Search Results (1,121)

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

This study explores the interplay of climate vulnerability and social capital in two rural communities: Brajaballavpur, a high-climate-prone village in the Indian Sundarbans characterized by high ecological fragility, recurrent cyclones, and saline water intrusion affecting water access, livelihoods, and infrastructure; and Jemua, a low-climate-prone village in the land-locked district of Paschim Bardhaman, West Bengal, India, with no extreme climate events. A total of 85 participants (44 in Brajaballavpur, 41 in Jemua) were selected through purposive sampling. Using a comparative qualitative research design grounded in ethnographic fieldwork, data were collected through household interviews, Participatory Rural Appraisals (PRAs), Focus Group Discussions (FGDs), and Key Informant Interviews (KIIs), and analyzed manually using inductive thematic analysis. Findings reveal that bonding and bridging social capital were more prominent in Brajaballavpur, where dense horizontal ties supported collective action during extreme weather events. Conversely, linking social capital was more visible in Jemua, where participants more frequently accessed formal institutions such as the Gram Panchayat, local NGOs, and government functionaries that facilitated grievance redressal and information access, but these networks were concentrated among more politically connected individuals. The study concludes that climate vulnerability shapes the type, strength, and strategic use of social capital in village communities. While bonding and bridging ties are crucial in high-risk contexts, linking capital plays a critical role in enabling long-term social structures in lower-risk settings. The study contributes to both academic literature and policy design by offering a relational and place-based understanding of climate vulnerability and social capital. Full article

Achieving Sustainable Development Goals (SDGs) remains a critical global challenge. This study analyses the environmental priorities related to SDGs 12, 14, and 15—interlinked and focused on responsible production and consumption, life below water, and life on land respectively—reflected in political party manifestos from the 2019, 2022, and 2024 Portuguese general elections, assessing their alignment with the SDGs and broader European political ideologies. A content analysis reveals significant disparities in attention across these goals, with SDG 15 receiving greater prominence than SDGs 12 and 14. Findings highlight the influence of political ideology, showing left-wing parties emphasize all three SDGs more consistently than their right-wing counterparts. These results underscore the need for a more balanced and comprehensive political commitment to sustainability. By exploring the interplay between national and European political agendas, this research provides valuable insights for aligning environmental policies with the UN 2030 Agenda and fostering transformative change in sustainability governance. Full article

Rural revitalization, as a crucial strategic goal for rural development in contemporary China, encompasses multidimensional connotations and requirements. Following the establishment of the ‘three rights separation’ system in 2014, land transfer has increasingly assumed a vital role, demonstrating a close and complex intrinsic logical relationship with rural revitalization. To comprehensively analyze the diverse impacts of land transfer on rural revitalization as discussed in the literature, we employ a ‘goal–strategy–indicator–outcome’ analytical framework to conduct a meta-analysis and visual assessment of 131 cases drawn from 52 articles published over the past decade. We systematically explore the pathways by which land transfer impacts rural revitalization and validate the results using typical cases reported by the Ministry of Agriculture and Rural Affairs through Python 3.9 analysis. The findings reveal the following: (1) Land transfer generally exerts a positive impact on rural revitalization (81.7% of 107 cases). (2) It significantly boosts living standards (84% positive cases) and industrial prosperity (88.4% positive cases); rural cultural civilization shows 100% positive cases yet with statistically insignificant coefficients, while its impacts on ecological livability (60%) and effective governance (70.6%) are insignificant. (3) Among 12 indicators, those related to agricultural production and farmers’ livelihoods are positive, whereas those concerning rural ecology and governance are negative. This study indicates that land transfer plays a key role in the rural revitalization strategy, but the ecological impacts and governance challenges that it presents require ongoing attention and optimization at the policy level. Full article

As shared micromobility grows quickly in metropolitan settings, e-scooter safety issues have become more urgent. This paper uses a Bayesian hierarchical model applied to census block groups in several Texas metropolitan areas to construct a spatial risk assessment methodology for e-scooter crashes. Based on crash statistics from 2018 to 2024, we develop a severity-weighted crash risk index and combine it with variables related to land use, transportation, demographics, economics, and other factors. The model comprises a geographically structured random effect based on a Conditional Autoregressive (CAR) model, which accounts for residual spatial clustering after capture. It also includes fixed effects for covariates such as car ownership and nightlife density, as well as regional random intercepts to account for city-level heterogeneity. Markov Chain Monte Carlo is used for model fitting; evaluation reveals robust spatial calibration and predictive ability. The following key predictors are statistically significant: a higher share of working-age residents shows a positive association with crash frequency (incidence rate ratio (IRR): ≈1.55 per +10% population aged 18–64), as does a greater proportion of car-free households (IRR ≈ 1.20). In the built environment, entertainment-related employment density is strongly linked to elevated risk (IRR ≈ 1.37), and high intersection density similarly increases crash risk (IRR ≈ 1.32). In contrast, higher residential housing density has a protective effect (IRR ≈ 0.78), correlating with fewer crashes. Additionally, a sensitivity study reveals that the risk index is responsive to policy scenarios, including reducing car ownership or increasing employment density, and is sensitive to varying crash intensity weights. Results show notable collision hotspots near entertainment venues and central areas, as well as increased baseline risk in car-oriented urban environments. The results provide practical information for targeted initiatives to lower e-scooter collision risk and safety planning. Full article

This study introduces Edible Streets as a distinct and scalable model of community-led urban food growing, specifically investigating the drivers and barriers to the initiative. Unlike traditional urban food-growing initiatives, Edible Streets explores the integration of edible plants into street verges and footpaths with direct community involvement of the people who live/work in a street. This study contributes new knowledge by evaluating Edible Streets through the COM-B model of behavioural change, through policy and governance in addition to behaviour change, and by developing practical frameworks to facilitate its implementation. Focusing on Oxford, the research engaged residents through 17 in-person interviews and 18 online surveys, alongside a stakeholder workshop with 21 policymakers, community leaders, and NGO representatives. Findings revealed strong motivation for Edible Streets, driven by values of sustainability, community resilience, and improved well-being. However, capability barriers, including knowledge gaps in gardening, land-use policies, and food preservation, as well as opportunity constraints related to land access, water availability, and environmental challenges, hindered participation. To address these, a How-to Guide was developed, and a pilot Edible Street project was launched. Future steps include establishing a licensing application model to facilitate urban food growing and conducting a Post-Use Evaluation and Impact Study. Nationally, this model could support Right to Grow policies, while globally, it aligns with climate resilience and food security goals. Locally grown food enhances biodiversity, reduces carbon footprints, and strengthens social cohesion. By tackling key barriers and scaling solutions, this study provides actionable insights for policymakers and practitioners to create resilient, equitable urban food systems. Full article

The accurate mapping of crop planting patterns is vital for sustainable agriculture and food security, particularly in regions with complex cropping systems and limited cloud-free observations. This research focuses on the Jianghan Plain in southern China, where diverse planting structures and persistent cloud cover make consistent monitoring challenging. We integrated multi-temporal Sentinel-2 and Landsat-8 imagery from 2017 to 2021 on the Google Earth Engine platform and applied a sample migration strategy to construct multi-year training data. A random forest classifier was used to identify nine major planting patterns at a 10 m resolution. The classification achieved an average overall accuracy of 88.3%, with annual Kappa coefficients ranging from 0.81 to 0.88. A spatial analysis revealed that single rice was the dominant pattern, covering more than 60% of the area. Temporal variations in cropping patterns were categorized into four frequency levels (0, 1, 2, and 3 changes), with more dynamic transitions concentrated in the central-western and northern subregions. A multiscale geographically weighted regression (MGWR) model revealed that economic and production-related factors had strong positive associations with crop planting patterns, while natural factors showed relatively weaker explanatory power. This research presents a scalable method for mapping fine-resolution crop patterns in complex agroecosystems, providing quantitative support for regional land-use optimization and the development of agricultural policies. Full article

Understanding forest-cover change and its drivers is vital for global forest management and policy development. This study analyzed perceptions of historical drivers behind land-use/land-cover change (LULCC) and forest change in gazetted forests from 1966 to 2022 to evaluate the impact of human activities around the gazetted forest reserves, comparing three forests in Nasarawa State, North Central Nigeria. Data were collected through questionnaires, interviews, and focus group discussions. Three gazetted forests (Doma, Risha, and Odu) were sampled to represent the three geopolitical zones of the state. SPSS IBM version 29, NVivo 1.7, and Python 3 were used for data analyses to generate statistics and identify coherent themes across the forests. Results show that changes were perceived to be triggered by sixteen drivers (direct and indirect) related to social, economic, environmental, policy/institutional, and technological elements. Agricultural expansion, lumbering, and charcoal production were the most reported direct drivers, while population growth, poverty, and government policies were the most perceived indirect drivers. The results showed variations in human activities across forest sites. For example, agricultural expansion, lumbering, and grazing were more widespread, while construction and settlement activities differed between forests. The Risha forest community saw agriculture expansion ahead of other drivers, Doma forest people saw population growth above other drivers, and the Odu forest community saw lumbering aiding other drivers that led to change. Implementation of policies focusing on these key drivers must match local perceptions and priorities to engage people in forest conservation. These efforts could ensure effective forest protection that is vital for achieving global biodiversity and climate targets and safeguarding local livelihoods. The specific drivers of changes in each forest need to be targeted in conservation efforts. Full article

Lifestyle blocks (LBs) are small rural holdings primarily used for residential and recreational purposes rather than commercial farming. Despite the rapid expansion of LBs over the last 25 years, which has been driven by lifestyle amenity preference and land subdivision incentives, their environmental performance remains understudied. This is the case even though their proliferation is leading to an irreversible loss of highly productive soils and accelerating land fragmentation in peri-urban areas. Through undertaking a systematic literature review of relevant studies on LBs in New Zealand and comparable international contexts, this paper aims to quantify existing knowledge and suggest future research needs and management strategies. It focuses on the environmental implications of LB activities in relation to water consumption, food production, energy use, and biodiversity protection. The results indicate that variation in land use practices and environmental awareness among LB owners leads to differing environmental outcomes. LBs offer opportunities for biodiversity conservation and small-scale food production through sustainable practices, while also presenting environmental challenges related to resource consumption, greenhouse gas (GHG) emissions, and loss of productive land for commercial agriculture. Targeted landscape design could help mitigate the environmental pressures associated with these properties while enhancing their potential to deliver ecological and sustainability benefits. The review highlights the need for further evaluation of the environmental sustainability of LBs and emphasises the importance of property design and adaptable planning policies and strategies that balance environmental sustainability, land productivity, and lifestyle owners’ aspirations. It underscores the potential for LBs to contribute positively to environmental management while addressing associated challenges, providing valuable insights for ecological conservation and sustainable land use planning. Full article

Karst mountain areas, as complex geological systems formed by carbonate rock development, possess unique three-dimensional spatial structures and hydrogeological processes that fundamentally influence regional ecosystem evolution, land resource assessment, and sustainable development strategy formulation. In recent years, through the implementation of systematic ecological restoration projects, the ecological degradation of karst mountain areas in Southwest China has been significantly curbed. However, the research on the fine-grained land use mapping and quantitative characterization of spatial heterogeneity in karst mountain areas is still insufficient. This knowledge gap impedes scientific decision-making and precise policy formulation for regional ecological environment management. Hence, this paper proposes a novel methodology for land use mapping in karst mountain areas using very high resolution (VHR) remote sensing (RS) images. The innovation of this method lies in the introduction of strategies of geographical zoning and stratified object extraction. The former divides the complex mountain areas into manageable subregions to provide computational units and introduces a priori data for providing constraint boundaries, while the latter implements a processing mechanism with a deep learning (DL) of hierarchical semantic boundary-guided network (HBGNet) for different geographic objects of building, water, cropland, orchard, forest-grassland, and other land use features. Guanling and Zhenfeng counties in the Huajiang section of the Beipanjiang River Basin, China, are selected to conduct the experimental validation. The proposed method achieved notable accuracy metrics with an overall accuracy (OA) of 0.815 and a mean intersection over union (mIoU) of 0.688. Comparative analysis demonstrated the superior performance of advanced DL networks when augmented with priori knowledge in geographical zoning and stratified object extraction. The approach provides a robust mapping framework for generating fine-grained land use data in karst landscapes, which is beneficial for supporting academic research, governmental analysis, and related applications. Full article

Water scarcity remains critical in Rwanda’s Eastern Savanna Agroecological Zone due to erratic rainfall, prolonged dry seasons, and rising water demands. This challenge threatens agricultural productivity, food security, and livelihoods. Stormwater harvesting presents a sustainable solution that increases water availability and mitigates the impacts of climate variability. This study utilizes Geographic Information System (GIS) tools and SCS-CN to assess stormwater harvesting potential in the region. The methodology includes analyzing land use, soil type, rainfall data (30 years, from 1994 to 2023), and topography. Key research steps involve delineating catchment areas, estimating runoff volumes, and selecting optimal storage sites using multi-criteria decision analysis. Findings include eight main water reservoirs, each with a unique code (W_R1 to W_R8), geographic coordinates (X and Y), and 10 million cubic meters storage volumes. W_R1 has the smallest volume at 0.242 × 10⁶ m³, while W_R2 has the largest volume at 8.51 × 10⁶ m³. W_R3, W_R5, and W_R7 are additional noteworthy reservoirs with sizable capacities. The findings contribute to policy formulation and Sustainable Development Goals (SDGs) related to clean water, food security, and climate action. This research provides a replicable framework for addressing water scarcity and enhancing long-term resilience in water-stressed regions. Full article

Valuation of ecosystem services (ESs) is crucial for understanding the benefits provided by ecosystems and informing sustainable management and policy decisions related to ecosystem protection. This study explores the disagreements in ecosystem service value (ESV) at the county level across China in 2020 by comparing ten land cover datasets of varying resolutions from 500 to 10 m, using the equivalent factor method. Significant disagreements in ESV estimates are identified, revealing spatial heterogeneity and large inconsistencies among estimates from different datasets, even with high spatial resolution (10 m). Across all counties, the typical discrepancy in ESV estimates between any two datasets reaches 3503 CNY/ha, and the ESV estimates for each county show an average coefficient of variation (CV) of 0.186 across the ten datasets, indicating considerable inconsistency attributable to dataset selection. The results highlight that ESV evaluations based on the CLCD, Globeland30, and GLC-FCS30 datasets demonstrate higher consistency and reliability, making them suitable for regional ecosystem service valuation. Both the landscape configurations and the area disparities of different land types have significant impacts on ESV disagreement. This study provides valuable insights into the applicability of different datasets for ESV evaluation, thereby enhancing the reliability of ESV assessments and supporting informed decision making in ecosystem management. Full article

Urbanization is rapidly transforming cities, especially in the Global South, with Sub-Saharan Africa expected to see the fastest growth in the next 30 years. In South Africa’s Mopani District, this urban expansion has led to the growth of informal settlements, increasing disaster risks related to water, health, and fire. This study focuses on Giyani Local Municipality, examining disaster risks in its informal settlements and the factors influencing the implementation of spatial planning tools. Using a SWOT analysis combined with the Analytical Hierarchy Process (AHP), the study found that while the municipality has strong land use and disaster management policies, poor enforcement, lack of integration, and weak governance limit their effectiveness. Opportunities for improvement include securing grants from the National Government and Disaster Management Centre to support disaster risk reduction (DRR) initiatives. However, challenges such as land shortages and ecological degradation threaten sustainable planning. The findings provide important insights for policymakers, urban planners, and disaster management professionals. The SWOT-AHP approach helps in prioritizing resource allocation, identifying risk trends, and focusing on key areas for mitigation. Overall, the study supports efforts to enhance resilience and promote sustainable urban development in informal settlements through better spatial planning. Full article

The construction of a fence in the sea made of bamboo sticks along the coastal areas of Tangerang, Indonesia, caused controversy and many public debates in most Indonesian media. The case is, however, not unique. It provides a means to pose three questions related to the following topics: (1) which controversies and contradictions between formal procedures and informal practices related to land and sea rights exist; (2) which values and perceptions of the involved stakeholders play a role in these controversies and contradictions; and (3) which kinds of boundary work or boundary objects could resolve these controversies and contradictions. The theoretical embedding for the subject lies in the theories of territory and space on the one hand and formal institutional models of land and sea on the other. The analytical model used to evaluate the controversies and contradictions is McKinsey’s 7S model, while the data used are extracted from journalistic public media reports and social media. The results show a significant discrepancy between the values connected to formal and informal territorial claims, as well as a lack of enforcement capacity to address this discrepancy. Instead, the policy response exhibits an excessive and uncontrolled discretionary space for all stakeholders to pursue their own interests. The theoretical novelty is that institutional models governing territorial sea and land rights, restrictions and responsibilities need to be aligned and connected based on detecting where and how the values of affected stakeholders can be harmonized, rather than enforcing a unilateral system of values of disconnected systems (of either land or sea). The policy implementation implications are to create stricter procedural steps when providing building permits in coastal areas, with better enforcement and stricter control. Soft governance campaigns should raise awareness of what is allowed and required for coastal building permits and reclamations. Additionally, there could be quicker, more thorough inspections of emerging or hidden practices of non-approved fencing and non-approved occupation of coastal land and sea. Full article

This study analyzes the integration of Sustainable Development Goals (SDGs) 9 (Industry, Innovation, and Infrastructure) and 15 (Life on Land) into the tourism development strategies of Lago Agrio Canton, Sucumbíos Province, Ecuador. The main objective is to assess how tourism can serve as a driver for sustainable infrastructure development, environmental conservation, and inclusive local growth, in alignment with the 2030 Agenda. A qualitative methodology was adopted, involving documentary analysis with exploratory and descriptive scopes. The sources included national development plans, regional policy frameworks, institutional reports, and the relevant academic literature. This study employed territorial indicators related to infrastructure quality, ecosystem protection, and stakeholder participation to evaluate SDG alignment. The results highlight that sustainable tourism practices—particularly those incorporating corporate social responsibility and environmental stewardship—can stimulate innovation and enhance resilience in underdeveloped territories. Wetlands and forested areas emerge as key natural assets with strong potential for ecological tourism and sustainable investment. The findings suggest that collaborative actions between the public and private sectors, guided by SDGs 9 and 15, can generate long-term benefits, including biodiversity preservation, improved service infrastructure, and economic inclusion for local communities. Overall, the research underscores the potential of sustainable tourism as a practical mechanism for localizing the SDGs in fragile yet high-value ecological regions. Full article