Proportion Of Construction Land Research Articles

Spatiotemporal Evolution and Driving Factors of Land Use Carbon Emissions in Jiangxi Province, China

Analyzing the spatiotemporal changes and influencing factors of carbon emissions generated by land use is of great importance for improving land use structure and promoting regional low-carbon economic development. This study, based on remote sensing and statistical yearbook data from 1995 to 2020, calculated the carbon emissions from land use in Jiangxi Province, China. Multiple spatial analysis methods and the logarithmic mean Divisia index were used to elucidate the spatiotemporal evolution and driving factors of carbon emissions, and the findings revealed the following: (1) The spatiotemporal changes in land use in Jiangxi Province during 1995–2020 were substantial as forest land accounted for 65% of the entire land area, while construction land increased by 98.1%. Cultivated land decreased the most, followed by forest land. (2) There was a fourfold rise in carbon emissions in Jiangxi Province, driven primarily by construction land, and northern areas produced higher carbon emissions compared with central and southern regions. Forest land was the main carbon sink. (3) Economic development (257.36%) and the impact of the proportion of construction land (211.31%) were the primary factors contributing to the increase in carbon emissions from land use, while other factors had inhibitory effects. This study transformed the macroscale low-carbon development strategy of cities into targeted local policies, and the research theories and methods adopted could provide scientific reference for other regions in urgent need of carbon reduction worldwide.

Spatiotemporal pattern and obstacle factors of coupling relationship between habitat quality and urbanization level in the Yellow River Basin, China.

Land use change stands as the primary factor influencing habitat quality (HQ). Clarifying the spatiotemporal change and the obstacle factors of the coupling relationship between HQ and urbanization level (UL) can provide imperative references for achieving sustainability in the Yellow River Basin (YRB). This study is based on the InVEST model, spatial autocorrelation, and obstacle factor analysis to measure the spatiotemporal dynamics and impediments of the coupling relationship between HQ and UL from 2000 to 2020 in the YRB. The findings were as follows: (1) From 2000 to 2020, the HQ showed a tendency of rise first and then fall, with the pattern of"High in the middle and west, low in the east"; (2) from 2000 to 2020, the UL had an upward trend, with the pattern of"Low in the west, high in the middle and east"; (3) the coupling and coordinationlevel of HQ and UL in the YRB changed from extreme incoordination to verge of coordination, and it had a distribution pattern of "High in the east, low in the west", with the high-value area expanding to the east and the low-value area shrinking to the west. (4) Location condition, climate, proportion of construction land, vegetation index, and proportion of non-agricultural employment are the main obstacle factors that determined the coupling and coordination of the HQ and UL.

Multi-scenario analysis and optimization strategy of ecological security pattern in the Weihe river basin

For many years, the Weihe River Basin (WRB) has struggled to achieve a balance between ecological protection and economic growth. Constructing an Ecological Security Pattern (ESP) is extremely important for ensuring ecological security (ES). This study employed a coupling of multi-objective programming (MOP) and the patch-generating land use simulation (PLUS) model to project land use change (LUCC) in 2040 across three scenarios. Leveraging circuit theory, we generated ecological corridors and identified key ecological nodes, enabling a comparative analysis of ESPs within the WRB. The main results showed that: (1) The Ecological Protection (EP) scenario showed the highest proportions of forestland, grassland, and water, indicating an optimal ecological environment. Conversely, the Economic Development (ED) scenario features the greatest proportion of construction land, particularly evident in the rapid urban expansion. The Natural Development (ND) scenario exhibits a more balanced change, aligning closely with historical trends. (2) The ecological source areas in the EP scenario is 13,856.70 km2, with the largest and most intact patch area. The ecological source patches that have been identified in the ED scenario exhibit fragmentation and dispersion, encompassing a total area of 8018.82 km2. The ecological source areas in the ND scenario is most similar to the actual situation in 2020, encompassing 8474.99 km2. (3) The EP scenario demonstrates minimal landscape fragmentation. The ED scenario presents a more intricate corridor pattern, hindering species and energy flow efficiency. The ND scenario is more similar to the actual distribution in 2020. Protecting and restoring key ecological nodes, and ensuring the integrity and connectivity of ecological sources are crucial for ESP optimization in various scenarios. Combining all results, we categorize the WRB's spatial pattern into "three zones, three belts, and one center" and offer strategic suggestions for ecological preservation, promoting sustainable local ecological and socioeconomic development.

The nexus between urbanization and ecosystem services balance in China: A coupling perspective.

Urbanization inevitably interfered with the supply and demand of ecosystem services (ESs), which has a crucial impact on the ESs balance. Scientific exploration and clarification of the coupling and decoupling relationship between them can effectively reveal the disturbance of urbanization to the ecosystem, which can help to reasonably manage and protect the ecosystem. Previous studies have paid more attention to the coupling relationship but less attention to the decoupling relationship. This study comprehensively reflected urbanization from the three aspects of construction land, population, and economy and used the evaluation matrix to measure ESs. On this basis, coupling and decoupling analyses were taken to fully clarify the complex relationship between urbanization and ESs balance in China, so as to provide a reference for the formulation of relevant policies. Coupling aspect, the coupling degrees between the proportion of construction land (CLP) and ESs balance index (ESBI) were higher only in the central and eastern plains. The coupling degrees between population density (PD) and ESBI, economic density (ED) and ESBI, and land development index (LDI) and ESBI were only lower in the central and eastern plains than in other regions. Decoupling aspect, strong, weak negative, weak, and strong negative decoupling were the main decoupling types between urbanization and ESs balance in China. Among them, the proportion of the strong decoupling type is much higher than other types, which proves the opposite relationship between the two. Weak decoupling can not only promote economic growth and social development but also protect the ecological environment and biodiversity, which is a type of sustainable development and an ideal state that urbanization should pursue. The results can provide scientific guidance for the formulation of differentiated ecosystem management policies.

Spatiotemporal Characteristics and Driving Factors of Ecosystem Regulation Services Value at the Plot Scale

The value of ecosystem regulation services (ERSV) is a crucial aspect of gross ecosystem product (GEP). Understanding and mastering the spatiotemporal evolution characteristics and driving factors of ERSV is essential for the efficient management of regional ecosystems. This study proposes an ERSV accounting model at the plot scale and uses the barycentric analysis method, the optimal parameters-based geographical detector model (OPGD), and the constraint line extraction method to analyze the spatiotemporal evolution characteristics, main driving factors, and constraint rules of ERSV in Yunyang District, Hubei Province in 2016, 2018, 2020, and 2021. The results show that (1) In the temporal dimension, the overall ERSV of the district increased by CNY 1.664 billion from 2016 to 2021, with an increase rate of 3.68%. The contribution values of climate regulation function and water retention function to ERSV was significant. (2) In the spatial dimension, the ERSV was high in the north and south and low in the middle, with high-value areas mainly located in woodland and wetland areas. The center of gravity of the ERSV increase shifted to the southwest by 12,455.42 m, while the center of gravity of the reduction shifted to the southwest by 3582.79 m from 2016 to 2021. (3) The interaction of any two driving factors had greater explanatory power for the spatial differentiation of ERSV than that of a single driving factor, and all of them showed nonlinear or double factor enhancement characteristics. The human active index (HAI) and construction land proportion (CLP) were the leading anthropogenic factors, while the land surface temperature (LST) and NDVI were the leading natural factors. (4) The ERSV could maintain a high and stable value output when the HAI was less than 0.3, CLP was less than 15%, LST was between 18 and 22 °C, and NDVI was greater than 0.5. These results can guide the practices of ecology, production, and life in Yunyang District and contribute to the high quality and sustainable development of the regional ecology and economy.

The Temporal and Spatial Evolution Characteristics and Driving Factors of Ecosystem Service Bundles in Anhui Province, China

Identifying ecosystem service bundles and their long-term evolutionary characteristics is essential for the overall enhancement of regional ecosystem services, as well as the division and management of functional areas, providing a basis for decision-making in formulating ecological and environmental protection policies, as well as regional development planning. Based on land use, remote sensing, and meteorological data obtained from Anhui Province, this study assessed six important ecosystem service functions, including food production (FP), water yield (WY), carbon sequestration (CS), soil conservation (SC), habitat quality (HQ), and landscape aesthetics (LA), at the township scale in 2000, 2010, and 2020. On this basis, the k-means clustering method was used to identify ecosystem service bundles, analyze the spatio-temporal evolution trajectory of service bundles, and explore the driving factors of the spatio-temporal evolution of ecosystem service bundles using GeoDetector 2015 The results indicate the following: (1) At the spatial level, diverse ecosystem services demonstrate pronounced spatial differentiation. The distribution pattern of HQ, carbon fixation, and SC services is generally lower in the north and higher in the south, with areas of high value predominantly located in the western Dabie Mountains and the mountains of Southern Anhui. Conversely, FP services exhibit the reverse pattern, and WY services display a gradual increase from north to south, while cultural services are more dispersed, with areas of high value primarily located in the western Dabie Mountains, the Yangtze River Basin, and other locations. On the temporal scale, WY, SC, and FP services mainly exhibit an increasing trend, marked by a significant increase, whereas other services tend to present a decreasing trend. (2) Anhui Province can be categorized into four distinct types of service bundles: the grain production bundle (GPB), mountain ecological conservation bundle (MECB), urban living bundle (ULB), and core protection bundle (CPB). Ecosystem service bundles exhibit clear spatial differentiation, and identical service bundles demonstrate substantial clustering in space. Between 2000 and 2020, ecosystem service bundles displayed a marked spatio-temporal evolution, with the prevalence of GPBs diminishing, whereas the share of ULBs progressively increased, and the number of MECBs and CPBs remained largely stable. (3) In the spatio-temporal evolution process, the average annual precipitation, the proportion of forest land, and slope constitute the principal natural factors influencing the spatio-temporal evolution of ecosystem service bundles, while the proportion of construction land represents the primary socio-economic factor, with natural factors exerting a more significant influence than socio-economic factors.

Spatiotemporal evolution and driving factors of ecosystem service bundle based on multi-scenario simulation in Beibu Gulf urban agglomeration, China.

Rapid urbanization is profoundly impacting the ecological environment and landscape patterns, leading to a decline in ecosystem services (ES) and posing threats to both ecological security and human well-being. This study aimed to identify the spatial and temporal patterns of ecosystem service bundles (ESB) in the Beibu Gulf urban agglomeration from 2000 to 2030, analyze the trajectory of ESB evolution, and elucidate the drivers behind ESB formation and evolution. We utilized the Patch-generating Land Use Simulation (PLUS) model to establish baseline (BLS), carbon sequestration priority (CPS), and urbanization priority (UPS) scenarios for simulating land use patterns in 2030. Following the assessment of ecosystem service values (ESV) through the equivalent factor method, we identified the spatiotemporal distribution patterns of ESB using the K-means clustering algorithm. By employing stability mapping and landscape indices, we identified and analyzed various types of ESB evolutionary trajectories. Redundancy analysis (RDA) was employed to pinpoint the drivers of ESB formation and evolution. The results revealed that from 2000 to 2030, land use changes were primarily observed in cropland, forestland, and construction land. Between 2000 and 2020, 92.88% of the region did not experience shifts in ESB types. In UPS, the ESB pattern in the study area underwent significant changes, with only 76.68% of the region exhibiting stabilized trajectories, while the other two scenarios recorded percentages higher than 80%. Key drivers of ESB-type shifts included initial food provision services, elevation, slope, changes in the proportion of construction land, and population change. This multi-scenario simulation of ESB evolution due to land use changes aids in comprehending potential future development directions from diverse perspectives and serves as a valuable reference for formulating and changing ecological management policies and strategies.

Evolution characteristics, carbon emission effects and influencing factors of production-living-ecological space in Taihang Mountain poverty belt, China

The rapid advancement of urbanization and industrialization in China has gradually spread to the poor mountainous areas, which has not only brought about rapid economic development but has also caused the increasing competition for production-living-ecological spaces (PLES) and many ecological and environmental problems, carbon emissions have also increased. As an economically less developed and ecologically fragile area in China, whether the transition of the PLES in the mountain poverty belt has unique characteristics? How the PLES transition in mountainous areas affects carbon emissions and what are the important factors affecting carbon emissions? To explore these issues in depth, we studied the Taihang Mountain area in Shijiazhuang (TMS) using remote sensing image interpretation data from 2000, 2010, and 2020, and we analyzed the PLES evolution characteristics, carbon emission changes, carbon emission effects and its influencing factors of PLES. The results are as follows: 1) The TMS was dominated by ecological and production space. From 2000 to 2020, the production space decreased by 384.66 km2, the ecological space increased by 123.80 km2, and the living space increased by 260.86 km2. Agricultural production space was mainly converted to ecological and rural living space. Industrial and mining productive space was mainly converted to agricultural productive space and urban living space. 2) The study area was in a state of carbon deficit, the transition of ecological space and agricultural productive space to industrial and mining productive space and living space were the main transition types caused the carbon emissions increasing, and that of industrial and mining productive space to agricultural productive space was the main type caused the carbon emissions decreasing. 3) The proportion of construction land, urbanization rate and proportion of secondary industry are the main factors leading to the increase of carbon emissions. Per capita energy consumption, forest coverage and proportion of tertiary industry are the main factors leading to the decrease of carbon emissions. This can provide new ideas for research on carbon emissions from land-use changes and a theoretical basis for the optimization of territorial space in the mountainous areas of China.

Flood Risk Identification of Zhengzhou Metropolitan Area Based on Invest Model

Rainstorm and urban flood are always one of the most serious natural disasters in China due to the change of ecological environment, terrain conditions and climate change. Rainstorm and flood disasters seriously threaten the security and development of regional economy and society. Therefore, how to identify the high-risk areas of flood disasters is an important issue to be solved in the prevention of flood disasters. Taking Zhengzhou metropolitan area as the research object, based on the Urban Flood Risk Mitigation module of InVEST model, the vulnerability of flood disaster, the supply capacity of flood regulation service and the supply-demand ratio of ecosystem service in the study area are obtained through analysis, and the areas vulnerable to flood disaster in the study area are identified. The results show that : (1) The flood regulation service supply capacity is mainly manifested in the spatial distribution pattern of high in the west and low in the east. The northern Jiaozuo, northern Xinyang, western Zhengzhou and western Xuchang have higher supply service levels. (2) Affected by factors such as population density, economic development level and land use development degree, there are also obvious spatial differences in the spatial distribution of flood regulation service demand. The high demand area of flood regulation service is concentrated in the central urban area. (3) In areas with low population density and high vegetation coverage, the high supply and low demand of flood regulation services lead to a higher service supply-demand ratio. In the central urban area of the city, due to the large proportion of construction land and dense population, the supply and demand of services is relatively low.

Analysis on spatio-temporal evolution and influencing factors of ecosystem service in the Changsha-Zhuzhou-Xiangtan urban agglomeration, China

Introduction: It is of great significance to strengthen the evaluation research and driving force analysis of ecosystem services value for the rational utilization and protection of the ecological environment of Changsha-Zhuzhou-Xiangtan (CZT) urban agglomeration and the promotion of the integration of urban agglomeration.Methods: Based on the remote sensing image data, the spatial and temporal evolution characteristics and influencing factors of the ecosystem services value of CZT urban agglomeration were analyzed by the methods of ArcGIS10.2, Geoda, value equivalent and spatial statistics.Results: The results showed that: 1) From 2000 to 2020, the total value of ecosystem service in the CZT urban agglomeration decreased gradually, with an overall decrease of 4,381.07 × 106 yuan. In the past 20 years, the ecosystem service Value (ESV) of cultivated land, forest land and grassland had declined, but the ESV of water area and unused land had fluctuated, and the single ESV had declined. 2) From 2000 to 2020, the spatial distribution of ESV in the CZT urban agglomeration showed an obvious pattern of “low in the middle and high in the surrounding areas”, and the changes were quite different in different periods. 3) The spatial correlation between ESV and distance from county government, distance from railway, proportion of construction land, NDVI, population density, economic density, slope and precipitation were significant. The spatial distribution of the distance from the county government, the distance from the railway, NDVI and ESV were similar; the population density and economic density were consistent with the spatial distribution of ESV; and the spatial distribution of construction land proportion, slope, precipitation and ESV were different.Discussion: The results of the study can provide some reference for the further development of ecological protection policies and related planning in urban agglomerations.

Design of a land use change prediction model incorporating neural networks

Abstract Land use change has gradually developed into a core area of global environmental change research. In this paper, we use object-orientated modeling to construct a model that combines Markov models, neural networks, and cellular automata. We extend the Markov model to the traditional CA, fully utilizing the advantage of ANN in simplifying the definition of land use transformation rules and obtaining a large number of spatial variable parameters of the model. This successfully simplifies the structure of the model and the definition of transformation rules. We apply the constructed Ann-CA-Markov land use change analysis model to the evolution and prediction of land use in County A. It has been found that the proportion of arable land area in County A decreased from 23.3% to 12.1%, and the proportion of construction land increased from 28.07% to 50.87%. From 2000 to 2020, other land continued to converge into construction land in large quantities, so the land area of County A increased from 1224.73km² to 1295.15km² in 2020. The area of arable land converted out is the largest among the five types of land, with an arable land area of only 308.11km² by 2020. The probability of conversion of four land types, namely, arable land, forest land, grassland, and watershed, to construction land is 21.7%, 10.5%, 10.9%, and 9.2%, respectively, by 2030, while the probability of conversion of construction land to arable land is 21.7%, 10.5%, 10.9%, and 9.2%, respectively. The probability of converting land to cropland is 13.9%. The model constructed in this paper shows strong performance in the analysis of land use change evolution and prediction of County A, which is in line with the design expectation and makes an innovative exploration for realizing the effective simulation of spatial and temporal land use changes.

Interactive relationship and zoning management between county urbanization and ecosystem services in the Loess Plateau

The interaction between urbanization and ecosystem services (ESs) is a hot topic in the modern human-earth system science. Currently, most studies only focus on the effects of urbanization on ESs supply, few studies have accurately quantified the ESs demand and explored the spatial–temporal coupling interactions between urbanization and ESs supply–demand balance. To address these gaps, this study used process-based modeling to estimate the absolute number of ESs demand. Ecosystem supply–demand ratio (ESDR) is employed to measure the ESs balance. Finally, pearson correlation analysis, coupling coordination degree model, and bivariate local Moran’s I method were used to explore the interactive relationship between urbanization and ESs balance in the Loess Plateau (LP). Results indicated that the LP experienced rapid urbanization with characteristics of faster economic urbanization than land and population urbanization from 2000 to 2018. Negative correlations between construction land proportion and ESDR enhanced over time. Although the coupling coordination degree between urbanization and ESDR increased, most counties were mild incoordination and basic coordination. The spatial interaction of urbanization and ESDR was divided into four types: co-promotion type, ecological lag type, urbanization lag type, and co-loss type. This study can contribute to providing a scientific reference and practical guidance for coordinating ecological protection and high-quality development in underdeveloped areas.

Spatial and temporal driving mechanisms of ecosystem service trade-off/synergy in national key urban agglomerations: A case study of the Yangtze River Delta urban agglomeration in China

Clarifying the ecosystem service (ES) trade-off/synergy is a prerequisite for scientific implementation and optimization of integrated ecological system management strategies, especially in highly urbanized areas with declining eco-environmental carrying capacity. This study took China's Yangtze River Delta urban agglomeration (YRDUA) as an example. First, we used a pixel-by-pixel analysis based on dynamic spatial correlation to quantify the trade-off/synergy among the 6 primary ESs' change amounts from 2005 to 2020 (habitat quality, soil retention, carbon sequestration, water yield, food production, leisure and recreation). Then, we integrated the multiple ES trade-off/synergy and explored their driving factors by spatial cluster analysis and geographically and temporally weighted regression (GTWR). The results showed synergy between supporting and regulating services predominated while regulating services were mostly trade-offs with regulating and cultural services. The trade-off/synergy of the 15 ES functional pairs within YRDUA can be downscaled into 4 ES trade-off and synergy bundles. Furthermore, the climate drivers (annual highest temperature (TH), annual total precipitation (PRE), annual total solar radiation (SRT)) significantly influenced the spatial heterogeneity of the 6 ESs in the YRDUA. The socio-economic drivers (night light index (NLI), gross domestic product (GDP)) and land use drivers (proportion of arable land (ALP), proportion of construction land (CLP), proportion of woodland (WLP)) had a more remarkable power of explanation for the ES temporal variation and ES trade-off/synergy. YRDUA and other urban agglomerations can use the study's findings to develop differentiated integrated ecological management strategies.

Scale effects on the supply–demand mismatches of ecosystem services in Hubei Province, China

Understanding the patterns, relationships, and driving forces between ecosystem services (ESs) supply–demand at multiple spatial scales can facilitate sustainable hierarchical management. However, the scale effects of ESs supply–demand mismatches were typically ignored, resulting in inadequate targeted ecosystem promotion policies. This study identified the supply–demand mismatches of the key ESs (grain production, water yield, carbon sequestration, and soil conservation) using the ecological supply–demand ratio and bivariate Moran's I at three grid and county scales from 2000 to 2020 in Hubei Province, China. Then the spatial regression models were applied to explore the driving forces of these mismatches. The major results revealed that (1) Hubei Province and counties located away from urban areas were self-sufficient in the ESs supply–demand, but the numbers of these counties declined over the twenty years. The characteristics of ESs mismatches in some patches may be obscured at coarser scales. (2) The directions of socioecological drivers were robust, but their intensities changed significantly at the four scales. The normalized difference vegetation index was the primary positive driver at the fine scale, while population, economy, and proportion of construction land became dominant drivers at coarser scales. Factors influencing mismatches were more diverse at the fine scale compared to the coarse scale. (3) Efficient strategies were scale-dependent and place-based. Different management units should clarify their responsibilities and strengthen linkages between upper and lower levels to achieve sustainable ESs development. At the provincial level, strengthening interregional cooperation and allocating surplus grain and water resources from the southwest to urban regions contributes to balancing regional ESs. At the county level, adopting region-specific strategies based on delineating ESs management zones is crucial. At finer management levels, incorporating micro-scale mismatch locations and natural background information can provide valuable guidance for localized ecological protection and restoration projects. The findings underscore the strengths of conducting assessments of ESs supply–demand at multiple scales, enabling different government levels to enhance effective ecosystem management and prevent misinformation.

Considering Regional Connectivity and Policy Factors in the Simulation of Land Use Change in New Areas: A Case Study of Nansha New District, China

Numerous emerging development areas worldwide are receiving attention; however, current research on land use change simulation primarily concentrates on cities, urban clusters, or larger scales. Moreover, there is a limited focus on understanding the impact of regional connectivity with surrounding cities and policy factors on land use change in these new areas. In this context, the present study utilizes a cellular automata (CA) model to investigate land use changes in the case of Nansha New District in Guangzhou, China. Three scenarios are examined, emphasizing conventional locational factors, policy considerations, and the influence of regional connectivity with surrounding cities. The results reveal several key findings: (1) Between 2015 and 2021, Nansha New District experienced significant land use changes, with the most notable shifts observed in cultivated land, water area, and construction land. (2) The comprehensive scenario exhibited the highest simulation accuracy, indicating that Nansha New District, as an emerging area, is notably influenced by policy factors and regional connectivity with surrounding cities. (3) Predictions for land use changes in Nansha by 2030, based on the scenario with the highest level of simulation accuracy, suggest an increase in the proportion of cultivated and forest land areas, alongside a decrease in the proportion of construction land and water area. This study contributes valuable insights to relevant studies and policymakers alike.

Spatial–Temporal Changes in Land Use and Their Driving Forces in the Circum-Bohai Coastal Zone of China from 2000 to 2020

Over the past two decades, the location and morphology of the coastline, as well as the land use/land cover (LULC) in the Circum-Bohai region in China, have undergone significant changes due to rapid industrialization and urbanization. Analyzing the temporal and spatial variation in coastal lines and LULC can provide a meaningful basis for the rational allocation of land resources. Using Landsat TM/OLI series dates from the Google Earth Engine (GEE) platform, this study applied the Linear Superposition Water Index (LSWI) and the Otsu threshold method (OTSU) algorithm to extract and analyze the coastline of the Circum-Bohai region. Additionally, the Random Forests (RF) method was employed to extract LULC information in the coastal zone. Using the geographical detector, we further explored the influence of social and economic factors, as well as natural factors, on spatial differentiation mechanisms of LULC change in the Circum-Bohai. Our results show that between 2000 and 2020, the Circum-Bohai coastline generally expanded towards the ocean by a total of 1062.99 km. The highest rate of change occurred during 2010 to 2015, and human activities were the primary cause of most of the changes, with the exception of the Yellow River Delta, where natural factors were dominant. The main types of LULC in the study area from 2000 to 2020 were farmland and construction land. The area of farmland proportion decreased by 1.75%, while the area of construction land proportion increased from 16.73% to 29.54%. Our findings indicate that the degree of land use in the Circum-Bohai is deepening. Based on our factor detection analysis, the added value of the secondary industry was the most critical influencing factor on LULC. Furthermore, the combined effect of the added value of the secondary industry and gross domestic product (GDP) has a significant driving impact on LULC. These findings can provide reference and data support for the sustainable development and comprehensive management of land resources. The relevant departments can use these results to prompt corresponding policies for the rational allocation of land resources.

Land Use and Ecosystem Services Evolution in Danjiangkou Reservoir Area, China: Implications for Sustainable Management of National Projects

The South-to-North Water Diversion Project (SNWDP) is one of the largest cross-basin and cross-region water transfer projects in the world. The Danjiangkou reservoir area, a haven of diverse species, serves as a core water source for the Central Line of the SNWDP. Yet, less research has been conducted on changes in land use and ecosystem services (ESs) in the Danjiangkou reservoir area in the context of the implementation of the SNWDP and other national projects. In this study, we aim to reveal evolutions of land uses and ESs in the Danjiangkou reservoir area and the response of ESs to natural and socio-economic factors. This is essential to enhance the regional sustainable management of the Danjiangkou reservoir area. Based on classified land use maps and the InVEST model, we first analyzed the land use changes and evaluated three typical types of ESs (i.e., water yield (WY), carbon storage (CS) and habitat quality (HQ)) in the Danjiangkou reservoir area during 2000 to 2018. Then, we detected the spatial clustering characteristics and tradeoffs and synergistic relationships of multiple ESs through hot spot analysis and correlation analysis. Finally, we adopt the geographical detector model (GDM) to identify key driving factors of ESs changes. The results show that: (1) During 2000–2018, the area of arable land and woodland decreased by 1.65% and 0.8%, respectively, while the proportion of construction land and water area increased by 1.31% and 1.39%, respectively. (2) The greatest decrease was in WY, decreasing by 59%, while the change in HQ was relatively stable, but showed spatial heterogeneity. (3) The northern, southern and western districts of the reservoir area showed mainly synergies among multiple ESs, while other regions showed mainly trade-offs. (4) Road network density, proportion of construction land and normalized difference vegetation index are the leading factors for ESs variations. These findings can provide reference for formulating more reasonable ecological protection strategies, so as to realize the sustainable management of SNWDP and its headwaters region.

Hazard assessment model of ground subsidence coupling AHP, RS and GIS – A case study of Shanghai

Urban ground subsidence (GS) causes ground elevation loss, threatens the safe operation of various facilities, and affects surface runoff and hydrological circulation. Therefore, it is vital to monitor the current status of GS to predict and evaluate potential risks to sustainable urban development. Sentinel SAR images from 2019 to 2020 combined with the data from the 2019–2020 Statistical Yearbook were used as data sources. Based on PS-InSAR and SBAS-InSAR, GIS was integrated with the AHP method. A ground subsidence risk evaluation index (REI) suitable for Shanghai was developed regarding three aspects of the amount of accumulated land subsidence (RS obtained): subsidence rate, and terrain elevation. The vulnerability evaluation index (VEI) was established from five aspects: population density, GDP per unit area, the proportion of construction land, viaduct density, and metro density. We introduced the fuzzy AHP method to complete the risk assessment of ground subsidence in Shanghai and obtained the ground subsidence hazard index (GSHI). We used GIS superimposed remote sensing images to visualize the individual evaluation indicators REI, VEI, and GSHI. Using GIS superimposed remote sensing images, various evaluation indicators and GSHI were visualized. Based on the evaluation results, targeted prevention and control recommendations are provided. The results of this research can provide a basis for scientific decision-making regarding Shanghai’s territorial spatial planning and socio-economic development.

The driving mechanisms for human settlement and ecological environment in the upper minjiang watershed, China

The Chinese urbanization process is undergoing rapid development and intensification. There is, however, little awareness of spatial development in rural areas, particularly in watersheds that are relatively backward. Consequently, human settlements have been disrupted and environmental damage has been caused. The upper reaches of the Minjiang River are not yet aware of the limited space resources and environmental elements due to topography, climate, and other factors, resulting in an unbalanced development. Human settlements and ecological environments are examined in this paper in light of the adaptive development strategy of the upper reaches of the Minjiang River watershed. This paper establishes a “habitat-ecology” variable system for the purpose of adaptability research. The study identified 35 explanatory variables, including 17 in the category of human settlements and 18 in the category of ecological environment. A total of 12 relevant research sample areas have been selected, including five target sample areas and seven comparison sample areas. As a result of differential analysis and correlation research, explanatory variables with high significance were identified as characteristic variables. In addition, a driving mechanism between human settlement and ecological environment is determined using correlation analysis results, optimal subset equations, and independent effects of variables. The results show that in the “habitat-ecology” driving mechanism model: (1) In terms of human settlement, factors such as population density, proportion of construction land, and service scope of medical facilities are the most prominent; (2) In terms of ecological environment, factors such as regional proportion, per capita water area, net flow, and grassland coverage are the most prominent; (3) Based on the element configuration of the above two research subjects, the driving mechanism with human settlement as the driving force and ecological environment as the carrying capacity is obtained.

Spatial-Temporal Variations in of Soil Conservation Service and Its Influencing Factors under the Background of Ecological Engineering in the Taihang Mountain Area, China

Soil conservation (SC) plays an important role in maintaining regional land productivity and sustainable development. Ecological engineering (EE) is being implemented in different countries to effectively alleviate the damage to the ecological environment and effectively protect soil and food security. It is important to determine whether or not the SC capacity becomes stronger after the implementation of EE and whether or not EE has a notable impact on SC in different altitude zones. The exploration of the influencing mechanism and identification of the dominate influencing factors in different geographical regions needs to be improved. In this study, the soil conservation services (SCSs) from 1980 to 2020 in the Taihang Mountain area was assessed using the integrated valuation of ecosystem services and trade-offs (InVEST) model, and the spatial and temporal distributions and influencing factors were explored. The results showed the following: (1) the average SCSs exhibited an increasing trend from 1980 to 2020 on the whole, and the rate of increase reached 50.53% during the 41-year period. The rate of increase of the SCSs varied in the different EE implementation regions, and it was significantly higher than that of the entire study area. (2) The spatial distribution of the SCSs was highly heterogeneous, and the high SCS value areas were coincident with the high-altitude areas where forest and grassland occupied a large proportion. The low value areas were mainly located in the hilly zone or some of the basin regions where the proportion of construction land was relatively high. (3) The distribution pattern of the SCSs was the result of multiple factors. The EE intensity had the strongest explanatory power for the SCSs in the hilly zone, explaining 34.63%. The slope was the most critical factor affecting the SCSs in the mid-mountain and sub-alpine zones. The slope and normalized difference vegetation index (NDVI) had the greatest interactions with the other factors in the three altitude zones, especially in the high-altitude regions. The quantitative analysis of the SCSs and the influences of EE and natural factors on the SCSs revealed the heterogeneity in the mountainous areas. These results also provide a scientific basis for the reasonable implementation of EE and sustainable management of SCSs in the Taihang Mountain area.