Built-up Land Research Articles

Urban expansion and agricultural land loss: a GIS-Based analysis and policy implications in Hawassa city, Ethiopia

This study investigated the historical and future trends of urban expansion and its subsequent impact on agricultural land-use in Hawassa city, Ethiopia. A time-series of remote-sensing imageries from Landsat Thematic Mapper for the years 1984, 1990, 2000, and 2010 and Operational Land Imager for 2021 were used to extract the LULC information from the study area. Seven major land-cover classes’ waterbody, built-up, agricultural land, wetland, grassland, woody vegetation, and agroforestry were identified with visual image interpretation along with supervised image classification techniques using the maximum-likelihood algorithm for the study years. The urban and agricultural lands were then extracted from the original LULC data to quantify the extent, rates, and number of area conversion between the two. The Land Change Modeler module of TerrSet software was used to predict the spatial extents of built-up and agricultural lands in 2030 and 2050. The results showed that there have been significant changes between the LULC types in Hawassa city within the past 37 years, from which built-up and agricultural land have shown the most prevalent changes. It showed that built-up land has increased from 584.73 ha in 1,984–3,939.03 ha in 2021, representing a 573.65% increase at an annual growth rate of 15.50%. However, agricultural land decreased from 8,324.64 ha to 3,595.68 ha in the respective years, with a 56.81% decrease at a rate of −1.54% each year. A total of 3,148.74 ha (37.82%) of agricultural land was converted into built-up land within the past 37 years (85.10 ha per year, a rate of 1.02%. The built-up land is projected to increase to 5,009.85 ha and 6,794.73 ha from 2021 to 2030 and 2050, with annual growth rates of 3.02% and 2.50%, respectively. In the same years, agricultural land will decrease to 2,849.58 ha and 2033.46 ha by 2.31% and 1.50% annually, respectively, from which 64.76 ha (1.80%) and 48.41 ha (1.35%) will be converted into built-up land, respectively. Future planning and development in the city should consider the rapid increase in built-up land toward agricultural land areas and develop appropriate adaptation mechanisms for the local community, which is highly dependent on agriculture.

Lacustrine Wetlands Landscape Simulation and Multi-Scenario Prediction Based on the Patch-Generating Land-Use Simulation Model: A Case Study on Shengjin Lake Reserve, China

Landscape simulation and prediction are crucial for understanding the dynamic evolution and future trends of wetlands. However, only a few existing studies have focused on the applicability and limitations of commonly used land-use/cover change (LUCC) simulation models in lake wetland landscapes. Taking Shengjin Lake Reserve in China as the study area, we firstly analyzed landscape variations during 2010–2020 using multisource remote sensing images. Then, the patch-generating land-use simulation (PLUS) model was employed to simulate wetland landscapes in 2020, the accuracy and limitation of which in simulating lacustrine wetlands were also explored. Lastly, the changing trends of wetland landscapes in 2030 under different development scenarios were predicted. The results show that the landscape of Shengjin Lake Reserve has changed significantly during 2010–2020, with increases in mudflats, reservoirs/ponds, woodlands, and built-up land, and there has been decreases in lakes, grass beaches, and croplands. The PLUS model demonstrated an ideal simulation accuracy for Shengjin Lake Reserve, with the overall accuracy exceeding 80%, kappa coefficient greater than 0.75, and figure of merit (FOM) coefficient of 0.35, indicating that the model can capture the dynamic changes in wetland landscapes accurately. The simulation accuracy can be effectively improved with the adjacent initial year, shorter time interval, and the primary driver factors. Under the natural development scenario, the number of patches in the Shengjin Lake Reserve increased sharply, and landscape fragmentation intensified. Under the urban development scenario, the expansion of built-up land increased, and the average patch area increased. In the ecological protection scenario, the Shannon diversity index and Shannon evenness index of the landscape improved significantly, and the natural wetlands such as grass beaches and lakes can be protected effectively. Our study confirms the applicability of the PLUS model in simulating and predicting lacustrine wetlands landscapes, and the conclusions provide a scientific basis for formulating reasonable development strategies to realize wetland resource conservation and management.

Land use modeling and carbon storage projections of the Bosten Lake Basin in China from 1990 to 2050 across multiple scenarios

Given the escalating issue of global climate change, it is imperative to comprehend and quantify the effects of land use change on carbon storage (CS), which pertains not only to the preservation of ecosystem functions but also directly influences the equilibrium and stability of the global carbon cycle. This study examines the correlation between CS and land use change, forecasts the future spatial distribution of CS, and offers a reference for the rational planning of watershed space. Focusing on the Bosten Lake Basin of Xinjiang in China, employing the land use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model to forecast the spatial distribution of carbon stocks across three developmental scenarios, while also examining the shift in the center of gravity of CS and the autocorrelation of their spatial distribution. The findings derived from the study are as follows: (1) From 1990 to 2020, the predominant land use type in the Bosten Lake Basin was grassland, while there was an upward trend in the areas of cropland, forest land, built-up land, and wetland, alongside a downward trend in the areas of grassland, water, and unused land. (2) In the long term, the regional CS exhibits an upward trend, with the most significant increase anticipated in the EPS scenario. Grassland constitutes the most extensive carbon reservoir in the Bosten Lake Basin, while wetlands exhibit the highest carbon sequestration potential. (3) The alteration in the center of gravity of CS is associated with the expansion or reduction of the major regional carbon reservoirs and types characterized by significant carbon sequestration potential. (4) In the long term, the spatial correlation of CS in the Bosten Lake Basin exhibits a consistent upward trend, with the most pronounced spatial correlation observed under EPS.

Quantifying the Effect of Land Use and Land Cover Changes on Spatial-Temporal Dynamics of Water in Hanjiang River Basin

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by 96.275×108t, 81.210×108t, and 84.13×108t relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply.

Assessment of wetland loss through industrialization and community expansion: a case study of the greater amanzule wetland in the Ellembelle district of Ghana

Wetland ecosystems provide numerous services to humanity and the biosphere at large. However, these services are constantly dwindling due to the massive wetland loss caused by urbanization. Urbanization-induced wetland loss is a global problem, with most developing countries experiencing it currently. Several studies on wetland loss have been conducted. However, there is a dearth of studies integrating GIS and other ecological models to estimate the periodic deterioration of wetlands in rural settings in underdeveloped nations. As a result, this study aims to determine wetland loss in a developing country’s countryside, using the Greater Amanzule Wetland in the Ellembelle District of Ghana as a case study. The study used the GIS and Remote Sensing dataset, the Normalization Difference Vegetation Index, and the InVEST-Habitat Quality model to analyze the spatial pattern of wetland loss and habitat quality variations caused by industrialization and community expansions between 2000 and 2020. Our results indicate that, from 2000 to 2015, community built-up and industrial land areas grew from 25.19 ha to 84.21 ha and 0–4.71 ha respectively, causing a wetland loss of −39.64 ha (−31.10%). Between 2015 and 2020, community built-up land grew to 78.65 ha while industrial land slightly reduced to 2.54 ha, leading to the wetland degradation of approximately −69.06 ha (−42.53%). Wetland habitat quality steadily declined, from 0.97 in 2000 to 0.93 in 2015 and 0.93 in 2020. The study findings led to policy recommendations to reduce wetland encroachment and enhance sustainability. These recommendations included conducting effective land-use plan inspections before issuing permits, coordinating effective management, and promoting the recovery of natural and artificial vegetation to sustain the wetland.

Impact of Forest Landscape Patterns on Ecological Quality in Coastal Cities of Fujian, China, from 2000 to 2020

The Fujian coastal zone, a key region in China’s coastal belt, has experienced significant landscape and ecological changes due to intense human activities. Understanding the relationship between landscape patterns and ecological quality is critical for sustainable development and ecological protection. Taking the coastal cities, including Fuzhou, Xiamen, and Ningde in Fujian Province of China, as a case, the spatio–temporal changes in landscape patterns and the remote sensing-based ecological index (RSEI) during 2000 and 2020 were explored by the Google Earth Engine (GEE) cloud platform, and then their spatial relationships were identified through Pearson correlation analysis and bivariate spatial autocorrelation analysis. The findings reveal that (1) forest land was the dominant landscape in Fuzhou and Ningde, while cropland prevailed in Xiamen. Significant changes occurred in the land use landscape patterns of the three cities, mainly due to a substantial increase in the built-up land and varying degrees of reduction in arable and forest land. At the landscape level, both Fuzhou and Xiamen exhibited increased landscape fragmentation, while Ningde showed a trend of landscape aggregation; at the class level, forest land in Fuzhou and Xiamen exhibited increased fragmentation, whereas in Ningde, it showed an aggregation trend. (2) Between 2000 and 2020, the ecological–environmental quality of Fuzhou and Ningde continuously improved, while the improvement in Xiamen was less significant. Poor and fair ecological environments in the three cities were mainly concentrated in city centers and coastal zones, and areas of ecological quality degradation were primarily concentrated in coastal zones. (3) Correlation analysis indicates that, whether at the landscape level or the class level, the ecological quality of the three cities is significantly negatively correlated with the fragmentation index and significantly positively correlated with the aggregation index. Moreover, the positive correlation between ecological quality and the forest landscape aggregation index, as well as the negative correlation with the forest landscape fragmentation index, are both significantly stronger than those at the landscape level. As urbanization progresses, forest landscape fragmentation intensifies, especially in city centers and coastal areas, having a significant negative impact on ecological quality. These results highlight the importance of landscape pattern management in maintaining ecological quality. This paper provides insights for coastal cities on balancing urban development with ecological preservation in the context of rapid urbanization.

Multi-scenario simulation and optimization of habitat quality under karst desertification management

IntroductionInvestigation of the evolutionary trend of habitat quality in karst and rocky desertification zones is crucial for enhancing ecological security and conservation.MethodsAnalysis of land use statistics from the years 2000, 2010, and 2020, changes in habitat quality (HQ) and land use (LULC) between 2000 and 2020 were analyzed using Huize County in Yunnan Province as an example. The InVEST and FLUS models were applied to simulate LULC under different scenarios in 2030 and 2040 and assess changes in spatial gradients of habitat quality at each timepoint and factors influencing them.ResultsThe findings indicated that (1) The predominant land use types are grassland and woodland, experiencing the most significant growth in urbanized areas, the main sources of which are paddy fields and high-cover grassland. (2) The habitat quality between 2000 and 2020 was average and displayed a consistent decline. The spatial distribution pattern indicates low HQ in urban areas, high HQ in the outskirts, low HQ in the south-west, and high HQ in the north-east. In all four scenarios, habitat quality predominantly decreases in urban areas and regions with a dense concentration of built-up land. (3) Habitat quality spatial distribution is primarily affected by the type of land use, with NDVI being the secondary determinant.DiscussionThe ecological environment of Huize County must be restored and safeguarded with a focus on ecological priorities and harmonious development scenarios. This study provides methodological lessons for ecorestoration and policymakers in areas of karstic rocky desertification.

Spatiotemporal Analysis of Urban Growth and PM2.5 Concentrations in Sylhet, Bangladesh

Environmental impacts of urbanization, such as increased air pollution, pose significant challenges for developing countries. This study examines land cover changes and their relationship with particulate matter 2.5 (PM2.5) concentrations in two upazilas of Bangladesh from 2001 to 2019 using GIS and remote sensing techniques. Results show significant urban expansion (i.e., increase in built-up area) in both upazilas, corresponding with increasing PM2.5 levels. Linear regression reveals correlations between land cover types and PM2.5 levels. Mixed forests and waterbodies tend to be negatively associated with PM2.5 concentrations; on the other hand, built-up and barren land show a positive correlation with PM2.5. The most significant increase in built-up land and PM2.5 was in Madhabpur, indicating urgent environmental and health issues. This study emphasizes the critical role of sustainable urban planning and environmental conservation in mitigating urbanization’s adverse effects on air quality, advocating for preserving natural landscapes to maintain ecological balance, protecting urban health, and providing policymakers with insights to develop strategies addressing urban expansion and air pollution.

Spatiotemporal Change Analysis and Multi-Scenario Modeling of Ecosystem Service Values: A Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration, China

Ecosystem service value (ESV) assessment is a crucial indicator of regional ecological quality and ecological management effectiveness. Ecosystem services (ES) provide the environmental foundation for human existence and social advancement. However, the future course of land use change (LUC) in urban agglomerations and its implications for human society remains uncertain, which presents a challenge to maintaining a balance between ecological service functions and regional socioeconomic growth. This paper took the Beijing-Tianjin-Hebei (BTH) urban agglomeration as an example and used the future land use simulation (FLUS) model to project the spatial distribution of land use under the natural development scenario (NDS), food security scenario (FSS), and ecological priority scenario (EPS) of BTH in 2030, 2040, and 2050. Next, the changes to ESV under various scenarios were investigated through the equivalent coefficient method. In order to make more targeted recommendations for regional development, the study also used hotspot analyses to explore the impacts of LUCs on ESV. The results showed that: (1) from 2000 to 2020, the LUC in the BTH was dramatic and mainly focused on the interconversions among the three land use categories of cropland, grassland, and built-up land. The total ESV demonstrated the tendency to decrease from CNY 386,859.89 × 106 in 2000 to CNY 371,968.78 × 106 in 2020. (2) Compared with 2020, the ESV in BTH in 2050 under the FSS loses 16,568.78 × 106 CNY, followed by the NDS (CNY 10,960.84 × 106), while the ESV under the EPS increases by CNY 9373.74 × 106. The results of the scenario simulation showed that there was significant variability in ESV under different political orientations. (3) Hotspot analysis indicated that the ESV changes were clustered in the northeastern part and the eastern coastal region of the BTH. On this basis, we identified Chengde, Beijing, Tianjin, and Zhangjiakou as the key cities to focus on and made meaningful suggestions for their future regional environmental protection and sustainable development. This research can serve as a guide in creating sustainable BTH development policies and offer fresh perspectives for investigating how land use patterns affect the ecological environment’s regional quality under various policy trajectories.

Land Use Change in a Typical Transect in Northern China and Its Impact on the Ecological Environment

This paper uses seven periods of land use/cover data from 1990 to 2020 to investigate the spatio-temporal features of land use change in a typical transect in northern China. By using the land use transfer matrix, transect analysis, and ecological contribution rate, image interpretation data obtained from the Chinese Academy of Sciences Resource and Environmental Science Data Platform were analyzed using a spatial overlay to quantitatively examine the transect’s land use changes and their impact on the eco-environment. The results indicate that (1) the transect’s land use is dominated by cropland and grassland. (2) Cropland, forest land, and waters experienced significant transitions in 1995 and 2000, which was linked to socio-economic development and policy factors. (3) The total dynamic percentage of land use change is 4.52%, with built-up land and cropland showing the highest change. (4) The transect’s eco-environmental quality (EQ) has significantly declined, with the quality index dropping from 0.3839 to 0.3773. The transformation of cropland to forest land improves the eco-environment, while the transformation to built-up land has negative impacts. Human activities adversely affect the EQ. The findings are promising for leading the development of conserving the eco-environment and supporting the formation of regionally differentiated paths of ecological civilization construction in the transect.

Evaluation of Suitability for Built-Up Land Expansion and Land Use Simulation Based on Obstacle Factor Constraints

Evaluation of Suitability for Built-Up Land Expansion and Land Use Simulation Based on Obstacle Factor Constraints

Spatial Dynamics Of Tsunami Prone Areas In Kalianda Sub-District, South Lampung Regency

Kalianda Sub-District is one of the areas that is vulnerable to earthquakes and tsunamis because it is located on the west coast of Sumatra Island and the Sunda Strait has a potency from the eruption of Anak Krakatau Volcano. Increasing population growth also increases the risk of disaster impacts that are difficult to predict. This research aims to analyze the spatial dynamics of tsunami-prone areas in Kalianda District. This research uses multi-temporal land cover data, driving data on built-up land development factors, existing roads, slope, distance from the coastline, and distance from rivers. The method used is Cellular Automata Markov Chain which is used to model the development of built-up land, and the Berryman method for tsunami hazard analysis . Based on modeling results for 2031, the type of built land cover will experience a large increase. The tsunami danger level in Kalianda District is dominated by the low level covering an area of 4,741.80 ha, then the high level covering an area of 3,047.29 ha and the medium level covering an area of 1,243.66 ha. According to research results, the number of tsunami-prone areas increases every year. Therefore, we need to improve education and outreach to the public about tsunami dangers and effective evacuation procedures. The development and maintenance of evacuation support infrastructure, as well as the implementation of a reliable early warning system, are also very important to increasing community preparedness for tsunami disasters.

Comparison of various models for multi-scenario simulation of land use/land cover to predict ecosystem service value: A case study of Harbin-Changchun Urban Agglomeration, China

Understanding the intricate changes in land use and land cover (LULC) transformations, as well as accurately quantifying the ecosystem services value (ESV), holds paramount importance in achieving sustainable development goals. However, previous studies have notably neglected conducting empirical evaluations across various LULC prediction models under identical conditions within the same geographical region. Additionally, the majority of relevant studies primarily concentrate on local scales. In this study, we used CA-Markov, Future Land Use Simulation (FLUS) and Patch-generating Land Use Simulation (PLUS) models to simulate the dynamics of LULC, respectively. Subsequently, we successfully projected the future LULC patterns and corresponding ESV within the Harbin-Changchun Urban Agglomeration (HCUA), China. During the period spanning from 2000 to 2020, a persistent reduction of 2067 km2 in farmland was witnessed within the HCUA, while an accompanying expansion of 4081 km2 in built-up land occurred concurrently. The ESV in HCUA experienced a fluctuating trend. There was an initial decline of 7.443 × 109 yuan during the first decade, which was subsequently followed by an increase of 4.615 × 109 yuan during the latter decade. PLUS, FLUS, and CA-Markov models can all simulate the LULC of HCUA, but in decreasing order of accuracy and ease of use, with OA values of 0.8987, 0.8944 and 0.8651, and Kappa values of 0.8217, 0.8150 and 0.7860, respectively. The PLUS model was chosen to predict the future LULC. Then four development scenarios were set. Our optimization results indicate that it is advisable to restrict the area of built-up land within 17000 km2 in 2030. Moreover, under the economic and ecological balance (EEB) scenario, both ESV and economic benefits are projected to increase compared to the business as usual (BAU) scenario. This study offers valuable insights and serves as a significant reference for future research endeavors focused on optimizing land use.

Multi-Source Remote Sensing Data for Wetland Information Extraction: A Case Study of the Nanweng River National Wetland Reserve

Wetlands play a vital role in regulating the global carbon cycle, providing biodiversity, and reducing flood risks. These functions maintain ecological balance and ensure human well-being. Timely, accurate monitoring of wetlands is essential, not only for conservation efforts, but also for achieving Sustainable Development Goals (SDGs). In this study, we combined Sentinel-1/2 images, terrain data, and field observation data collected in 2020 to better understand wetland distribution. A total of 22 feature variables were extracted from multi-source data, including spectral bands, spectral indices (especially red edge indices), terrain features, and radar features. To avoid high correlations between variables and reduce data redundancy, we selected a subset of features based on recursive feature elimination (RFE) and Pearson correlation analysis methods. We adopted the random forest (RF) method to construct six wetland delineation schemes and incorporated multiple types of characteristic variables. These variables were based on remote sensing image pixels and objects. Combining red-edge features, terrain data, and radar data significantly improved the accuracy of land cover information extracted in low-mountain and hilly areas. Moreover, the accuracy of object-oriented schemes surpassed that of pixel-level methods when applied to wetland classification. Among the three pixel-based schemes, the addition of terrain and radar data increased the overall classification accuracy by 7.26%. In the object-based schemes, the inclusion of radar and terrain data improved classification accuracy by 4.34%. The object-based classification method achieved the best results for swamps, water bodies, and built-up land, with relative accuracies of 96.00%, 90.91%, and 96.67%, respectively. Even higher accuracies were observed in the pixel-based schemes for marshes, forests, and bare land, with relative accuracies of 98.67%, 97.53%, and 80.00%, respectively. This study’s methodology can provide valuable reference information for wetland data extraction research and can be applied to a wide range of future research studies.

Land Use and Land Cover Change in East Java Indonesia from 1972 to 2021: Learning from Landsat

This study analyses land use and land cover (LULC) changes during the last five decades (1970–2021) in East Java Province, Indonesia. The changes are analysed by comparing four maps interpreted from Landsat images (MSS 1972, TM 1997, OLI 2013, and OLI 2021). The main research procedures consist of (1) data collection, (2) field survey, (3) image classification, and (4) LULC change interpretation. The classification uses the maximum likelihood algorithm, achieving an overall kappa accuracy of > 75%. The classification produces eight classes, i.e., built-up land (BU), heterogeneous agricultural land (HAL), bare soil (BS), paddy fields (PF), open water (OW), vegetation (VG), shrubland (SH), and wetlands (WL). The analysis shows a significant shift in land use from 1972 to 2021, with HAL declining by 46%, SH by 91%, and BS by 88%. In contrast, PF has increased by 105%, VG (forest and plantation) by 64%, and built-up areas by a remarkable 366%. These changes show a significant shift from dryland agriculture, shrublands, and barren lands to irrigated regions, vegetated areas, and urban growth. Furthermore, there are increases in water bodies due to the construction of several reservoirs to support water availability. In coastal regions, the development of inland aquaculture leads to a proliferation of wetlands (salt evaporation ponds, fish ponds, and rice-fish integrated farming).

Dynamics System Modeling of Declining Agricultural Land Area Potentially Causing Jakarta Flood Disaster

The change or evolution of land use in the DKI Jakarta area has caused various environmental problems in the city that have an impact on disasters that occur from time to time. The conversion of agricultural land that has a relatively high ability to absorb water into built-up land has reduced the water absorption capacity because the built-up area is increasingly impermeable which is at risk of causing flood disasters. This research focuses on a simple dynamic system modeling approach to understand the cause-and-effect relationship of the decline in agricultural land area in the DKI Jakarta area. The method used in this research is a qualitative-based dynamic system, dynamic system is a method that can be used to form structures and predict behavior and feedback. Dynamic system modeling using Powersim Studi 10 Express software uses time specifications ranging from 2020 to 2070. The results of the dynamic system model of agricultural land decline can be said to be valid, where the dominant structure formed is Negative Feedback (Balancing Loop) with Exponential Decay behavior and Average Means Error (AME) test results obtained a value of 29.6%

Urban Habitat Quality Enhancement and Optimization under Ecological Network Constraints

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning.

Spatially Heterogeneous Relationships between Ecosystem Service Trade-Offs and Their Driving Factors: A Case Study in Baiyangdian Basin, China

Clarifying the complex relationships among ecosystem services (ESs) and their driving mechanisms is essential for effective ecosystem management and enhancing human welfare. Nonetheless, the current research on these issues still remains limited; therefore, further theoretical exploration is required. This study aims to quantitatively illustrate the trade-off strength of ESs and investigate the spatiotemporal heterogeneity connections between these relationships and various anthropogenic and natural factors in Baiyangdian basin, China, integrating InVEST, RMSE, geographical detector and MGWR methods. From 2000 to 2020, the total water yield (WY) and nutrient export (NE) increased, while the total carbon storage (CS) and habitat quality (HQ) decreased slightly. The trade-offs of ESs showed spatiotemporal heterogeneity. The most serious trade-off occurred between regulating services (CS and NE) and supporting services (HQ) in 2000, which was mainly distributed in the densely forested and grassed western and northern regions of the basin. The trade-off intensities of half of the pairwise ESs in 2020 increased, with the strengthened areas mainly located in the southeast of the watershed where built-up lands are concentrated. Various factors dominated the trade-offs among ESs, with the interactive effects of multiple drivers being more significant than those of individual factors. Land use type, vegetation cover and precipitation have the most pronounced effect on the trade-offs among ESs. The findings of this study may suggest and advocate for spatial ecological strategies to enhance the integrated and holistic advancement of various ESs and also serve as a reference for regional ecosystem governance and the attainment of sustainable growth.

Spatio-temporal pattern change of LULC and its response to climate in the Loess Plateau, China

Exploring land use/cover (LULC) change is essential for the sustainable development of ecologically fragile areas. The main objective of this study was to clarify the characteristics and differences in the spatiotemporal changes of LULC on the Loess Plateau (LP) based on the transfer matrix and land use dynamics and to quantitatively describe the impact of natural factors on LULC using a geodetector. The results indicated that the overall LULC change in the LP was characterized by a decrease in the area of cropland, grassland, and bare land, and an increase in the area of woodland and built-up land. This trend shows a clear phase-change characteristic around 2000. LULC changes were primarily affected by human activities in the southeastern agricultural region. The project of returning farmland to forest and grassland had a great impact on LULC change in the central region. Vegetation was sensitive to temperature and precipitation, and the impact of LULC change was significantly higher than that in the humid region in the northwest arid region. NDVI, PRE, and TEM were determined to be the main contributors to LULC changes in the LP. These results provide a scientific basis for the sustainable development of LP.

Impacts of land use structures on ecosystem services relationships within specialized tea planting regions: a case study of Anxi County

The increasing demand for tea has resulted in the swift expansion of tea plantations, leading to significant alterations in the local ecosystem. This has garnered considerable attention. However, research on rationally modifying land use structures (LUSs) in specialized tea regions to achieve a balance with ecosystem services (ESs) and enhance their synergistic effects remains limited. In this study, we quantified the values of water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ) by the InVEST model, utilized K-means clustering to categorize the LUSs of the village areas in Anxi County from 2010 to 2020, and then investigated the influences of the LUSs on the ESs by the improvement of the constraint line tool, according to which we utilized the ecosystem services trade-off degree (ESTD) and the Pearson correlation coefficient to explore the trade-offs and synergies among ecosystem services. The findings indicated that: (1) LUSs in Anxi County are tea garden structure (TS), forest land-tea garden structure (FTS), and construction land-cropland-tea garden structure (CCTS); (2) In LUSs, to achieve a balance among WY, SC, CS, and HQ, the dominant land use proportions were as follows: 0.5 for tea plantations in TS; a range of 0.55–0.6 for forest land and 0.05–0.1 for tea plantations in FTS; and CCTS, 0.25–0.3 for built-up land, 0–0.1 for cropland, and 0.2 for tea plantations; (3) The trade-offs and synergies of ESs vary across different LUSs. The synergy is particularly evident in FTS. Increasing the quantity of forest area is helpful in enhancing the synergy of ESs. This study offers an analysis of the effect of LUSs on ESs and their interconnections in specialized tea planting regions. It serves as a valuable insight into informing urban planning for future land usage and ecological conservation efforts.