Low-value Areas Research Articles

Spatio-temporal analysis of the impact of land urbanization on the gross primary productivity of vegetation in the Middle Reaches of the Yangtze River Urban Agglomeration: new evidence from the township scale

The urgent need to maintain ecosystem provisioning services and achieve urban sustainable development goals has led to a long-standing focus on the driving effects of land urbanization (LU) in the Middle Reaches of the Yangtze River Urban Agglomeration (MRYRU) on vegetation cover system productivity. Previous studies have lacked consideration for the long-term correlation between land urbanization (LU) and the Gross Primary Productivity (GPP) of vegetation, as well as the spatial non-stationarity of LU’s impact in the region. This study is based on land cover remote sensing data and GPP imagery data to monitor the long-term evolution trends of LU and GPP in MRYRU from the perspectives of townships and grids. It further investigates the spatial correlation and clustering characteristics between the two using bivariate spatial autocorrelation method. Additionally, a Geographically and Temporally Weighted Regression (GTWR) model was employed to analyze the spatial effects of LU on GPP. The results indicate that the GPP of MRYRU grows to 1572.88gCm-2a-1 with an average annual growth rate of 0.848% from 2000 to 2020. High-value areas are distributed in the central and eastern mountainous of the urban agglomeration, while low-value areas gradually formed an “n”-shaped clustered distribution pattern. The negative spatial autocorrelation between LU and GPP shows a general upward trend, and Low-High is the dominant agglomeration type, concentrated in Hengyang and some mountainous cities in Jiangxi Province. The overall negative impact of land urbanization on GPP in MRYRU is maintained in the spatially nonstationary pattern of driving coefficients, with negative impact areas mostly concentrated in the city’s main city zone and positive impact areas concentrated in the urban agglomeration’s mountainous townships. This study provides support for MRYRU to adopt more resilient land optimization management strategies and vegetation ecological restoration plans.

Microscopic Pore Structure Characteristics and Fluid Mobility in Tight Reservoirs: A Case Study of the Chang 7 Member in the Western Xin’anbian Area of the Ordos Basin, China

This research addresses the limited understanding of movable fluid occurrence characteristics in the Chang 7 reservoir by employing mercury injection capillary pressure, constant-rate mercury injections, and nuclear magnetic resonance methods. This study investigates the microscopic pore structure characteristics and movable fluids in the tight reservoir of the western Xin’an region, located in the Ordos Basin. The finding reveals that as permeability decreases, the distribution of the throat radius becomes more concentrated in the low-value area, resulting in a narrow distribution range with high curve peaks. Conversely, with an increasing permeability, the distribution range expands towards the high-value area while the curve peak decreases. This research underscores the significance of the throat radius, especially the main flow throat radius, in constraining the permeability of rock samples. Furthermore, this study highlights a stronger correlation between permeability and movable fluid saturation than porosity. This finding emphasizes the importance of considering movable fluid saturation when assessing reservoir characteristics. Notably, the throat radius plays a crucial role in influencing the occurrence characteristics of movable fluids, with a smaller throat radii posing hindrances to fluid flow in the reservoir. Additionally, the presence of clay minerals in the reservoir leads to pore segmentation and increased fluid flow resistance, ultimately reducing the saturation of movable fluids. I must be understood that these factors are essential for developing and producing reservoirs with similar characteristics. In conclusion, the insights gained from this study hold considerable theoretical value and provide essential references for developing and producing reservoirs with tight characteristics, particularly in the western Xin’an region of the Ordos Basin.

Assessing Spatial Variation and Driving Factors of Available Phosphorus in a Hilly Area (Gaozhou, South China) Using Modeling Approaches and Digital Soil Mapping

Soil fertility plays a crucial role in crop growth, so it is important to study the spatial distribution and variation of soil fertility for agricultural management and decision-making. However, traditional methods for assessing soil fertility are time-consuming and economically burdensome. Moreover, it is hard to capture the spatial variation of soil properties across continuous geographic space using the conventional methods. As key techniques of digital soil mapping (DSM), spatial interpolation techniques have been widely applied in soil surveys and analysis in recent years, since they can predict soil properties at unknown points in continuous space based on limited sample points. However, further research is needed on spatial interpolation models for DSM in regions with variable climates and complex terrains, which are characterized by strong spatial variation in both environmental variables and soil fertility. In this study, taking a typical hilly area in a subtropical monsoon climate, i.e., Gaozhou, Guangdong Province, China, as an example, the performances of four popular spatial interpolation models (Random Forest (RF), Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function) for digital soil mapping on available phosphorus (AP) are compared. Based on RF, the spatial variation and its driving factors of the AP of Gaozhou are then analyzed. Furthermore, by selecting three typical truncation lines from different directions, the correlations between environmental variables and AP in different spatial positions are demonstrated. The root mean square error (RMSE) results of the above four models are 32.01, 32.08, 32.74, and 33.08, respectively, which indicate that the RF has a higher interpolation accuracy. Based on the mapping results of RF, the minimum, maximum, and mean values of AP in the study area are 38.90, 95.24, and 64.96 mg/kg, respectively. The high-value areas of AP are mainly distributed in forested and orchard areas, while the low-value areas are primarily found in urban and cultivated areas in the eastern and western regions. Vegetation and topography are identified as the key factors shaping the spatial variations of AP in the study area. Furthermore, the spatial heterogeneity of the influence strength of altitude and EVI is revealed, providing a new direction for further research on DSM in the future, i.e., spatial interpolation models considering the spatial heterogeneity of the influence of environmental variables.

Spatial correlation analysis and prediction of carbon stock of “Production-living-ecological spaces” in the three northeastern provinces, China

The “Production-Living-Ecological Space” (PLES) is a paramount indicator in the filed of territory space development and optimization in China, under the new era. Exploring the driving factors of the PLES'land expansion is of great significance for improving space utilization, mitigating severe climate changes, and promoting green, healthy and sustainable development. In the background of the “Carbon Emissions Peak and Carbon Neutrality” strategy, analyzing and predicting the carbon stock of PLES is effective to boosting the achievement of ‘Dual-Carbon’ vision. Based on the above research questions， this study constructs the PLES based on statistics about land use (Year 1990, 2000, 2010 and 2020) in three northeastern provinces, and reveals the spatial correlation of PLES’ carbon stock in the research area through ArcGIS spatial analysis and InVEST model. Then, the PLUS model was used to clarify the contribution of each driver to the conversion of space land, and to predict the distribution of the PLES pattern and the carbon stock's spatial correlation in 2030 and 2060 under the Natural-Development Scene and Ecological-Protection-Development Scene. Results show that: (1) The PLES in the three northeastern provinces of China is primarily green ecological space (55.71%) and agricultural production space (38.10%), while industrial production space (3.60%) and urban living space (2.76%) expand significantly, and green ecological space (−0.17%) and blue ecological space (−0.89%) are on a recession trend. Besides, 2000–2010 is the most intense period of all kinds of space land transformation in the study area. (2) Population density, proximity to roads at all levels, annual average temperature and elevation are the prime drivers of PLES’ profile within the scope of the study region, but the contribution rate is significant difference. (3) The urban living space decreases and the green and blue ecological space increases significantly in the predicted years under the scene of Natural-Development and Ecological-Protection development; the pattern of PLES is relatively stable in the predicted years under both scenarios. (4) The spatial correlation of carbon stock is closely related to the distribution of PLES, with the high-value significant regions primarily in the distribution region of green ecological space, otherwise, the low-value significant regions mostly concentrated in the region with complex spatial land use types and large spatial development intensity; the overall structure within the scope of the study region shows a layout of high value areas surrounding low value areas. It can show that insisting on the ecological civilization construction is an effective way to achieve sustainable development and practice the “double carbon” strategy; in the future spatial land use control, ecological protection measures should still be adopted to ensure the sustainable development and positive operation of the study area.

Spatiotemporal Evolution of Land Use Efficiency in Southwest Mountain Area of China: A Case Study of Yunnan Province

The study of land use efficiency (LUE) evaluation and coupled coordination (CC) relationships under the perspective of urbanization can reasonably allocate land resources and contribute to the solution for agriculture, rural areas, and farmers. The LUE evaluation index system is constructed in three aspects: economy, society, and ecology. Then the LUE and CC degrees of Yunnan Province from 2010 to 2020 are measured, and the characteristics of LUE and the relationship of CC in each administrative region at each level are analyzed in space. Besides, the overall LUE and CC relationship in Yunnan Province is described. The study concludes that (1) The urbanization process in Yunnan Province is accelerating, unused land is decreasing, and construction land is increasing. (2) During the study period, the LUE of Kunming was much higher than that of other regions. The economic efficiency of the inner circle cities centered on Kunming is higher, while the economic efficiency of the outer circle cities is lower; social efficiency is increasing year by year except for Nujiang and Diqing, showing a higher pattern in the east than in the west; ecological efficiency is not increasing year by year except for Kunming, Qujing, and Lijiang, showing a higher pattern in the east than in the west; comprehensive efficiency is on the rise, with Kunming and Qujing leading the way with the overall pattern of “east > central > west”. The high-value area is relatively stable, and the low-value area has a clear tendency to shift eastward. (3) The coupling level of economic, social, and ecological efficiency of land use in administrative regions of Yunnan Province is low, but the coupling relationship is gradually optimized, showing the “contiguous effect” and realizing the state of extreme disorder to severe disorder in a large area. (4) The overall CC of three subsystems in Yunnan Province shows a fluctuating upward trend; the comprehensive efficiency index has an upward trend except for a slight decrease in 2017–2018; from 2010 to 2019, ecological and social efficiency is better than economic efficiency.

Spatiotemporal Distributions of Multiple Land Use Functions and Their Coupling Coordination Degree in the Yangtze River Delta Urban Agglomeration, China

In order to gain a comprehensive understanding of land system changes and regional sustainable development, it is crucial to explore the spatiotemporal distributions of multiple land use functions (LUFs). Therefore, herein, considering the Yangtze River Delta urban agglomeration (YRDUA) as the research object, we constructed an evaluation system based on the perspective of production–living–ecological (PLE) land functions. Furthermore, the coupling coordination model, kernel density curve, trend surface analysis, and spatial autocorrelation model were used to examine the spatial and temporal characteristics of LUFs and their coupling coordination and analyze the spatial clustering of the coupling coordination effect in the urban agglomeration from 2005 to 2020. The following results were obtained: The level of PLE functions and its coupling coordination degree in the YRDUA have been improved in the study period, and the distribution of high value areas of different functions is diverse. In terms of the spatial distribution of the coupling coordination degree, the high value areas of production function (PF)–living function (LF) is distributed in “clusters”, the PF–ecological function (EF) demonstrated a single-polarized development structure, and the LF-EF exhibited a multi-core structure. The coupling coordination of the LUFs demonstrated a “high in the east and low in the west” pattern in the east–west direction and an inverted “U” shape in the north–south direction. Moreover, both high-value and low-value areas exhibited a clustering phenomenon, with an evident spatial positive correlation. The results of this study can serve as a reference for the integrated socioeconomic development of the Yangtze River Delta region and the sustainable development of urban land use.

Trade-Off and Synergy Relationships and Spatial Bundle Analysis of Ecosystem Services in the Qilian Mountains

Significant heterogeneity has been observed among different ecosystem services (ES). Understanding the trade-offs and synergies among ES and delineating ecological functional zones is crucial for formulating regional management policies that improve human well-being and sustainably develop and maintain ecosystems. In this study, we used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Carnegie–Ames–Stanford Approach (CASA) models to evaluate the spatial distribution patterns of nine ES (food supply, raw material supply, water resource supply, water connotation, climate regulation, soil conservation, water purification, habitat quality, and entertainment tourism) in the Qilian Mountains from 2000 to 2018. We also investigated the trade-offs and synergistic relationships among ES through Spearman correlation analysis, identified ES hotspots through exploratory spatial data analysis, and identified ES bundles (ESB) using K-means clustering. Our results revealed that water purification and habitat quality remained relatively stable, while food supply, raw material supply, water resource supply, water conservation, climate regulation, soil conservation, and entertainment tourism increased by 1038.83 Yuan·ha−1, 448.21 Yuan·ha−1, 55.45 mm, 7.80 mm, 0.60 tc·ha−1, 40.01 t·ha−1 and 4.82, respectively. High-value areas for water resource supply were mainly concentrated in the high-altitude mountainous area, whereas high-value areas for soil conservation were found in the western and eastern parts of the study area. The low-value areas of water purification were primarily located in the east, while the remaining six services were highly distributed in the east and were less common in the west. Correlation analysis showed that water resource supply, water conservation, and soil conservation exhibited a synergistic relationship in the Qilian Mountains. Moreover, food supply, raw material supply, climate regulation, habitat quality, and entertainment tourism showed synergistic relationships. However, there were trade-offs between food supply and water purification as well as water resource supply, and habitat quality showed a tradeoff with water resource supply, water conservation, and soil conservation. We identified four ESB. The food supply bundle consisted mainly of farmland ecosystems, while the windbreak and sand fixation and ecological coordination bundles were dominant in the Qilian Mountains. Notably, the area of the water conservation bundle increased significantly. Our comprehensive findings on ES and ESB can provide a theoretical foundation for the formulation of ecological management policies and the sustainable development of ecosystems in the Qilian Mountains.

Study on the Temporal and Spatial Distribution of Air Pollutants in Typical Cities of China

The present study selects cities such as Zhengzhou, Kaifeng, Anyang, Hebi, Xinxiang, Jiaozuo, and Puyang along the Yellow River Basin in Henan Province. The data of six pollutants, such as PM2.5, PM10, SO2, CO, NO2, and O3, in various cities from 2019 to 2021, and the monthly primary pollutant data of seven cities in the past five years were collected through various channels. The air quality of the above seven cities was analyzed with the spatial-temporal distribution of pollutants as the research objective and geographic information system as the research tool. The results show that affected by the distribution of key pollution sources and meteorological conditions in the urban area, the PM2.5 concentration generally shows a zonal feature of decreasing from northwest to Southeast. The high-value area is located in the north and west of the integrated area of the seven cities, and the low-value area is located in the Southeast of the seven cities.

The Peri-Urban Gentrification Process in Cisauk Subdistrict, Tangerang Regency, Indonesia

Gentrification is a phenomenon that occurs in many regions. Gentrification is characterized by the influx of more affluent residents into initially low-value areas. This influx increases the value of these areas, potentially leading to the displacement of people who cannot afford to remain in the neighborhood. This study aims to examine the cause and impacts of peri-urban gentrification in Cisauk District, Tangerang Regency. This study uses qualitative and remote sensing-based analysis to investigate gentrification's impact on six Cisauk sub-district villages. We used primary and secondary data for the analysis. The primary data was collected from observations, interviews, questionnaires, and Google Earth Engine data catalog to get Landsat 7 and 8 image-ries. The secondary was collected from the Central Bureau of Statistics. The Landsat data was used to identi-fy the change on the physical aspect, while the others were used to analyze the non-physical aspect. After-ward, positive and negative effects were explored, emphasizing residents' responses and adaptations. The re-sults showed that Cisauk Subdistrict faced a gentrification process driven by locational factors (i.e., proximity to toll road) and local government policies (i.e., spatial planning policy designating it as a high-density residential area). The positive impact of the gentrified area is that the region is developing economically much better, and many areas function better economically and so benefit the region and its people. On the other hand, the negative impacts of gentrified areas are that indigenous people are threatened with being forced to leave their villages, there are significant increases in land prices, and changes in people's social lives occur. To minimize the negative impact of gentrification, the government should promote the capacity of low-income households to access its benefits.

Ecosystem Quality Assessment and Ecological Restoration in Fragile Zone of Loess Plateau: A Case Study of Suide County, China

The Loess Plateau is the world’s largest loess landform region, characterized by a fragile ecosystem and frequent natural disasters that render it highly susceptible to ecological damage, highlighting urgent ecological restoration. We constructed a “Pattern-Service-Stress Ecosystem Quality Assessment Model” based on the connotation of ecosystem quality and the ArcGIS platform, then applied it to Suide County, a representative area of the Loess Plateau, as the research object. Next, using the dispersal ecology theory and the MCR model, we constructed an ideal ecological network. According to the quality assessment and ecological network analysis, we selected areas with low ecosystem quality within the scope of an ecological corridor as key areas for restoration. Finally, we proposed restoration strategies using regional ecological techniques. This study yielded the following results: The spatial pattern of ecosystem quality in Suide County exhibited a “high in the south and low in the north” pattern, with a high-value area of 823.87 km2, and a low-value area of 509.31 km2, accounting for 44.45% and 27.48% of the total area, respectively. In Suide County’s ecological network, the spatial distribution of ecological sources and corridors is dense in the south and sparse in the north, with a significant amount of path overlap within ecological corridors. Located on the southern ecological corridor of Suide County, forty-five key areas for restoration were classified into seven types. Eight problems were identified in the key areas, and twenty-three targeted restoration measures were proposed. These measures can result in 6.44 km2 of forest land and 5.26 km2 of grassland, improving the ecosystem quality of the key areas and even the entirety of Suide County. This study guides Suide County’s ecological restoration work and provides a paradigm for ecosystem quality assessment and ecological restoration on the Loess Plateau, pointing out directions. It has a certain radiation-driven effect and an important reference significance for ecological restoration in ecologically fragile areas.

Evidence for Urbanization Effects on Eco-Environmental Quality: A Case Study of Guyuan City, China

Achieving sustainable development and a good quality of life depends largely on the state of the ecological environment. This research is centered on Guyuan City and examines the changes in the ecological environment quality across space and time, based on Landsat imagery and the remote sensing ecological environment index (RSEI) between 2000 and 2019. Correlation analysis and partial least squares structural equation modeling was used to investigate the environmental and human factors that affect the quality of the ecological environment. The results indicate a significant reduction in areas with a very-poor-quality ecological environment and a significant increase in excellent ecological environment management from 2000 to 2019, especially in eastern Guyuan City. The low-value area of the RSEI index gradually shifted from eastern counties to western areas relative to Guyuan City, exhibiting a significant change from a high-cluster distribution to a significantly discrete distribution. Elevation, precipitation, and total organic carbon showed significantly positive correlations with the RSEI, while temperature, land use, and pH showed significantly negative correlations. This study also reveals that topography and climate change have a positive impact on ecological changes, and urbanization is becoming less limiting for ecological improvement. In future ecological construction processes, emphasis should be placed on the terrain and climatic conditions to maximize the restoration of the ecological environment affected by urban construction. This work provides regional guidance for future sustainable development and high-quality development in the Yellow River Basin.

Spatiotemporal Evolution and Multi-Scenario Prediction of Carbon Storage in the GBA Based on PLUS–InVEST Models

In the context of sustainable development and dual-carbon construction, in order to clarify the future changes in land use and carbon storage in the GBA, this study used the PLUS and InVEST models as well as Geoda software to simulate and predict the spatial development pattern of land use as well as the changes in carbon stocks in the GBA in 2030 under multiple scenarios. The results show that (1) From 1990 to 2020, carbon storage decreased year by year. (2) In 2030, except for the EPS, the future carbon storage prediction values of the remaining scenarios are lower than those in 2020, especially the carbon storage prediction value under the EDS, which is the lowest at 8.65 × 108 t. (3) The spatial distribution of carbon storage in the GBA has significant spatial heterogeneity. The high-value areas of carbon storage are distributed in the east and west wings as well as southwest of the GBA, while the low-value areas are concentrated in the middle and east. The research results can provide a reasonable scientific basis for the territorial space resource planning of the GBA under the goal of “dual carbon”.

Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China’s Pinglu Canal Estuary

Mangrove forests are a valuable resource for biological and species diversity, and play a critical role in maintaining biodiversity. However, traditional plant biodiversity survey methods, which rely on labor-intensive field surveys, are not suitable for large-scale continuous spatial observations. To overcome this challenge, we propose an innovative framework for mangrove biodiversity assessment and zoning management based on drone low-altitude remote sensing, integrating data such as vertical structure features and spectral diversity features extracted from on-site measurements, airborne LiDAR, and hyperspectral data. This study focuses on the Maowei Sea mangrove community, located in the estuary of China’s first Pinglu Canal since the founding of the People’s Republic of China. Using the proposed framework, we construct an evaluation index for mangrove biodiversity at the levels of species diversity, ecosystem diversity, and landscape diversity, achieving a quantitative calculation of mangrove biodiversity and an evaluation of spatial distribution patterns. The results show that the biodiversity index of mangroves ranges from 0 to 0.63, with an average value of 0.29, and high-biodiversity areas are primarily concentrated in the southwest of the study area, while low-value areas are mainly located in the north. We also select the elevation and offshore distance of mangrove growth for the spatial zoning of biodiversity. The core area of biodiversity occupies the smallest area, at 2.32%, and is mainly distributed in areas with an elevation of 1.43–1.59 m and an offshore distance of 150.08–204.28 m. Buffer zones and experimental zones account for a significant proportion, with values of 35.99% and 61.69%, respectively. Compared to traditional methods for monitoring mangrove biodiversity, such as community field-sample surveys, the proposed method using unmanned-aerial-vehicle LiDAR and hyperspectral coupling technology to assess mangrove biodiversity and establish a zoning management framework is more conducive to formulating mangrove biodiversity conservation strategies. The study provides a feasible solution for the large-scale biodiversity mapping of mangroves in the Maowei Sea at the estuary of the Pinglu Canal.

Construction of carbon budget balance index and its application in the lake area

The imbalance of the carbon cycle in terrestrial ecosystems exacerbates global warming. Identifying the spatial–temporal characteristics and drivers of the carbon budget is important for the effective management of complex ecosystems and the achievement of the United Nations Sustainable Development Goals. Based on the complex ecosystem theory, this article constructs two carbon indicators, carbon carrying capacity–carbon footprint matching degree (Carbon-MD), and carbon carrying capacity–carbon footprint coupling coordination degree (Carbon-CCD). Taking a typical lake region—urban agglomeration around Poyang Lake as an example, the spatial–temporal characteristics and driving factors of the carbon budget from 2000 to 2020 are revealed by GIS technology and geographically–temporally weighted regression model. The results show that there is a significant spatial and temporal variability of carbon budget in Poyang Lake city agglomerations from 2000 to 2020, the Carbon-MD shows a gradually decreasing trend, and the Carbon-CCD shows a gradually increasing characteristic from moderate disorder to basic coordination development. From the spatial pattern, the Carbon-MD of the study area showed an increasing character from the core area to the peripheral area of the lake, and the low-value area of Carbon-MD shows the trend of spreading from point to surface and the Carbon-CCD changes from scattered to group type. In addition, land use type always has a significant effect on the carbon budget, while there is a spatial and temporal heterogeneity in the effects of natural and socioeconomic factors on the carbon budget. The research results show that it is reasonable and scientific to construct carbon budget indicators from the perspective of matching supply and demand and coupling and coordination, which provides a quantitative carbon budget analysis tool for local policymakers.

Spatial pattern optimization of rural production-living-ecological function based on coupling coordination degree in shallow mountainous areas of Quyang County, Hebei Province, China

IntroductionThe shallow mountainous area in Hebei province is a crucial part of the ecological security barrier and regional ecological conservation construction in the Beijing-Tianjin-Hebei (BTH) region. In recent years, the contradictions in the development of the rural “production-living-ecological” function (PLEF) in shallow mountainous areas are prominent, so optimize its spatial pattern is beneficial to rural sustainable development. But there are significant problems in the existing research, such as the lack of fine-scale research and effective guidance for rural PLEF. Based on this, this study takes Quyang County as an example, starts from the perspective of PLEF coordinated development, finally puts forward the optimization strategy of rural production-living-ecological space (PLES) pattern by evaluating rural PLEF and its coupling co-scheduling.MethodsThis study first fused multi-source data such as POI and remote sensing images to build a comprehensive evaluation system of rural PLES, combined with entropy weight method and analytic hierarchy process to give weight to various indicators, and calculated the PLEF distribution of Quyang County on the 300 × 300m grid scale. Then the collaborative development of PLEF is measured by coupling coordination degree model. Finally, according to PLEF and its coupling and coordination, the functional space types are divided according to the principles of coordinated development and ecological optimization, and the optimization strategy of PLES pattern is proposed on the village scale.Results(1) The spatial distribution of PLEF in Quyang County is significantly different, and the order of functional intensity is: ecological space (ES) > production space (PS) > living space (LS). (2) The PLEF coupling coordination degree generally presents the spatial distribution characteristics of “low in the north and high in the south”, which is highly related to its topographic features. The high-value areas are mainly spread over southern plains with developed economy and rich ecological resources, while the low-value areas are located in the northern mountains and the central hills. (3) On the grid scale, the PLES pattern is identified as six types: production-living-ecological balance space (PLEBS), production-living space (PLS), production-ecological space (PES), living-ecological space (LES), ES and PS. Among them, the proportion of PLEBS and ES is larger. (4) On the village scale, it is suggested that PLEBS villages further emphasize high-quality coordinated development; ecological function leading optimization type (EFLOT) villages adhere to ecological priorities and ensure the development of ecological space functions; villages with composite functions should combine their own advantages and the spatial characteristics of the surrounding countryside, optimize and control infrastructure configuration, industrial structure, ecological protection and other aspects of classification, overcome shortcomings and improve the coordination of the PLEF.DiscussionBased on previous studies, this paper explored and improved the research scale, analysis methods, evaluation indexes and optimization ideas in the field of rural PLEF. Therefore, the results can guide for the high-quality coordinated development of territorial space and rural revitalization construction of counties in shallow mountainous areas.

PM2.5 concentration assessment based on geographical and temporal weighted regression model and MCD19A2 from 2015 to 2020 in Xinjiang, China.

PM2.5 is closely linked to both air quality and public health. Many studies have used models combined with remote sensing and auxiliary data to inverse a large range of PM2.5 concentrations. However, the data's spatial resolution is limited. and better results might have been obtained if higher resolution data had been used. Therefore, this paper establishes a geographical and temporal weighted regression model (GTWR) and estimates the PM2.5 concentration in Xinjiang from 2015 to 2020 using 1 km resolution MCD19A2 (MODIS/Terra+Aqua Land Aerosol Optical Thickness Daily L2G Global 1km SIN Grid V006) data and 9 auxiliary variables. The findings indicate that the GTWR model performs better than the simple linear regression (SLR) and geographically weighted regression (GWR) models in terms of accuracy and feasibility in retrieving PM2.5 concentrations in Xinjiang. Simultaneously, by combining the GTWR model with MCD19A2 data, a spatial distribution map of PM2.5 with better spatial resolution can be obtained. Next, the regional distribution of annual PM2.5 concentrations in Xinjiang is consistent with the terrain from 2015 to 2020. The low value area is primarily found in the mountainous area with higher terrain, while the high value area is primarily in the basin with lower terrain. Overall, the southwest is high and the northeast is low. In terms of time change, the six-year PM2.5 shows a single peak distribution with 2016 as the inflection point. Lastly, from 2015 to 2020, the seasonal average PM2.5 concentration in Xinjiang has a significant difference, thereby showing winter (66.15μg/m3)>spring (52.28μg/m3)>autumn (40.51μg/m3)>summer (38.63μg/m3). The research shows that the combination of MCD19A2 data and GTWR model has good applicability in retrieving PM2.5 concentration.

Patterns and controls of ecosystem service values under different land-use change scenarios in a mining-dominated basin of northern China

Exploring future land use/cover change (LULC) and ecosystem service values (ESV) dynamics is crucial for sustainable development from regional to global scales. However, ESV dynamics is significantly affected by economic development and policy changes, and future projections of ESV are generally characterized by large uncertainties due to complexity in LULC dynamics. Mining activities are supposed to exert significant effects on ESV dynamics, while the patterns and controls of ESV in mining-dominated basins are still less understood, especially under different land-use scenarios. Here, based on multi-source remote sensing data and land-use data in the Fenhe River Basin, we integrated the SD model, Markov model and PLUS model to simulate LULC in the Fenhe River Basin under four scenarios, i.e., the economic development priority (EDP), natural development priority (ND), cultivated land protection priority (CLP), and ecological protection priority (EPP). Based on ESV equivalent coefficient method and geographical detector, we further determined the patterns and controls of ESV. Results showed that construction land and cultivated land were mainly concentrated in the central parts of the basin, and grassland and woodland were concentrated in the edge area of the basin. Over the past two decades, construction land and woodland have experienced significant expansion, while the areas of grasslands and cultivated lands have declined due to mining activities. The high-value and sub-high-value areas of ESV were concentrated in woodland, grassland, reservoir and concentrated water area of mainstream and tributary. The low-value area was mainly located in the gathering area of construction land. The total ESV showed a downward trend with time, and the highest decline in the total ESV under the four land use scenarios was the EDP, while the lowest drop was the EPP. The highest contribution rate of ESV was woodland, which was equivalent to the contribution rate of cultivated land, grassland and water area, totally accounting for 58.54% of the whole ESV. The geographical detector method indicated that distance to the residential area, soil erodibility, distance to the river, soil type and annual average temperature were the main driving factors affecting the spatial patterns of ESV. Our results highlighted the fundamental role of mining activity in affecting LULC characterized by grassland and cultivated land shrinkage, and suggested that mining areas rehabilitation should be given priority in terms of further improving ESV in mining-dominated basins.

Comprehensive Evaluation and Promotion Strategy of Agricultural Digitalization Level

The development of digitalization is a crucial aspect of agricultural progress, and expediting the establishment of digital systems is a significant driving force behind high-quality agricultural advancements in the current era. Utilizing data from 16 cities within Shandong Province in China between 2014 and 2020, we created an assessment system to measure the degree of agricultural digitalization, utilized the entropy technique to assess the level of digitalization, scrutinized the general trends and time-dependent features of each city, and then utilized the obstacle degree model to pinpoint the primary hindrances to digitalization in agriculture. Lastly, the ESDA method was utilized to examine the differences in spatial distribution among regions and the spatial characteristics of agricultural digitalization at different stages and levels. Overall, the degree of agricultural digitalization can be categorized into three stages: deceleration and upswing (2014–2015), steady fluctuation (2016–2017), and high-level upswing (2018–2020). From the perspective of obstacles, the main hurdles to agricultural digitalization are e-commerce transaction volume and the total amount of telecommunication business. To accelerate the development of the entire agricultural industry chain, it is required to leverage the strengths of high-value areas and reinforce the coordination mechanism among various departments while hastening the construction of rural infrastructure in low-value areas. Additionally, it is necessary to improve inter-regional communication and cooperation to nurture different regional development models in line with local conditions.

Simulation of land use trends and assessment of scale effects on ecosystem service values in the Huaihe River basin, China.

Land use demand change in the Huaihe River basin (HRB) and ecosystem service values (ESVs) in watersheds are important for the sustainable development and use of land resources. This paper takes the HRB as the research object, and using remote sensing images of land use as the data source adopts the comprehensive evaluation analysis method of ESVs based on equivalent factors and sensitivity analysis of the performance characteristics of ESV changes of different land use types. The PLUS model is used to predict spatiotemporal land use change characteristics to 2030 combining inertial development, ecological development, and cultivated land development. The spatial distribution and aggregation of ESVs at each scale were also explored by analyzing ESVs at municipal, county, and grid scales. Considering also hotspots, the contribution of land use conversion to ESVs was quantified. The results showed that (1) from 2000 to 2020, cultivated land decreased sharply to 28,344.6875 km2, while construction land increased sharply to 26,914.563 km2, and the change of other land types was small. (2) The ESVs in the HRB were 222,019 × 1012 CNY in 2000, 235,015 × 1012 CNY in 2005, 234,419 × 1012 CNY in 2010, 229,885 × 1012 CNY in 2015, and 224,759 × 1012 CNY in 2020, with an overall fluctuation, first increasing and then decreasing. (3) The ESVs were 219,977 × 1012 CNY, 218,098 × 1012 CNY, 219,757 × 1012 CNY, and 213,985 × 1012 CNY under the four simulation scenarios of inertial development, ecological development, cultivated land development, and urban development, respectively. At different scales, the high-value areas decreased, and the low-value areas increased. (4) The hot and cold spots of ESV values were relatively clustered, with the former mainly clustered in the southeast region and the latter mainly clustered in the northwest region. The sensitivity of ecological value was lower than 1, while the ESV was inelastic to the ecological coefficient, and the results were plausible. The mutual conversion of cultivated land to water contributed the most to ESVs. Based on the multi-scenario simulation of land use in the HRB by the PLUS model, we identified the spatial distribution characteristics of ESVs at different scales, which can provide a scientific basis and multiple perspectives for the optimization of land use structure and socio-economic development decisions.

Spatial Differentiation and Influencing Mechanisms of Farmland Transfer Rents in Mountainous Areas: Evidence from Chongqing and Its Surrounding Areas

This study used Chongqing, a municipality in mountainous southwest China, and its surrounding areas as a case study to explore the spatial differentiation of farmland transfer rents in mountainous areas, with the aim of serving as a theoretical and practical reference to realize the value of farmland, ensure regional food security, and promote stable and sound development of the farmland transfer market. In doing so, we applied the GIS spatial analysis method to explore the spatial differentiation and influencing mechanisms of farmland transfer rents in mountainous areas. Our results indicate that farmland transfer rents in mountainous areas have a significant high and low clustering tendency. The high-value areas of farmland transfer rents are mainly located in the downtown area and the west of Chongqing, while the low-value areas are mainly distributed in the Daba Mountains and Wuling Mountains, which are two national contiguous areas of dire poverty. Location and terrain factors are the main driving forces for the spatial differentiation of farmland transfer rents in mountainous areas. Specifically, a 1% increase in farmland mean slope and farmland supply-demand ratio in the study area will lead to a 0.13 and 0.15% decrease in farmland transfer rents, respectively, while a 1% increase in GDP will drive up farmland transfer rents by 0.09%. The policy factor is not significant. The influence of terrain and farmland supply and demand on transfer rents increased from west to east, whereas the influence of traffic location on transfer rents decreased in an outward direction from the southwest of the study area. It is concluded that local governments should objectively view the spatial differentiation of farmland transfer rents in mountainous areas and avoid the blind comparison of transfer rents between regions. Mountainous areas with low transfer rents should focus on increasing the intrinsic value of farmland assets by stimulating effective demand for farmland and improving farming conditions, while mountainous areas with high transfer rents in major grain-producing counties should be wary of their impact on grain production to ensure regional food security.