How wildfire risk is related to urban planning and Fire Weather Index in SE France (1990-2013)

Spatio-temporal assessment of soil properties immediately and eight months after a high intensity-controlled burn in the south of Spain

In recent years, the use of fire as a means by which to manage forest ecosystems has become more frequent in Europe. Fire has a significant impact on the soil, and it is therefore necessary to understand how controlled burns affect this invaluable resource. The purpose of this study was to evaluate the main alterations in the physical-chemical and biological properties of the soil because of a high intensity-controlled burn in "Los Boquerones" area (Villaviciosa de Córdoba, Spain). Additionally, we assessed the spatial heterogeneity of the alterations of different soil properties. A grid of 12 points was established on a hillside in Sierra Morena (Córdoba). Thermocouples were placed at each point, and soil samples were collected at two depths (0-2 cm and 2-5 cm) before burning, immediately after burning and eight months later. Soil pH, electrical conductivity, nutrient content and/or availability, among others, and their spatio-temporal variations were analysed. Soil pH, increased in the first centimetres of the soil (0-2 cm) immediately after burning up to >2 units, and the increase was maintained eight months following the burn. Additionally, the high-intensity burn had a positive short-term effect on some of the soil properties, such as nutrient availability for plants, which was considerably increased. The magnitude of the alterations in the soil indicators assessed was spatially explained by the behaviour of the fire during the controlled burning. The burn also had both direct and indirect effects on soil microorganisms. In conclusion, the possible immediate and short-term effects of burning on the soil resource should be considered for a more holistic management of fire in forest ecosystems, as its functionality and capacity to provide ecosystem services is largely altered by these events as a function of their intensity.

Decoupling relationship between carbon emissions and economic development and prediction of carbon emissions in Henan Province: based on Tapio method and STIRPAT model

In order to cope with global warming, China has put forward the "30 · 60" plan. We take Henan Province as an example to explore the accessibility of the plan. Tapio decoupling model is used to discuss the relationship between carbon emissions and economy in Henan Province. The influence factors of carbon emissions in Henan Province were studied by using STIRPAT extended model and ridge regression method, and the carbon emission prediction equation was obtained. On this basis, the standard development scenario, low-carbon development scenario, and high-speed development scenario are set according to the economic development model to analyze and predict the carbon emissions of Henan Province from 2020 to 2040. The results show that energy intensity effect and energy structure effect can promote the optimization of the relationship between economy and carbon emissions in Henan Province. Energy structure and carbon emission intensity have a significant negative impact on carbon emissions, while industrial structure has a significant positive impact on carbon emissions. Henan Province can achieve the "carbon peak" goal by 2030 years under the standard and low-carbon development scenario, but it cannot achieve this goal under the high-speed development scenario. Therefore, in order to achieve the goals of "carbon peaking" and "carbon neutralization" as scheduled, Henan Province must adjust its industrial structure, optimize its energy consumption structure, improve energy efficiency, and reduce energy intensity.

Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking

Wildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland-urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10694-023-01371-1.

Optimization of the Territorial Spatial Patterns Based on MOP and PLUS Models: A Case Study from Hefei City, China

Optimization of the territorial spatial patterns can promote the functional balance and utilization efficiency of space, which is influenced by economic, social, ecological, and environmental factors. Consequently, the final implementation of spatial planning should address the issue of sustainable optimization of territorial spatial patterns, driven by multiple objectives. It has two components-the territorial spatial scale prediction and its layout simulation. Because a one-sided study of scale or layout is divisive, it is necessary to combine the two to form complete territorial spatial patterns. This paper took Hefei city as an example and optimized its territorial spatial scale using the multiple objective programming (MOP) model, with four objective functions. A computer simulation of the territorial spatial layout was created, using the patch-generating land use simulation (PLUS) model, with spatial driving factors, conversion rules, and the scale optimization result. To do this, statistical, empirical, land utilization, and spatially driven data were used. The function results showed that carbon accumulation and economic and ecological benefits would be ever-increasing, and carbon emissions would reach their peak in 2030. The year 2030 was a vital node for the two most important land use types in the spatial scale-construction land and farmland. It was projected that construction land would commence its transition from reduced to negative growth after that time, and farmland would start to rebound. The simulation results indicated that construction land in the main urban area would expand primarily to the west, with supplemental expansion to the east and north. In contrast, construction land in the counties would experience a nominal increase, and a future ecological corridor would develop along the route south of Chaohu County-Chaohu Waters-Lujiang County-south of Feixi County.

Study on the Optimization of Territory Spatial "Urban-Agricultural-Ecological" Pattern Based on the Improvement of "Production-Living-Ecological" Function under Carbon Constraint

The spatial layout of the "Production-Living-Ecological" (PLE) function and the spatial optimization of the "Urban-Agricultural-Ecological" (UAE) pattern are the key points and difficulties in territorial space planning. This paper analyzes their spatial concepts and holds that PLE space is a functional space, while UAE space belongs to a regional space. The optimization of the UAE pattern should be guided by the improvement of the PLE function. Therefore, taking Hefei City, China, as an example, this paper analyzes the evolution of the present UAE pattern, evaluates the PLE function under carbon constraint and then determines the improvement direction of the PLE function and finally simulates the future UAE pattern of territory space. The conclusions are as follows: ① From 2011 to 2019, the urban space increased incrementally, while the agricultural space and ecological space decreased continuously, and the urban space expansion squeezed the agricultural and ecological spaces greatly; ② The PLE functions of four districts in the main city are higher than that of five other counties. After the carbon constraint conditions are included, the PLE functions of the main city were reduced due to the relatively strong capacity of carbon source, while the counties' increased due to a stronger carbon sink capacity; ③ According to the normalized revealed comparative advantage (NRCA) index, it was determined that the functional improvement direction of each district and county are Yaohai District and Shushan District have comprehensive function as a priority, Luyang District and Baohe District give priority to living-ecological function, Changfeng County, Feidong County, Feixi County and Chaohu County give priority to production-ecological function, and Lujiang County gives priority to ecological function; ④ The simulation results show that 2025 is an important node for the evolution of the UAE pattern. The urban spatial expansion during the "14th Five-Year Plan" period will still bring great pressure on agriculture and ecological spaces, and then, the UAE pattern will continue to be optimized and balanced.

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.

On the complexity of fire dinamics at the wildland-urban interface

Complexity is the main feature of many fire-prone environments, in which the fire regime is driven by climate and socio-economic development on short and long timescales. In this study, the interaction between social and forest environments is modelled for the first time by assimilating socio-economic assets to a new flammable species with its own dynamics. This is a completely new approach that offers a new perspective to interpret shifts in fire regimes. The ten-years fire regime trend observed in Italy between 1970 and 2018, according to the model results, may be attributed to a progressive change of land use and inhabited development. The introduction of a new species adds complexity to fire dynamics and modifies the self-regulating Mediterranean forest fire regime. The results evidence that the evolution of a mosaic of natural and man-managed tiles of land may erase the "natural" chaotic fire regime, exacerbate fire frequency and increase fire risk in inhabited areas.

Rapid Extraction of Regional-scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of spatial and temporal disaster patterns of large-scale and long-duration series. Google Earth Engine provides the possibility of quickly extracting the disaster range over a large area. Based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products with 250-m spatial resolution synthesized over 16 days from the period 2005–2019 to develop a rapid and effective method for monitoring disasters across a wide spatiotemporal range. Three types of disaster monitoring and scope extraction models are proposed: the normalized difference vegetation index (NDVI) median time standardization model (RNDVI_TM(i)), the NDVI median phenology standardization model (RNDVI_AM(i)(j)), and the NDVI median spatiotemporal standardization model (RNDVI_ZM(i)(j)). The optimal disaster extraction threshold for each model in different time phases was determined using Otsu’s method, and the extraction results were verified by medium-resolution images and ground-measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang Province from 2010–2019 was extracted, and the spatial and temporal patterns of the disasters were analyzed based on meteorological data. This analysis revealed that the three aforementioned models exhibited high disaster monitoring and range extraction capabilities, with verification accuracies of 97.46%, 96.90%, and 96.67% for RNDVI_TM(i), RNDVI_AM(i), and (j)RNDVI_ZM(i)(j), respectively. The spatial and temporal disaster distributions were found to be consistent with the disasters of the insured plots and the meteorological data across the entire province. Moreover, different monitoring and extraction methods were used for different disasters, among which wind hazard and insect disasters often required a delay of 16 days prior to observation. Each model also displayed various sensitivities and was applicable to different disasters. Compared with other techniques, the proposed method is fast and easy to implement. This new approach can be applied to numerous types of disaster monitoring as well as large-scale agricultural disaster monitoring and can easily be applied to other research areas. This study presents a novel method for large-scale agricultural disaster monitoring.

Wildfires in the wildland-urban interface: Key concepts and evaluation methodologies

Over the last decades, the different issues regarding the expansion of the wildland-urban interface (WUI) - particularly those related to fires - have spread around the world with particular exposure in the USA, Canada, Australia, and, more recently, in southern European countries (e.g. Portugal and Greece). It has been receiving even more attention from the scientific community particularly due to the ecological and sociological implications on the management of natural resources and decisions associated with spatial planning. Consequently, throughout the extensive research conducted on wildfires, there has been a growing interest and body of literature on wildfires in the WUI worldwide. Although there are many articles published in English, in indexed journals, there is an excellent body of literature published in other languages (e.g. French, Spanish, Portuguese), which is not very well known and rarely cited. In this body of literature, whether in English or other languages, concepts and definitions are not always consensual. In this sense, this paper aims at reviewing the key concepts regarding intrinsic characteristics of the WUI and wildfires in the WUI, presenting evaluation methodologies that have been applied to WUI and analyzing several risk prevention and reduction programs developed in WUI affected by forest fires in different parts of the world. Through our analysis we found that the work developed by researchers worldwide on this subject is significant, considering the increasing relevance of this environmental problem. However, it is fundamental to define standardized methodologies in order to facilitate the transfer of knowledge and promote cooperation, interdisciplinarity. The implementation of a collaborative approach is needed, especially in the development of strategies to prevent and reduce fire risk in these areas.