Machine learning techniques for fine dead fuel load estimation using multi‐source remote sensing data

Fine dead fuel load is one of the most significant components of wildfires without which ignition would fail. Several studies have previously investigated 1‐h fuel load using standard fuel parameters or site‐specific fuel parameters estimated ad hoc for the landscape. On the one hand, these methods have a large margin of error, while on the other their production times and costs are high. In response to this gap, a set of models was developed combining multi‐source remote sensing data, field data and machine learning techniques to quantitatively estimate fine dead fuel load and understand its determining factors. Therefore, the objectives of the study were to: (1) estimate 1‐h fuel loads using remote sensing predictors and machine learning techniques; (2) evaluate the performance of each machine learning technique compared to traditional linear regression models; (3) assess the importance of each remote sensing predictor; and (4) map the 1‐h fuel load in a pilot area of the Apulia region (southern Italy). In pursuit of the above, fine dead fuel load estimation was performed by the integration of field inventory data (251 plots), Synthetic Aperture Radar (SAR, Sentinel‐1), optical (Sentinel‐2), and Light Detection and Ranging (LIDAR) data applying three different algorithms: Multiple Linear regression (MLR), Random Forest (RF), and Support Vector Machine (SVM). Model performances were evaluated using Root Mean Squared Error (RMSE), Mean Squared Error (MSE), the coefficient of determination (R2) and Pearson’s correlation coefficient (r). The results showed that RF (RMSE: 0.09; MSE: 0.01; r: 0.71; R2: 0.50) had more predictive power compared to the other models, while SVM (RMSE: 0.10; MSE: 0.01; r: 0.63; R2: 0.39) and MLR (RMSE: 0.11; MSE: 0.01; r: 0.63; R2: 0.40) showed similar performances. LIDAR variables (Canopy Height Model and Canopy cover) were more important in fuel estimation than optical and radar variables. In fact, the results highlighted a positive relationship between 1‐h fuel load and the presence of the tree component. Conversely, the geomorphological variables appeared to have lower predictive power. Overall, the 1‐h fuel load map developed by the RF model can be a valuable tool to support decision making and can be used in regional wildfire risk management

The wildland-urban interface map of Italy: A nationwide dataset for wildfire risk management

A wildland-urban interface (WUI) raster map was created for the Italian peninsula with a resolution of 30 m per pixel. The map creation process consisted of three fundamental steps: (1) selection of buildings within the wildland-urban interface areas and subsequent classification of these into isolated, scattered, and clustered buildings; (2) creation of the tree canopy cover layer; (3) generation of WUI map by the intersection of two previous products. According to the WUI map, more than half of the total area of Italy is occupied by interface areas. Areas with buildings classified as clustered (24.61%) and scattered (19.15%) predominate on the territory compared to isolated buildings (14.93%). Most of the buildings are located in areas with a tree cover canopy between up to 64%. This map is functional to the implementation of forest fire prevention plans and to the identification of buildings that are close to fire risk areas such as forests, grasslands, and pastures

Are community gardening and horticultural interventions beneficial for psychosocial well-being? A meta-analysis

Recent literature has revealed the positive effect of gardening on human health; however, empirical evidence on the effects of gardening-based programs on psychosocial well-being is scant. This meta-analysis aims to examine the scientific literature on the effect of community gardening or horticultural interventions on a variety of outcomes related to psychosocial well-being, such as social cohesion, networking, social support, and trust. From 383 bibliographic records retrieved (from 1975 to 2019), seven studies with a total of 22 effect sizes were selected on the basis of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Meta-analytic findings on 11 comparisons indicate a positive and moderate effect of horticultural or gardening interventions on psychosocial well-being. Moderation analysis shows a greater effect size in individualistic than collectivistic cultures. A greater effect size was also observed in studies involving community gardening compared to horticultural intervention. Nevertheless, an effect of publication bias and study heterogeneity has been detected. Despite the presence of a large number of qualitative studies on the effect of horticulture/gardening on psychosocial well-being, quantitative studies are lacking. There is a strong need to advance into further high-quality studies on this research topic given that gardening has promising applied implications for human health, the community, and sustainable city management

Is experience the best teacher? Knowledge, perceptions, and awareness of wildfire risk

Wildfires represent a natural phenomenon with detrimental effects on natural resources and human health. A better knowledge, perception, and awareness of wildfire risk may help communities at risk of exposure to prevent future events and safeguard their own lives. The aim of this study is to explore differences between individuals with and without previous wildfire experience, in terms of (1) subjective and advanced wildfire knowledge, (2) self-reported perceptions, (3) level of information, (4) self-protection measures, and (5) importance of community involvement. As a second step, we investigated differences in the same variables, focusing more deeply on a group of individuals with previous wildfire experience, classifying them according to fire-related employment (fire-related workers vs. non-workers) and wildland–urban interface (WUI) proximity (WUI residents vs. non-WUI residents). The Kruskal–Wallis test was applied to establish differences between the pairs of subsamples. Our results partially confirmed our hypothesis, that direct experience leads individuals to have a greater preparedness on the topic of wildfires. Perception of knowledge is reflected only at a shallow level of expertise, and, therefore, no relevant within-group differences related to fire-related employment or to WUI proximity were detected. Moreover, available information was perceived to be insufficient, thus we report a strong need for developing effective communication to high-risk groups, such as homeowners and fire-related workers

Modeling fire ignition probability and frequency using Hurdle models: a cross-regional study in Southern Europe

Background: Wildfires play a key role in shaping Mediterranean landscapes and ecosystems and in impacting species dynamics. Numerous studies have investigated the wildfire occurrences and the influence of their drivers in many countries of the Mediterranean Basin. However, in this regard, no studies have attempted to compare different Mediterranean regions, which may appear similar under many aspects. In response to this gap, climatic, topographic, anthropic, and landscape drivers were analyzed and compared to assess the patterns of fire ignition points in terms of fire occurrence and frequency in Catalonia (Spain), Sardinia, and Apulia (Italy). Therefore, the objectives of the study were to (1) assess fire ignition occurrence in terms of probability and frequency, (2) compare the main drivers affecting fire occurrence, and (3) produce fire probability and frequency maps for each region. Results: In pursuit of the above, the probability of fire ignition occurrence and frequency was mapped using Negative Binomial Hurdle models, while the models’ performances were evaluated using several metrics (AUC, prediction accuracy, RMSE, and the Pearson correlation coefficient). The results showed an inverse correlation between distance from infrastructures (i.e., urban roads and areas) and the occurrence of fires in all three study regions. This relationship became more significant when the frequency of fire ignition points was assessed. Moreover, a positive correlation was found between fire occurrence and landscape drivers according to region. The land cover classes more significantly affected were forest, agriculture, and grassland for Catalonia, Sardinia, and Apulia, respectively. Conclusions: Compared to the climatic, topographic, and landscape drivers, anthropic activity significantly influences fire ignition and frequency in all three regions. When the distance from urban roads and areas decreases, the probability of fire ignition occurrence and frequency increases. Consequently, it is essential to implement long- to medium-term intervention plans to reduce the proximity between potential ignition points and fuels. In this perspective, the present study provides an applicable decision-making tool to improve wildfire prevention strategies at the European level in an area like the Mediterranean Basin where a profuse number of wildfires take place

Uncovering current pyroregions in Italy using wildfire metrics

Background: Pyrogeography is a major field of investigation in wildfire science because of its capacity to describe the spatial and temporal variations of fire disturbance. We propose a systematic pyrogeographic analytical approach to cluster regions on the basis of their pyrosimilarities. We employed the Affinity Propagation algorithm to cluster pyroregions using Italian landscape as a test bed and its current wildfire metrics in terms of density, seasonality and stand replacing fire ratio. A discussion follows on how pyrogeography varies according to differences in the human, biophysical, socioeconomic, and climatic spheres. Results: The algorithm identified seven different pyroregion clusters. Two main gradients were identified that partly explain the variability of wildfire metrics observed in the current pyroregions. First, a gradient characterized by increasing temperatures and exposure to droughts, which coincides with a decreasing latitude, and second, a human pressure gradient displaying increasing population density in areas at lower elevation. These drivers exerted a major influence on wildfire density, burnt area over available fuels and stand replacing, which were associated to warm-dry climate and high human pressure. The study statistically highlighted the importance of a North–South gradient, which represents one of the most important drivers of wildfire regimes resulting from the variations in climatic conditions but showing collinearity with socioeconomic aspects as well. Conclusion: Our fully replicable analytical approach can be applied at multiple scales and used for the entire European continent to uncover new and larger pyroregions. This could create a basis for the European Commission to promote innovative and collaborative funding programs between regions that demonstrate pyrosimilarities

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

Enhancing proteotoxic stress in leiomyosarcoma cells triggers mitochondrial dysfunctions, cell death, and antitumor activity in vivo

Leiomyosarcomas are rare and aggressive tumors characterized by a complex karyotype. Surgical resection with or without radiotherapy and chemotherapy is the standard curative treatment. Unfortunately, a high percentage of leiomyosarcomas recurs and metastasizes. In these cases, doxorubicin and ifosfamide represent the standard treatment but with low response rates. Here, we evaluated the induction of proteotoxic stress as a possible strategy to kill leiomyosarcoma cells in a therapeutic perspective. We show that aggressive leiomyosarcomas coexist with high levels of proteotoxic stress. As a consequence, we hypothesized that leiomyosarcoma cells are vulnerable to further increases of proteotoxic stress. The small compound 2c is a strong inducer of proteotoxic stress. In leiomyosarcoma cells, it triggers cell death coupled to a profound reorganization of the mitochondrial network. By using stimulated emission depletion microscopy, we have unveiled the existence of DIABLO/SMAC clusters that are modulated by 2c. Finally, we have engineered a new version of 2c linked to polyethylene glycol though a short peptide, named 2cPP. This new prodrug is specifically activated by proteases present in the tumor microenvironment. 2cPP shows a strong antitumor activity in vivo against leiomyosarcomas and no toxicity against normal cells

Photosensitization of pancreatic cancer cells by cationic alkyl-porphyrins in free form or engrafted into POPC liposomes: The relationship between delivery mode and mechanism of cell death

Cationic porphyrins bearing an alkyl side chain of 14 (2b) or 18 (2d) carbons dramatically inhibit proliferation of pancreatic cancer cells following treatment with light. We have compared two different ways of delivering porphyrin 2d: either in free form or engrafted into palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine liposomes (L-2d). Cell cytometry shows that while free 2d is taken up by pancreatic cancer cells by active (endocytosis) and passive (membrane fusion) transports, L-2d is internalized solely by endocytosis. Confocal microscopy showed that free 2d co-localizes with the cell membrane and lysosomes, whereas L-2d partly co-localizes with lysosomes and ER. It is found that free 2d inhibits the KRAS-Nrf2-GPX4 axis and strongly triggers lipid peroxidation, resulting in cell death by ferroptosis. By contrast, L-2d does not affect the KRAS-Nrf2-GPX4 axis and activates cell death mainly through apoptosis. Overall, our study demonstrates for the first time that cationic alkyl porphyrins, which have a IC50 ~ 23 nM, activate a dual mechanism of cell death, ferroptosis and apoptosis, where the predominant form depends on the delivery mode