Spatial Evolution Characteristics Research Articles

Characterization and Multi-Scenario Prediction of Habitat Quality Evolution in the Bosten Lake Watershed Based on the InVEST and PLUS Models

Habitat quality is an important basis for human well-being and the achievement of sustainable development. Based on land-use data for the Bosten Lake Basin in 2000, 2005, 2010, 2015, and 2022, the PLUS and InVEST models are applied in this study to predict and analyze land-use changes and explore the spatial and temporal evolution characteristics of the region’s habitat quality. Additionally, we use a geographic detector model to reveal the drivers of spatial variation in habitat quality. The results show that: (1) Land use in Bosten Lake Basin is dominated by grassland and bare land, with an area share of 93.21%. Habitat quality shows a trend of degradation followed by improvement, with a spatial pattern of high in the northwest and low in the southeast. (2) Habitat quality in 2030 increased from 2022 in all cases, with a mean of 0.354 for the natural development scenario, a maximum of 0.355 for the ecological development scenario, and a minimum of 0.353 for the economic development scenario. (3) The main drivers affecting habitat quality in the Bosten Lake watershed are DEM, mean annual precipitation (MAP), and GDP per capita. X1∩X4 (0.50) and X4∩X10 (0.51) are the interaction factors with the largest dominant effect in 2000, 2010 and 2020, respectively.

A study on the spatial and temporal evolution patterns of water resource–ecology–social economy composite system resilience in the Huaihe River Basin

ABSTRACT Water resources are important supporting elements in the ecological environment and socio-economic system of sustainable development. The purpose of this study is to evaluate the comprehensive resilience level of the water resources–ecology–socioeconomic system against external disturbances in the Anhui and Shandong sections of the Huaihe River Basin. The comprehensive index system is constructed with the characteristic dimensions of resistance, resilience, and adaptability. Use the game theory combination weighting-VIKOR method to quantify the resilience level, and use the kernel density analysis and Markov chain to explore the spatial and temporal evolution characteristics and transition probability. The results show that (1) the resilience index of the composite system in the Huaihe River Basin shows an increasing trend, and the resilience level of the Anhui section is generally higher than that of the Shandong section. (2) The resilience level gradually evolved into the spatial distribution characteristics of high in the west and low in the east, high in the south and low in the north during the study period. (3) The resilience grade has strong robustness, and the probability of transferring to the higher grade is greater than that of transferring to the lower grade.

Analysis of the Current Situation of Sustainable Development of the Yangtze River Economic Belt based on SDGs

This paper evaluates the level of sustainable development of 11 provinces and cities in the Yangtze River Economic Belt from 2011 to 2020, and analyzes its spatial and temporal differentiation and trend evolution characteristics. This paper adopts the coupling coordination model based on CRITIC-entropy weight combination weight, spatial autocorrelation model, spatial Markov chain and other methods, based on the measurement indicators of the United Nations Sustainable Development Goals, and conducts a comprehensive evaluation from four aspects: innovation-driven, welfare guarantee, resources and environment, and economic development. The research results show that the sustainable development level of the Yangtze River Economic Belt presents the characteristics of continuous improvement, regional difference, hierarchical leap, spatial dependence, spillover effect, etc. According to the research findings, this paper puts forward some suggestions, such as strengthening regional coordinated development, optimizing spatial planning and governance, coordinating policies and work, promoting rule of law and innovation, etc., aiming to promote the high-quality development of the Yangtze River Economic Belt, achieve the coordinated development of economy, society and ecology, and localize the SDGs. This paper’s research has important theoretical significance and practical value for deeply understanding the current situation and problems of sustainable development of the Yangtze River Economic Belt.

The Temporal and Spatial Evolution Characteristics of the Ecosystem Service Value and Conversion Rate in China’s Key State-Owned Forest Regions

To achieve a sustainable development path that harmonizes ecological and economic considerations, China has advocated the “two mountains” concept: “lucid waters and lush mountains are invaluable assets”. This idea posits that those who protect the environment can economically benefit by selling pristine landscapes and utilizing rich ecological resources. This paper use “the equivalence factor method” to calculate ecological benefits, introduces a technical measure—the conversion rate of ecosystem service value—and analyzes its temporal and spatial evolution from 2003 to 2020 in the operational areas of 87 state-owned forestry enterprises in Northeast China. The findings show: (1) a significant improvement in ecosystem-service quality, with its value increasing from 404.7 to 850.2 billion CNY between 2003 and 2020. The restoration of the ecological environment in China’s KSFR provides a foundation for economic and social development. (2) A decrease in the economic gains derived by operators from developing protected ecosystems, with the most significant decline observed in economic benefits generated from the supply product, including timber harvesting. However, the industrial structure in KSFR shifted from being dominated by timber production to diversified development, with non-timber forest resources becoming an important part of regional economic growth. (3) Significant potential for realizing the value of ecosystem services, evidenced by an increasing trend in the conversion rates of cultural, regulatory, and supporting services. These findings underscore the effectiveness of China’s natural forest protection and restoration policies in optimizing forest ecology and realizing the “two mountains” concept through appropriate market transactions and ecological compensation mechanisms.

Analysis and Prediction of Urban Surface Transformation Based on Small Baseline Subset Interferometric Synthetic Aperture Radar and Sparrow Search Algorithm-Convolutional Neural Network-Long Short-Term Memory Model.

With the acceleration of urbanisation, urban areas are subject to the combined effects of the accumulation of various natural factors, such as changes in temperature leading to the thermal expansion or contraction of surface materials (rock, soil, etc.) and changes in precipitation and humidity leading to an increase in the self-weight of soil due to the infiltration of water along the cracks or pores in the ground. Therefore, the subsidence of urban areas has now become a serious geological disaster phenomenon. However, the use of traditional neural network prediction models has limitations when examining the causal relationships between time series surface deformation data and multiple influencing factors and when applying multiple influencing factors for predictive analyses. To this end, Sentinel-1A data from March 2017 to February 2023 were used as the data source in this paper, based on time series deformation data acquired using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. A sparrow search algorithm-convolutional neural network-long short-term memory (SSA-CNN-LSTM) neural network prediction model was built. The six factors of temperature, humidity, precipitation, and ground temperature at three different depths below the surface (5 cm, 10 cm, and 15 cm) were taken as the input of the model, and the surface deformation data were taken as the output of the neural network model. The correlation between the spatial and temporal evolution characteristics of the ground subsidence in urban areas and various influencing factors was analysed using grey correlation analysis, which proved that these six factors contribute to some extent to the deformation of the urban surface. The main urban area of Hohhot City, Inner Mongolia Autonomous Region, was used as the study area. In order to verify the efficacy of this neural network prediction model, the prediction effects of the multilayer perceptron (MLP), backpropagation (BP), and SSA-CNN-LSTM models were compared and analysed, with the values of the correlation coefficients of the feature points of A1, B1, and C1 being in the range of 0.92, 0.83, and 0.93, respectively. The results show that compared with the traditional MLP and BP neural network models, the SSA-CNN-LSTM model achieves a higher performance in predicting time series surface deformation data in urban areas, which provides new ideas and methods for this area of research.

Spatial Evolution Characteristics of Plasmapause Surface Wave During a Geomagnetic Storm on 16 July 2017

AbstractBoundary dynamics are crucial for the transport of energy, mass, and momentum in geospace. The recently discovered plasmapause surface wave (PSW) plays a key role in the inner magnetosphere dynamics. However, a comprehensive investigation of spatial variations of the PSW remains absent. In this study, we elucidate the spatial characteristics of a PSW through observations from multiple spacecrafts in the magnetosphere. Following the initiation of the PSW, quasi‐periodic injections of energetic ions, rather than electrons, are suggested to serve as energy source of the PSW. Based on the distinct wave and particle signatures, we categorize the PSW into four regions: seed region, growth region, stabilization region and decay region, spanning from nightside to afternoon plasmapause. These findings advance our understanding of universal boundary dynamics and contribute to a deeper comprehension of the pivotal roles of surface waves in the energy couplings within the magnetosphere‐plasmasphere‐ionosphere system.

Research on the Laws of Overlying Rock Fracture and Energy Release under Different Mining Speeds

Mining activities are key triggers for strong mine earthquakes and even rock bursts in coal mines. This study explores the impact of mining speed on the overlying strata’s deformation and energy release through theoretical analysis, numerical simulation, and the digital speckle method. The temporal and spatial evolution characteristics of the impact energy during mining are simulated. The digital speckle method illustrates a positive correlation between rapid mining and increased fracture block degree of overburden rock and roof separation, confirming that accelerated mining speed extends the fracture distance of the stope. Furthermore, numerical simulations establish that both the energy associated with overlying rock breaking and the frequency of energy occurrence events are amplified during rapid mining, in contrast to slow mining. This observation corroborates that escalating mining speed augments the energy dispensed by the breaking of the upper rock. Consequently, this escalation induces a transformation in the energy levels of mine earthquakes, culminating in a heightened incidence of large-energy mine earthquakes.

Analysis of the Spatial Correlation Network and Driving Mechanism of China’s Transportation Carbon Emission Intensity

From 2008 to 2021, this study analyzed the spatial correlation characteristics between provincial transportation carbon emission intensity and explored ways to reduce transportation carbon emissions. This study used the modified gravity model, social network analysis (SNA) method, and temporal exponential random graph model (TERGM) to analyze the spatial correlation network evolution characteristics and driving mechanism of China’s transportation carbon emission intensity. This study found that China’s transportation carbon emission intensity and spatial correlation network have unbalanced characteristics. The spatial correlation network of transportation carbon emission intensity revealed that Shanghai, Beijing, Tianjin, Guangdong, Fujian, and other provinces were at the center of the network, with significant intermediary effects. The spatial correlation of transportation carbon emission intensity was divided into four functional plates: “two-way spillover”, “net benefit”, “broker”, and “net spillover”. The “net benefit” plate was mainly located in developed regions, and the “net spillover” plate was primarily located in underdeveloped regions. Endogenous structural and exogenous mechanism variables were the main factors affecting the evolution of the spatial correlation network of provincial transportation carbon emission intensity.

The Spatiotemporal Variation Characteristics and Influencing Factors of Green Vegetation in China

Green vegetation is one of the main objects of ecological environment restoration and protection, objectively reflecting the quality of regional ecological environments. Studying its spatial distribution characteristics is of great significance to the formulation of ecological environment restoration policies. Based on data on urban green vegetation in China from 2000 to 2022, this study attempts to analyze the destruction and protection patterns of urban green vegetation in China from the perspectives of total changes in green vegetation contraction and growth and spatial evolution characteristics and trends, and it explores the driving factors affecting the change in green vegetation area. The results show the following: (1) Green vegetation growth and contraction occurred alternately in China from 2000 to 2022. Vegetation contraction showed a “point–line–plane” evolution pattern, forming a contraction stage of point-like aggregation, linear series, and planar spread. Vegetation growth has always presented a frontal pattern. (2) The growth and contraction of green vegetation in China showed a north–south differentiation phenomenon. The vegetation contraction phenomenon spread in the Central Plains urban agglomeration and its surrounding areas and showed an expanding trend. The growth trend is obviously moving northward, mainly concentrated in Inner Mongolia, Ningxia, Gansu, Xinjiang, and other northern provinces, which also coincides with the key ecological restoration policies in northern China in recent years. (3) City scale, economic level, population scale, agro-industrial structure, and water resources content have significant effects on the spatial distribution of green vegetation.

Changes in Vegetation NDVI and Its Response to Climate Change and Human Activities in the Ferghana Basin from 1982 to 2015

Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.

Joint Observations of Energy Transport and Dissipation during Plasma Flow Vortex in the Terrestrial Magnetotail

Plasma flow vorticity is ubiquitous in space and plays a key role in material mixing and energy transfer. The five THEMIS satellites orbiting in different regions of the terrestrial magnetotail provide an unprecedented opportunity to study the temporal–spatial evolution characteristics of a plasma flow vortex on large spatial scales. We present an analysis of the flow vorticity that occurred between 05:50 and 06:30 UT on 2009 March 23 during a quiet time of the terrestrial magnetotail. The uneven distributions of the density and temperature of the vortex observed by the three near-Earth satellites (THA, THD, and THE) indicate that the plasma in the solar wind gradually mixed into the near-Earth magnetotail through a series of nonequilibrium processes. Both the flow vortices and dipolarization observed by the three near-Earth satellites were about 10 minutes earlier than those observed by the two satellites (THB and THC) in the mid-magnetotail. Further analysis of the relationship between vorticity, field-aligned current, and energy transport reveals that the flow vortex interacted with the surrounding plasma during its tailward propagation. The field-aligned current related to the vorticity could only generate a pseudo-breakup of the aurora in the ionosphere. Thus, we speculate that this flow vortex mainly transports mass and energy from the solar wind to the near-magnetotail, propagates tailward to the mid-magnetotail, and heats the encountered plasma by dissipating its bulk flow and dominant thermal energy. These results shed light on the mass mixing, energy transport, and dissipation of the plasma flow vortex during quiet levels of geomagnetic activity on large spatial scales.

Study on Temporal and Spatial Evolution Characteristics of Inter-provincial Boundary Effect in Pan-Pearl River Delta Region

In this paper, Barro regression model is constructed by using urban per capita GDP and the shortest transportation distance, and the border effect of Pan-Pearl River Delta region in 2011-2021 is measured in stages. The results show that: (1) the convergence of economic development in this region is strong at first and then weak, especially in Guizhou and Guangxi; (2) The inter-provincial border shielding effect is weakened, but the intermediary effect is enhanced, but the intensity is low, which shows that the boundaries of intermediary effect have increased from 8 in the first five years to 11 in the last five years, and the border shielding effect in Guizhou is stronger; (3) Traffic improvement has promoted urban economic growth, but it has no significant impact on inter-provincial economy, and the influence of distance factors has weakened.

Coupling and Coordination Relationship of Economic–Social–Natural Composite Ecosystem in Central Yunnan Urban Agglomeration

Exploring the spatio-temporal differentiation characteristics and coupling coordination relationship of the composite ecosystem of urban agglomerations is of great significance for promoting the synergistic sustainable development and integration construction of urban agglomerations. This paper is based on LUCC (Land Use and Land Cover Change) data, a DEM (Digital Elevation Model), and temperature, precipitation, and other multi-source data, using the central Yunnan urban agglomeration as an example and constructing a multi-dimensional evaluation index system highlighting development quality and efficiency. The entropy weight method was first used to determine the comprehensive weights to evaluate the regional economic and social development level. Then, the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was used to quantitatively calculate and analyze the spatial and temporal evolution characteristics of the four key ecosystem services, evaluating the spatio-temporal evolution characteristics of the natural subsystem. The coupling coordination model was used to quantitatively analyze the evolution of the coupling coordination of the composite ecosystems in the central Yunnan urban agglomeration during the period of 2010–2020, and to reveal its development law. The results show the following: ➀ During the study period, the socio-economic subsystems in the central Yunnan urban agglomeration demonstrated an outward radiative growth from Kunming City, marked by underdeveloped sub-centers and prevalent low-level areas. ② Trends in ecosystem services varied, with water and soil conservation showing fluctuating increases, carbon sequestration remaining stable, and habitat quality declining. The critically important integrated ecosystem services zone of the natural subsystem is mainly located in the northeastern region and southwestern edge of the study area. ③ In 2020, the coupling coordination degree of the composite ecosystem was 0.9492. This showed that economic, social, and ecological subsystems are highly coupled, with consistent overall development trends and strong interactions. ④ The increase in the degree of harmonization amounted to 7.82%, with lagging subsystems varying in the degree of harmonization in subregions. This study can provide a scientific foundation for the development of policies for the Central Yunnan urban agglomeration, promoting regional sustainable development and optimizing the spatial pattern of the national territory.

Remote Sensing Ecological Quality and Its Response to the Rocky Desertification in the World Heritage Karst Sites

Clarifying the spatial and temporal evolution characteristics of the ecological environment quality of World Heritage Karst Sites (WHKSs) and its response to different rocky desertification grades at spatial scales is crucial for the monitoring and protection of WHKSs as well as the implementation of ecological and environmental policies in karst regions. The ecological evaluation model of Remote Sensing Ecological Index (RSEI) was used to evaluate the ecological environment of Libo–Huanjiang World Heritage Karst site and Shibing World Heritage Karst site, and then the spatial autocorrelation and geo-detection model was used to further analyze the ecological environment, and final spatial overlay of RSEI and rocky desertification by year to analyze the linkage relationship between RSEI and rocky desertification. The results showed that (1) in the three-phase ecological environmental quality evaluation of the two heritage sites, the RSEI in 2010, 2016, and 2022 reached 0.60, 0.67, and 0.64 for the Libo–Huanjiang heritage site, and RSEI in 2010, 2016, and 2022 for the Shibing heritage site reached 0.60, 0.74, and 0.70, respectively; (2) the RSEI of both heritage sites show a gradually increasing positive spatial correlation, and has significant spatial aggregation characteristics, with both heritage sites dominated by the high-high and low-low spatial aggregation categories; (3) both heritage sites have the highest degree of explanation of changes in ecological quality by the NDBSI factor, indicating that this factor plays a key role in changes in ecological quality at heritage sites; (4) the response of the RSEI mean value of Libo–Huanjiang in each grade of rocky desertification area is, from high to low, no rocky desertification, non-karst, potential rocky desertification, mild rocky desertification, moderate rocky desertification, intensive rocky desertification, and extreme intensity rocky desertification, and the response of the RSEI mean value of Shibing is, from high to low, non-karst, no rocky desertification, potential rocky desertification, mild rocky desertification, and moderate rocky desertification. The spatial superposition analysis of the RSEI index and rocky desertification index can quantitatively study the changing status of the ecological environment in different rocky desertification areas, and the results of the study can provide theoretical references for the environmental monitoring and the prevention and control of rocky desertification in the karst areas and WHKSs.

Study on the spatial and temporal evolution characteristics and future trends of China’s coal mining and dressing industry green total factor productivity

Study on the spatial and temporal evolution characteristics and future trends of China’s coal mining and dressing industry green total factor productivity

Spatial-temporal evolution and trend prediction of ecological civilization construction efficiency from the perspective of audit

The performance evaluation of ecological civilization construction is an important content of ecological civilization audit. The super-efficiency slacks-based measure model measured inter-provincial ecological civilization construction efficiency based on the panel data of Chinese provinces and cities during 2000–2020. Based on the time series and spatial correlation analyses, the traditional and spatial Markov probability transfer matrixes were constructed to explore the spatial and temporal dynamic evolution characteristics of China’s ecological civilization construction efficiency and predict its long-term trend. The study revealed that China’s ecological civilization construction efficiency has a “bimodal” distribution with a stable increase in fluctuation. The gap between the peak heights is small; however, the overall ecological civilization construction efficiency is low. We also revealed that from the long-term evolution trend forecast, most provinces and cities gradually shift to higher levels of ecological civilization construction efficiency and gradually evolve into having a gradual increase pattern in the geographical context of low ecological civilization construction efficiency, resulting in the long-term evolution of the stable state performance. In the geographic context of low ecological civilization construction efficiency, the long-term evolution of the stable state is a partial “single-peaked” distribution. Finally, we analyzed the directions for improvement in this study and suggested that inter-regional ecological civilization construction policy connections and the fortification of inter-regional ecological civilization construction cooperation and exchange can effectively improve China’s ecological civilization construction efficiency, narrow the gap between provinces and cities, and promote the construction of ecological civilization.

Calculation of Urban Green Competitiveness and Analysis of Spatial and Temporal Evolution Characteristics in China

It is particularly important to analyze the influencing factors of urban green competitiveness and the spatial distribution characteristics under the constraint of carbon emissions. The research ideas of this paper: firstly, this paper selects the carbon emission intensity and urban green competitiveness data in 2010, 2013, 2015, 2018 and 2020 for panel data regression; secondly, this paper applies a variety of methods to carry out the robustness test, and the results show that the regression model is better, and analyzes the development of urban green competitiveness for the heterogeneity of large cities and small cities; subsequently, the use of inverse geographic matrix to analyze the spatial correlation between the global Moran index and local Moran index for urban green competitiveness, and to analyze the spatial and temporal pattern evolution of urban green competitiveness. The conclusions of the study show that, from the viewpoint of influencing factors, carbon emission intensity presents a significant negative effect on the development of urban green competitiveness, and has a greater impact on the green competitiveness of large cities than that of small cities. From the perspective of spatial correlation, urban green competitiveness presents positive spatial correlation and shows a growing trend over time. Finally, this paper puts forward relevant policy recommendations based on the findings of the study.

Monitoring Analysis of Urban Subsidence in Northern Henan Province Based on TS-InSAR Technology

The protracted and pervasive incidence of land subsidence emerges as a pivotal factor exerting a substantial impact on the sustainable development of urban landscapes. A nuanced comprehension of the spatiotemporal evolution characteristics of land subsidence within the Northern Henan Plain assumes paramount significance in the context of mitigating potential urban geological disasters. This study endeavors to redress the deficiency in information concerning the temporal and spatial evolution characteristics of enduring deformation in cities within the northern plain of Henan Province. To this end, the authors leveraged Sentinel-1A radar data processed through persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology to elucidate the distribution patterns of ground deformation and temporal evolution characteristics within the expansive 24-scene coverage research area. Empirical findings illuminate conspicuous surface deformation in Anyang, Puyang, and Hebi throughout the monitoring period. Spatially, land subsidence in the study area predominantly clusters in the suburban peripheries of the cities, with Hebi and Puyang registering a maximum subsidence rate exceeding 25 mm per annum. Temporally, land subsidence manifests predominantly during autumn and winter, whereas spring and summer display relatively stable land subsidence interspersed with a slight ground uplift. In order to rectify the spatial disparities observed between leveling data and PS-InSAR monitoring data, this experiment employed an averaging procedure on the PS-InSAR monitoring data, subsequently subjecting it to comparative analysis with the leveling data. Additionally, through the integration of the singular spectrum analysis (SSA) method and the time series deformation model, this study aspires to attain a comprehensive understanding of the temporal dynamics manifested in the PS-InSAR monitoring outcomes, while concurrently elucidating the factors influencing the observed deformations. Ultimately, this analysis discloses that the monitoring outcomes derived via PS-InSAR technology exhibit a root mean square error of ±12.9 mm and a standard deviation of ±13.31 mm. These statistical metrics furnish valuable insights into the precision and consistency of the PS-InSAR monitoring data. Drawing upon a comparative scrutiny of on-site data and historical remote sensing imagery within the study area, it has been discerned that excessive groundwater extraction and expansive surface engineering initiatives stand as the principal instigators of land subsidence in the research domain. Consequently, this experiment assumes the role of a salient reference for the mitigation of urban ground subsidence within the study area.

Spatial Patterns and the Evolution of Logistics Service Node Facilities in Large Cities—A Case from Wuhan

Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city’s functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation and spreading characteristics of diverse LSNFs in Wuhan in 2011, 2014, 2017, and 2020, employing kernel density analysis, average nearest neighbor index, mean center, and distance distribution frequency, seeking to characterize the spatial evolution characteristics of LSNF, alongside examining the trends in distances to city cores, principal adjoining roads, and production and consumption sites. The following conclusions were made: (1) Between 2011 and 2020, various types of LSNFs in Wuhan experienced a pattern characterized by the noticeable coexistence of spatial expansion and agglomeration, particularly visible after 2014. The degree of agglomeration is classified in a descending order as follows: CWC, STN, PSN, and PDN. (2) An “absolute diffusion” phenomenon characterizes the distribution of distances between various kinds of LSNFs and city cores or neighboring roads, with the lion’s share of high-frequency distribution zones spreading beyond city cores by 5–10 km, and a majority of the LSNFs being situated within 1 km from adjacent roads. (3) While the LSNF collective exhibits a stronger tendency towards the consumption facet, it reflects a surrounding of industrial production sites on the production facet and locations of manufactured goods consumption on the consumption facet, followed by locations of agricultural product consumption and comprehensive consumption sites.

Deep fault sliding rates for Ka-Ping block of Xinjiang based on repeating earthquakes

Abstract The seismically active Ka-Ping Block within Xinjiang, China, represents a zone of potential earthquake hazards, and existing surface measurements cannot fully reflect the area’s sub-surface slip rates. To determine these slip rates and characterize the level of hazard that the study area may face in future years, using a cross-correlation of waveforms, we identified 432 repeat sequences along large faults (F1–F5) in the Ka-Ping Block between September 2009 and April 2022 and computed the annual slip rate for every sequence with the empirical relationship of the moment and the seismic magnitude. Spatial distribution images and temporal evolution characteristics of deep deformation in fault zones were constructed. We obtained five asperities in the Ka-Ping Block, the western portion of the PiQiang fault (F4) had a larger yearly slide rate than its eastern portion, and the southwest and eastern areas of the KEP station show an elevated risk of seismic activity within the next two years.