Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca ...Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca lating urbanization and a dwindling rural populace in China,reconstructing rural settlements to enhance public service accessibility has become a fundamental strategy for achieving the SDGs in rural areas.However,few stud ies have examined the optimal methods for rural settlement reconstruction that ensure accessible and equitable public services while considering multiple existing facilities and service provisions.This paper focuses on rural settlement reconstruction in the context of the SDGs,employing an inverted MCLP-CC(maximal coverage loca tion problem for complementary coverage)model to identify optimal rural settlements and a rank-based method for their relocation.Conducted in Changyuan,a county-level city in Henan Province,China,this study observed significant enhancements in both accessibility and equity following rural settlement reconstruction by utilizing the MH3SFCA(modified Huff 3-step floating catchment area)and the spatial Lorenz curve method.Remarkably,these improvements were achieved without the addition of new facilities,with the accessibility increasing by 44.21%,4.97%,and 3.11%;Gini coefficients decreasing by 19.53%,1.64%,and 3.18%;Ricci-Schutz coef-ficients decreasing by 21.09%,2.09%,and 4.33%for educational,medical,and cultural and sports facilities,respectively.It indicated that rural settlement reconstruction can bolster the accessibility and equity of public ser-vices by leveraging existing facilities.This paper provides a new framework for stakeholders to better reconstruct rural settlements and promote sustainable development in rural areas in China.展开更多
A ground girder is laid on the preprocessed subgrade by gravity compaction and integrally uniformly supported by subgrade in maglev transit.The settlement of the maglev subgrade inevitably affects the vibration state ...A ground girder is laid on the preprocessed subgrade by gravity compaction and integrally uniformly supported by subgrade in maglev transit.The settlement of the maglev subgrade inevitably affects the vibration state of the medium and low speed maglev coupled system by the additional deformation of the maglev track.This study investigated the dynamic properties of the coupled vibration system affected by the subgrade settlement.First,a theoretical coupled vibration model of a maglev train-track-ground girder system with uneven subgrade settlement was proposed and verified.Then,the effect mechanism of the coupled system caused by the uneven subgrade settlement was explored.Finally,settlement types and subgrade support voiding were examined.The analysis showed that the uneven subgrade settlement considerably increased the dynamic responses of the levitation control system and maglev vehicle while having a minor influence on those of the track-ground girder.The influence of a single ground girder settling was the strongest,and adjacent sides’settling of two ground girders was the weakest for the vibration of a maglev train.An extremely large uneven settlement exceeding 6 mm led to active levitation control system instability.The subgrade support voiding enlarged the vehicle-induced vibration of the track ground girder.展开更多
This study focused on realizing Sustainable Development Goal(SDG)6 for inclusive clean water and sanitation;in particular Target 6.3,which aims to reduce untreated wastewater by 2030 while promoting circular wastewate...This study focused on realizing Sustainable Development Goal(SDG)6 for inclusive clean water and sanitation;in particular Target 6.3,which aims to reduce untreated wastewater by 2030 while promoting circular wastewater reuse and recycling globally.The main objective was to assess the adequacy and efficiency of communal septic tank systems in informal settlements while helping local planners and authorities in their decision-making regarding Target 6.3.Quantitative and qualitative approaches were employed with secondary data from previous researchers,and primary data were collected from field surveys,observations,and interviews with members of the local community.The research was delimited to two village administrative divisions known as Rukun Warga(Village Administrative Division,RW):RW 7 and RW 8 of Lebak Siliwangi Kampung in Coblong District,Bandung,West Java,Indonesia.The findings were also compared with situations in other informal settlements in Brazil,Bangladesh,and Nairobi.The results indicated the inadequacy of communal septic tanks in informal settlements due to factors such as substandard system design,limited support and communication between authorities and residents,and the gap between septic tank availability and capacity vis-a-vis demand.Other limiting factors included limited land availability and irregular geomorphology,the latter of which affected the siting and operation of septic tanks due a lack of room for upgrades or expansion in response to continuous population growth.These findings illustrate the need to complement communal septic systems with flexible centralized or decentralized systems to achieve Target 6.3 of SDG 6.展开更多
A gigantic project named Gully Land Consolidation(GLC)was launched in the hillgully region of the Chinese Loess Plateau in 2011 to cope with land degradation and create new farmlands for cultivation.The dynamic change...A gigantic project named Gully Land Consolidation(GLC)was launched in the hillgully region of the Chinese Loess Plateau in 2011 to cope with land degradation and create new farmlands for cultivation.The dynamic change of groundwater table and loess subsidence in the backfilled farmland are the main causes of site disasters and soil disease,but there is a lack of research on these issues.Based on this,the Shijiagou(SJG)backfilled farmland which is a typical GLC engineering site located in Ansai District,Yan'an City,Shaanxi Province was selected as the study area in this paper.Field site monitoring was carried out in this area,including four aspects of monitoring:rainfall,groundwater table,soil moisture and soil settlement displacement.The following findings were obtained from the analysis of the monitoring data in 2019-2020:(1)The backfilled farmlands have suffered a significant groundwater table rise.And the percentage increase of groundwater table increased from the upstream of F-1(such as 49.2%,46.3%,26.4%)to the downstream of F-5(90.0%,52.3%,34.2%correspondingly),which is related to the terrain of the valley channel and dam seepage.It is also revealed that rainfall characteristics are positively correlated with the depth of water infiltration and groundwater table.(2)The influence depth of rainfall infiltration on soil moisture of the backfilled loess in the GLC study area is no more than 2.5 m,and that within 1.5 m depth is significantly affected by rainfall.In addition,the dramatic rise in the groundwater table led to a steep increase in soil moisture,thus the soil underwent collapse deformation due to water immersion,and the farmland experienced large subsidence displacement.(3)The backfilled loess of the GLC farmland was in a continuous consolidation and settlement stage after the filling completion.With the passage of time,the settlement displacement and settlement rate of the backfilled loess gradually decreased,from 1.0-1.9 mm/d in 2019 to 0.4-0.8 mm/d in 2020,which indicates the GLC farmland tended to be stable.This study reveals the hydrological evolution characteristics and settlement deformation laws of the backfilled loess,which is important for the stability of the farmland and the management of the GLC project.展开更多
In contemporary geotechnical projects,various approaches are employed for forecasting the settlement of shallow foundations(S_(m)).However,achieving precise modeling of foundation behavior using certain techniques(suc...In contemporary geotechnical projects,various approaches are employed for forecasting the settlement of shallow foundations(S_(m)).However,achieving precise modeling of foundation behavior using certain techniques(such as analytical,numerical,and regression)is challenging and sometimes unattainable.This is primarily due to the inherent nonlinearity of the model,the intricate nature of geotechnical materials,the complex interaction between soil and foundation,and the inherent uncertainty in soil parameters.Therefore,thesemethods often introduce assumptions and simplifications,resulting in relationships that deviate from the actual problem’s reality.In addition,many of these methods demand significant investments of time and resources but neglect to account for the uncertainty inherent in soil/rock parameters.This study explores the application of innovative intelligent techniques to predict S_(m) to address these shortcomings.Specifically,two optimization algorithms,namely teaching-learning-based optimization(TLBO)and harmony search(HS),are harnessed for this purpose.The modeling process involves utilizing input parameters,such as thewidth of the footing(B),the pressure exerted on the footing(q),the count of SPT(Standard Penetration Test)blows(N),the ratio of footing embedment(Df/B),and the footing’s geometry(L/B),during the training phase with a dataset comprising 151 data points.Then,the models’accuracy is assessed during the testing phase using statistical metrics,including the coefficient of determination(R^(2)),mean square error(MSE),and rootmean square error(RMSE),based on a dataset of 38 data points.The findings of this investigation underscore the substantial efficacy of intelligent optimization algorithms as valuable tools for geotechnical engineers when estimating S_(m).In addition,a sensitivity analysis of the input parameters in S_(m) estimation is conducted using@RISK software,revealing that among the various input parameters,the N exerts the most pronounced influence on S_(m).展开更多
Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunne...Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.展开更多
Accurate prediction of ground surface settlement(GSS)adjacent to an excavation is important to prevent potential damage to the surrounding environment.Previous studies have extensively delved into this topic but all u...Accurate prediction of ground surface settlement(GSS)adjacent to an excavation is important to prevent potential damage to the surrounding environment.Previous studies have extensively delved into this topic but all under the limitations of either imprecise theories or insufficient data.In the present study,we proposed a physics-constrained neural network(PhyNN)for predicting excavation-induced GSS to fully integrate the theory of elasticity with observations and make full use of the strong fitting ability of neural networks(NNs).This model incorporates an analytical solution as an additional regularization term in the loss function to guide the training of NN.Moreover,we introduced three trainable parameters into the analytical solution so that it can be adaptively modified during the training process.The performance of the proposed PhyNN model is verified using data from a case study project.Results show that our PhyNN model achieves higher prediction accuracy,better generalization ability,and robustness than the purely data-driven NN model when confronted with data containing noise and outliers.Remarkably,by incorporating physical constraints,the admissible solution space of PhyNN is significantly narrowed,leading to a substantial reduction in the need for the amount of training data.The proposed PhyNN can be utilized as a general framework for integrating physical constraints into data-driven machine-learning models.展开更多
Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway s...Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.展开更多
The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying ge...The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.展开更多
Twin curved tunnels are often encountered in shield tunnelling,where significant complexities in densely exploited underground space are observed.In this study,the ground settlement and tunnel deformation due to twin-...Twin curved tunnels are often encountered in shield tunnelling,where significant complexities in densely exploited underground space are observed.In this study,the ground settlement and tunnel deformation due to twin-curved shield tunnelling in soft ground were investigated using numerical simulation and field monitoring.Different curvature radii of twin curved tunnels and subsequent effects of tunnel construction were considered to reveal the tunnelling effect on ground surface settlement and tunnel deformation.The results show that the settlement trough yields one offset towards inside of curved shield tunnelling.The location of settlement trough and maximum settlement were affected by curvature radius but except for the shape and width of settlement trough.Adjacent parallel twin-curved shield tunnelling could increase the offset of existing settlement trough and maximum settlement.Then,an empirical prediction of surface settlement trough due to twin-curved shield tunnelling with same tunnel diameters in soft clay was proposed,which was applicable to curvature radius less than 800 m.Finally,a minimum radius of 600 m of curvature tunnel was proposed in terms of allowable convergence deformation of tunnel.The result could provide guidance on safety evaluation for twin curved shield tunnelling construction.展开更多
This study focuses on the analytical prediction of subsurface settlement induced by shield tunnelling in sandy cobble stratum considering the volumetric deformation modes of the soil above the tunnel crown.A series of...This study focuses on the analytical prediction of subsurface settlement induced by shield tunnelling in sandy cobble stratum considering the volumetric deformation modes of the soil above the tunnel crown.A series of numerical analyses is performed to examine the effects of cover depth ratio(C/D),tunnel volume loss rate(h t)and volumetric block proportion(VBP)on the characteristics of subsurface settle-ment trough and soil volume loss.Considering the ground loss variation with depth,three modes are deduced from the volumetric deformation responses of the soil above the tunnel crown.Then,analytical solutions to predict subsurface settlement for each mode are presented using stochastic medium theory.The influences of C/D,h t and VBP on the key parameters(i.e.B and N)in the analytical expressions are discussed to determine the fitting formulae of B and N.Finally,the proposed analytical solutions are validated by the comparisons with the results of model test and numerical simulation.Results show that the fitting formulae provide a convenient and reliable way to evaluate the key parameters.Besides,the analytical solutions are reasonable and available in predicting the subsurface settlement induced by shield tunnelling in sandy cobble stratum.展开更多
It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical fra...It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.展开更多
Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization...Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.展开更多
Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is cruc...Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.展开更多
For a long time,due to lack of accurate data covering large areas,it is difficult to capture the continuous spatial evolutionary trajectory of rural settlements shaped by rapid urbanization and rural land use policies...For a long time,due to lack of accurate data covering large areas,it is difficult to capture the continuous spatial evolutionary trajectory of rural settlements shaped by rapid urbanization and rural land use policies.To fill this gap,based on theoretical analysis this paper systemically detected the changing characteristics of scale,spatial morphology,distribution,and land use pattern of rural settlements in Southern Jiangsu in the past 20 years depending on the data of land resource survey in 2009 and 2019.The study suggests that the total area and per capita size of rural settlements declined by 30%and 2%respectively as a result of rural land consolidation and the influx of enormous immigrants from underdeveloped regions.The spatial density and average shape index dropped by 14%and 44%respectively in the recent decade,indicating an evident trend of decentralization in spatial distribution,and regularization in the spatial morphology.Furthermore,residential land within rural settlements decreased by 33%over the past decade while the land for industry and commercial service steadily increased,demonstrating that the function for manufacturing and diversified services had been strengthened.Considering the emerging issue of the aging population and new business opportunities in rural Southern Jiangsu,rural settlements regeneration might be the focus offutureresearch.展开更多
Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wol...Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)method.High-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet transform.Furthermore,high-embankment settlements were predicted using the EGWO-n-SVR method.In this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model hyperparameters.The proposed NHM was then tested in two case studies.Finally,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were investigated.The results indicate that the NHM suppresses noise and restores details in high-embankment field measurements.Simultaneously,the NHM out-performs other alternative prediction methods in prediction accuracy and robustness.This demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field mea-surements.Moreover,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.展开更多
The classification of Chinese traditional settlements(CTSs)is extremely important for their differentiated development and protection.The innovative double-branch classification model developed in this study comprehen...The classification of Chinese traditional settlements(CTSs)is extremely important for their differentiated development and protection.The innovative double-branch classification model developed in this study comprehensively utilized the features of remote sensing(RS)images and building facade pictures(BFPs).This approach was able to overcome the limitations of previous methods that used only building facade images to classify settlements.First,the features of the roofs and walls were extracted using a double-branch structure,which consisted of an RS image branch and BFP branch.Then,a feature fusion module was designed to fuse the features of the roofs and walls.The precision,recall,and F1-score of the proposed model were improved by more than 4%compared with the classification model using only RS images or BFPs.The same three indexes of the proposed model were improved by more than 2%compared with other deep learning models.The results demonstrated that the proposed model performed well in the classification of architectural styles in CTSs.展开更多
Post-disaster recovery and reconstruction provide an effective way to reduce the disaster vulnerability of, and promote leapfrog development in, an affected area. To date, studies that have used administrative boundar...Post-disaster recovery and reconstruction provide an effective way to reduce the disaster vulnerability of, and promote leapfrog development in, an affected area. To date, studies that have used administrative boundaries to investigate the reconstruction of settlement space have not been able to clearly define the real boundaries of land use changes or quantify the degree of response to the ‘Build-Back-Better’ initiative, and have lacked any consideration of the fourth reconstruction stage–development period(10 years). This study constructed a mountain settlement niche and analyzed the characteristics, spatial reconstruction, and drivers of rural settlements during 2009–2019 in the upper reaches of the Minjiang River, southwest China. The results showed the following:(1) Natural factors were the basis for the formation and development of mountain settlement niches. The scale of the settlement niche and its land use structure depended on the physical geography features and the ethnic farming and grazing traditions. The settlement niche provided a realistic boundary for the spatial reconstruction.(2) The layout of residential land around cropland was the common feature of the mountain settlement niche. Of all the land use types, the roads and rural residential lands showed the most change over the 10 years;13,860 residential patches increased in size and 4,742 patches were abandoned.(3) The area of orchards, planted to reconstruct the economy in the mountains, increased by nearly 2.5 times.(4) Collapses, landslides, and debris flow disasters and the ecological red line influenced the spatial reconstruction. While the main focus of post-disaster recovery is spatial reconstruction, initiatives should include economic and spiritual recovery, and should also achieve sustainable development of the region.展开更多
Pseudo Human Settlements(PHS)are a fundamental element in human settlements geography,serving as an innovative frontier in the exploration of human–land relationships.Since entering the information age,PHS have emerg...Pseudo Human Settlements(PHS)are a fundamental element in human settlements geography,serving as an innovative frontier in the exploration of human–land relationships.Since entering the information age,PHS have emerged as a new catalyst for people's lives and urban development.Based on the Baidu Index,cold hot spot analysis and the Pearson correlation coefficient method were used to evaluate the spatiotemporal variation characteristics of the development of the quality of PHS at different levels in the three provinces of Northeast China(TPNC)during 2011–2022 and to characterize the influence of the system and factors.The results indicated that:1)temporally,PHS exhibits significant fluctuations,with an overall pattern of rapid increase followed by a gradual decline;2)spatially,PHS is marked by regional differentiation,with“three-core”dominance and a“cluster-like”distribution;3)systematically,the five major PHS systems generally exhibit an ascending and then a descending trend;4)in terms of influence,the socialization system serves as the core influence of PHS,with WeChat,JD.COM,and others are identified as the core influencing factors of subsystems.The findings of this study can provide scientific guidance for diversifying approaches to human settlements,promoting sustainable urban development,and revitalizing Northeast China.展开更多
基金funded by the National Nat-ural Science Foundation of China(Grants No.42371433,U2443214)National Key Project of High-Resolution Earth Observation System of China(Grant No.80Y50G19900122/23)Foundation of Key Laboratory of Soil andWater Conservation on the Loess Plateau ofMinistry ofWater Resources(Grant No.WSCLP202301).
文摘Ensuring the provision of accessible,affordable,and high-quality public services to all individuals aligns with one of the paramount aims of the United Nations’Sustainable Development Goals(SDGs).In the face of esca lating urbanization and a dwindling rural populace in China,reconstructing rural settlements to enhance public service accessibility has become a fundamental strategy for achieving the SDGs in rural areas.However,few stud ies have examined the optimal methods for rural settlement reconstruction that ensure accessible and equitable public services while considering multiple existing facilities and service provisions.This paper focuses on rural settlement reconstruction in the context of the SDGs,employing an inverted MCLP-CC(maximal coverage loca tion problem for complementary coverage)model to identify optimal rural settlements and a rank-based method for their relocation.Conducted in Changyuan,a county-level city in Henan Province,China,this study observed significant enhancements in both accessibility and equity following rural settlement reconstruction by utilizing the MH3SFCA(modified Huff 3-step floating catchment area)and the spatial Lorenz curve method.Remarkably,these improvements were achieved without the addition of new facilities,with the accessibility increasing by 44.21%,4.97%,and 3.11%;Gini coefficients decreasing by 19.53%,1.64%,and 3.18%;Ricci-Schutz coef-ficients decreasing by 21.09%,2.09%,and 4.33%for educational,medical,and cultural and sports facilities,respectively.It indicated that rural settlement reconstruction can bolster the accessibility and equity of public ser-vices by leveraging existing facilities.This paper provides a new framework for stakeholders to better reconstruct rural settlements and promote sustainable development in rural areas in China.
基金National Natural Science Foundation of China under Grant Nos.52478467and 52108417Guangdong Basic and Applied Basic Research Foundation under Grant No.2024A1515012569the Natural Science Basic Research Program of Shaanxi under Grant No.2021JQ-101。
文摘A ground girder is laid on the preprocessed subgrade by gravity compaction and integrally uniformly supported by subgrade in maglev transit.The settlement of the maglev subgrade inevitably affects the vibration state of the medium and low speed maglev coupled system by the additional deformation of the maglev track.This study investigated the dynamic properties of the coupled vibration system affected by the subgrade settlement.First,a theoretical coupled vibration model of a maglev train-track-ground girder system with uneven subgrade settlement was proposed and verified.Then,the effect mechanism of the coupled system caused by the uneven subgrade settlement was explored.Finally,settlement types and subgrade support voiding were examined.The analysis showed that the uneven subgrade settlement considerably increased the dynamic responses of the levitation control system and maglev vehicle while having a minor influence on those of the track-ground girder.The influence of a single ground girder settling was the strongest,and adjacent sides’settling of two ground girders was the weakest for the vibration of a maglev train.An extremely large uneven settlement exceeding 6 mm led to active levitation control system instability.The subgrade support voiding enlarged the vehicle-induced vibration of the track ground girder.
文摘This study focused on realizing Sustainable Development Goal(SDG)6 for inclusive clean water and sanitation;in particular Target 6.3,which aims to reduce untreated wastewater by 2030 while promoting circular wastewater reuse and recycling globally.The main objective was to assess the adequacy and efficiency of communal septic tank systems in informal settlements while helping local planners and authorities in their decision-making regarding Target 6.3.Quantitative and qualitative approaches were employed with secondary data from previous researchers,and primary data were collected from field surveys,observations,and interviews with members of the local community.The research was delimited to two village administrative divisions known as Rukun Warga(Village Administrative Division,RW):RW 7 and RW 8 of Lebak Siliwangi Kampung in Coblong District,Bandung,West Java,Indonesia.The findings were also compared with situations in other informal settlements in Brazil,Bangladesh,and Nairobi.The results indicated the inadequacy of communal septic tanks in informal settlements due to factors such as substandard system design,limited support and communication between authorities and residents,and the gap between septic tank availability and capacity vis-a-vis demand.Other limiting factors included limited land availability and irregular geomorphology,the latter of which affected the siting and operation of septic tanks due a lack of room for upgrades or expansion in response to continuous population growth.These findings illustrate the need to complement communal septic systems with flexible centralized or decentralized systems to achieve Target 6.3 of SDG 6.
基金funded by the National Natural Science Foundation of China for Distinguished Young People(No.41825018)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA23090402)the Natural Science Foundation of China(No.41790442)。
文摘A gigantic project named Gully Land Consolidation(GLC)was launched in the hillgully region of the Chinese Loess Plateau in 2011 to cope with land degradation and create new farmlands for cultivation.The dynamic change of groundwater table and loess subsidence in the backfilled farmland are the main causes of site disasters and soil disease,but there is a lack of research on these issues.Based on this,the Shijiagou(SJG)backfilled farmland which is a typical GLC engineering site located in Ansai District,Yan'an City,Shaanxi Province was selected as the study area in this paper.Field site monitoring was carried out in this area,including four aspects of monitoring:rainfall,groundwater table,soil moisture and soil settlement displacement.The following findings were obtained from the analysis of the monitoring data in 2019-2020:(1)The backfilled farmlands have suffered a significant groundwater table rise.And the percentage increase of groundwater table increased from the upstream of F-1(such as 49.2%,46.3%,26.4%)to the downstream of F-5(90.0%,52.3%,34.2%correspondingly),which is related to the terrain of the valley channel and dam seepage.It is also revealed that rainfall characteristics are positively correlated with the depth of water infiltration and groundwater table.(2)The influence depth of rainfall infiltration on soil moisture of the backfilled loess in the GLC study area is no more than 2.5 m,and that within 1.5 m depth is significantly affected by rainfall.In addition,the dramatic rise in the groundwater table led to a steep increase in soil moisture,thus the soil underwent collapse deformation due to water immersion,and the farmland experienced large subsidence displacement.(3)The backfilled loess of the GLC farmland was in a continuous consolidation and settlement stage after the filling completion.With the passage of time,the settlement displacement and settlement rate of the backfilled loess gradually decreased,from 1.0-1.9 mm/d in 2019 to 0.4-0.8 mm/d in 2020,which indicates the GLC farmland tended to be stable.This study reveals the hydrological evolution characteristics and settlement deformation laws of the backfilled loess,which is important for the stability of the farmland and the management of the GLC project.
文摘In contemporary geotechnical projects,various approaches are employed for forecasting the settlement of shallow foundations(S_(m)).However,achieving precise modeling of foundation behavior using certain techniques(such as analytical,numerical,and regression)is challenging and sometimes unattainable.This is primarily due to the inherent nonlinearity of the model,the intricate nature of geotechnical materials,the complex interaction between soil and foundation,and the inherent uncertainty in soil parameters.Therefore,thesemethods often introduce assumptions and simplifications,resulting in relationships that deviate from the actual problem’s reality.In addition,many of these methods demand significant investments of time and resources but neglect to account for the uncertainty inherent in soil/rock parameters.This study explores the application of innovative intelligent techniques to predict S_(m) to address these shortcomings.Specifically,two optimization algorithms,namely teaching-learning-based optimization(TLBO)and harmony search(HS),are harnessed for this purpose.The modeling process involves utilizing input parameters,such as thewidth of the footing(B),the pressure exerted on the footing(q),the count of SPT(Standard Penetration Test)blows(N),the ratio of footing embedment(Df/B),and the footing’s geometry(L/B),during the training phase with a dataset comprising 151 data points.Then,the models’accuracy is assessed during the testing phase using statistical metrics,including the coefficient of determination(R^(2)),mean square error(MSE),and rootmean square error(RMSE),based on a dataset of 38 data points.The findings of this investigation underscore the substantial efficacy of intelligent optimization algorithms as valuable tools for geotechnical engineers when estimating S_(m).In addition,a sensitivity analysis of the input parameters in S_(m) estimation is conducted using@RISK software,revealing that among the various input parameters,the N exerts the most pronounced influence on S_(m).
基金supported by the Natural Science Foundation of Beijing Municipality(No.8222004),Chinathe National Natural Science Foundation of China(No.51978019)+3 种基金the Natural Science Foundation of Henan Province(No.252300420445),Chinathe Doctoral Research Initiation Fund of Henan University of Science and Technology(No.4007/13480062),Chinathe Henan Postdoctoral Foundation(No.13554005),Chinathe Joint Fund of Science and Technology R&D Program of Henan Province(No.232103810082),China。
文摘Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.
基金funded by the National Natural Science Foundation of China(Grant No.52090082)support provided by the China Scholarship Council(Grant No.202206260206).
文摘Accurate prediction of ground surface settlement(GSS)adjacent to an excavation is important to prevent potential damage to the surrounding environment.Previous studies have extensively delved into this topic but all under the limitations of either imprecise theories or insufficient data.In the present study,we proposed a physics-constrained neural network(PhyNN)for predicting excavation-induced GSS to fully integrate the theory of elasticity with observations and make full use of the strong fitting ability of neural networks(NNs).This model incorporates an analytical solution as an additional regularization term in the loss function to guide the training of NN.Moreover,we introduced three trainable parameters into the analytical solution so that it can be adaptively modified during the training process.The performance of the proposed PhyNN model is verified using data from a case study project.Results show that our PhyNN model achieves higher prediction accuracy,better generalization ability,and robustness than the purely data-driven NN model when confronted with data containing noise and outliers.Remarkably,by incorporating physical constraints,the admissible solution space of PhyNN is significantly narrowed,leading to a substantial reduction in the need for the amount of training data.The proposed PhyNN can be utilized as a general framework for integrating physical constraints into data-driven machine-learning models.
文摘Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.
基金supported by a grant from the Research Grant Council of Hong Kong Special Administrative Region(Project No.11207724).
文摘The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.
基金financially supported by the National Natural Science Foundation of China(Grant No.42307260)the Sichuan Natural Science Foundation(Grant No.2023NSFSC0882)the Open Project of the Research Center of Tunnelling and Underground Engineering of Ministry of Education(Grant No.TUC2022-03).
文摘Twin curved tunnels are often encountered in shield tunnelling,where significant complexities in densely exploited underground space are observed.In this study,the ground settlement and tunnel deformation due to twin-curved shield tunnelling in soft ground were investigated using numerical simulation and field monitoring.Different curvature radii of twin curved tunnels and subsequent effects of tunnel construction were considered to reveal the tunnelling effect on ground surface settlement and tunnel deformation.The results show that the settlement trough yields one offset towards inside of curved shield tunnelling.The location of settlement trough and maximum settlement were affected by curvature radius but except for the shape and width of settlement trough.Adjacent parallel twin-curved shield tunnelling could increase the offset of existing settlement trough and maximum settlement.Then,an empirical prediction of surface settlement trough due to twin-curved shield tunnelling with same tunnel diameters in soft clay was proposed,which was applicable to curvature radius less than 800 m.Finally,a minimum radius of 600 m of curvature tunnel was proposed in terms of allowable convergence deformation of tunnel.The result could provide guidance on safety evaluation for twin curved shield tunnelling construction.
基金This study was supported by the National Natural Science Foundation of China(Grant Nos.51538001 and 51978019).
文摘This study focuses on the analytical prediction of subsurface settlement induced by shield tunnelling in sandy cobble stratum considering the volumetric deformation modes of the soil above the tunnel crown.A series of numerical analyses is performed to examine the effects of cover depth ratio(C/D),tunnel volume loss rate(h t)and volumetric block proportion(VBP)on the characteristics of subsurface settle-ment trough and soil volume loss.Considering the ground loss variation with depth,three modes are deduced from the volumetric deformation responses of the soil above the tunnel crown.Then,analytical solutions to predict subsurface settlement for each mode are presented using stochastic medium theory.The influences of C/D,h t and VBP on the key parameters(i.e.B and N)in the analytical expressions are discussed to determine the fitting formulae of B and N.Finally,the proposed analytical solutions are validated by the comparisons with the results of model test and numerical simulation.Results show that the fitting formulae provide a convenient and reliable way to evaluate the key parameters.Besides,the analytical solutions are reasonable and available in predicting the subsurface settlement induced by shield tunnelling in sandy cobble stratum.
基金Under the auspices of the Taishan Scholars Project Special FundsNational Natural Science Fundation of China(No.42077434,42001199)Youth Innovation Technology Project of Higher School in Shandong Province(No.2019RWG016)。
文摘It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.
基金funded by the National Natural Science Foundation of China (Grant Nos. 41971015)Doctoral research program of China West Normal University (Grant Nos.19E067)。
文摘Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.
基金the financial support from the Guangdong Provincial Department of Science and Technology(Grant No.2022A0505030019)the Science and Technology Development Fund,Macao SAR,China(File Nos.0056/2023/RIB2 and SKL-IOTSC-2021-2023).
文摘Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.
基金National Natural Science Foundation of China,No.42171211。
文摘For a long time,due to lack of accurate data covering large areas,it is difficult to capture the continuous spatial evolutionary trajectory of rural settlements shaped by rapid urbanization and rural land use policies.To fill this gap,based on theoretical analysis this paper systemically detected the changing characteristics of scale,spatial morphology,distribution,and land use pattern of rural settlements in Southern Jiangsu in the past 20 years depending on the data of land resource survey in 2009 and 2019.The study suggests that the total area and per capita size of rural settlements declined by 30%and 2%respectively as a result of rural land consolidation and the influx of enormous immigrants from underdeveloped regions.The spatial density and average shape index dropped by 14%and 44%respectively in the recent decade,indicating an evident trend of decentralization in spatial distribution,and regularization in the spatial morphology.Furthermore,residential land within rural settlements decreased by 33%over the past decade while the land for industry and commercial service steadily increased,demonstrating that the function for manufacturing and diversified services had been strengthened.Considering the emerging issue of the aging population and new business opportunities in rural Southern Jiangsu,rural settlements regeneration might be the focus offutureresearch.
基金We acknowledge the funding support from the National Natural Science Foundation of China(Grant No.51808462)the Natural Science Foundation Project of Sichuan Province,China(Grant No.2023NSFSC0346)the Science and Technology Project of Inner Mongolia Transportation Department,China(Grant No.NJ-2022-14).
文摘Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)method.High-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet transform.Furthermore,high-embankment settlements were predicted using the EGWO-n-SVR method.In this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model hyperparameters.The proposed NHM was then tested in two case studies.Finally,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were investigated.The results indicate that the NHM suppresses noise and restores details in high-embankment field measurements.Simultaneously,the NHM out-performs other alternative prediction methods in prediction accuracy and robustness.This demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field mea-surements.Moreover,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.
基金The Science and Technology Project of Hebei Education Department,No.BJK2022031The Open Fund of Hebei Key Laboratory of Geological Resources and Environmental Monitoring and Protection,No.JCYKT202310。
文摘The classification of Chinese traditional settlements(CTSs)is extremely important for their differentiated development and protection.The innovative double-branch classification model developed in this study comprehensively utilized the features of remote sensing(RS)images and building facade pictures(BFPs).This approach was able to overcome the limitations of previous methods that used only building facade images to classify settlements.First,the features of the roofs and walls were extracted using a double-branch structure,which consisted of an RS image branch and BFP branch.Then,a feature fusion module was designed to fuse the features of the roofs and walls.The precision,recall,and F1-score of the proposed model were improved by more than 4%compared with the classification model using only RS images or BFPs.The same three indexes of the proposed model were improved by more than 2%compared with other deep learning models.The results demonstrated that the proposed model performed well in the classification of architectural styles in CTSs.
基金financially supported by the National Natural Science Foundation of China (Grant No. 42171085)The Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (Grant No.2019QZKK0307)。
文摘Post-disaster recovery and reconstruction provide an effective way to reduce the disaster vulnerability of, and promote leapfrog development in, an affected area. To date, studies that have used administrative boundaries to investigate the reconstruction of settlement space have not been able to clearly define the real boundaries of land use changes or quantify the degree of response to the ‘Build-Back-Better’ initiative, and have lacked any consideration of the fourth reconstruction stage–development period(10 years). This study constructed a mountain settlement niche and analyzed the characteristics, spatial reconstruction, and drivers of rural settlements during 2009–2019 in the upper reaches of the Minjiang River, southwest China. The results showed the following:(1) Natural factors were the basis for the formation and development of mountain settlement niches. The scale of the settlement niche and its land use structure depended on the physical geography features and the ethnic farming and grazing traditions. The settlement niche provided a realistic boundary for the spatial reconstruction.(2) The layout of residential land around cropland was the common feature of the mountain settlement niche. Of all the land use types, the roads and rural residential lands showed the most change over the 10 years;13,860 residential patches increased in size and 4,742 patches were abandoned.(3) The area of orchards, planted to reconstruct the economy in the mountains, increased by nearly 2.5 times.(4) Collapses, landslides, and debris flow disasters and the ecological red line influenced the spatial reconstruction. While the main focus of post-disaster recovery is spatial reconstruction, initiatives should include economic and spiritual recovery, and should also achieve sustainable development of the region.
基金National Natural Science Foundation of China,No.42471246,No.42201221Liaoning Province Natural Science,No.2023-MS-254+1 种基金Liaoning Province Social Science Planning Fund Project,No.L22CJY016Dalian Federation of Social Sciences,No.2022dlskzd037。
文摘Pseudo Human Settlements(PHS)are a fundamental element in human settlements geography,serving as an innovative frontier in the exploration of human–land relationships.Since entering the information age,PHS have emerged as a new catalyst for people's lives and urban development.Based on the Baidu Index,cold hot spot analysis and the Pearson correlation coefficient method were used to evaluate the spatiotemporal variation characteristics of the development of the quality of PHS at different levels in the three provinces of Northeast China(TPNC)during 2011–2022 and to characterize the influence of the system and factors.The results indicated that:1)temporally,PHS exhibits significant fluctuations,with an overall pattern of rapid increase followed by a gradual decline;2)spatially,PHS is marked by regional differentiation,with“three-core”dominance and a“cluster-like”distribution;3)systematically,the five major PHS systems generally exhibit an ascending and then a descending trend;4)in terms of influence,the socialization system serves as the core influence of PHS,with WeChat,JD.COM,and others are identified as the core influencing factors of subsystems.The findings of this study can provide scientific guidance for diversifying approaches to human settlements,promoting sustainable urban development,and revitalizing Northeast China.
