Sustainable Land Management Research Articles

Design and Implementation of Battery-Operated Brush Cutter with Improved DC Motor Control System

In this piece of academic work, an advanced battery-powered brush cutter with an intelligent DC motor control system is designed and optimized to address the limitations of conventional gasoline-powered tools in sustainable land management. The study focuses on the development, testing, and validation of a high-efficiency system that integrates a rechargeable lithium-ion battery pack and microcontroller-based pulse width modulation (PWM) for precise motor speed regulation. By replacing fossil fuel-dependent engines, the constructed design reduces carbon emissions by 92% and operational noise by 75%, offering an environmentally sustainable alternative for lawn, garden, and farmland maintenance. The system’s adaptive speed control enables users to dynamically adjust cutting power across diverse terrains, optimizing energy consumption while maintaining cutting precision. A robust battery management system (BMS) ensures safe operation by monitoring voltage, current, and temperature, extending battery lifespan and reliability. Prototype testing under real-world conditions demonstrated significant improvements in energy efficiency (35% reduction compared to traditional DC motor systems) and operational versatility. The project highlights the viability of leveraging locally sourced materials and reverse engineering to achieve scalable, cost-effective solutions for agro-industrial applications. This work not only advances brush cutter technology but also contributes to global sustainability goals by prioritizing zero direct emissions, reduced noise pollution, and user-centric innovation. Future research directions include modular battery-swapping mechanisms and solar hybridization to further enhance sustainability.

Soil Quality Prediction and Classification Using Machine Learning Algorithms

Soil quality assessment is critical for sustainable agriculture and land management, yet traditional methods lack scalability and efficiency. This study presents a novel Soil Quality Prediction and Classification (SQPC) framework that leverages advanced machine learning, including hybrid ensembles and deep learning models. Using a rich dataset of soil attributes—such as pH, nutrients, and texture—we apply automated feature engineering and dimensionality reduction (PCA, t-SNE) to enhance interpretability. Ensemble models like XGBoost and Stacked Generalization improve prediction accuracy, while a new Spatial-Aware Neural Network (SANN) incorporates geospatial data for localized insights. Our models achieve over 95% classification accuracy, with the SANN improving predictions by up to 10% in sparse data regions. Explainable AI tools (e.g., SHAP, LIME) enhance transparency, making outputs actionable for stakeholders. The framework also integrates transfer learning and adaptive algorithms for robust performance on small and evolving datasets. This research offers a scalable, interpretable approach to soil quality modelling, paving the way for real-time, data-driven decision support in agriculture and environmental policy.

Forest dynamics mapping in central Vietnam from 1988 to 2022 using Landsat time-series data

Abstract Forests provide essential ecosystem services, including biodiversity conservation, climate regulation, and livelihoods for millions of people worldwide. This study provides a comprehensive analysis of land-use and land-cover (LULC) changes with a focus on forest cover changes in Huế, central Vietnam, over the period from 1988 to 2022. Huế is a region of ecological and cultural significance, home to diverse forest ecosystems that play a critical role in water regulation, flood mitigation, and soil stabilization. The province’s forests also support rich biodiversity and provide vital resources for local livelihoods. By leveraging time-series Landsat observations and employing the continuous change detection and classification—spectral mixture analysis method, we synthesized multi-decadal geospatial data to track and categorize forest dynamics. The results indicate substantial LULC changes, highlighted by a significant reduction in stable forest cover from 58.3% in 1993 to 48.9% in 2022, accompanied by an increase in degraded forests from 11.7% to 18.0%. Peak forest loss was recorded at 1.5% by the end of 2013. The study discusses economic expansion, infrastructure development, climate variability, and agricultural intensification as key drivers of forest cover change. The findings underscore the importance of sustainable land management practices and provide actionable insights to inform policy development, particularly in regions with complex socio-economic and ecological interactions.

Comparative Analysis of Microbiological Aspects in Forest and Agricultural Soils across Major Soil Orders of Haryana

This study evaluates and compares the microbiological properties of forest and agricultural soils across major soil orders (Inceptisols, Entisols, Aridisols, and Alfisols) in Haryana to assess the impact of land use on soil biological health. Surface soil samples were collected at five representative sites of each soil order, spanning districts including Sirsa, Hisar, Jind, Karnal, Ambala, Mahendergarh, and Bhiwani. Composite soil samples were prepared by mixing three randomly collected auger cores per site, avoiding disturbed or recently fertilized areas. Each sample was split: one part air-dried for physico-chemical analysis, the other kept moist for immediate microbiological assessment. Forest soils exhibited 83.78 µgNH4-N g h-1 higher urease activity vs. 38.36 µgNH4-N g h-1, 65.25 µg TPF/g/ h greater dehydrogenase activity (DHA) vs 27.13 µg TPF/g/ h, 937.60 µg PNP/g/h maximum alkaline phosphatase (APA) vs. 406.80 µgPNP/g/h, higher 383.89 mg kg-1 microbial biomass carbon (MBC) vs. 107.33 mg kg-1, and greater 88.82 mg kg-1 microbial biomass nitrogen (MBN) vs. 28.32 mg kg-1 compared to agricultural systems. Among soil orders, Inceptisols and Alfisols supported more diverse and active microbial communities compared to Aridisols and Entisols, indicating a strong relationship between inherent soil characteristics and microbial functionality. The study concludes that land use type and soil order collectively influence soil microbial dynamics, with forest ecosystems preserving higher microbial vitality. A novel observation in this investigation was the remarkably high enzymatic activity recorded in forest Alfisols, suggesting their exceptional potential for nutrient cycling and soil health preservation. These findings emphasize the need to incorporate soil biological indicators into sustainable land management practices in Haryana’s diverse agro-ecological settings.

Soil Conservation Measures Enhanced Soil Organic Carbon Storage Across China

ABSTRACTSevere soil erosion accelerates the depletion of soil organic carbon (SOC). While the role of soil conservation measures (SCMs) in mitigating erosion is well‐documented, their influence on SOC storage remains insufficiently synthesized. This study incorporates 846 datasets from 55 peer‐reviewed studies to evaluate the effects of SCMs on SOC storage across diverse regions of China, with a particular focus on underlying processes and controlling factors. Results show that SCMs implementation increased SOC content by an average of 3.17 g/kg—a 30.3% improvement compared to areas without SCMs. Biological measures (BMs) enhanced plant biomass input and root turnover, promoting SOC accumulation through increased organic matter supply and stabilization in aggregates. These mechanisms were especially effective in the Huang‐Huai‐Hai Region (HHR), Northern Arid and Semiarid Regions (NAS), Northeast China (NE), and the Sichuan Basin and its surrounding areas (SBS). Engineering measures (EMs) reduced surface runoff and erosion intensity, thereby minimizing SOC loss and promoting in situ retention, which dominated in the Yunnan–Guizhou Plateau (YGP) and Loess Plateau (LP). Combined EMs and BMs enhanced SOC sequestration by simultaneously reducing erosion and boosting organic matter inputs, proving most effective in the Middle‐Lower Yangtze Region (MYR) and Southern China (SC). The effectiveness of SCMs for SOC sequestration was modulated by multiple factors, including rainfall, slope, soil moisture content, soil depth, bulk density, and aggregate particle size, with soil moisture identified as the predominant driver. Our findings provide a scientific basis for implementing region‐specific conservation strategies to enhance carbon sequestration and promote sustainable land management.

Unravelling Landscape Evolution and Soil Erosion Dynamics in the Xynias Drained Lake Catchment, Central Greece: A GIS and RUSLE Modelling Approach

Understanding a catchment’s geomorphological and erosion processes is essential for sustainable land management and soil conservation. This study investigates the Xynias drained lake catchment in Central Greece using a twofold geospatial modelling approach that combines morphometric analysis with the Revised Universal Soil Loss Equation (RUSLE) to evaluate the area’s landscape evolution, surface drainage features, and soil erosion processes. The catchment exhibits a sixth-order drainage network with a dendritic and imperfect pattern, shaped by historical lacustrine conditions and the carbonate formations. The basin has an elongated shape with steep slopes, high total relief, and a mean hypsometric integral value of 26.3%, indicating the area is at an advanced stage of geomorphic maturity. The drainage density and frequency are medium to high, reflecting the influence of the catchment’s relatively flat terrain and carbonate formations. RUSLE simulations also revealed mean annual soil loss to be 1.16 t ha−1 y−1 from 2002 to 2022, along with increased erosion susceptibility in hilly and mountainous areas dominated by natural vegetation. In comparison to these areas, agricultural regions displayed less erosion risk. These findings demonstrate the effectiveness of combining GIS with remote sensing for detecting erosion-prone areas, informing conservation initiatives. Along with the previously stated results, more substantial conservation efforts and active land management are required to meet the Sustainable Development Goals (SDGs) while considering the monitored land use changes and climate parameters for future catchment management.

Insights into determinants influencing food security in the IGAD region of Eastern Africa

BackgroundFood security in the Intergovernmental Authority on Development (IGAD) region of Eastern Africa is affected by a complex interplay of climatic and non-climatic factors. This study explores the major determinants of food security in the region, including extreme climate events (droughts and floods), land use, population growth, food production, market dynamics, and political and economic stability.MethodsThe study employed a combination of descriptive and analytical approaches. Climatic data were derived from CHIRPS (1981–2023) to assess drought and flood patterns using the Standardized Precipitation Index (SPI). Non-climatic data, including population statistics, land availability, food production, trade data, and price trends, were sourced from FAOSTAT. The graphical data illustration, correlation analysis was conducted to examine the temporal patterns and relationships between food security determinants and outcomes such as cereal production, food prices, and undernourishment.ResultsFindings reveal that droughts and extreme wet conditions significantly impact food security outcomes across IGAD countries. Rainfall and arable land showed the strongest positive correlation with cereal production. However, despite vast land resources, countries like Sudan and South Sudan have not fully utilized their agricultural potential. Population growth, unbalanced trade policies, and limited investment in agriculture contribute to high food prices and undernutrition. The correlation analysis indicates that economic stability and population dynamics are key influencers of food production and accessibility. Urban–rural population imbalances and policy gaps further exacerbate food insecurity risks.ConclusionThis study highlights the urgent need for a multi-sectoral and regionally coordinated approach to enhance food security in the IGAD region. Strategies should focus on climate-resilient agriculture, sustainable land management, inclusive economic policies, and food system innovations. Regional cooperation, targeted investments, and context-specific policy interventions are essential to reduce vulnerability and achieve sustainable food security.

Runoff and Sediment Response to Different Fire Intensities in a Hyrcanian Mixed Broadleaved Forest Ecosystem

ABSTRACTWildfires are increasingly recognized as a critical driver of ecosystem degradation, with post‐fire hydrological and soil impacts posing significant threats to biodiversity, water quality, and long‐term land productivity. In fire‐prone regions, understanding how varying fire intensities exacerbate runoff and erosion is essential for guiding post‐fire recovery and sustainable land management. The loss of vegetation and changes in soil properties following fire events can significantly increase surface runoff and soil erosion. This study investigates the effects of varying fire intensities on runoff and sediment yield in the Kheyrud Educational Forest. Controlled burns were conducted at low, moderate, and high intensities, along with an unburned plot serving as the control. For each treatment, three replicate plots of 2 m2 were established. Runoff and sediments were measured over the course of 1 year under natural rainfall. In addition, key soil physical properties, including bulk density, penetration resistance, and particle size distribution (sand, silt, and clay fractions), were assessed to better understand the underlying mechanisms driving hydrological responses. The results revealed that bulk density and penetration resistance were lowest in the control and highest for the high‐intensity fire treatment. A significant correlation was observed between bulk density, penetration resistance, and both runoff and sediment production. However, no significant correlation was found between runoff and soil texture (sand, silt, and clay content). Fire intensity had a pronounced effect on runoff and sediment, with the lowest levels recorded in the control and low‐intensity fire treatment, and the highest in the high‐intensity fire treatment. The total annual erosion rates were 0.88, 1.10, 1.57, and 2.24 tons/ha/year for the control, low‐, moderate‐, and high‐intensity treatments, respectively. The study demonstrates that high‐intensity fires induce substantial changes in soil structure and vegetation cover, exacerbating runoff and sediment loss. To mitigate post‐fire soil degradation, proactive forest management strategies are essential. Preventive measures—such as reducing fuel loads (e.g., removing uprooted trees in beech stands), minimizing soil compaction and vegetation damage during logging operations, can help reduce the ecological impact of wildfires. These findings provide a scientific basis for adaptive management in fire‐prone forests, addressing urgent needs to balance ecological resilience and human activities in wildfire‐vulnerable landscapes.

Determinants of Land Use Change in Phonthong County, Phonxay District, Luang Prabang Province, Lao PDR

Land use change is a key global issue with significant impacts on human livelihoods and the environment. This study aims to identify the factors influencing land use change practices among local communities in Phonxay District, Luang Prabang Province, in the Northern Uplands of Lao P.D.R. A binomial logistic regression analysis was conducted to examine the determinants of land use change, based on data collected through structured interviews with 252 households in two villages. The questionnaire focused on demographic and economic characteristics, land tenure, physical conditions, and institutional factors. The results indicate that significant factors influencing land use change in Phonthong County include landholding size, product prices, access to quality extension services, distance, and household income. These variables were found to strongly influence local land use decisions. The findings suggest that demographic-economic characteristics, land tenure systems, physical factors, and institutional support all play a crucial role in shaping land use practices. To promote more sustainable land management in the Northern Uplands, policy measures should be tailored to the local context, encouraging communities to adopt responsible and sustainable land-use practices. This includes empowering local people to manage their village resources effectively and implementing context-specific policies that enhance sustainable land resource management

Deep Learning and Remote Sensing for Agricultural Land Use Monitoring: A Spatio-Multitemporal Analysis of Rice Field Conversion using Optical Satellite Images

Rice is a staple food for over half of the global population, making its production crucial for food security, especially in Indonesia, the world's third-largest rice consumer. Population growth and urban expansion have led to agricultural land conversion, necessitating efficient monitoring methods. Traditional approaches, such as area sample frameworks and tile surveys, are costly and time-consuming, prompting the need for remote sensing and deep learning solutions. This study utilizes medium-resolution Sentinel-1, Sentinel-2, and Landsat-8 optical satellite imagery from 2013 and 2021 to analyze land cover changes in West Bandung and Purwakarta Regencies, key agricultural regions in Indonesia. A deep learning model is developed to classify land cover, validated through ground-truth evaluation, and applied to assess spatio-multitemporal land use conversion, paddy field estimation, and conversion rates. Results show that deep learning models effectively classify land cover with high accuracy, revealing significant agricultural land loss due to urban expansion. This research contributes to artificial intelligence (AI)-driven land monitoring, particularly in tropical regions, and supports policymakers in sustainable food agriculture land management. The findings highlight the potential of integrating remote sensing and deep learning for cost-effective agricultural monitoring, ensuring food security and sustainable land use. Future research should explore higher-resolution imagery and advanced AI techniques to enhance predictive accuracy and decision-making.

Interactive Effects of Harvester Ant Nests and Abandoned Sheep Corrals on Soil Nutrient Dynamics and Vegetation in Semiarid Pastures

ABSTRACTSemiarid regions like the Negev Desert face significant challenges due to low precipitation, nutrient‐poor soils, and grazing‐induced land degradation. Traditional grazing practices, particularly sheep corrals, have created nutrient‐rich hotspots that have influenced soil nutrient dynamics and vegetation patterns for decades. Simultaneously, harvester ants (Messor spp.) act as ecosystem engineers, modifying soil properties and promoting biodiversity. However, the interplay between ant nests and abandoned sheep corrals in influencing soil and vegetation remains understudied. This study assessed the synergistic effects of harvester ant nests and abandoned sheep corrals on soil nutrient dynamics and vegetation characteristics in semiarid pastures. Using a factorial experimental design, we compared four treatment combinations: open spaces and corrals, with and without ant nests. Key variables measured included soil properties (e.g., pH, electrical conductivity [EC], nitrate, potassium, and sodium absorption ratio [SAR]), vegetation height, biomass, and species composition. Results revealed that harvester ant nests within corrals significantly mitigated salinity (reducing EC and SAR) and redistributed potassium, restoring soil properties closer to open‐pasture conditions. Vegetation shifts were evident, with taller cereals (Avena sterilis) dominating open areas with ant nests, while nutrient‐enriched corrals favored nitrophilous species such as Chenopodium murale. Despite these changes, plant biomass differences across treatments were not statistically significant. These findings highlight the potential of integrating harvester ants into ecological restoration strategies for degraded semiarid landscapes. By redistributing nutrients and seeds, reducing salinity, and supporting plant richness, harvester ants act as natural agents of restoration. This study underscores the importance of leveraging biotic interactions and traditional grazing practices for sustainable land management and ecosystem recovery in semiarid regions.

Role of Cover Crops in Mitigating Greenhouse Gas Emissions in Agricultural Systems

Agriculture is a significant contributor to global greenhouse gas (GHG) emissions, particularly carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). At the same time, it offers viable pathways for climate change mitigation through sustainable land management. This systematic literature review evaluates the potential of cover crops non-harvested plant species typically grown during fallow periods to reduce GHG emissions and support climate-smart agriculture. Cover crops influence GHG dynamics through multiple mechanisms, including carbon sequestration, biological nitrogen fixation, and reduced nitrate leaching. They also improve soil health by enhancing organic matter content, stabilizing soil structure, conserving water, and supporting beneficial microbial activity. Drawing from 80 peer-reviewed studies selected from an initial pool of 250, the review categorizes cover crops into leguminous and non-leguminous types. Legumes, such as clover and vetch, fix atmospheric nitrogen, decreasing the need for synthetic fertilizers and associated N₂O emissions. Non-leguminous species like rye and radish scavenge excess nutrients and improve carbon storage. Despite strong empirical support for their environmental benefits, the effectiveness of cover crops varies by species, soil type, climate, and management practices. In some cases, cover crops can even increase N₂O emissions under poorly drained or mismanaged conditions. Adoption of cover crops remains uneven, particularly in the Global South, due to financial, technical, and institutional barriers. Constraints include limited seed access, labor shortages, and lack of policy incentives. This review identifies key research gaps in understanding long-term effects, species mixtures, and cover crop performance under future climate scenarios. To scale adoption and maximize climate benefits, future efforts should focus on improving predictive models, expanding farmer training, and enhancing policy and financial support. Overall, cover crops present a promising, nature-based strategy for reducing agricultural emissions while enhancing soil health and resilience in the face of climate change.

Normative Pluralism and Socio-Environmental Vulnerability in Cameroon: A Literature Review of Urban Land Policy Issues and Challenges

African cities are experiencing rapid, unregulated growth, characterized by high land pressure and growing demand for housing and urban infrastructure. New arrivals often settle in vulnerable areas (wetlands, hills, flood) where land is cheaper and unregulated by public authorities. This type of settlement is accompanied by numerous land conflicts, exacerbated by the coexistence of formal and customary land tenure systems, which struggle to harmonize. In this context, public land regulation policies often remain centralized and ill-adapted, revealing their limitations in ensuring equitable and sustainable management of urban land. Faced with this gap, our systematic study explores the socio-environmental dynamics of this normative pluralism in land governance within Cameroonian cities. Our findings highlight the tensions and opportunities of this complex coexistence, which vary significantly according to city size (small, medium, and large), the colonial heritage (Francophone and Anglophone), and the dominant legal framework (civil law and common law). The analysis highlights the need to take into account historical, linguistic, and politico-administrative roots, which profoundly influence local forms of the institutionalization of normative pluralism and the associated socio-environmental vulnerabilities. This normative plurality underlines the importance of a hybrid system of land governance capable of integrating local specificities while ensuring land security for all. Future research will include comparisons with other African countries in order to understand transferable mechanisms for better land governance.

Evaluation of Land Suitability and Potential Development of Cardamom (Amomum compactum L.) in Padang Jaya Subdistrict, North Bengkulu Regency

Cardamom (Amomum compactum) is a high-value spice with significant applications in the pharmaceutical, food, and cosmetics industries. The increasing global demand makes cardamom a promising commodity for agricultural expan sion. However, limited information on land suitability in Padang Jaya Subdistrict poses a challenge to optimizing cultivation. This study aimed to map the land suitability classes for cardamom cultivation and assess the potential for cardamom development in Padang Jaya Subdistrict, North Bengkulu. The research involved in field surveys, soil sampling, laboratory analysis, and GIS-based land suitability evaluation using the FAO framework. Key parameters as sessed included rooting media, nutrient retention, slope, and climate condition in the past 10 years. The FAO classification system categorized land into four suitability classes, namely: S1 (high suitable), S2 (moderately suitable), S3 (marginally suitable), and N (not suitable). The result indicate the actual land suitability is predominantly S3nrnaeh and S2nrnaeh, with major limiting factors including rooting media, nutrient retention, nutrient availability, and slope. Land improvement efforts such as liming, organic matter applications, fertilization, and soil conservation techniques led to an increase in land suitability, with 62.3% of S3 land upgraded to S2 and 37.7% of S2 land reached S1. Furthermore, GIS-based analysis identified four land cover types suitable for extensification: mixed gardens, seasonal crops, plantations, and bare land, totaling 8,747.71 hectares. These findings provide valuable insights for optimizing land use planning, improving productivity, and promoting sustainable agricultural development. Integrating GIS and remote sensing in future studies could enhance land suitability assessments with a more refined spatial scale. The results also serve as a scientific reference for policymakers and farmers in designing sustainable land management strategies and minimizing environmental degradation.

Leveraging Artificial Intelligence for Land Use/Land Cover Change Detection to Improve Monitoring of the National Land Use Development Master Plan (NLUDMP) in the City of Kigali (CoK), Rwanda

This research introduces a novel AI-driven framework, the Convolution Sequential Segmentation Network (ConvSegNet), which integrates Convolutional Long Short-Term Memory (ConvLSTM) networks for sequential multi-scale feature extraction from multispectral airborne and satellite imagery. ConvSegNet enhances high-resolution Land Use and Land Cover Change Detection (LULCCD), particularly for monitoring urban expansion and agricultural encroachment in Kigali, Rwanda. Using multi-temporal satellite imagery from 2009, 2020, and 2024, this study offers a detailed analysis of spatial and temporal LULC dynamics, capturing subtle changes that conventional methods often miss. ConvSegNet’s integration of spatial and temporal dependencies improves the detection of land cover transformations, such as urban sprawl and agricultural encroachment into forested areas. A key innovation is its ability to distinguish previously undifferentiated land cover classes, such as built-up areas and road networks, which traditional models have struggled to classify. The model demonstrated high accuracy, achieving 92% for urban areas, 85% for agricultural land, and 75% for forested regions. The results show significant LULC changes: agricultural land decreased from 70.68% (1,419.52 km²) in 2009 to 60.92% (1,213.49 km²) in 2024, while built-up areas grew by 32.71%, means from 0.81% (16.09 km²) in 2009 to 3.46% (69.38 km²) in 2024. Forest cover declined by 202.23 km², from 16.42% (327.27 km²) in 2009 to 11.15% (222.92 km²) in 2024, indicating significant environmental degradation in the city of Kigali. Despite high classification accuracy, ConvSegNet showed limitations in detecting gradual land cover transitions, especially in forests affected by agricultural encroachment. This highlights the need for further model improvements, including higher temporal resolution data and additional spectral features. Overall, the study provides valuable insights for sustainable land management in Rwanda, supporting the National Land Use Development Master Plan (NLUDMP) with advanced AI tools for monitoring LULC changes, mitigating urban sprawl, and enhancing environmental conservation efforts.

Geospatial assessment of land use/land cover changes from feldspar exploitation in Zango-Daji, Nigeria

This study investigates the extent to which feldspar mining has altered land use/land cover (LULC) changes in Zango Daji, a topic underexplored in existing literature. These changes are linked to reduced agricultural productivity and increased conflicts over land rights. The Landsat imageries were used to assess the LULC changes as a result of artisanal mining of feldspar in the study area from 2002 to 2022. Online imageries obtained from archive of Global Land Cover Facility (GLCF) under the United States Geological Survey (USGS) were analyzed using Enhanced Thematic Mapper Plus (ETM+) of 2002, 2007 and 2012, and the Operational Land Imager (OLI) of 2017 and 2022. ArcMap 10.8 was used for the pre-processing and clipping of the area of interest, using both the administrative and local government maps. It was later used for visualization, calculation, processing and analysis of all the digital imageries. Four geospatial index maps of normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), normalized difference built-up index (NDBI), and dry bare soil index (DBSI) were generated between 2002 and 2022 at an interval of five years. The accuracy was enhanced using Google Earth imagery for validation. The results revealed that vegetation improved marginally after mining began, compared to the pre-mining era. Meanwhile, a year (2012) after artisanal mining began in 2011, water witnessed its peak stress. Dry bare soil and built-up have increased considerably since feldspar mining began in the area. The findings inform sustainable land management and conflict mitigation strategies in mining regions.

Tracking the Construction Land Expansion and Its Dynamics of Ho Chi Minh City Metropolitan Area in Vietnam

International industrial transfer has driven rapid construction land expansion in emerging metropolitan areas, posing challenges for sustainable land management. However, existing research has largely overlooked the spatiotemporal patterns and driving mechanisms of this expansion, particularly in Southeast Asian metropolitan regions. To address this gap, we focused on the Ho Chi Minh City metropolitan area, utilizing construction land data from GLC_FCS30D to analyze the dynamics of construction land expansion during this period. Findings indicated that: (1) Continuous expansion of construction land, with the expansion rate during 2010–2020 being five times that of 2000–2010; (2) The spatial pattern evolved from initial infilling development in urban cores to subsequent leapfrogging and edge expansion toward peripheral counties and transportation corridors; (3) The expansion of construction land occurred alongside substantial losses of wetland and cultivated land. Between 2000 and 2020, the conversion of cultivated land to construction land increased significantly, particularly during 2010–2020 when cultivated land conversion accounted for 93.76% of newly developed construction land. Wetland conversion also showed notable growth during this period, comprising 3.86% of total newly added construction land; (4) Foreign direct investment (FDI) served as the primary catalyst, while industrial park development and transport infrastructure projects functioned as secondary accelerants. This study constructed a framework to systematically analyze the global and local driving mechanisms of metropolitan land expansion. The findings deepen the understanding of land-use transitions in emerging countries and provide both theoretical support and policy references for sustainable land management.

Evaluation of Selected Soil Physical Properties in Oil Palm, Rubber, and Forest Land in Mukomuko Regency

This study investigates the influence of land use on soil physical properties and horizon thickness in Mukomuko Regency, Indonesia, to assess the impacts of agricultural practices on soil quality. Conducted between February and April 2020, the research utilized a nested design across four districts, with laboratory analyses performed at the Soil Science Laboratory, Bengkulu University. Land use types evaluated included oil palm, rubber, and natural forest. Variables measured comprised soil structure, horizon thickness, aggregate stability, bulk density (BD), texture, and organic carbon (C-organic). Statistical analysis (ANOVA, p < 0.05) revealed significant effects of land use on BD, C organic content, and soil texture, whereas aggregate stability was not significantly influenced by vegetation type or depth. Forest soils exhibited the highest C-organic content (5.78%) and lowest BD (0.82 g cm⁻³), contrasting with oil palm soils, which had the lowest C-organic content (4.22%) and highest BD (0.86 g cm⁻³). Texture analysis showed forest soils had higher sand (19.69%) and clay (50.20%) fractions, while rubber land had the highest silt content (57.59%). Soil physical properties generally declined with depth under rubber and oil palm but fluctuated in forest soils. These results suggest that vegetation type significantly affects soil quality, with forest ecosystems maintaining superior soil conditions compared to intensively managed agricultural systems. Adoption of sustainable land management practices is essential to mitigate soil degradation and enhance long-term productivity.

Geospatial Assessment of Soil Loss Using Revised Universal Soil Loss Equation (RUSLE) in the Dibrugarh District, Assam, India

Soil erosion is a critical global challenge, leading to the loss of fertile topsoil and contributing to decreased agricultural productivity, increased sedimentation in waterways, and ecosystem disruption. This environmental problem is more vulnerable in developing countries because of farmers' failure to restore degraded soil and nutrients. The depletion of soil is driven by extensive farming practices, land degradation, and various human activities that impact the environment. It is an emerging threat to sustainable land management in Dibrugarh District, Assam. This study uses the Revised Universal Soil Loss Equation (RUSLE) model, integrated with remote sensing and GIS, to quantify soil erosion that incorporates annual average rainfall, soil properties, topographic characteristics, and LULC as inputs to detect the soil erosion-prone areas. This study divides the whole Dibrugarh district into five soil erosion severity classes, i.e., very slight, slight, moderate, severe, and very severe. The results demonstrate that 91.147% of the area experiences very slight erosion (<2 t ha-1 yr-1) while severe erosion affects 0.148% and very severe erosion impacts 0.044% of the area, requiring urgent conservation efforts. Effective soil management and targeted conservation strategies are essential to mitigate erosion and ensure the region's long-term land productivity and environmental health.

Navigating between local visions and goals of national policies for sustainable land management in Ghana

ABSTRACT This study sought to understand the extent to which goals of national land policies are reflective of the visions of diverse land users for sustainable land management in northern Ghana. The study is qualitative and employs semi-structured interviews, a multi-stakeholder workshop, and document reviews, to unpack the synergies between national land policies and stakeholders’ visions for sustainable land management in northern Ghana. The study finds that national visions for sustainable land management diverge from local stakeholders’ visions and fail to capture the complexities of gendered land uses. The overall goal of the newly enacted Land Act 2020 coheres with the goals of the National Land Policy, although unlike the policy, the Act has provisions that could advance the quest to improve gendered land rights. It is concluded that the National Land Policy is obsolete and should be reviewed to reflect current land governance challenges and to provide guidance to future legislation on land management.