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The southeastern region of Tibet, which serves as the primary concentration area for marine-type glaciers, has fostered a multitude of glacial lakes that are highly sensitive to global climate change. Glacial lakes play a crucial role in regulating the freshwater ecosystems of the region, but they also pose a significant threat to local infrastructure and populations due to flooding caused by glacial lake outbursts. Currently, a limited amount of research has focused on the monitoring and analysis of glacial lakes in southeastern Tibet. Using Google Earth Engine (GEE) data in conjunction with meteorological data, this study examined the variation characteristics of glacial lakes in southeastern Tibet from 1993 to 2023. The region is subjected to segmentation and extraction of glacial lake boundaries via the FCN model. According to research findings, by 2023, southeastern Tibet is projected to contain 3,877 glacial lakes, encompassing an area of approximately 395.74 ± 22.72 km2. The distribution of glacial lakes in this region follows a pattern characterized by a relatively high concentration in the southern region and a relatively low concentration in the northern region. The glacial lakes with areas less than 0.1 km2 accounted for 94.24%, whereas those exceeding 3.0 km2 experienced the least amount of change. The analysis of regional elevation using the natural segmentation method reveals that glacial lakes are predominantly distributed within the altitude range of 4442 ~ 4909 m. The fluctuations in the annual mean precipitation and average annual temperature in the study area have decreased since 2008, while the growth trajectories of both the area and number of glacial lakes have gradually stabilized. However, given the backdrop of a slight increase in precipitation and a gradual increase in temperature, the proliferation of glacial lakes is projected to accelerate predominantly in Nyingchi City’s eastern and western regions. [ABSTRACT FROM AUTHOR]

Abstract Urban agglomeration system resilience involves multiple subsystems that are interconnected and interactive, and exploring the relationships among subsystems can elucidate and increase urban agglomeration resilience. This study constructed a social-economic-built environment resilience model and proposed a social-economic-built environment resilience index system. Using the entropy weight method, the coupling coordination degree (CCD) model, GeoDetector, spatial autocorrelation analysis and the autoregressive integrated moving average model (ARIMA) model, the resilience development level of the Beijing‒Tianjin‒Hebei (BTH) region from 2000 to 2020 was evaluated, the main influencing factors for the spatiotemporal differentiation pattern were identified, and the development levels in 2030 and 2050 were predicted. The results show that (1) high-resilience and high-CCD regions are concentrated in the region of Beijing and Tianjin in the centre, and low-value regions are concentrated in the districts and counties in the west and south; (2) economic elements, especially the economic aggregate status of a region as a whole, are the main factors contributing to the differences in resilience levels between regions, but their influence gradually decreases; and (3) the gap between the CCDs of Beijing, Tianjin and cities in Hebei increased from 2000 to 2020, but this gap is expected to narrow by 2030 and 2050. On this basis, five categories of future development guidelines for cities in the BTH region are proposed.

Abstract Aligned with the imperatives of national ecological civilization construction, the systematic investigation into the intricate interplay between shifts in land utilization and the assessment of ecosystem services plays a pivotal and indispensable role in advancing ecological civilization. This endeavor holds significant implications. It aids in optimizing the ecological landscape at the regional level and fosters harmonious coexistence between humanity and the natural world. The study utilizes land-use remote sensing interpretation data from three time periods (2000, 2010, and 2020) and employs various methodologies, including equivalent factor coefficient correction, sensitivity analysis, and spatial autocorrelation. The objective is to uncover the spatiotemporal dynamics of land-use changes and Ecosystem Service Value (ESV) in Lanzhou City. Furthermore, geographic detectors are applied to explore the driving factors influencing ESV spatial heterogeneity and their interactions. The research findings indicate the following: (1) From 2000 to 2020, grassland and cropland were the predominant land-use types in Lanzhou City, with cropland and urban land experiencing the most active changes. (2) ESV in Lanzhou City increased from 179.37 billion RMB in 2000 to 193.86 billion RMB in 2020, reflecting an ESV total growth rate of 8.07% and a gradual improvement in the ecological environment. Spatially, ESV exhibits a “west high, east low” distribution pattern, with the center shifting towards the northwest and southeast, gradually reducing spatial imbalance. (3) Analysis of ESV spatial autocorrelation reveals that high-high clusters are predominantly found within the Tulu Gou National Forest Park and the Xinglong Mountain National Natural Reserve, while low-low clusters are primarily concentrated in the central urban area of Lanzhou City. Over the period from 2000 to 2020, the spatial clustering effect of ESV within the study area has progressively intensified. 4)NDVI, precipitation, and GDP emerge as pivotal factors influencing spatial differentiation within Lanzhou City, with natural and societal elements exerting interactive effects on ESV spatial disparities. The research results integrate environmental considerations into the decision-making process, offering valuable insights for formulating targeted ecological protection policies in Lanzhou City. This study embodies concrete measures taken by Lanzhou City in practicing China’s concept of “green water and green mountains are golden silver mountains,” providing a theoretical basis for the harmonious and sustainable development of the ecological economy.

Abstract Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities.

Abstract In low mountain and hilly regions, vegetation cover is higher and plant growth has an accumulative effect, sequestering carbon more strongly. The traditional remote sensing based ecological index (RSEI) lacks the consideration of vegetation productivity, and using it to evaluate ecological environment in low mountain and hilly regions will be biased. In this study, the vegetation productivity was introduced to construct a natural remote sensing based ecological index (NRSEI) that responds to the low mountain and hilly regions, as an example of Gaizhou City, China. Additionally, this study explored the spatiotemporal evolution of ecological environment quality from 2014 to 2020 and quantified the influences of factors. The results show that the first principal component (PC1) increased from 56 to 67% to 65–87% and considered the accumulation process in the ecosystem. NRSEI was more valid. From 2014 to 2020, the quality of the ecological environment generally declined and then increased. The area with “Excellent” increased from 23 to 38%. The quality of ecosystems in the west, northwest, and south deteriorated significantly, a distribution pattern of “high in the center, low in the north and south”. Landuse and topographic conditions dominate the impacts on the ecosystem in the context of social, economic and policy influences. The interactions of the factors were two-factor enhancement that together affect the ecological environment. The results contribute to the development of urban conservation policies in low mountain and hilly regions.

Abstract During the oilfield development process, various factors can cause different types of reservoir damage, leading to reduced oil well production or even shutdown, and decreased water injection capacity in water wells, resulting in significant economic losses for the oilfield. However, formation damage control measures must be based on the quantitative diagnosis of the types and degrees of reservoir damage. This paper establishes a spatiotemporal evolution numerical model for 12 common types of damage during the oil and gas exploration and development process, based on the material balance theory and Fick’s diffusion law in reservoir damage processes. This model achieves numerical simulation of the degree of various reservoir damage types in different spatiotemporal domains. The overall damage degree of a specific well’s evolution with time and space is further simulated in simple superposition way. The sequential core flow experiment was carried out in the laboratory, and then compared with the calculation results. The accuracy is above 90%. Finally, using field test data, the simulation results show a 95% or higher degree of agreement with the actual field measurements, proving that the reservoir damage spatiotemporal evolution quantitative simulation technology established in this paper has high accuracy and practicality.

Abstract Net primary productivity (NPP) is an important parameter reflecting vegetation growth, and water is one of the necessary factors for vegetation growth. Investigating the mutual influence between NPP and water is significant for ensuring the stable development of the ecological environment. This study focuses on the Yangtze River Basin (YRB) as the research area, and based on medium-resolution imaging spectrometer (MODIS) data, climate data, and gravity recovery and climate experiment (GRACE) data, the spatiotemporal evolution characteristics of vegetation NPP and terrestrial water storage (TWS) in the YRB from 2000 to 2022 are explored and analyzes the mutual influence of NPP with climate factors and TWS. The results show that vegetation NPP (4.10 gC·m−2·a−1) and TWS (0.55 mm) in the YRB have exhibited an increasing trend from 2000 to 2022, with a strong correlation between the two, which is related to recent environmental policies. Analysis of the impact of climate factors on NPP reveals that temperature and TWS significantly positively impact NPP changes. Furthermore, comparisons between NPP and TWS indicate that changes in TWS substantially promote plant growth. In addition, the comparison between NPP and TWS indicates that changes in TWS have an important promoting effect on plant growth. Surface water (SWS) and soil water (SM) have a significant promoting effect on plant growth, but with a strong lag, while the consumption of groundwater (GWS) has been promoting plant growth without significant lag.

Abstract The conservation and sustainable development of traditional villages have raised global attention in the context of rapid urbanization and modernization. Taking 703 traditional villages in Hunan Province as an example, this study first constructed a Traditional Village Human Settlement Suitability (TVHSS) evaluation system based on the Pressure-State-Response (PSR) model. Then, the entropy weighting method was used to assess the spatiotemporal evolution of TVHSS from 2005 to 2020, while the Geographically Weighted Regression (GWR) model was employed to analyze the influencing factors. The results indicate that the overall TVHSS score increased from 0.521 to 0.776 from 2005 to 2020, with a spatial distribution characterized by lower suitability in the northwest and higher suitability in the southeast. During this period, the pressure subsystem experienced an increase, peaking at 0.058 in 2015 before declining to 0.055 in 2020. Meanwhile, the state subsystem remained relatively stable, with scores slightly decreasing from 0.040 in 2005 to 0.033 in 2020. In contrast, the response subsystem showed a continuous upward trend, rising from 0.430 in 2005 to 0.688 in 2020. The distance to educational institutions, degree of relief, distance to water, and distance on intangible cultural heritage sites have the highest effects on TVHSS. These findings provide a scientific basis for the conservation and sustainable development of traditional villages and offer a replicable analytical framework for similar contexts globally. By addressing the complex interactions between environmental, social, and economic factors, this study contributes to the global discourse on rural sustainability, offering insights that can inform policy-making and guide the preservation of cultural heritage in the face of modernization pressures.

Aligned with the imperatives of national ecological civilization construction, the systematic investigation into the intricate interplay between shifts in land utilization and the assessment of ecosystem services plays a pivotal and indispensable role in advancing ecological civilization. This endeavor holds significant implications. It aids in optimizing the ecological landscape at the regional level and fosters harmonious coexistence between humanity and the natural world. The study utilizes land-use remote sensing interpretation data from three time periods (2000, 2010, and 2020) and employs various methodologies, including equivalent factor coefficient correction, sensitivity analysis, and spatial autocorrelation. The objective is to uncover the spatiotemporal dynamics of land-use changes and Ecosystem Service Value (ESV) in Lanzhou City. Furthermore, geographic detectors are applied to explore the driving factors influencing ESV spatial heterogeneity and their interactions. The research findings indicate the following: (1) From 2000 to 2020, grassland and cropland were the predominant land-use types in Lanzhou City, with cropland and urban land experiencing the most active changes. (2) ESV in Lanzhou City increased from 179.37 billion RMB in 2000 to 193.86 billion RMB in 2020, reflecting an ESV total growth rate of 8.07% and a gradual improvement in the ecological environment. Spatially, ESV exhibits a "west high, east low" distribution pattern, with the center shifting towards the northwest and southeast, gradually reducing spatial imbalance. (3) Analysis of ESV spatial autocorrelation reveals that high-high clusters are predominantly found within the Tulu Gou National Forest Park and the Xinglong Mountain National Natural Reserve, while low-low clusters are primarily concentrated in the central urban area of Lanzhou City. Over the period from 2000 to 2020, the spatial clustering effect of ESV within the study area has progressively intensified. 4)NDVI, precipitation, and GDP emerge as pivotal factors influencing spatial differentiation within Lanzhou City, with natural and societal elements exerting interactive effects on ESV spatial disparities. The research results integrate environmental considerations into the decision-making process, offering valuable insights for formulating targeted ecological protection policies in Lanzhou City. This study embodies concrete measures taken by Lanzhou City in practicing China's concept of "green water and green mountains are golden silver mountains," providing a theoretical basis for the harmonious and sustainable development of the ecological economy. [ABSTRACT FROM AUTHOR]

Urban agglomeration system resilience involves multiple subsystems that are interconnected and interactive, and exploring the relationships among subsystems can elucidate and increase urban agglomeration resilience. This study constructed a social-economic-built environment resilience model and proposed a social-economic-built environment resilience index system. Using the entropy weight method, the coupling coordination degree (CCD) model, GeoDetector, spatial autocorrelation analysis and the autoregressive integrated moving average model (ARIMA) model, the resilience development level of the Beijing‒Tianjin‒Hebei (BTH) region from 2000 to 2020 was evaluated, the main influencing factors for the spatiotemporal differentiation pattern were identified, and the development levels in 2030 and 2050 were predicted. The results show that (1) high-resilience and high-CCD regions are concentrated in the region of Beijing and Tianjin in the centre, and low-value regions are concentrated in the districts and counties in the west and south; (2) economic elements, especially the economic aggregate status of a region as a whole, are the main factors contributing to the differences in resilience levels between regions, but their influence gradually decreases; and (3) the gap between the CCDs of Beijing, Tianjin and cities in Hebei increased from 2000 to 2020, but this gap is expected to narrow by 2030 and 2050. On this basis, five categories of future development guidelines for cities in the BTH region are proposed. [ABSTRACT FROM AUTHOR]

The conservation and sustainable development of traditional villages have raised global attention in the context of rapid urbanization and modernization. Taking 703 traditional villages in Hunan Province as an example, this study first constructed a Traditional Village Human Settlement Suitability (TVHSS) evaluation system based on the Pressure-State-Response (PSR) model. Then, the entropy weighting method was used to assess the spatiotemporal evolution of TVHSS from 2005 to 2020, while the Geographically Weighted Regression (GWR) model was employed to analyze the influencing factors. The results indicate that the overall TVHSS score increased from 0.521 to 0.776 from 2005 to 2020, with a spatial distribution characterized by lower suitability in the northwest and higher suitability in the southeast. During this period, the pressure subsystem experienced an increase, peaking at 0.058 in 2015 before declining to 0.055 in 2020. Meanwhile, the state subsystem remained relatively stable, with scores slightly decreasing from 0.040 in 2005 to 0.033 in 2020. In contrast, the response subsystem showed a continuous upward trend, rising from 0.430 in 2005 to 0.688 in 2020. The distance to educational institutions, degree of relief, distance to water, and distance on intangible cultural heritage sites have the highest effects on TVHSS. These findings provide a scientific basis for the conservation and sustainable development of traditional villages and offer a replicable analytical framework for similar contexts globally. By addressing the complex interactions between environmental, social, and economic factors, this study contributes to the global discourse on rural sustainability, offering insights that can inform policy-making and guide the preservation of cultural heritage in the face of modernization pressures. [ABSTRACT FROM AUTHOR]

During the oilfield development process, various factors can cause different types of reservoir damage, leading to reduced oil well production or even shutdown, and decreased water injection capacity in water wells, resulting in significant economic losses for the oilfield. However, formation damage control measures must be based on the quantitative diagnosis of the types and degrees of reservoir damage. This paper establishes a spatiotemporal evolution numerical model for 12 common types of damage during the oil and gas exploration and development process, based on the material balance theory and Fick's diffusion law in reservoir damage processes. This model achieves numerical simulation of the degree of various reservoir damage types in different spatiotemporal domains. The overall damage degree of a specific well's evolution with time and space is further simulated in simple superposition way. The sequential core flow experiment was carried out in the laboratory, and then compared with the calculation results. The accuracy is above 90%. Finally, using field test data, the simulation results show a 95% or higher degree of agreement with the actual field measurements, proving that the reservoir damage spatiotemporal evolution quantitative simulation technology established in this paper has high accuracy and practicality. [ABSTRACT FROM AUTHOR]

In low mountain and hilly regions, vegetation cover is higher and plant growth has an accumulative effect, sequestering carbon more strongly. The traditional remote sensing based ecological index (RSEI) lacks the consideration of vegetation productivity, and using it to evaluate ecological environment in low mountain and hilly regions will be biased. In this study, the vegetation productivity was introduced to construct a natural remote sensing based ecological index (NRSEI) that responds to the low mountain and hilly regions, as an example of Gaizhou City, China. Additionally, this study explored the spatiotemporal evolution of ecological environment quality from 2014 to 2020 and quantified the influences of factors. The results show that the first principal component (PC1) increased from 56 to 67% to 65–87% and considered the accumulation process in the ecosystem. NRSEI was more valid. From 2014 to 2020, the quality of the ecological environment generally declined and then increased. The area with "Excellent" increased from 23 to 38%. The quality of ecosystems in the west, northwest, and south deteriorated significantly, a distribution pattern of "high in the center, low in the north and south". Landuse and topographic conditions dominate the impacts on the ecosystem in the context of social, economic and policy influences. The interactions of the factors were two-factor enhancement that together affect the ecological environment. The results contribute to the development of urban conservation policies in low mountain and hilly regions. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities. [ABSTRACT FROM AUTHOR]

In the information age, digital information technology has gradually become a new quality of productivity to improve international competitiveness, and the status and importance of the pseudo human settlements(PHS) constructed by digital and information has been increasing in the human settlements(HS) system. In this context, exploring the coupling coordination of the internal systems of the PHS provides a theoretical basis for promoting the comprehensive improvement of the quality of the HS in the urban agglomerations, provides a theoretical reference for rationally interpreting the new type of human-land relationship in the information age, and provide a new perspective for the study of the human settlements geography. Currently, research on PHS is in its nascent stages, therefore, we construct a theoretical framework for the coupling coordination of the "three states" of the HS, takes the internal system of PHS as the entry point, empirically analyze the spatiotemporal characteristics of the PHS coupling coordination degree within urban agglomerations in eastern China and the driving factors by using the coupling coordination degree, spatial autocorrelation, the center of gravity and the ellipse of the standard deviation, and geo-detector models. Research shows: (1) Time course: exhibits an upward "inverted L" trend. (2) Spatial pattern: exhibits a general spatial pattern of "high in the north and low in the south". (3) Spatial correlation: shows a spatially positively correlated clustering trend. (4) Spatial evolution: demonstrates a decentralized pattern of migration from the northeast to the southwest, indicating that the coupling coordination grows faster in the southwest than in the northeast. (5) Driving factor: the development of coupling coordination degree of PHS results from multiple factors and systems. This research provides theoretical support for promoting the comprehensive improvement of the quality of PHS in the urban agglomerations in eastern China, and offers scientific reference for the construction of PHS in other regions of China. [ABSTRACT FROM AUTHOR]

Abstract Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit–based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995–2000, 2000–2005, 2005–2009 and 2015–2020, and the improvement was most significant in 1995–2000, covering an area of 823.95 km2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.