Land Use Planning Research Articles

"Assessing Urban Transformation and Land-Use Dynamics in Unplanned Settlements: Case Studies of 10 No. Market and Bittan Market

- Unplanned settlement areas, such as '10 No. Market' and 'Bittan Market,' highlight the dynamic transformation of urban zones due to rapid population growth, economic activities, and shifting societal demands. Initially planned as low-density residential neighborhoods, these areas have evolved into bustling commercial hubs, exposing the disconnect between land-use planning and actual urban development. This study examines the key drivers behind these changes, including population growth, economic incentives, cultural shifts, and regulatory gaps. Through surveys, interviews, historical analysis, and geospatial data, the research identifies both the positive impacts—such as enhanced local economies and improved access to goods—and the negative consequences, including traffic congestion, inadequate infrastructure, and environmental degradation. The study reveals a mismatch between planned intentions and reality, emphasizing the importance of adaptive urban planning frameworks. The paper recommends integrated land-use planning, zoning flexibility, infrastructure upgrades, community engagement, and sustainability initiatives as strategies for mitigating the adverse effects of uncontrolled commercialization. The findings underscore the necessity of resilient, flexible urban policies to address the complexities of fringe area development and ensure a balance between economic growth, environmental sustainability, and residents' quality of life. Key Words: urban transformation, mixed-use development, informal zoning, infrastructure strain, fringe areas, adaptive planning

Investigation of Spatio-Temporal Simulation of Mining Subsidence and Its Determinants Utilizing the RF-CA Model

It is important to carry out timely scientific assessments of surface subsidence in coal resource cities for ecological environmental protection. Traditional subsidence simulation methods cannot quantitatively describe the driving factors that contribute to or ignore the dynamic connections of subsidence across time and space. Thus, a novel spatio-temporal subsidence simulation model is proposed that couples random forest (RF) and cellular automaton (CA) models, which are used to quantify the contributions of driving factors and simulate the spatio-temporal dynamic changes in subsidence. The RF algorithm is first utilized to clarify the contributions of the driving factors to subsidence and to formulate transformation rules for simulation. Then, a spatio-temporal simulation of subsidence is accomplished by combining it with the CA model. Finally, the method is validated based on the Yongcheng coalfield. The results show that the depth–thickness ratio (0.242), distance to the working face (0.159), distance to buildings (0.150), and lithology (0.147) play main roles in the development of subsidence. Meanwhile, the model can effectively simulate the spatio-temporal changes in mining subsidence. The simulation results were evaluated using 2021 subsidence data as the basis data; the simulation’s overall accuracy (OA) was 0.83, and the Kappa coefficient (KC) was 0.71. This method can obtain a more realistic representation of the spatio-temporal distribution of subsidence while considering the driving factors, which provides technological support for land-use planning and ecological and environmental protection in coal resource cities.

Predicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques

This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies. Landsat images from various sensors (TM, OLI) were employed for supervised classification, attaining high accuracy (> 90%). Historical LULC changes from 1994 to 2024 were analyzed, revealing significant transformations in Lahore. The build-up area expanded by 359.8 km², indicating rapid urbanization, while vegetation cover decreased by 198.7 km² and barren lands by 158.5 km². Water bodies remained relatively stable during this period. Future LULC trends were projected for 2034 and 2044 using the CA-Markov hybrid model (CA-MHM), which achieved a high prediction accuracy with a kappa coefficient of 0.92. The research indicated significant urban growth at the expense of vegetation and barren land. Future forecasts suggest ongoing urbanization, underscoring the necessity for sustainable land management techniques. This research is a significant framework for urban planners, providing insights that combine development with ecological conservation. The results highlight the necessity of incorporating predictive models into urban policy to promote sustainable development and environmental preservation in quickly changing areas such as Lahore.

The Role of Agrarian Law in Urban Spatial Planning and Regional Development in South Sulawesi: a Contribution to Achieving SDGs 11

Objectives: The rapid development of Makassar City and other cities in South Sulawesi Province has intensified the critical issue of spatial planning (land use) in urban areas. If not addressed early, this could lead to sharper social conflicts and other societal problems. Ineffective implementation of spatial planning and poor supervision of land allocation exacerbate these challenges, highlighting the risk of increasing social disparities. Method: This explanatory research employs a survey approach. Quantitative data from primary sources were used to test research hypotheses, while qualitative data from secondary sources were analyzed to complement descriptive insights. Descriptive analysis was applied to secondary data, and multiple regression analysis was conducted on primary data using a statistical analysis system (SAS) to process research variables relevant to the objectives. Results and Discussion: The study finds that urban development patterns in South Sulawesi Province have been less than optimal due to a lack of synchronization with Provincial and Regency/City Urban Spatial Planning Plans. The research underscores the need for an integral institution with full authority over land use to enhance urban area development. Key factors positively influencing urban development patterns include legal substance, legal structure, legal culture, facilities and infrastructure, and legal awareness. Research Implications: The study emphasizes the necessity of an integrated institutional framework to streamline urban spatial planning, reduce social disparities, and promote sustainable development. The findings align with United Nations Sustainable Development Goals (SDGs), particularly Goal 11 (Sustainable Cities and Communities) by addressing inclusive urban development and strengthening governance frameworks. Originality/Value: This research provides a unique perspective by analyzing the intersection of legal frameworks and urban spatial planning, focusing on the role of legal culture and institutional integration in addressing land use challenges in South Sulawesi.

Использование B-сплайнов для выравнивания данных спутниковой геолокации о высоте рельефа

The possibility of constructing analytical models of terrain elevation is studied with mathematical apparatus of B-splines based on satellite geolocation data. For constructing regression models the main nodes of splines are chosen independently of measurements. An algorithmic approach is discussed to avoid degenerate cases, which may arise from this selection. B-splines can be used to create more accurate digital elevation models; their applications in practical field are land-use planning, disaster risk management and mapping, operational visualization of more accurate geofield data. The presented method of assigning spline boundary nodes, allows excluding the effect of over fitting, usually occurring when the number of spline knots is comparable to that of measurements. Calculations are performed due to the data obtained with the help of mobile application developed by the authors

Zoning and urban restructuring: long-term change in the location of manufacturing in industrialised city-regions

ABSTRACT This paper responds to the lack of longitudinal research on the role of urban planning in mediating broader processes of economic restructuring in industrialised city-regions. Our research tracks the location of manufacturing activity against industrial zoning changes from the 1950s to the 2020s within the Melbourne metropolitan region of Victoria, Australia. We find consolidation in established middle suburbs rather than greenfield areas, and evidence that land-use planning mediated this geography. By taking a long-run view, our study highlights the consequences of land-use planning for future urban economic development in a context where many city-regions face critical industrial land shortages.

Patch-Level and Neighborhood-Dependency Spatial Optimization Method (PNO): Application to Urban Land-Use Planning to Facilitate Both Socio-Economic and Environmental Development in Beijing

Rapid urban expansion and chaotic urban land-use patterns cause many socio-economic and environmental issues, e.g., traffic congestion and urban heat islands; thus, scientific planning considering land-use trade-offs and layout optimization is highly required for resolving these issues, especially in the urban renewal stage. However, previous spatial optimization methods were weak in processing land-use patches and ignored their neighborhood dependency, leading to fragmented and inapplicable optimization results. Accordingly, this study proposes a patch-level and neighborhood-dependency spatial optimization method (PNO) to adjust urban land-use patterns considering multiple optimization targets (i.e., improving population and economy but controlling land surface temperature). The PNO represents land-use patterns in a graph structure, quantifies land-use patterns’ impacts on the population, economy, and land surface temperature, defines the spatiotemporal constraints of land-use optimization considering neighborhood-dependency and optimization sequences, and finally optimizes land uses and their spatial layouts based on a multi-objective genetic algorithm. Experiments were conducted in the urban area of Beijing, and the results suggested that, after optimization, the population and GDP can be improved by 667,323 people (4.72%) and USD 10.69 billion in products (2.75%) in the study area; meanwhile, the land surface temperature can be reduced by 0.12 °C (−0.32%). Through comparison, the proposed PNO outperforms previous spatial optimization methods, e.g., NSGA-II, in processing land-use patches as well as their neighborhoods. Taking the land-use map in 2022 as a reference, the PNO optimization results are more consistent with actual land-use changes (consistency of 25%), compared to the existing spatial optimization results (consistency of 10.6%). Thus, PNO is more applicable to land-use planning in urban renewal circumstances.

Dynamic simulation of landscape ecological risk in Gansu’s farming-pastoral ecotone based on topographic gradients

The farming-pastoral ecotone in Gansu Province, a crucial green barrier in northwestern China, faces a conflict between economic development and environmental fragility. Scientifically assessing the landscape ecological risks in this region is essential for developing an early warning system for ecological security and ensuring the sustainable management of regional ecosystems. This study systematically analyzes the dynamic evolution patterns and clustering characteristics of landscape ecological risk along the topographic gradient in the area, using Land-Use and Land-Cover Change (LUCC) data from five periods (each period representing 10 years) between 1980 and 2020, as well as Digital Elevation Model (DEM) data. Methods such as CA-Markov and the Topographic Position Index (TPI) were employed to assess these risks. Additionally, the study simulates the spatial distribution patterns of ecological risks in future years. The results reveal that from 1980 to 2020, the area of built-up land in the farming-pastoral ecotone of Gansu Province increased by approximately 82%, with roughly 21% of the expansion occurring at the expense of grasslands and 53% from arable land. Ecological risk in the study area exhibits a spatial distribution pattern characterized by lower risk in the southwest and higher risk in the northeast. Overall, ecological risk initially increased and then decreased. The area of high-risk zones has steadily decreased by approximately 50% since 2010, primarily in regions with low topographic gradients and high human activity. In other areas, high-risk levels are directly proportional to the topographic gradient, showing a high degree of spatial clustering. Consequently, land-use planning should be tailored to local conditions, and a long-term monitoring mechanism should be established. This study provides novel insights into the spatiotemporal changes in landscape ecological risk in ecologically vulnerable areas, focusing on topographic gradients.

Exploring the Transmission Process of Carbon Sequestration Services and Its Applications: A Case Study of Hainan

The pressing need to address climate change and advance global sustainable development has heightened the emphasis on ecosystem services, especially carbon sequestration. This research assesses the supply and demand dynamics of carbon sequestration services on Hainan Island, China, highlighting its significant contributions to global biodiversity conservation and carbon balance. The analysis considers the spatial distribution and interrelation of these services in light of recent land use and ecological policy changes. The methodology incorporates land use and land cover data, the Normalized Difference Vegetation Index (NDVI), meteorological data, and soil data. A gravity model is employed to elucidate the supply–demand relationship for carbon sequestration services, examining the flow across different regions and identifying spatial connections and their intensities. The results indicate a notable increase in carbon sequestration supply in Hainan from 2000 to 2020, particularly in the central mountainous areas. Conversely, the demand for these services has risen, especially in the northern plains’ urban areas and southern coastal towns. The gravity model reveals a strong spatial interdependence between the central mountainous supply zones and the high-demand urban locales. This study underscores the disparities in carbon sequestration supply and demand on Hainan, emphasizing the need for the strategic management of these elements. It provides critical data for ecological compensation policies and offers insights into the roles of regional ecosystems in climate change mitigation. The research highlights the necessity of incorporating ecosystem services into land-use planning and decision-making to foster sustainable development and strengthen climate resilience.

Combining local monitoring data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats

ContextPromoting grassland habitat networks within agricultural landscapes is essential for supporting biodiversity. However, the characteristics of these networks are often poorly documented, making it difficult to prioritize conservation strategies and effectively protect grassland-dependent species.ObjectivesWe set to identify conservation priorities for (semi)natural grasslands by assessing habitat network characteristics based on a combination of monitoring data and scientific model output for European Ground Squirrel (EGS), a keystone grassland specialist, in agricultural settings of northern Serbia.MethodsWe used the spatially explicit model, LARCH, to determine the current habitat networks and available monitoring data on presence/absence and habitat suitability together with Circuitscape to better understand the characteristics of those networks. The combination of modeling results and monitoring data was used to prioritize conservation measures for each network to support a stable and viable EGS metapopulation.ResultsWe identified 15 habitat networks. Our analysis showed that two of these need no interventions, but most of them need a mix of improving habitat quality and connections within and between the networks to support local populations and the metapopulation overall.ConclusionsResults revealed areas in which spatial adaptation measures (e.g., grassland restoration and corridor development) should be deployed to accommodate the long-term survival of EGS. It might be considered to stop conservation efforts in some abandoned networks as the network characteristics are too poor, and resources should be used to improve habitat networks that are still occupied. Our findings may guide the conservation of (semi)natural grasslands and future sustainable land-use planning in intensively farmed landscapes.

The Impact of Agricultural Land Reclamation and Conversion on Farmers' Livelihoods: A Case Study of the Thai Nguyen Stadium Project in Phuc Trieu Commune, Thai Nguyen City, Thai Nguyen Province

This study focuses on evaluating the impacts of agricultural land reclamation and conversion on the livelihoods of households affected by the Thai Nguyen Stadium Project in Phuc Trieu Commune, Thai Nguyen City. The research employed a combination of methods, including information collection through literature review and interviews with households whose agricultural land was reclaimed. Collected data were synthesized to analyze and evaluate the economic conditions of farming households post-reclamation. Statistical analysis and comparative methods were applied to examine changes in key indicators, such as employment and income, before and after the reclamation and conversion of agricultural land in the study area. The findings reveal that the project has had significant impacts on the lives of local residents. Specifically, the reclamation and conversion of agricultural land have altered the labor structure, employment opportunities, and income levels of the affected population. These results provide a basis for proposing necessary measures to enhance the effectiveness of land-use planning and management in the local context.

Predicting Soil Salinity Based on Soil/Water Extracts in a Semi-Arid Region of Morocco

Soil salinity is a major constraint to soil health and crop productivity, especially in arid and semi-arid regions. The most accurate measurement of soil salinity is considered to be the electrical conductivity of saturated soil extracts (ECe). Because this method is labor-intensive, it is unsuitable for routine analysis in large soil sampling campaigns. This study aimed to identify the best models to estimate soil salinity based on ECe in relation to a rapid electrical conductivity (EC) measurement in soil/water (referred to as S:W henceforward) extracts. We evaluated the relationship between ECe and the ECS:W extract ratios (1:1, 1:2, and 1:5) in salt-affected soils from the semi-arid Sehb El Masjoune region of Morocco. The soil salinity in this region is 0.5 to 235 dS/m, as determined by the ECe method. A total of 125 soil samples, from topsoil (0–15 cm) and subsoil (15–30 cm) with mainly fine to medium textures, were analyzed using linear, logarithmic, and second-order polynomial regression models. The models included all samples or grouped samples according to soil texture (fine, medium) or specific textural classes. The mean ECe values were 2.6, 3.1, and 7.9 times greater than the EC of 1:1, 1:2, and 1:5 S:W extracts, respectively. Polynomial regression models had the best predictive accuracy, R2 = 0.98, and the lowest root mean square error of 10.6 to 10.7 dS/m for the ECS:W extract ratios of 1:5 and 1:2. The polynomial models could represent the non-linear relationships between ECe and salinity indicators, especially in the 80–170 dS/m salinity range, where other models typically underestimate the salinity. These results confirm that advanced regression techniques are suitable for predicting soil salinity in a salt-affected semi-arid region. The site-specific models outperformed previously published models, because they consider the spatial variability and heterogeneity of the salinity in the study area explicitly. This confirms the importance of calibrating soil salinity models according to the local soil and environmental conditions. Consequently, we can undertake soil salinity assessments in hundreds of samples by using the simple, rapid ECS:W extraction method as a direct indicator of EC and extrapolate to ECe with a polynomial regression model. Our approach enables the widespread soil salinity assessments that are needed for land-use planning, irrigation management, and crop selection in salt-affected landscapes.

Assessing Vegetation Canopy Growth Variations in Northeast China.

Studying climate change's impact on vegetation canopy growth and senescence is significant for understanding and predicting vegetation dynamics. However, there is a lack of adequate research on canopy changes across the lifecycles of different vegetation types. Using GLASS LAI (leaf area index) data (2001-2020), we investigated canopy development (April-June), maturity (July-August), and senescence (September-October) rates in Northeast China, focusing on their responses to preseason climatic factors. We identified that early stages saw canopy development acceleration, with over 71% of areas experiencing such acceleration in April and May. As the vegetation grew, the accelerating canopy development slowed down, and the canopy reached its maturation earlier. By analyzing the partial correlation between canopy growth and preseason climatic factors, it was identified that changes in canopy growth were most significantly affected by preseason air temperature. A positive correlation was observed in the early stages, which shifted to a negative correlation during canopy maturation and senescence. Notably, the transition timing varied among different vegetation types, with grasslands (June) occurring earlier than forests (July) and farmlands (August). Additionally, grassland canopy growth showed a stronger response to precipitation than forests and farmlands, with a lagged effect of 2.50 months. Our findings improve understanding of vegetation canopy growth across different stages, holding significant importance for ecological environmental monitoring, land-use planning, and sustainable development.

Pytaxon: A Python software for resolving and correcting taxonomic names in biodiversity data.

The standardisation and correction of taxonomic names in large biodiversity databases remain persistent challenges for researchers, as errors in species names can compromise ecological analyses, land-use planning and conservation efforts, particularly when inaccurate data are shared on global biodiversity portals. We present pytaxon, a Python software designed to resolve and correct taxonomic names in biodiversity data by leveraging the Global Names Verifier (GNV) API and employing fuzzy matching techniques to suggest corrections for discrepancies and nomenclatural inconsistencies. The pytaxon offers both a Command Line Interface (CLI) and a Graphical User Interface (GUI), ensuring accessibility to users with different levels of computing expertise. Tests on spreadsheets derived from datasets published in the Global Biodiversity Information Facility (GBIF) demonstrated its effectiveness in identifying and resolving taxonomic errors. By mitigating the propagation of inaccuracies from researchers' datasets to global biodiversity databases, pytaxon supports more reliable conservation decisions and robust scientific investigations. Its contributions enhance data integrity and promote informed biodiversity management in a rapidly evolving global environment.

Ecological Network Construction Based on Ecosystem Services and Landscape Pattern Indices in the Tabu River Basin

Unsustainable human activities threaten the ecological security of arid and semi-arid watersheds. However, improving the connectivity of ecological networks can enhance ecosystem services and preserve biodiversity in these fragile environments. In this study, we aimed to identify ecological sources of the Tabu River Basin by quantifying five key ecosystem services and using a morphological spatial pattern analysis model. We further optimized resistance surfaces using landscape pattern indices, constructed an ecological network, and provided recommendations for sustainable management. The results obtained were as follows: (1) Ecosystem services in the Tabu River Basin exhibit clear spatial heterogeneity, with significant increases in water yield, food supply, and carbon sequestration over the past two decades. (2) Landscape pattern indices, such as the aggregation index, patch cohesion index, and Shannon’s diversity index, showed declines, indicating heightened landscape fragmentation and reduced connectivity. (3) Over the study period, the number of ecological sources increased from 6 to 17, although the total area of these sources decreased. The number of corridors expanded from 9 to 36, with a total length increase of 362.47 km, whereas pinch points increased from 27 to 40. (4) After optimization, one additional corridor and 24 new pinch points were identified, alongside a marked reduction in resistance in the northern and central-western regions. These results provide a robust scientific basis for optimizing land-use planning and reinforcing ecological security in the Tabu River Basin.

Developing land-use planning scenarios in Türkiye to reduce water-induced soil erosion

Summary Because soil erosion constrains agricultural productivity and overuse of soils exacerbates erosion, land use can only be sustained through the implementation of land evaluation. We studied five land-use scenarios including erosion-reducing land terracing and contour farming using ILSEN modelling. These scenarios’ rates of soil loss were determined using the revised universal soil loss equation (RUSLE) method. We found that all the erosion-reducing scenarios reduced soil loss compared to the current land use of the study area; in the non-agricultural land use, soil erosion was reduced 4.25 times. The model is expected to inform reduction of soil erosion in geographies characterized by rugged topography.

Geospatial Analysis of Landslide and Assessing its Risk Along the Swat Motorway, Pakistan

Landslides significantly threaten infrastructure and human lives, highlighting the need for effective landslide susceptibility mapping. This research focuses on creating a map showing landslide susceptibility along the Swat Motorway using Remote sensing (RS) and geographic information system (GIS) methods. The objective is to assess the spatial distribution of landslide-prone areas along the motorway corridor, aiding in informed decision-making for infrastructure development and risk mitigation measures. The study begins by collecting and analyzing relevant geological, geomorphological, and climatic data to identify factors contributing to landslide occurrences. This includes slope gradient, lithology, land cover, rainfall intensity, and land use patterns. Remote sensing data, such as satellite imagery and digital elevation models, are utilized to extract information on land surface characteristics and terrain attributes. GIS-based techniques are employed to integrate and analyze the collected data, employing various spatial analysis tools and algorithms to locate potential landslide locations. The Weighted Overlay Method is applied to assign weights and combine the different factors, generating a landslide susceptibility index. Based on the landslide susceptibility map, this research aims to identify and discuss the areas along the highway that are extremely vulnerable to landslides. After creating a map of the Swat Motorway's landslide susceptibility, numerous zones that are prone to landslides were found. Two of these zones are particularly prone to landslides. The creation of a susceptibility map of landslides provides valuable information for planning land use, management of infrastructure, and hazard mitigation along the Swat Motorway. It identifies high-risk zones prone to landslides, enabling policymakers and engineers to make informed decisions regarding the construction of new roads, slope stabilization, and implementation of early warning systems. The results of this research add knowledge to the already-existing knowledge on susceptibility mapping of landslides, specifically in the context of the Swat Motorway. By utilizing GIS and RS techniques, the study demonstrates an effective and efficient approach for assessing landslide hazards along transportation corridors.

How exceptions to land use regulations enter planning legislation. The Flemish case of rebuilding non-conforming dwellings

ABSTRACT Existing research shows that exceptions, i.e. planning permissions for developments that deviate from land use regulations, have become common in planning as a means of addressing unique or urgent building project needs. In Flanders, the Northern region of Belgium, one can observe a long history of exceptions ever since the Belgian government implemented territory-wide national land-use plans in the 1970s. However, how the legal provision for granting exceptions became embedded in planning legislation has never been the subject of academic research. This paper fills this gap by examining the decision-making process behind the 1999 legal provision for rebuilding residential dwellings in agricultural zones in Flanders (i.e. non-conforming dwellings). An analysis of parliamentary reports and press releases was complemented by semi-structured interviews with the top-level actors involved in this decision and the actors with whom they interacted down to the local government level. This actor-interaction-set analysis (AISA) revealed the subtle interactions between public, semi-public, and private actors in legislative decision-making processes. Additionally, we found seven different roles these actors personified in cross-level interactions: homeowners, caseworkers, high-level caseworkers, constituency advocates, lobbyists, associational advocates, and legislators. These actor-roles and their interaction-sets have enabled individual building projects to be subtly articulated into planning legislation.

RISK ASSESSMENT OF HAZARDOUS WASTE MANAGEMENT PROCESS

Urbanization and industrial activities are responsible for the increasing quantities of wastes each year leading to environmental and health consequences. Wastes are also generated from household, commercial, agricultural or medical activities industrial, mining or metallurgical sectors. Hazardous wastes can be identified as any solid, liquid, or gaseous waste that, in its chemical and physical characteristics, represents a potential harm to human health and/or the environment. Therefore, it requires specific management, such as compliance with the EU Waste Framework Directive for waste prevention and reduction. This study explores the hazardous waste management process to identify potential hazards during the treatment phase. It analyses the risk to the population using the qualitative preliminary hazard analysis (PHA) method and performs consequence analysis using Effects modelling software. The results of the PHA indicate a low to moderate risk, if specific safety measures are applied. The most severe accident scenario may result in reversible effects outside the establishment over short distances. These analyses can support decision-making in land-use and emergency planning procedures.

How does Agricultural Expansion Affect Nipah Virus Ecology?

In locations experiencing rapid agricultural expansion, the Nipah virus is an emerging zoonotic pathogen that brings about a serious threat to public health. This study looks at the effects that agricultural expansion has on the ecology of the Nipah virus. The study examines the consequences of habitat loss on fruit bat populations, the natural reservoir hosts for the Nipah virus, and how these changes influence bat foraging behaviour and interaction rates with other living organisms. Through reviews of outbreak data, the research identifies a link between agricultural activities and the increased risk of Nipah virus spillover into populations. The findings suggest that the expansion of agriculture disturbs the natural habitats of bats, forcing them to forage near humans and livestock which encourages the virus's spread. The results emphasize the importance of strategies for agricultural biosecurity, wildlife conservation, and land-use planning in order to minimize the potential for Nipah virus outbreaks.