Urban Land Research Articles

Applying Low-Impact Development Techniques for Improved Water Management in Urban Areas

Worldwide, the increase in impervious surfaces due to urbanization has led to significant water cycle issues such as groundwater depletion, urban heat islands, and flooding. To address these challenges, Low-Impact Development (LID) techniques are increasingly being applied in stormwater management. This study focuses on Ulsan, designated as a water cycle model city in South Korea, with a particular emphasis on the highly urbanized Okgyo drainage watershed. Using the Stormwater Management Model (SWMM) version 5.1, long-term runoff simulations were conducted to evaluate the effects of LID implementation on water cycle change rates and recovery rates. The model incorporates detailed hydrological and hydraulic parameters, including inflow, runoff, infiltration, and evapotranspiration for six subcatchments within the watershed. The SWMM was calibrated and validated using 30 years of historical rainfall data (1987–2016) from the Ulsan weather station. Calibration and validation processes used the NRCS-CN (Curve Number) method to ensure accuracy in simulating runoff patterns and water balance. The study specifically evaluated the effectiveness of two LID techniques: bioretention and permeable pavements. Three scenarios were modeled: bioretention applied to 5% of the area, permeable pavements applied to 5% of the area, and a combined application of both techniques. The results showed that the combined scenario provided the best outcome, with a 7.80% reduction in surface runoff and a 14.56% improvement in water cycle health. The LID application scenario confirmed the potential to achieve the water cycle management target of handling 25.5 mm of rainfall. These findings demonstrate that the introduction of LID techniques in public spaces can significantly enhance water management. This research provides insights into effective water cycle management methods tailored to specific urban land uses, laying a foundation for future urban planning and sustainable development.

Field assessment of engineered bioretention as microplastics sink through site characterization and hydrologic modeling

Green stormwater infrastructure (GSI) practices like bioretention are considered a sink for microplastics washed in from urbanized land uses-land covers, and thereby regulating the environmental dispersion of microplastics. However, the capacity of GSI in microplastic sequestration remain unclear. This work investigated the spatial distributions of microplastics within bioretention cells and their soils, concentration in the GSI groundwater monitoring well, and the overall potential of GSI as a sink for microplastics. The average microplastic concentration in GSI soils (2718 - 3833 MPs/kg dry soil) is 7−10 times higher than background soils (262 - 520 MPs/kg dry soil). The most abundant microplastics observed were polypropylene (57 %), polyethylene (17 %), and rubber/bituminous (16 %), indicating the major sources of microplastics derived from post-consumer plastics and tire wear. Soils closest to the GSI stormwater inlet sequestered the most particles, and the microplastic concentration decreased with soil depth. Our hydrologic modeling, based on measured soil and hydraulic parameters, suggested that runoff overtopping the freeboard of the bioretention cell – and potentially dispersing microplastics into the surrounding environment – was unlikely. Microplastics in the GSI groundwater monitoring well was minimal at 11 MPs/L. These results suggest that GSI can capture and sequester microplastics to mitigate microplastic pollution in the environment.

The Clustering of the Population at Building Scale in Bursa City (Türkiye)

Research on spatial statistical methods related to population estimation at the building scale and its implications for urban land use has attained little attention. The main target of this study is to propose a new method for population estimation at the building level with minimal data and methodology and a high accuracy rate. In addition to this, it discusses urban population from various perspectives by using spatial statistical methods (Local Moran’s I and Hot–Cold Spot) to examine the population calculated based on the number of residential units in buildings and the household size of the neighborhood along with urban land use types in the case of Bursa. The results showed the following: (1) The suggested method achieves a 76% accuracy rate in population estimation at the building level; (2) 64.6% of the city’s population (2,101,581 individuals) is located in areas classified as Discontinuous High-Density Urban Fabric (50–80%) and Continuous Urban Fabric (>80); (3) 13.2% of the population is located in hot spot areas of these two types, while 14.5% is in cold spot areas. This research provides decision-makers with a framework for addressing urban problems related to housing, transportation, health, and energy in addition to the methods it proposes.

Impact of urbanization on water-energy-carbon nexus system: The case of Zhengzhou, China

Exploring the impact of urbanization on water-energy‑carbon nexus system is helpful to discover the inherent interaction mechanism and co-evolutionary pattern of water-energy‑carbon nexus in urban expansion. Based on the calculation of water-energy‑carbon of different land use types, the impact of urbanization on water-energy‑carbon nexus system in Zhengzhou was analyzed, and the future evolution of water-energy‑carbon nexus system under different urbanization scenarios was simulated. The results showed that land use change during urbanization was affected by the industrial pattern and the intensity of human activities, which further caused the increases in water and energy consumption and carbon emissions. There was a positive correlation between urbanization level and coupling coordination degree of water-energy‑carbon nexus system. Especially, the changes in water and energy consumption caused by land use change during urbanization largely determined the coupling coordination level of water-energy‑carbon nexus system. Additionally, different urbanization scenarios would lead to different growth rates of water and energy consumption and carbon emissions, in which the impact of land urbanization on urban water-energy‑carbon nexus system was greater than that of the economic and population urbanization. In the future, urban expansion control and land use regulation based on collaborative optimization of water-energy‑carbon should be adopted.

Optimization of speech intelligibility in street-facing rooms of adult care home based on acoustic simulation

Due to the limited availability of urban land in China, many adult care facilities have resorted to constructing roadside living spaces. However, this has led to a significant issue of traffic noise disturbance. Besides, many rooms lack of control over indoor reverberation. As a result, the communication efficiency of the residents might be greatly impacted. This study aims to investigate the impact of traffic noise level, room size, and surface sound absorption on speech transmission index (STI), based on a typical room layout and conducted using acoustic simulation. The simulation results indicated that in order to achieve the required STI over 0.79 for elderly residents, it is imperative to control the road noise interference below 40 dBA and ensure that the room reverberation time under 0.42 s. To achieve this, it is recommended that for a road with a noise emission level of 72 dBA, the distance between the roadside room and the road should not less than 10 m. Additionally, windows with Rw+Ctr over 28 dB without road sound barriers (over 20 dB with sound barriers) should be installed. Besides, the room area needs to be controlled within 20 m2 and an acoustic ceiling with NRC>0.65 should be installed.

The impact of heterogeneous accessibility to metro stations on land use changes in a bike-sharing context

The integration of urban rail transit and land use has been adopted as a crucial approach to fostering compact development in cities. Proximity to rail transit stations can increase the probability of land use changes, while few studies have analyzed the spatial heterogeneity of the impact of rail transit on land use changes. This study proposes a distance-decay function to delineate the spatial heterogeneity of metro station accessibility using bike-sharing data and examines the impact of metro stations accessibility on land use changes. Jiading New Town in Shanghai, China, is selected as our study case. By utilizing a non-linear distance-decay function to delineate metro station accessibility as a driving factor for training neural networks in a vector-based cellular automata model, an improvement in simulation accuracy is achieved compared to the model using a linear distance-decay function. This study could help establish more efficient strategies for promoting integrated development of rail transit and land use. The significance of this study lies in the generality of the optimized land use vector-based cellular automata model considering the spatial heterogeneity of metro station accessibility, which could also be applied to other situations, such as considering the accessibility to bus stops and road networks.

Coupling coordination analysis and spatiotemporal heterogeneity between urban land green use efficiency and ecosystem services in Yangtze River Economic Belt, China

Rapid urbanization has resulted in the conversion of different land types, leading to a serious disruption of the balance of ecosystems, and the contradiction between land use and ecological security becomes increasingly severe. As a key factor affecting ecosystem services (ESs), improving the urban land green use efficiency (ULGUE) can effectively mitigate the decline in the ecosystem services function. This study tried to verify the profound impact of land use on ESs by measuring the coupling coordination degree (CCD) between ULGUE and ESs from the perspective of coupling coordination. However, the traditional CCD model suffers from volatility and non-comparable confidence levels in results. For this background, this study adopted the improved CCD model to measure the association between ULGUE and ESs in the Yangtze River Economic Belt (YREB). Also, a comprehensive spatial evolution of the CCD was further explored. The main conclusions are as follows: (a) The overall level of ULGUE in YREB showed an increasing trend with the distribution of ULGUE in most cities ranging from 0.71 to 1.00, showing a higher level overall and the spatial distribution character of “small aggregation, large distribution”; (b) The ESs of YREB from 2005 to 2020 demonstrated a decreasing trend and majority of cities’ current ecological protection efforts are lagging behind the extent of ecosystem damage caused by human activities; (c) The overall average CCD of YREB was largely at basically balanced level and the average CCD change ranges from 0.38 to 0.45 between 2005 and 2020, but the overall CCD had a strong spatial correlation strength. (4) To some extent, the improved CCD model solved the problems of volatility and credibility based on the traditional CCD results, which have strong rationality and scientific validity. Identifying the coupling and coordination characteristics and mechanisms can effectively provide theoretical support for the sustainable development of watersheds.

Urban expansion in highly populous East Asian megacities during 1990–2020: Tokyo, Seoul, Beijing, and Shanghai

The world is experiencing unprecedented urbanization, particularly through the continuous growth of megacities, leading to significant urban land expansion. The spatial layout and growth patterns of urban areas play a critical role in determining cities' sustainable development. However, the optimal path for cities undergoing rapid urbanization remains uncertain. This study examines four megacities—Tokyo, Seoul, Beijing, and Shanghai—and, from the perspective of urban land density, compares their patterns and processes of land expansion in 1990, 2000, 2010, and 2020. Findings reveal that the urban land area of China's megacities has expanded nearly fourfold over the past three decades. Meanwhile, Tokyo and Seoul have adopted a polycentric urban structure, becoming increasingly compact. In contrast, Beijing and Shanghai are only beginning to show signs of polycentric development. The study concludes that cities experiencing rapid growth should not impose excessive limitations on urban expansion. Polycentric and compact development has become a critical strategy for megacities. These insights offer valuable guidance for urban planning and sustainable development in both established and emerging megacities across East Asia.

Decentralization of land development approval and economic impacts: A study on China's urban construction land reform

This paper explores how China's reform of the urban construction land approval system, which decentralized authority to provincial governments, affects enterprise total factor productivity (TFP) using a quasi-natural experiment approach. The reform streamlined processes, reduced legal ambiguities, and enhanced resource efficiency. Our findings indicate significant TFP gains primarily due to lower administrative costs and improved legal frameworks, emphasizing the pivotal role of regional governance and legal enforcement in economic outcomes. Additionally, the analysis highlights substantial TFP enhancements from reduced inefficient investments and financing constraints, with notable regional and enterprise-specific variations in the impact of legal reform.

Exploring the Coupling Relationship and Driving Factors of Land Use Conflicts and Ecosystem Services Supply–Demand Balances in Different Main Functional Areas, Southwest China

ABSTRACTConflicts between different types of land use, driven by rapid urbanization, are altering ecosystem services supply–demand balances (ESDB), and the reduction of ESDB will threaten regional sustainable development and human welfare. However, there are few studies on the interrelationships and their drivers between land use conflicts (LUCs) and ESDB from a coupling perspective, especially in different main functional areas. Therefore, this study focused on Southwest China. Firstly, the coupling coordination degree model was employed to measure the ESDB‐LUCs relationship and analyze its dynamic changes from 1990 to 2020. Then, the RDA method was used to explore the driving factors of the ESDB‐LUCs relationship in different functional areas (i.e., urban development area (UDA), agricultural development area (APA), and ecological protection area (EPA)). The results show that the LUCs index displayed a downward trend in the SW during 1990–2020, with a decreasing distribution pattern from the northeast to the southwest. The ESDB index exhibited a downward and then upward trend, with an increasing distribution mode from the northeast to the southwest. There was a spatial dependence between LUCs and ESDB. The type of coupling coordination between LUCs and ESDB was dominated by moderate coordination, with the index showing a spatial pattern of UDA > APA > EPA. Among these, the proportion of cropland and the proportion of urban land were the main factors influencing the degree of coordination of the UDA (explanation rate > 80%), showing positive and negative effects, respectively. The proportion of forestland and the proportion of cropland were the main factors influencing the APA and EPA (explanation rate > 70%), with negative and positive effects, respectively. Therefore, mitigating the conflict between cropland and urban land, cropland and forest land is essential to achieve ecosystem balance in the SW.

Predicting land use dynamics, surface temperature and urban thermal field variance index in mild cold climate urban area of Pakistan

Rapid urbanization attributed to population growth is affecting the built environment's thermal and landscape dynamics. Using Landsat satellite datasets, this study investigated the complex interplay between urban Land Cover (LC) modification, fluctuation in Land Surface Temperature (LST) and severity of Urban Heat Island (UHI) from 1990 to 2020 in Peshawar City, Pakistan. Thermal bands were used to calculate LST and severity of UHI using the Urban Thermal Field Variance Index (UTFVI). Furthermore, through Cellular Automata (CA), Logistic Regression (LR), and Artificial Neural Network (ANN), future predictions on thermal characteristics associated with land use changes were made. The results showed that the urban areas expanded by ∼25 % from 1990 to 2020, while a ∼10 % decrease occurred in urban vegetation. The city is projected to expand by ∼45 % and ∼56 % in 2035 and 2050, respectively. Notably, the results also demonstrated that urban hotspots were found the warmest with the strongest UHI severity (∼34 °C), followed by the barren land (∼32 °C), and vegetation. The results further predicted an increase of LST (∼55 % and ∼82 %) and UTFVI (∼62 % and ∼83 %) in 2035 and 2050, respectively. These findings provide useful insights for policymakers and city planners to mitigate heat stress and create a sustainable urban environment through the development of effective urban land use policies and urban greening.

Impacts of LULC changes on runoff from rivers through a coupled SWAT and BiLSTM model: A case study in Zhanghe River Basin, China

Changes in river runoff have a significant impact on the sustainable use of water resources in a watershed, and these changes are closely linked to variations in land use/land cover (LULC). This research explores an innovative approach in the Zhang River Basin (ZRB), China, by coupling a concept-based hydrological model, the Soil and Water Assessment Tool (SWAT), with a deep-learning model, the Bidirectional Long Short-Term Memory Network (Bi-LSTM), to improve the accuracy of river runoff simulations. By analyzing LULC changes in 2002, 2012, and 2022, this study developed three SWAT models and three coupled SWAT-BiLSTM models to quantitatively assess the impacts of these changes on river runoff through eight LULC scenarios. The findings revealed significant LULC changes from 2002 to 2022, with cropland and grassland areas decreasing while forest and urban land areas increased. The total area of grassland, forest, and cropland made up over 93 % of the basin, indicating active land type conversions. Calibration and validation results demonstrated that the SWAT-BiLSTM model outperformed the conventional SWAT model, yielding higher accuracy in runoff simulations. Specifically, the SWAT-BiLSTM model achieved R2 values of 0.89 and 0.90 during calibration and validation, compared to the SWAT model's R2 values of 0.76 and 0.79. Scenario analyses indicated that expansions in farmland, grassland, and urban areas were correlated with increased river runoff, while an expansion in forested areas led to reduced runoff. Notably, urban land changes had the most pronounced impact on runoff, emphasizing the need for careful runoff management and flood risk mitigation in urban planning. By combining SWAT and Bi-LSTM models, this study provides an innovative assessment of the impact of LULC changes on water resources in the ZRB. The results offer valuable insights for water resource management, LULC optimization, and flood risk management, highlighting the potential application of deep learning techniques in hydrological simulation. This research serves as a scientific basis for policy-making and sustainable land use planning in the ZRB and similar regions.

The increasing rate of net carbon uptake in Eurasia has been declining since the early 2000s

The analysis of terrestrial ecosystem carbon dynamics, based on scarce carbon flux observations or carbon flux products simulated by reanalysis meteorological data, has great uncertainties. A more accurate understanding of carbon dynamics in Eurasia was achieved by using a carbon flux dataset (CFD) from meteorological stations with quasi-observational characteristics. The growth of net carbon uptake of ecosystems over Eurasia has been decreasing since the early 2000s. The net ecosystem productivity (NEP) increased significantly with the growth rate of 8.7 × 10−3 g C m−2d−1 yr−1 in spring, summer, and autumn (SSA) during 2003–2011 (p < 0.05), which was correlated with the enhanced vegetation index (EVI) and land surface water index (LSWI). This growth was mostly in dry subhumid and humid regions. However, the change in Eurasian NEP was not significant after 2011. Additionally, about 79 % of the stations in Eurasia were in net carbon uptake in SSA, and net carbon emission stations were mainly located in southwestern Eurasia. The intensity of net carbon uptake was highest in the forest, with a mean carbon uptake of 1.73 ± 0.76 g C m−2d−1 in SSA during 2003–2018, and almost all stations demonstrated carbon uptake. During 2011–2018, the number of stations experiencing reduced NEP exceeded those with increased NEP, and this ratio was higher compared to 2003–2011, mainly due to the decrease in EVI and LSWI. The rate of NEP decline at stations with reduced NEP was 5.2 × 10−3 g C m−2d−1 yr−1 faster during 2011–2018 than in the previous period (p < 0.01). Most of the decreases in NEP during 2011–2018 occurred in cropland, grassland and urban land. The spatio-temporal dynamic analysis of Eurasian NEP could provide references for effective carbon management.

INTEGRATING LAND USE ANALYSIS WITH WATER DEMAND ESTIMATION: A CASE STUDY OF PUTRAJAYA, MALAYSIA

The challenges posed by population growth, urbanization, and changing land use patterns on sustainable water resource management are significant. This paper puts forth an integrated framework aimed at assessing future water demand in Putrajaya, Malaysia. The proposed framework combines population projections, estimations of water demand, and analyses of land use activities. Through an examination of demographic trends and land use patterns, the framework predicts population growth and identifies areas with high water demand. Daily water use patterns in homes and businesses (temporal analysis) inform the designing future water infrastructure, incorporating temporal aspects. Statistical and spatial analysis techniques are then utilized to merge these projections with water demand estimations to quantify water requirements in various zones and types of land use. This study has unveiled two daily peaks in water demand, which align with household schedules. Residential areas emerge as the primary consumers of water, displaying an evening peak distinct from the midday peak seen in businesses. The current water demand in Putrajaya is estimated at 94 million litres per day, with domestic usage surpassing non-domestic usage in a ratio of 3:2. Projections based on future land use plans foresee a 19% increase in demand, underscoring the urgency for proactive water management strategies. Spatial analysis has highlighted residential areas as the main users of water, with demand levels varying throughout the city. By comprehending these temporal and spatial patterns, water authorities can strategically target interventions, optimize infrastructure siting, and forecast future demand trends. These proactive measures are essential for securing a sustainable water future for Putrajaya.

Integrating Nature-Based Solutions for urban stormwater management into existing urban fabrics

Abstract Nature-Based Solutions (NBSs) have been proven to address urban stormwater challenges effectively while providing multiple benefits to the economy, society, and environment. Urban fabrics profoundly influence flood risk as the changes in urban form, land use, and building layout will affect the urban hydrological cycle, thereby altering precipitation and runoff. However, few studies look at the connection between NBSs and urban fabrics, which can contribute to urban stormwater management. This paper aims to categorize the general types of urban fabrics and consider NBSs as strategic interventions that can improve water-related issues and help to create a resilient neighborhood. This paper elaborates on some strategic approaches to integrate NBSs in existing urban fabrics at the neighborhood scale to optimize their response capacity according to the local conditions. The novelty lies in adopting a systemic vision to deliver a design toolkit that can be adapted to different conditions and with different typologies across the places and countries facing similar water-related challenges. In conclusion, this paper emphasizes the importance of understanding how different NBSs fit various urban fabric types, and future work is needed to provide assessment tools to evaluate the efficiency of different design scenarios.

Separation of the Urbanization Effects on Thermal Environment

Rapid urbanization leads to changes in the thermal characteristics of urban areas. Despite cities serving as natural laboratories to investigate responses to global change, it remains unclear how urbanization affects the thermal environment during global warming. Urbanization effects can be categorized as either the effect of urban climate (UCE) or land cover change (LCCE). This study proposes a conceptual framework for separating the urbanization effects on the thermal environment in 29 major Chinese cities. Results show that land surface temperature increases with impervious surface fractions in the urban area and decreases with vegetation fractions in rural areas, resulting in significant UCE and LCCE across cities, with LCCE approximately 1.3 to 5.7 times greater than UCE. These findings provide a comprehensive understanding of the thermal environment change caused by urbanization. To mitigate the negative effects of urbanization on the thermal environment, reducing land cover change would be more effective.

Spatio-temporal tendencies of urban land surface temperature on the Andean piedmont under climate change: A case study of Metropolitan Lima, Peru (1986–2024)

The increase in land surface temperature (LST) in megacities has contributed to global warming due to poor urban planning and high population concentration. This study analyzes spatio-temporal trend patterns of LST in the city of Metropolitan Lima, Peru, during the summers of 1986–2024. The Mann-Kendall tests and the Theil-Sen Slope method were used to analyze the spatiotemporal trends of LST, relating R2 and the Mann-Kendall p-value of the annual average LST in each district. A hierarchical cluster analysis was performed to group districts according to their average yearly LST. Urban heat islands were identified based on basin configuration and distance to the sea at 1 km intervals. The results reveal a significant increase in LST (p<0.001) related to El Niño-Southern Oscillation phenomena, in addition to urban growth and land cover change. The significant positive trend of LST showed a heterogeneous distribution in all districts. The districts were grouped into three clusters with statistically significant differences in LST (p<0.001), spatially configured radially from the sea to the foot of the Andes, up to 1179 m a.s.l. Urban heat islands did not correlate with significant positive trends in basins. Still, they showed a considerable increase in LST in areas of high economic activity, including dense commercial, industrial, and residential areas. This information is crucial to managing climate change adaptation and mitigation measures and contributing to sustainable urban planning focused on the population’s well-being.

Reexamining exposure from truck emissions considering daily movement of individuals

With the growing demand for urban freight transportation, trucks emit a large amount of pollutants such as particulate matters and nitrogen oxides, increasingly affecting public health. This study establishes a modelized air dispersion structure to simulate pollutant concentration distribution. By integrating multiple data sources including mobile phone signals and satellite images, we reconstruct the daily trajectories of individuals and further incorporate simulated pollution concentrations in calculating dynamic and static exposure of individuals to truck emissions. Econometric models considering spatial dependence are developed to evaluate the influencing factors and elucidate the mechanisms of pollutant exposure. Results show factors including freight demand, road network, residential and employment locations, personal commuting distance, and population age structure matter in assessing truck emission exposure. As a result, a mixture of vehicular emission standards, urban traffic control, land planning, and industrial policies is proposed to reduce truck pollutant exposure and safeguard public health.

The impact of urban morphology on land surface temperature across urban-rural gradients in the Pearl River Delta, China

Optimizing urban morphology effectively mitigates urban heat island effects. However, previous research on urban morphology and land surface temperature (LST) has often concentrated on entire cities or specific local areas, neglecting the heterogeneity within urban regions. This study investigates the impact of two-dimensional (2D) and three-dimensional (3D) urban morphology on LST based on urban-rural gradients. Firstly, we calculated nine 2D and 3D indicators to comprehensively depict the urban morphology. Then, we employed a multi-iterative quantile method based on nighttime light data to delineate three city subclasses: urban core, suburb, and rural area (USR). Finally, we quantified the impact of these indicators on LST thorough correlation analysis and a random forest (RF) model. Results indicate that, overall and post-USR classification, the sum of building area (SBA) is the primary factor influencing LST, contributing up to 31.6% in suburb. The main 3D factors affecting LST differ across subclasses: in rural area, it is the sum of building surface (SBS, 12.9%); in suburb, it is the spatial congestion degree (SCD, 9.7%); and in urban cores, it is the mean building height (MBH, 12.0%). Notably, the influence of 3D indicators increases from 68.1% in rural area to 72.3% in urban core. In urban core, MBH and standard deviation of height (SDH) are negatively correlated with LST. Case studies in Tianhe District (Guangzhou) and Futian District (Shenzhen) confirmed these indicators do have a certain effect on reducing the temperature. This study provides valuable insights for improving the urban thermal environment and promoting sustainable urban development.

Government Policy Influence on Land Use and Land Cover Changes: A 30-Year Analysis

This study investigated land use and land cover (LULC) patterns and changes in the Bandon Bay area of Thailand from 1991 to 2021 using satellite imagery, the first comprehensive effort to assess historical LULC trends over the past 30 years and forecast future LULC scenarios using the CA-Markov model for 2031, 2041, and 2051. Results showed the predominant LULC during 1991-2001 was the abandoned paddy fields, and during 2006-2021 was the oil palm plantations. During 1991-2001, the abandoned paddy fields changed significantly, with a net gain of 59.28 km2. From 2001-2011 and 2011-2021, the oil palm plantations experienced the most crucial change, with a net gain of 292.94 km2 and 70.06 km2. In 2031, 2041, and 2051, the LULC was predicted to be oil palms, shrimp farms, mangroves, and urban and built-up lands. The LULC changes were consistent with the government policies implemented and indicated government policy as a driving force in LULC dynamics on Bandon Bay area forestry, aquaculture, and agriculture, particularly on oil palm cultivation. Government management and regulation on land use is crucial for reducing the expansion of agricultural areas, especially oil palm plantations and aquaculture areas, to mitigate negative impacts on the Bandon Bay ecosystem. Doi: 10.28991/ESJ-2024-08-05-06 Full Text: PDF