the most vulnerable because they show a significant increase in erosion following a fire event. The study findings are of secondary importance to the combined approach devised because the focal point of the study is to create the basis for a future tool to facilitate decision making in landscape management.

Assessing Soil Loss by Water Erosion in a Typical Mediterranean Ecosystem of Northern Greece under Current and Future Rainfall Erosivity

Soil is a non-renewable resource essential for life existence. During the last decades it has been threatened by accelerating erosion with negative consequences for the environment and the economy. The aim of the current study was to assess soil loss changes in a typical Mediterranean ecosystem of Northern Greece, under climate change. To this end, freely available geospatial data was collected and processed using open-source software package. The widespread RUSLE empirical erosion model was applied to estimate soil loss. Current and future rainfall erosivity were derived from a national scale study considering average weather conditions and RCMs outputs for the medium Representative Concentration Pathway scenario (RCP4.5). Results showed that average rainfall erosivity (R-Factor) was 508.85 MJ mm ha h−1 y−1 while the K-factor ranged from 0.0008 to 0.05 t ha h ha−1 MJ−1 mm−1 and LS-factor reached 60.51. Respectively, C-factor ranged from 0.01 to 0.91 and P-factor ranged from 0.42 to 1. The estimated potential soil loss rates will remain stable for the near future period (2021–2050), while an increase of approximately 9% is expected by the end of the 21th century (2071–2100). The results suggest that appropriate erosion mitigation strategies should be applied to reduce erosion risk. Subsequently, appropriate mitigation measures per Land Use/Land Cover (LULC) categories are proposed. It is worth noting that the proposed methodology has a high degree of transferability as it is based on open-source data.

Observational Evidence of the Need for Gender-Sensitive Approaches to Wildfires Locally and Globally: Case Study of 2018 Wildfire in Mati, Greece

The study takes an equality justice perspective to compare resilience against the controlled management of wildfires, for an effective preparedness, which is a prerequisite for equitable mitigation. The objectives were (a) conceptualizing wildfire mitigation by exploring the ties with gender equality to wildfire hazards, (b) taking the case of wildfire 2018 in Mati, Greece, to contribute reducing the country’s gender inequality, and (c) increasing resilience to climate change hazards by considering lessons learnt. The authors underscore the benefits of a workshop-based and instrumental case study methodology for unravelling evidence on the need for gender-sensitive approaches and tools for future planning at local, regional, and global scales. The case study unravels women’s lack of preparedness to wildfires in Greece, their absence in decision-making for fire management, and the need for capacity building to transform communities’ resilience. The literature research and the specific interviews conducted helped bring awareness to the wildfire’s dynamics, in alignment with the fundamental aspect of gender equality, and to ground recommendations for socio-ecological resilience transition and gender-sensitive approaches in fire management, from reactive fire-fighting to proactive integration. Although in the geographical-context, the study can bring widespread geographical awareness, bringing insights for relevance to similar areas worldwide.

Potential Dam Breach Analysis and Flood Wave Risk Assessment Using HEC-RAS and Remote Sensing Data: A Multicriteria Approach

Dam breach has disastrous consequences for the economy and human lives. Floods are one of the most damaging natural phenomena, and some of the most catastrophic flash floods are related to dam collapses. The goal of the present study is to analyse the impact of a possible failure–collapse on a potentially affected area downstream of the existing Bramianos dam on southern Crete Island. HEC-RAS hydraulic analysis software was used to study the dam breach, the flood wave propagation, and estimate the extent of floods. The analysis was performed using two different relief datasets of the same area: a digital elevation model (DEM) taken from very high-resolution orthophoto images (OPH) of the National Cadastre and Mapping Agency SA and a detailed digital surface model (DSM) extracted from aerial images taken by an unmanned aerial vehicle (UAV). Remote sensing data of the Sentinel-2 satellite and OPH were utilised to create the geographic information system (GIS) layers of a thorough land use/cover classification (LULC) for the potentially flooded area, which was used to assess the impact of the flood wave. Different dam breach and flood scenarios, where the water flows over man-made structures, settlements, and olive tree cultivations, were also examined. The study area is dominated mainly by three geological formations with different hydrogeological characteristics that dictated the positioning and structure of the dam and determine the processes that shape the geomorphology and surface roughness of the floodplain, affecting flow conditions. The results show that the impact of a potential dam break at Bramianos dam is serious, and appropriate management measures should be taken to reduce the risk. The water flow downstream of the collapsed dam depends on the water volume stored in the reservoir. Moreover, the comparison of DSM and DEM cases shows that the detailed DSM may indicate more accurately the surface relief and existing natural obstacles such as vegetation, buildings, and greenhouses, enabling more realistic hydraulic simulation results. Dam breach flood simulations and innovative remote sensing data can provide valuable outcomes for engineers and stakeholders for decision-making and planning in order to confront the consequences of similar incidents worldwide.

Hydrological Response of Natural Mediterranean Watersheds to Forest Fires

Fires are common in forested Mediterranean-climate watersheds. Forest fires cause abrupt land use/cover (LULC) changes affecting soil properties and hydrological processes within and across watersheds. A major forest fire in Attica, Greece, that affected the Lykorrema stream experimental watershed provided the opportunity for an in-depth study of the impact of forest fires on the hydrological balance of natural Mediterranean watersheds. To this end, detailed hydrometeorological data recorded for five years before and for five years after the fire incidence were utilized. SWAT model was also used to consider the potential influence of meteorological conditions temporal variability on the results of the analysis. Specifically, SWAT model was parameterized calibrated and validated for the pre-fire and the post-fire conditions using the corresponding detailed hydrometeorological data for the respective periods. Then the two versions of the model were applied for the entire period providing comprehensive time series for all the flows and storages in the studied watershed. In this way, the post-fire LULC and soil properties changes were the only influencing factors driving the alterations in the hydrological balance allowing an impartial comparison. The obtained results highlighted the considerable impact of forest fires on the watersheds’ hydrological functioning. Specifically, the maximum direct runoff depths and the maximum flow rates were substantially higher in the post-fire conditions. In contrast, actual evapotranspiration was reduced, when the effect of fire was considered. The obtained results indicate that the altered post-fire LULC and soil properties are major drivers of the watershed’s hydrological balance changes. SWAT model performed sufficiently well for both the pre- and post-fire conditions and provided a deeper insight into the impact of forest fires on the hydrological functioning of natural Mediterranean watersheds.

Effectiveness of soil erosion barriers to reduce sediment connectivity at small basin scale in a fire-affected forest

Forest fires and post-fire management practices (PFMP) cause changes in the hydrological response of a hillslope. This study evaluates the effect of log erosion barriers (LB) and Easy-Barriers® (EB) on the spatial patterns and values of structural sediment connectivity (SC) in a Mediterranean mountainous pine forest affected by an arson fire in August 2017. A drone flight was done in July 2019 (23 months after the fire and 11 months after the PFMP) to obtain a high-resolution orthomosaic and DEM (at 0.05 m). Two contrasted areas, with and without PFMP, were selected along the same hillslope and 26 small basins were identified: 16 in the treated area (mean area, slope and vegetation recovery of 916 m², 60% and 25%; with 94 LB and 39 EB) and 10 in the untreated area (1952 m², 75% and 20%). The aggregated index of sediment connectivity (AIC) was chosen to compute SC in three temporal scenarios: Before and just after the fire and when all PFMP were implemented including the incipient vegetation recovery. Output normalization allowed the comparison of the non-nested basins among them. After accounting the intrinsic differences among the basins and areas, and the temporal changes of SC between the three scenarios, the contribution of the barriers was estimated in 27% from the total decrease of SC in the treated area (-8.5%). The remaining 73% was explained by the vegetation recovery. The effectiveness of the LB (11.3% on average) and EB (13.4%) did not diminish with increasing slope gradients. These percentages become relevant considering the small area affected by the LB (2.8%) and EB (1.3%). Independent metrics (convergence index, flow width, flat areas and LS factor) also reported clear differences between the two areas -higher soil erosive intensity in the untreated area- and in accordance with the AIC results.

Estimating Soil Erosion Rate Changes in Areas Affected by Wildfires

In recent decades, wildfires have become a serious threat worldwide, producing disasters in the natural and anthropogenic environment as well as serious economic losses. One of wildfire’s major impacts is soil erosion, as it may cause major problems in both the physical and anthropogenic environment and seriously affect the landscape. This study investigates the soil erosion rate changes in areas affected by wildfires and uses, as a pilot area, the drainage basin of the Pinios earth-filled dam located in the Ilia Regional Unit, western Greece, which has suffered serious erosion changes after a wildfire event. For this purpose, the Revised Universal Soil Loss Equation (RUSLE) is applied in GIS software, and the soil erosion rate changes in the selected investigation area are estimated at different time intervals. Specifically, soil erosion rate changes are calculated by importing the factors from the RUSLE equation in the GIS software and uses as a dependent variable the cover management factor C, which is strongly influenced by large destructive fires. The models that are produced are compared with each other by collating average annual soil erosion maps and rates before the fire, immediately after the fire and for the existing conditions occurring in the pilot area.

Investigating the Correlation of Tectonic and Morphometric Characteristics with the Hydrological Response in a Greek River Catchment Using Earth Observation and Geospatial Analysis Techniques

Morphometric analysis can be used to investigate catchment dynamics and tectonic processes responsible for the development of drainage catchments and to support flood risk assessment. In this study, a comparative GIS-based morphometric analysis between the main southern and northern sub-catchments of the Sperchios River basin, Central Greece, was performed, using geospatial and remote sensing data. The goal was to investigate their correlation with the peculiar geotectonic activity and the frequent flash-flood events that occur in the river floodplain. All sub-catchments characteristics are linked with the geological formation types of the area, in combination with ongoing tectonic activity. The results indicate that drainage network development is significantly controlled by the region’s overall tectonic activity. The morphometric characteristics—i.e., bifurcation ratio, drainage density, circularity ratio, elongation ratio and water concentration–time values, reflect the flood-prone character of the southern part of Sperchios River catchment in comparison to the northern part, especially during intense rainfall events. The study can provide valuable insight into identifying how morphometric characteristics are associated with increased flood hazard.

Earth Observation and GIS-Based Analysis for Landslide Susceptibility and Risk Assessment

Landslides can cause severe problems to the social and economic well-being. In order to effectively mitigate landslide hazards, the development of detailed susceptibility maps is required, towards implementing targeted risk management plans. This study aims to create detailed landslide susceptibility (LS) and landslide risk (LR) maps of the Sperchios River basin by applying an expert semi-quantitative approach that integrates the Geographic Information Systems (GIS)-based multicriteria analysis and Earth Observation (EO) data. Adopting the analytic hierarchy process (AHP) for a weighted linear combination (WLC) approach, eleven evaluation parameters were selected. The results were validated using a historic landslide database, enriched with new landslide locations mapped by satellite and aerial imagery interpretation and field surveys. Moreover, the landslide risk map of the area was also developed, based on the LS delineation, considering additionally the anthropogenic exposure and overall vulnerability of the area. The results showed that the most susceptible areas are located at the west and south-west regions of the basin. The synergistic use of GIS-based analysis and EO data can provide a useful tool for the design of natural hazards prevention policy at highly susceptible to risk landslide risk areas.

Rainfall erosivity in South America: Current patterns and future perspectives

Rainfall erosivity is the driving factor for soil erosion and can be potentially affected by climate change, impacting agriculture and the environment. In this study, we sought to project the impact of climate change on the long-term average annual rainfall erosivity (R-factor) and mean annual precipitation in South America. The CanESM2, HadGEM2-ES, and MIROC5 global circulation models (GCMs) and the average of the GCMs (GCM-Ensemble) downscaled by the Eta/CPTEC model at a spatial resolution of 20 km in the representative concentration pathway (RCP) 8.5 were applied in this study. A geographical model to estimate the R-factor across South America was fitted. This model was based on latitude, longitude, altitude, and mean annual precipitation as inputs obtained from the WorldClim database. Using this model, the first R-factor map for South America was developed (for the baseline period: 1961-2005). The GCMs projected mean annual precipitation for three 30-year time periods (time slices: 2010-2040; 2041-2070; 2071-2099). These projections were used to run the R-factor model to assess the impact of climate change. It was observed that the changes were more pronounced in the Amazon Forest region (namely, the North Region, NR, and the Andes North Region, ANR) with a strong reduction in the mean annual precipitation and R-factor throughout the century. The highest increase in the R-factor was projected on the Central and South Andes regions (CAR and SAR) because of the increase in the mean annual precipitation projected by the GCMs. The GCMs pointed contradictory projections for the Central-South Region (CSR), indicating greater uncertainty. An increase in the R-factor was projected for this region, eastern Argentina, and southern Brazil, whereas a decrease in the R-factor was expected for southeastern Brazil. In general, the GCMs projected reductions in the R-factor and annual precipitation for South America, with the highest changes projected from the baseline to the 2010-2040 time slice.

Using SCS-CN and Earth Observation for the Comparative Assessment of the Hydrological Effect of Gradual and Abrupt Spatiotemporal Land Cover Changes

In this study a comparative assessment of the impacts of urbanization and of forest fires as well as their combined effect on runoff response is investigated using earth observation and the Soil Conservation Service Curve Number (SCS-CN) direct runoff estimation method in a Mediterranean peri-urban watershed in Attica, Greece. The study area underwent a significant population increase and a rapid increase of urban land uses, especially from the 1980s to the early 2000s. The urbanization process in the studied watershed caused a considerable increase of direct runoff response. A key observation of this study is that the impact of forest fires is much more prominent in rural watersheds than in urbanized watersheds. However, the increments of runoff response are important during the postfire conditions in all cases. Generally, runoff increments due to urbanization seem to be higher than runoff increments due to forest fires affecting the associated hydrological risks. It should also be considered that the effect of urbanization is lasting, and therefore, the possibility of an intense storm to take place is higher than in the case of forest fires that have an abrupt but temporal impact on runoff response. It should be noted though that the combined effect of urbanization and forest fires results in even higher runoff responses. The SCS-CN method, proved to be a valuable tool in this study, allowing the determination of the direct runoff response for each soil, land cover and land management complex in a simple but efficient way. The analysis of the evolution of the urbanization process and the runoff response in the studied watershed may provide a better insight for the design and implementation of flood risk management plans.

Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data

The western part of Crete Island has undergone serious landslide events in the past. The intense rainfalls that took place in the September 2018 to February 2019 period provoked extensive landslide events at the northern part of Chania prefecture, along the motorway A90. Geospatial analysis methods and earth observation data were utilized to investigate the impact of the various physical and anthropogenic factors on landslides and to evaluate landslide susceptibility. The landslide inventory map was created based on literature, aerial photo analysis, satellite images, and field surveys. A very high-resolution Digital Elevation Model (DEM) and land cover map was produced from a dense point cloud and Earth Observation data (Landsat 8), accordingly. Sentinel-2 data were used for the detection of the recent landslide events and offered suitable information for two of them. Eight triggering factors were selected and manipulated in a GIS-based environment. A semi-quantitative method of Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) was applied to evaluate the landslide susceptibility index (LSI) both for Chania prefecture and the motorway A90 in Chania. The validation of the two LSI maps provided accurate results and, in addition, several susceptible points with high landslide hazards along the motorway A90 were detected.

A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union

Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016. This small decrease of soil loss was due to a limited increase of applied soil conservation practices and land cover change observed at the EU level. The modelling results suggest that, currently, ca. 25% of the EU land has erosion rates higher than the recommended sustainable threshold (2 t ha−1 yr−1) and more than 6% of agricultural lands suffer from severe erosion (11 t ha−1 yr−1). The results suggest that a more incisive set of measures of soil conservation is needed to mitigate soil erosion across the EU. However, targeted measures are recommendable at regional and national level as soil erosion trends are diverse between countries which show heterogeneous application of conservation practices.