Mining plays a crucial role in diversifying the energy matrix towards renewable energies, but it is one of the human activities with the highest environmental and social impacts. The Brazilian Amazon accounts for 72.5% of the country's mineral extraction. The loss of rainforest, soil, and water contamination due to the use of heavy metals impact the ecosystem and have implications for human settlements, such as the Quilombola Territories. 'Quilombolas' is the name given to communities descended from enslaved people who survived the regime of wealth production for Europe. Although this regime was abolished in 1888, they continue to fight for their land ownership rights due to the expansion of mining in their localities. This study aimed to identify the Quilombola Territory within the Amazon biome, which has the highest number of mining deforestation alerts, and to assess changes in Land Use and Land Cover (LULC) resulting from the impact of this activity by integrating remote sensing data and geospatial analysis techniques. The methodology was based on three steps: i) characterisation of the Quilombola Territories within the Amazon biome via a regularisation phase; ii) identification of the delimited Quilombola Territory with the highest number of mining deforestation alerts in the period 2016 - 2020; iii) estimation of LULC changes within the Quilombola Territory during the period 2014 - 2020. The results showed that mining was the class with the highest gain, with an increase of 1219 ha. Meanwhile, the natural vegetation class of primary forest showed the most significant loss of area, with 1182 ha. These changes are associated with the advancement of the industrial mining fronts of the largest bauxite producer in Brazil. This paper highlights the use of remote sensing data and geospatial analysis for monitoring the pressures from the expansion of mining projects in traditional territories.

In Mali, the market gardening sector is considered a priority in the strategic framework for growth and poverty reduction, and in the national plan for agricultural investment and food and nutritional security. However, areas devoted to market gardening are in the process of being converted into building zones. These practices are increasingly controversial and are likely to affect vegetable production, which is an important component of daily diets and a major source of income in towns. This study made use of structured questionnaires for household surveys and remote sensing. Descriptive statistics were used in order to identify the means by which this activity could be characterized, assess the spatial dynamics, and create employment. The results of the spatial analysis showed that market gardening regressed in Bamako from 1990 to 2020 by -53.83%, while it progressed in Sikasso from 1990 to 2010 (by 20.9%), and regressed by -4.83% in 2020. The majority of the farms identified are characterised by low sustainability, with the agro-ecological dimension being the limiting factor, along with the reduction in surface area. Improving the “Soil Fertility”, “Spatial Organization” and “Good Agricultural Practices” components will improve the overall sustainability of urban market gardening in Mali. The socio-territorial sustainability of production is characterised by poor organisation of urban market gardeners and a lack of capacity building, low financial autonomy, and a lack of hygiene and safety in production activities (especially watering). To ensure the sustainability of market gardeners in Bamako and Sikasso cities, it is crucial to promote integrated soil fertility management with the use of improved seeds.

Urban heat is one of the most pressing challenges facing cities today, exacerbated by climate change, population growth, and expanding impervious surfaces. Urban tree canopy cover has emerged as a key nature-based solution to mitigate the urban heat island effect by providing shade, improving evapotranspiration, and influencing local microclimates. This paper presents a meta-analysis of existing empirical and modelling studies that examine the relationship between canopy cover and urban cooling outcomes across diverse climatic and geographic contexts.

Drawing on the peer-reviewed literature from 2000 to 2024, the study systematically reviews and synthesizes quantitative findings on canopy density, spatial distribution, species composition, and their effects on surface and ambient temperature reductions. The meta-analysis reveals that increased canopy cover consistently contributes to cooling benefits, with temperature reductions ranging from 1°C to 6°C depending on urban morphology, canopy structure, and land use type. The analysis also highlights diminishing returns beyond certain coverage thresholds, the importance of equitable canopy distribution, and interactions between vegetation, built form, and socio-economic variables based on the findings from the current studies.

Key themes emerging from the analysis include the role of canopy cover in climate adaptation strategies, its integration into urban planning tools, and barriers to implementation such as land use competition, maintenance costs, and policy fragmentation. The paper concludes by identifying strategic opportunities to maximise the cooling benefits of urban canopy cover—particularly in vulnerable, high-density neighbourhoods—and by recommending urban greening policies that align with climate resilience, public health, and sustainability goals.

This meta-analysis contributes to the growing body of evidence supporting urban forestry as a cost-effective, scalable, and multifunctional solution for creating cooler, more liveable cities in the face of accelerating urban heat challenges.

Urban development zones and their climate exhibit cyclical changes throughout the year. Climate change is linked to deforestation, vehicular emissions, industrial activity, and dust storms. The consequences of urban land use and transport system development, influencing local environmental quality in general, and air quality in particular, are well-known and alarming. So, an increase in pollutants in the environment affects human and animal health, along with leading to a continuous increase in temperature. Particulate matter with a diameter of less than 2.5 µm (PM2.5) is a ubiquitous air pollutant released by biomass burning, vehicle and cooking exhausts, industrial processes, and non-exhaust sources. Due to its small size, PM2.5 can penetrate both the upper and lower respiratory systems. The application of advanced decision-making tools is necessary to predict upcoming climate action and the increase in environmental degradation. This research examines the application of machine learning techniques in assessing the impact of environmental change. Deploying different algorithms helped in the prediction of concentrations of high-risk pollutants. Models were analysed and compared based on different parameters to observe the performance of the models. To address the need for emissions reduction for sustainable urbanisation and to improve air quality, innovative decision-making tools that can be used in practice are necessary. The experiences and needs of stakeholders in charge of urban gross pollutant emissions reduction were analysed through a dedicated device. Environmental Impact Analysis will help achieve sustainability goals, such as Climate Action (SDG13) and Good Health and Well-being (SDG3). The use of machine learning techniques will enhance the efficiency of environmental performance and urban development.

Land ecosystems are critical frontlines in the battle against climate change and play a critical role in combating environmental degradation and ensuring the sustainable use of natural resources. Their hydrological cycling capacity, pollutant cleaning function, and ecological balance recuperation ability make them irreplaceable when it comes to developing nature-based solutions for treating water and landscape restoration. In this context, the present research examines the potential of Salix babylonica (weeping willow), a fast-growing and easily accessed tree species, as a sustainable source of environmentally friendly biosorbents for water treatment. The biomass was processed to obtain fine powders of leaves and roots and assessed for adsorption potential for the removal of calcium (Ca²⁺), magnesium (Mg²⁺), and the synthetic dye Crystal Violet (CV) from polluted water. Structural and surface analysis through FT-IR and laser granulometry determined material appropriateness for adsorption. Batch experiments at varied pH values, temperatures, and contact times assessed performance. Root powder desorbed 79.5% Mg²⁺ and 72.3% Ca²⁺, and leaf powder desorbed 43.2% and 70.0%, respectively. Both powders desorbed more than 80% CV in the best conditions. The results point to the influence of physicochemical conditions and place S. babylonica as a terrestrial climate-resilient biosorbent with the potential to help achieve circular land use and ecological rehabilitation in marginal or degraded land.

Organic and inorganic fertilization management in intensive cropping systems is essential to ensure long-term crop productivity and sustainability. This study evaluated the immediate and residual effects of cattle corralling combined with mineral fertilizer application on maize cropping systems in northern Benin. A four-year field trial (2012–2015) using a strip-plot design was conducted with four levels of corralling (NM: no manure, C0: immediate effect, C1–C3: one- to three-year residual effects) and three mineral fertilization rates (F0: none, F1: half, F2: full recommended dose). Over the four years, cattle corralling significantly increased the average maize yield from 2.0 t/ha (range: 1.0 – 2.9 t/ha) in NM to 4.0 t/ha (range: 3.4 – 5.1 t/ha) in C0, and the average net profitability from 384 USD/ha (range: 159 – 668 USD/ha) in NM to 1000 USD/ha (range: 792 – 1336 USD/ha) in C0. Water use efficiency (WUE) improved from 3.4 in NM to 6.8 in C0, and soil organic carbon (SOC) increased from 3.0 g/kg to 11.2 g/kg. The residual benefits of corralling declined over time without mineral input (C0 > C1 > C2 > C3 > NM) but were sustained and amplified when combined with mineral fertilizers (C3 > C2 > C1 > C0 > NM). Fertilizer effects were minor in C0 and C1, but became significant in C2 and C3, highlighting positive organic–inorganic synergies. Nutrient recovery efficiency (N, P, K) was initially lower in C0 and C1 but surpassed NM levels from C2 onwards (C3 > C2 > NM ≥ C1 > C0). These findings support an integrated soil fertility strategy combining corralling and optimized fertilizer use as a sustainable intensification pathway for maize production in sub-humid, low-fertility rainfed systems. Future research should examine long-term nutrient cycling, soil biology, and economic risk to refine sustainable management practices.

The ongoing inequalities in land access and ownership in South Africa pose a serious challenge that fundamentally threatens the human dignity, personal rights, and overall safety of numerous citizens. The historical effects of apartheid policies have led to a significantly unequal allocation of land, which has had a disproportionate impact on marginalised communities. Recognising these critical issues, the current debates and public forums related to land reform policy are vital steps toward attaining social justice and restorative justice and promoting economic progress across the country. Using qualitative data, this research will examine information gathered from various stakeholders engaged in the land reform discussion, including government bodies, civil society groups, advocates for land rights, and impacted communities. Participants will be chosen using purposive sampling, focusing on individuals with specific characteristics or experiences relevant to restorative justice and land reform policy. This recruitment approach will ensure that the data collected is both relevant and insightful to the topic under investigation. Data will be collected through semi-structured interviews. This approach enables a richer understanding of individual experiences and perspectives. The data from this study will be thoroughly analysed using thematic analysis, a qualitative research method that systematically identifies, analyses, and reports patterns within the collected data. It is essential to note that this research is ongoing, and the comprehensive findings on the empirical data will be available before the conference in September this year. However, based on secondary data gathered from the existing literature, despite the South African government’s efforts to tackle persistent inequalities in land access and ownership, several challenges have emerged. Firstly, the redistribution of land frequently encounters resistance from current landowners, which complicates negotiations and makes them argumentative. Secondly, the execution of land reform policies has been hindered by bureaucratic inefficiencies and a lack of adequate funding and resources to support beneficiaries.

The improvement of the rural homestead system is fundamental to increasing farmers’ property income and achieving rural revitalization in China. Based on the sustainable livelihood framework, this study constructs an analytical framework and employs data from a 2022 field survey of 1,764 rural households across seven provinces. Using interpretable machine learning methods, we evaluate the predictive power of various types of capital characteristics on farmers’ decisions to voluntarily exit their rural homesteads. The results indicate that (1) the Extreme Gradient Boosting (XGBoost) algorithm yields the highest prediction accuracy for homestead exit decisions and significantly outperforms traditional statistical models such as logistic regression; (2) the importance ranking of different capital categories is as follows: human capital > social capital > natural capital > physical capital > psychological capital > financial capital; (3) among the variables, frequency of participation in village collective activities, household non-agricultural income, contracted arable land area, and education level positively influence the likelihood of homestead exit, whereas homestead size and housing area exert a negative influence; (4) the key factors affecting homestead exit vary across pilot and non-pilot villages and between suburban and remote areas. Local governments should prioritize the enhancement of human capital, strengthen social capital networks, optimize the disposal of natural and physical capital, and provide psychological support and institutional guarantees. A differentiated policy approach should be adopted to improve farmers’ willingness to voluntarily exit homesteads, thereby accelerating reform of the rural homestead system.

Eaton Canyon, in California, serves as the focal point for a comprehensive post-wildfire ecological impact assessment. This study employs an approach integrating satellite imagery from the European Space Agency's Sentinel constellation to study an area of 271.49 ??2. The data encompasses both radar and multispectral data, offering a multi-dimensional view of the affected landscape. The analysis leverages the power of the Random Forest Algorithm. Firstly, three widely-used indices—the Difference Normalized Burn Ratio (dNBR), Relative Burn Ratio (RBR), and Relative Difference Normalized Burn Ratio (RdNBR)—were calculated and compared based on their accuracy and Kappa Index. Secondly, we developed a fusion approach to create a precise fire severity map by classifying the affected area into distinct severity classes. Thirdly, a separate fusion approach was developed utilizing the Normalized Difference Vegetation Index (NDVI), Radar Vegetation Index (RVI), and Modified Normalized Difference Vegetation Index (MNDVI) to classify and analyze the distribution of trees types before and after the wildfire, such as Schinus Molle, Handroanthus Heptaphyllus, Koelreuteria Bipinnata, and Platanus Racemose. The results showed a perfect 100%accuracy and Kappa Index in all the predictions. A percentage of 56.79% did not burn due to the topography of the Canyon creating natural firebreaks. Areas classified as low-severity (13.49%) showed minimal damage with minimal tree mortality. Moderate-to-low-severity areas (5.79%) represented regions with partial crown burn and some tree mortality. Moderate-to-high severity areas (3.57%) showed significant tree mortality. Finally, high-severity areas (20.36%), characterized by complete tree mortality and a significant loss of vegetation cover, were largely concentrated in specific sections of the canyon, likely influenced by factors such as slope and fuel type. These findings, corroborated by ground-truth data, provide valuable information for post-fire ecological recovery efforts and future land management strategies in Eaton Canyon and similar fire-prone landscapes.

Urban resilience in facing environmental hazards, especially air pollution, is one of the most significant challenges for metropolises. Isfahan city, given its dry and semi-dry climate, rapid population growth, and uncontrolled industrialization, is confronted with an air quality crisis and a reduction in per capita green space. This study aims to examine the relationship between the level of urban resilience, the severity of air pollution, and the role of urban green spaces in mitigating pollution effects in the metropolis of Isfahan.
In this regard, through field studies, air quality monitoring station data, satellite information on green coverage, and a review of scientific literature, an attempt has been made to analyze the strategic role of green spaces in improving urban resilience.
The investigations show that the average per capita green space in Isfahan is less than the global standard, and in some urban areas, this figure falls below 5 square meters. According to the results, green spaces play a key role in reducing pollution load by creating barriers to the transfer of suspended particles, absorbing pollutant gases, and moderating ambient temperature. Moreover, green spaces, as social gathering points and urban livability zones, increase psychological and social resilience against environmental crises.
The research methodology is a combination of qualitative methods and GIS, remote sensing data, and correlation analysis. The results indicate that increasing green space density in areas with higher population density and pollution has a direct effect on reducing the average suspended particles.
Finally, while proposing solutions such as revising Isfahan’s detailed urban plan, prioritizing the expansion of green spaces in critical areas, utilizing smart air quality monitoring technologies, and implementing spatial justice-based policies, it emphasizes that achieving an air pollution-resilient city is not possible without precise planning for green space development.