Search Results (10,163)

Extreme weather events are increasing the frequency and intensity of forest fires, generating serious environmental and socio-economic impacts. These fires cause soil loss through erosion, organic matter depletion, increased surface runoff and the release of greenhouse gases, intensifying climate change. They also affect biodiversity, terrestrial and aquatic ecosystems, and soil quality. The assessment of forest fires by remote sensing, such as the use of the Normalised Difference Vegetation Index (NDVI), allows rapid analysis of damaged areas, monitoring of vegetation changes and the design of restoration strategies. On the other hand, models such as RUSLE are key tools for calculating soil erosion and planning conservation measures. A study of the impacts on soils and vegetation in the south of Salamanca, where one of the worst fires in the province took place in 2022, has been carried out using RUSLE and NDVI models, respectively. The study confirms that fires significantly affect soil properties, increase erosion and hinder vegetation recovery, highlighting the need for effective restoration strategies. It was observed that erosion intensifies after fires (the maximum rate of soil loss before is 1551.85 t/ha/year, while after it is 4899.42 t/ha/year) especially in areas with steeper slopes, which increases soil vulnerability, according to the RUSLE model. The NDVI showed a decrease in vegetation recovery in the most affected areas (with a maximum value of 0.3085 after the event and 0.4677 before), indicating a slow regeneration process. The generation of detailed cartographies is essential to identify critical areas and prioritise conservation actions. Furthermore, the study highlights the importance of implementing restoration measures, designing sustainable agricultural strategies and developing environmental policies focused on the mitigation of land degradation and the recovery of fire-affected ecosystems. Full article

The meteorology-driven multiscale behavior of snow depth over the Tibetan Plateau was investigated via analyzing the spatio-temporal variability of snow depth over 28 intraseasonal continuous snow cover regions. By employing power spectra and the Kullback–Leibler (K-L) distance, the spectral similarities between snow depth and meteorological factors were examined at scales of 5 km, 10 km, 20 km, and 50 km across seasons from 2008 to 2014. Results reveal distinct seasonal and scale-dependent dynamics: in spring and winter, snow depth exhibits lower spectral variance with scale breaks around 50 km, emphasizing the critical roles of precipitation, atmospheric moisture, and temperature, with lower K-L distances at smaller scales. Summer shows the highest spatial variance, with snow depth primarily influenced by wind and radiation, as indicated by lower K-L distances at 15–45 km. Autumn demonstrates the lowest spatial heterogeneity, with windspeed driving snow redistribution at finer scales. The alignment between spatial variance maps and power spectra implies that snow depth data can be effectively downscaled or upscaled without significant loss of spatial information. These findings are essential for improving snow cover modeling and forecasting, particularly in the context of climate change, as well as for effective water resource management and climate adaptation strategies in this strategically vital plateau. Full article

Sustainable community development is a prerequisite for national parks’ coordinated ecological and socio-economic development. This study analyzes the sustainable development challenges communities face in national parks, including the marginalization of indigenous peoples, the passive role of stakeholders, and insufficient protection of community interests. Using a grounded theory approach and a mixed research method (semi-structured interviews and questionnaires), the development constraints of community residents in Hainan Tropical Rainforest National Park in China were systematically studied. The research framework identified five core dimensions (economic, social, ecological, institutional, and cultural) and eight major categories that characterize the community’s development dilemma. The analysis revealed systemic problems, including differences in income distribution, limited access to resources, gaps in policy implementation, and ambiguous stakeholder roles. A new framework for coordinated development of national park communities was constructed through multidimensional analysis, and coordinated development strategies were proposed from the five dimensions of economy, society, ecology, institution, and culture. These findings contribute to the theoretical underpinnings of national park governance in China and offer a transferable methodological system for managing nature reserves and national parks worldwide, particularly in achieving a balance between ecological protection and community development needs. Full article

Land serves as a crucial repository of resource elements, and enhancing the green use efficiency of urban land (GUEUL) is essential for attaining sustainable development. Based on 296 cities in China from 2006 to 2022, this study explored the relationship between land system innovation and GUEUL by integrating multi-source data, ArcGIS analysis, the EBM-DEA model, and the DID model, and elucidating the temporal trend and spatial utilization characteristics of GUEUL in China. Based on the natural experimental scenario of the pilot reform of China’s urban construction land use approval system, this study finds through in-depth analysis of the double-difference model that the vertical transfer of land approval authority has fundamentally optimized the development pattern of GUEUL, and that this positive impact is mainly reflected in two dimensions: on the one hand, it reduces the systematic transaction costs, and on the other hand, it enhances the density of industrial spatial agglomeration. Second, the lower the initial level of infrastructure and the lower the degree of dependence on land finance, the more significant the decentralization of land approval power in the promotion of GUEUL. Currently, China is undergoing a swift phase of urbanization and industrialization, and this study provides policy support for improving the comprehensive efficiency of green land use and promoting high-quality and sustainable development of the region. Full article

The assessment of ecosystem service (ES) supply–demand relationships is critical for addressing regional sustainable development challenges, yet systematic studies integrating spatial drivers analysis and multiscenario forecasting in rapidly urbanizing mountainous regions remain scarce. This study focuses on Chongqing as a representative case to investigate spatial patterns, driving mechanisms, and future trajectories of ES supply–demand dynamics. Through spatial quantification of four key ES (food provision, water retention, soil conservation, carbon fixation) and statistical analysis of socioeconomic datasets from 2010 to 2020, geographical weighted regression modeling was employed to identify spatially heterogeneous drivers. Long-term projections (2030–2060) were developed using climate–economy integrated scenarios reflecting different global development pathways. The results demonstrate three principal findings: First, while regional ecosystem quality maintains stable with an improved supply–demand ratio (0.260 to 0.320), persistent deficits in carbon fixation capacity require urgent attention. Second, spatial mismatches exhibit intensifying polarization, with expanding deficit zones concentrated in metropolitan cores and their periurban peripheries. Third, thermal-hydrological factors (aridity index, temperature) coupled with land intensification pressures emerge as dominant constraints on ES supply capacity. Scenario projections suggest coordinated climate mitigation and sustainable development strategies could maintain the supply–demand ratio at 0.189 by 2060, outperforming conventional development pathways by 23.5–41.2%. These findings provide spatial decision support frameworks for balancing ecological security and economic growth in mountainous megacities, with methodological implications for cross-scale ES governance in developing regions. Full article

The present study was conducted in Extremadura, a region in southwestern Spain with a significant area dedicated to olive cultivation. An analysis of the olive growing climatology of its territory was conducted using bioclimatic indices that affect the development of olive cultivation, focusing on water requirements, thermal requirements, and leaf carbohydrate synthesis. The study revealed that very dry conditions during the olive growing season are the main characteristic of the Mediterranean climate in the region. A principal component analysis was performed to analyze the main sources of variability, revealing two main components, determined by annual rainfall, annual water requirement, mean annual temperature, degree days above 14.4 °C accumulated during the olive growing season, and the number of days with optimal temperatures for leaf carbohydrate synthesis. Three homogeneous groups were determined by cluster analysis, one of which had cooler thermal conditions and no water requirements. The study found that an increase in the olive growing season or a shortening of the dormant period could result in a higher water input during the growing season and a lack of accumulation of chilling hours during the dormant period, causing crop maintenance problems in warmer locations. Climate change is expected to have significant impacts on this crop where climatic conditions are already very hot and dry. In the future, it is possible that the current olive-growing areas in Extremadura will move to other areas where the temperature is cooler. Full article

Thermal comfort in urban commercial spaces significantly impacts both business performance and public well-being. Traditional evaluation methods relying on field surveys and expert assessments are often time-consuming and labor-intensive. This study proposes a novel vision–language model (VLM)-based agent system for thermal comfort assessment in commercial spaces, simulating eight distinct heat-sensitive roles with varied demographic backgrounds through prompt engineering using ChatGPT-4o. Taking Harbin Central Street, China as a case study, we first validated model accuracy through ASHRAE scale evaluations of 30% samples (167 images) by 50 experts, and then conducted thermal comfort simulations of eight heat-sensitive roles followed by spatial and interpretability analyses. Key findings include (1) a significant correlation between VLM assessments and expert evaluations (r = 0.815, p < 0.001), confirming method feasibility; (2) notable heterogeneity in thermal comfort evaluations across eight agents, demonstrating the VLMs’ capacity to capture perceptual differences among social groups; (3) spatial analysis revealing higher thermal comfort in eastern regions compared to western and central areas despite inter-role variations, demonstrating consistency among agents; and (4) the shade and vegetation being identified as primary influencing factors that contribute to the agent’s decision making. This research validates VLM-based agents’ effectiveness in urban thermal comfort evaluation, showcasing their dual capability in replicating traditional methods while capturing social group differences. The proposed approach establishes a novel paradigm for efficient, comprehensive, and multi-perspective thermal comfort assessments in urban commercial environments. Full article

Global challenges such as climate change, ecological imbalance, and resource scarcity are closely related with land-use change. Arid land, which is 41% of the global land area, has fragile ecology and limited water resources. To ensure food security, ecological resilience, and sustainable use of land resources, there is a need for multi-scenario analysis of land-use change in arid regions. To carry this out, multiple spatial analysis techniques and land change indicators were used to analyze spatial land-use change in a typical inland river basin in arid Northwest China—the Tailan River Basin (TRB). Then, the PLUS model was used to analyze, in a certain time period (1980–2060), land-use change in the same basin. The scenarios used included the Natural Increase Scenario (NIS), Food Security Scenario (FSS), Economic Development Scenario (EDS), Water Protection Scenario (WPS), Ecological Protection Scenario (EPS), and Balanced Eco-economy Scenario (BES). The results show that for the period of 1980–2020, land-use change in the TRB was mainly driven by changes in cultivated land, grassland, forest land, and built-up land. For this period, there was a substantial increase in cultivated land (865.56 km²) and a significant decrease in forest land (197.44 km²) and grassland (773.55 km²) in the study area. There was a notable spatial shift in land use in the period of 1990–2010. The overall accuracy (OA) of the PLUS model was more than 90%, with a Kappa value of 85% and a Figure of Merit (FOM) of 0.18. The most pronounced expansion in cultivated land area in the 2020–2060 period was for the FSS (661.49 km²). This led to an increase in grain production and agricultural productivity in the region. The most significant increase in built-up area was under the EDS (61.7 km²), contributing to economic development and population growth. While the conversion of grassland area into other forms of land use was the smallest under the BES (606.08 km²), built-up area increased by 55.82 km². This presented an ideal scenario under which ecological conservation was in balance with economic development. This was the most sustainable land management strategy with a harmonized balance across humans and the ecology in the TRB study area. This strategy may provide policymakers with a realistic land-use option with the potential to offer an acceptable policy solution to land use. Full article

Ensuring that “each household has a dwelling” is a fundamental principle in the reform of the rural housing system. Pilot areas for residential reform have achieved positive outcomes in rural collective housing. This paper, based on a field study conducted in District D of Province G, utilizes a case study methodology and the Institutional Analysis and Development (IAD) framework to explore the driving mechanisms behind the implementation of collective housing in the pilot villages of District D. It comprehensively analyzes the roles of various stakeholders throughout the entire process of “planning, construction, distribution, and management”, and evaluates the effectiveness of the initiative. The findings of the study indicate that collective housing construction can effectively alleviate land scarcity, meet the housing demands of rural residents, and enhance the overall rural environment. To ensure the successful implementation of collective housing projects, the government must assume a coordinating and guiding role, providing necessary financial and land support while streamlining the approval process. Village collectives should actively manage residential land and respect the preferences of farming households. Furthermore, pricing, allocation, and management strategies should be tailored to local conditions to ensure fairness and safeguard farmers’ rights and interests. Policies should remain adaptable, taking into account regional differences in geography, society, and culture, and selectively incorporating collective housing models to achieve the goal of “each household having a dwelling.” Full article

Traditional urban analysis and planning often neglect intangible emotional responses, leaving a gap in comprehending and addressing appropriately how urban spaces are experienced by individuals and communities. However, in contemporary urban research, emotional dimensions have increasingly been recognized as integral to understanding place and its identity, although the methods for systematically mapping these emotions and addressing both their qualitative and quantitative aspects remain under development. In order to address this research gap, this study presents an analysis of the emotional geography of Kaunas city (Lithuania) center using a mixed-method approach combining qualitative and quantitative methods to examine public narratives collected from social media posts and comments and open-ended responses from a sociological survey of local residents. A qualitative approach, grounded in the classification of emotions by Plutchik, was applied in order to categorize emotional expressions. Simultaneously, a quantitative sentiment analysis using the NLTK VADER tool was performed in order to assess the polarity of emotions and classify them into Positive, Negative, or Neutral within the collected narratives. The social media posts and comments were then georeferenced and mapped using Geographic Information Systems (GISs), while survey data were manually linked to specific locations. This allowed for the creation of emotion maps that highlight emotional hotspots and spatial sentiment trends within Kaunas city center. The results reveal how varying emotional responses are geographically connected to different areas, providing insights into both emotional responses to qualities of physical space and activities directly and indirectly linked to this space. Furthermore, the study demonstrates the potential of emotional mapping as a tool for urban planning, place-making, and sustainable development. Full article

Hollow-dependent wildlife has been declining globally due to the removal of hollow-bearing trees, yet these trees are often unaccounted for in habitat mapping. As on-ground field surveys are costly and time-consuming, we aimed to develop a simple, accessible and transferrable geospatial approach using freely accessible LiDAR to refine habitat mapping by identifying high densities of potential hollow-bearing trees. We assessed if LiDAR from 2009 could be accurately used to detect tree heights, which would correlate to tree diameter at breast height (DBH), which in turn would identify trees that are more likely to be hollow-bearing. Here, we use habitat mapping of greater gliders (Petauroides spp.) in the Fraser Coast region of Australia as a case study. Across four sites, field surveys were conducted in 2023 to assess the tree height and density of large trees (>50 cm DBH per 1 km²) at 19 transects (n = 91). This was compared to outputs from individual tree detection derived from unsupervised classification using a local maximal filter and variable window size to identify treetops in freely available LiDAR. Tree height was measured with an accuracy of RMSE 5.75 m, and we were able to identify transects with large trees (>50 cm DBH), which were more likely hollow bearing. However, there was no statistical evidence to suggest that transects with a high density of large trees could be accurately identified based on LiDAR alone (>50 cm DBH p 0.2298). Despite this, we have demonstrated that freely accessible LiDAR and unsupervised machine learning techniques can be utilised to identify large, potentially hollow-bearing trees on a broad scale to refine habitat mapping for hollow-dependent species. It is important to develop geospatial analysis methods that are more accessible to land managers, as deep machine learning methods and current LiDAR can be computationally intensive and expensive. We propose a workflow using free and accessible geospatial analysis methods to identify large, potentially hollow-bearing trees and determine how to address some limitations in this geospatial approach. Full article

This study investigates the often-overlooked phenomenon of land drainage interventions as a means of climate change adaptation, focusing on a conceptual case study from Northern Bohemia, Czech Republic. The intensification of agriculture has led to extensive tile drainage systems, which have had significant environmental impacts, including disruption of water balance, nutrient leaching, and ecological degradation. With climate change expected to alter precipitation patterns and increase temperatures, these impacts are likely to intensify, leading to more frequent droughts and pollutant delivery from soil to water bodies. This study explores the options for the allocation and implementation of drainage-related measures such as controlled drainage, constructed wetlands, and partial drainage elimination to mitigate these effects, with the use of readily available archival data as well as aerial images, current as well as historical soil, land use, geomorphological and landowner-land user relationships. At two cadastral units with local potable water resources at the hilly Lovečkovicko case study, the paper proposes conceptual, practical approaches for integrating drainage-related measures into land consolidation processes. Here, eleven sites based on the cross-intersection of the above interventions’ criteria were selected, and twenty various drainage-related measures were tentatively designed. This study categorizes the implementation potential of the proposed measures into three levels: high, medium, and low, highlighting the feasibility and transferability of these interventions within the land consolidation or similar process. Full article

The transformation of the Cerrado biome into areas with different levels of activity and anthropic pressure negatively impacts biodiversity. This study evaluated the response of the dung beetle community to changes in land use systems: forests, rubber trees, pastures, and soybeans. Five areas were sampled in each system with a minimum distance of 2 km between them. Dung beetles were collected using pitfall traps, and both local (vegetation density, basal area of wooded vegetation, fractal dimension, litter height, electrical conductance (mV), water content in the soil (%), and soil resistance (kPa)) and landscape-related environmental variables (land use and overall composition and configuration of the landscape surrounding the sampling areas) were measured. In total, 2294 specimens were collected and distributed among 34 species and 18 genera. There was no significant difference in abundance between the systems, but differences in the number of species and biomass were observed between forest and soybean systems, as well as a separation of communities between the tree-covered (forest and rubber tree) and open (pasture and soybean) systems. Density and arboreal basal area were the main predictive variables for the diversity of the dung beetle community, reinforcing the importance of vegetation cover for maintaining diversity, whereas local and landscape-related variables influenced community composition. Full article

During urbanisation, extensive production and construction activities encroach on ecological spaces, leading to changes in environmental structures and soil erosion. The issue of yellow muddy water caused by rainfall in cities with high construction intensity has garnered significant attention. Taking Guangzhou City as the research area, this study is the first to propose a risk assessment model for yellow muddy water in cities with high construction intensity, and the influence of construction sites on yellow muddy water was fully considered. Rainfall and construction sites were used as indicators to assess the hazards of yellow muddy water. Elevation, slope, normalised difference vegetation index (NDVI), soil erosion modulus, stream power index (SPI), surface permeability, and roads represent the exposure evaluation indicators. Population number and GDP (Gross Domestic Product) were used as vulnerability evaluation indicators. Based on the analytic hierarchy process (AHP) method, the weights of each evaluation indicator were determined, and a risk assessment system for yellow muddy water was established. By overlaying the weighted layers of different evaluation indicators on the geographic information system (GIS) platform, a risk degree distribution map of yellow muddy water disasters was generated. The evaluation results demonstrated that the disaster risk levels within the study area exhibited spatial differentiation, with areas of higher risk accounting for 14.76% of the total. The evaluation results were compared with historical yellow muddy water event information from Guangzhou, and the effectiveness of the model was verified by the receiver operating characteristic (ROC) curve. The validation results indicate that this model provides high accuracy in assessing the degree of risk of yellow muddy water in high-construction-intensity cities, offering effective technical support for precise disaster prevention and mitigation. Full article

Improving the quality of rural human settlements is a key objective in China’s rural revitalization strategy. The purpose of this study is to construct and evaluate the quality of rural human settlements in China from a micro perspective. To achieve this objective, the main tasks include constructing an evaluation system for rural human settlement quality from a micro perspective; measuring the overall and dimension-specific quality levels of rural human settlements using the entropy method based on data from 108 villages in Shandong, Jilin, and Hubei provinces; and further analyzing the influencing factors of rural human settlement quality, focusing on village per capita income, resident population, fire incidents, and agricultural input prices. The findings reveal the following: (1) The overall quality of rural human settlements in Hubei, Shandong, and Jilin is at a moderate-to-low level, with no significant differences among provinces. (2) Among the various dimensions of rural human settlement quality, economic development and public services score higher, whereas living facilities and sanitary conditions score relatively lower, reflecting the inertia of long-term resource allocation and the lagged effects of emerging projects. (3) An increase in village per capita net income and the resident population significantly improves rural human settlement quality, whereas incidents such as village fires and sharp increases in agricultural input prices significantly reduce it. This study provides empirical insights into the mechanisms affecting rural human settlement quality from a micro perspective and offers policy implications for its targeted improvement. Full article