The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factor...The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factors(elevation,slope and topographic wetness index),intrinsic soil factors(soil bulk density,sand content,silt content,and clay content)and combined environmental factors(including the first two principal components(PC1 and PC2)of the Vis-NIR soil spectra)along three sampling transects located at the upstream,midstream and downstream of Taiyuan Basin on the Chinese Loess Plateau.We separated the multivariate data series of STN and influencing factors at each transect into six intrinsic mode functions(IMFs)and one residue by multivariate empirical mode decomposition(MEMD).Meanwhile,we obtained the predicted equations of STN based on MEMD by stepwise multiple linear regression(SMLR).The results indicated that the dominant scales of explained variance in STN were at scale 995 m for transect 1,at scales 956 and 8852 m for transect 2,and at scales 972,5716 and 12,317 m for transect 3.Multi-scale correlation coefficients between STN and influencing factors were less significant in transect 3 than in transects 1 and 2.The goodness of fit root mean square error(RMSE),normalized root mean square error(NRMSE),and coefficient of determination(R2)indicated that the prediction of STN at the sampling scale by summing all of the predicted IMFs and residue was more accurate than that by SMLR directly.Therefore,the multi-scale method of MEMD has a good potential in characterizing the multi-scale spatial relationships between STN and influencing factors at the basin landscape scale.展开更多
Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from i...Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.展开更多
The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions.Taking the proportion of ur...The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions.Taking the proportion of urbanization zones,agricultural development zones and ecological security zones as the basic parameter,this paper explores the spatial structures of major function zoning at different scales using spatial statistics,spatial modeling and landscape metrics methods.The results show:First,major function zones have spatial gradient structures,which are prominently represented by latitudinal and longitudinal gradients,a coastal distance gradient,and an eastern-central-western gradient.Second,the pole-axis system structure and core-periphery structure exist at provincial scales.The general principle of the pole-axis structure is that as one moves along the distance axis,the proportion of urbanization zones decreases and the proportion of ecological security zones increases.This also means that the proportion of different function zones has a ring-shaped spatial differentiation principle with distance from the core.Third,there is a spatial mosaic structure at the city and county scale.This spatial mosaic structure has features of both spatial heterogeneity,such as agglomeration and dispersion,as well as of mutual,adjacent topological correlation and spatial proximity.The results of this study contribute to scientific knowledge on major function zones and the principles of spatial organization,and it acts as an important reference for China’s integrated geographical zoning.展开更多
The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity d...The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.展开更多
Imaging quality is a critical component of compressive imaging in real applications. In this study, we propose a compressive imaging method based on multi-scale modulation and reconstruction in the spatial frequency d...Imaging quality is a critical component of compressive imaging in real applications. In this study, we propose a compressive imaging method based on multi-scale modulation and reconstruction in the spatial frequency domain. Theoretical analysis and simulation show the relation between the measurement matrix resolution and compressive sensing(CS)imaging quality. The matrix design is improved to provide multi-scale modulations, followed by individual reconstruction of images of different spatial frequencies. Compared with traditional single-scale CS imaging, the multi-scale method provides high quality imaging in both high and low frequencies, and effectively decreases the overall reconstruction error.Experimental results confirm the feasibility of this technique, especially at low sampling rate. The method may thus be helpful in promoting the implementation of compressive imaging in real applications.展开更多
Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variati...Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion blur.To enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial context.We build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small objects.We replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small objects.Furthermore,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple scales.This module enhances the perception of spatial contextual features and the utilizationof multiscale feature information.On the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.展开更多
Land-use efficiency is low for the urban agglomeration of China. High-speed transportation construction has been an important factor driving land use change. It is critically important to explore the spatial relations...Land-use efficiency is low for the urban agglomeration of China. High-speed transportation construction has been an important factor driving land use change. It is critically important to explore the spatial relationship between the high-speed transportation superiority degree and land-use efficiency. We built a model to evaluate the benefits of convenient high-speed transportation using the relative density of highways and the distance from high-speed rail stations and airports as a metric. We used 42 counties of the Shandong Peninsula urban agglomeration as an example. Land-use efficiency was calculated by a DEA model with capital, labor, economic benefits and environmental benefits as input and output factors. We examined the spatial relationships between high-speed transport superiority degree and land-use efficiency and obtained the following results. First, there are significant spatial differences in the relationships between the high-speed transportation superiority degree and land-use efficiency. Taking the two major cities of Jinan and Qingdao as the hubs, the core surrounding counties show significant spatial relationship between land-use efficiency and the high-speed transportation superiority degree. Spatial correlation declines as the distance from the hubs increases. Land-use efficiency is less than high-speed transportation convenience in areas along the transportation trunks that are distant from the hub cities. Correlation is low in areas that are away from both hub cities and transportation trunk routes. Second, high-speed transportation has a positive relationship with land-use efficiency due to the mechanism of element agglomeration exogenous growth. Third, high-speed transportation facilitates the flow of goods, services and technologies between core cities and peripheral cities as space spillover(the hub effect). This alters the spatial pattern of regional land-use efficiency. Finally, the short-board effect caused by decreased high-speed transport construction can be balanced by highway construction and the proper node layouts of high-speed rail stations and airports, resulting in a well-balanced spatial pattern of land-use efficiency.展开更多
With the urban expansion and economic restructuring, the jobs-housing relationship has become an important issue in studies on urban spatial structure. This paper employed a job accessibility model, which is an evalua...With the urban expansion and economic restructuring, the jobs-housing relationship has become an important issue in studies on urban spatial structure. This paper employed a job accessibility model, which is an evaluation instrument to measure the jobs-housing relationship in Beijing Metropolitan Area from a job accessibility perspective. The results indicate that the population in the central city is declining, whereas the population in the suburbs is consistently growing and forming new population centers. However, the distribution pattern of employment is still highly centralized. Job accessibility varies in different locations, but the inner-city areas(within the Third Ring road) have seen improved job accessibility over time while job accessibility in the suburbs(especially outside the Fourth Ring road) has decreased, and this has led it to become a primary area of residential and employment mismatch. At the same time, the new towns in the outer suburbs have not yet demonstrated great potential to attract more jobs. In addition we find that, to some extent, urban planning changes the jobs-housing relationship, but a polycentric urban spatial structure is not yet evident. The floating population and related housing policy also affect the jobs-housing relationship. We propose some measures to resolve the spatial mismatch as well as some future research directions.展开更多
The water adsorption by shale significantly affects shale gas content and its seepage capacity.However,the mechanism of water adsorption by shale is still unclear due to its strong heterogeneity and complicated pore s...The water adsorption by shale significantly affects shale gas content and its seepage capacity.However,the mechanism of water adsorption by shale is still unclear due to its strong heterogeneity and complicated pore structure.The relationship between the adsorbed water content at different relative humidities(RHs)and shale compositions,as well as shale pore structure and the spatial configuration relationship between organic matter(OM)and clay minerals,was investigated to clarify the controlling factors and mechanisms of water adsorption by Longmaxi Formation shale from the Southern Sichuan Basin in China.Consequently,the water adsorption process could be generally divided into three different stages from 0%RH to 99%RH.Furthermore,the Johnston’s clay mine ral interlayer pore structure model(JCM),the Freundlich model(FM)and the Dubinin-Astakhov model(DAM)were tested to fit the three water adsorption stages from low RH to high RH,respectively.The fitting results of the JCM and FM at lower RHs were far from good,while the fitting results of DAM at higher RHs were acceptable.Accordingly,two revised models(LRHM and MRHM)considering the spatial configuration relationship between OM and clay minerals were proposed for the two stages with lower RHs,and performed better fitting results indicating the pronounced effect of the spatial configuration relationship between OM and clay minerals on the water adsorption process of Longmaxi Formation shale.The outcomes of this study will contribute to clarifying the water distribution characteristics in the pore network of shale samples with variable water contents.展开更多
Numerous studies deal with spatial analysis of green innovation(GI).However,researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China.This paper seeks...Numerous studies deal with spatial analysis of green innovation(GI).However,researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China.This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000-2019.We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales,including regional,provincial,and prefectural.Additionally,we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development.The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale,with significant spatial differences of GI decreasing in each scale.Furthermore,the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales,exhibiting the“club convergence”effect and a tendency to transfer to higher levels of proximity.This effect is more pronounced on a larger scale,but it is increasingly challenging to transfer to higher levels.The study also indicates a steady and sustained growth of GI in China,which concentrates on higher levels over time.These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.展开更多
Regional drought analysis provides useful information for sustainable water resources management.In this paper,a standardized precipitation index(SPI) at multiple time scales was used to investigate the spatial patter...Regional drought analysis provides useful information for sustainable water resources management.In this paper,a standardized precipitation index(SPI) at multiple time scales was used to investigate the spatial patterns and trends of drought in the Han River Basin,one of the largest tributaries of Yangtze River,China.It was found that,in terms of drought severity,the upper basin of the Han River is the least,while the growing trend is the most conspicuous;a less conspicuous growing trend can be observed in the middle basin;and there is an insignificant decreasing trend in the lower basin.Meanwhile,the impact of drought on the Middle Route of the South-to-North Water Transfer Project was investigated,and it is suggested that water intake must be reduced in times of drought,particularly when successive or simultaneous droughts in the upper and middle basins of the Han River Basin occur.The results can provide substantial information for future water allocation schemes of the South-to-North Water Transfer Project.展开更多
Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods fo...Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.展开更多
Spatial object and spatial relationship are two basic concepts of GIS.Spatial object is the digital representation of geographical entity or phenomenon,which forms the basis for data management and analysis;spatial re...Spatial object and spatial relationship are two basic concepts of GIS.Spatial object is the digital representation of geographical entity or phenomenon,which forms the basis for data management and analysis;spatial relationship is theconnexion between spatial objects when geometric properties are considered.Thecommonly used classification of spatial objects as points,lines and areas is mathe-matically strict,and suitable for data management,but a bit too generalized forrepresenting real entities and extracting spatial relationships.A good classificationmodel should not only be good for representing real entities,but also good for re-vealing spatial relationships,therefore good for formalizing spatial analyses.展开更多
A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of rel...A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of relative distance and relative direction are derived torepresent the spatial orientation relationships among objects of the image. A novel image retrievalalgorithm is presented using these two CASs. The proposed retrieval approach not only satisfies thetransformational invariance, butalso attains the quantitative comparison of matching. Experimentsidentify the effectiveness and efficiency of the algorithm adequately.展开更多
A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model exten...A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.展开更多
At present, gas hydrates are known to occur in continental high latitude permafrost regions and deep sea sediments. For middle latitude permafrost regions of the Tibetan Plateau, further research is required to ascert...At present, gas hydrates are known to occur in continental high latitude permafrost regions and deep sea sediments. For middle latitude permafrost regions of the Tibetan Plateau, further research is required to ascertain its potential development of gas hydrates. This paper reviewed pertinent literature on gas hydrates in the Tibetan Plateau. Both geological and ge- ographical data are synthesized to reveal the relationship between gas hydrate formation and petroleum geological evo- lution, Plateau uplift, formation of permafrost, and glacial processes. Previous studies indicate that numerous residual basins in the Plateau have been formed by original sedimentary basins accompanied by rapid uplift of the Plateau. Ex- tensive marine Mesozoic hydrocarbon source rocks in these basins could provide rich sources of materials forming gas hydrates in permafrost. Primary hydrocarbon-generating period in the Plateau is from late Jurassic to early Cretaceous, while secondary hydrocarbon generation, regionally or locally, occurs mainly in the Paleogene. Before rapid uplift of the Plateau, oil-gas reservoirs were continuously destroyed and assembled to form new reservoirs due to structural and thermal dynamics, forcing hydrocarbon migration. Since 3.4 Ma B.P., the Plateau has undergone strong uplift and extensive gla- ciation, periglacier processes prevailed, hydrocarbon gas again migrated, and free gas beneath ice sheets within sedi- mentary materials interacted with water, generating gas hydrates which were finally preserved under a cap formed by frozen layers through rapid cooling in the Plateau. Taken as a whole, it can be safely concluded that there is great temporal and spatial coupling relationships between evolution of the Tibetan Plateau and generation of gas hydrates.展开更多
Spatial relationships are core components in the design and definition of spatial queries.A spatial relationship determines how two or more spatial objects are related or connected in space.Hence,given a spatial datas...Spatial relationships are core components in the design and definition of spatial queries.A spatial relationship determines how two or more spatial objects are related or connected in space.Hence,given a spatial dataset,users can retrieve spatial objects in a given relationship with a search object.Different interpretations of spatial relationships are conceivable,leading to different types of relationships.The main types are(i)topological relationships(e.g.overlap,meet,inside),(ii)metric relationships(e.g.nearest neighbors),and(iii)direction relationships(e.g.cardinal directions).Although spatial information retrieval has been extensively studied in the literature,it is unclear which types of spatial queries can be defined using spatial relationships.In this article,we introduce a taxonomy for naming,describing,and classifying types of spatial queries frequently found in the literature.This taxonomy is based on the types of spatial relationships that are employed by spatial queries.By using this taxonomy,we discuss the intuitive descriptions,formal definitions,and possible implementation techniques of several types of spatial queries.The discussions lead to the identification of correspondences between types of spatial queries.Further,we identify challenges and open research topics in the spatial information retrieval area.展开更多
A distance measure that infers to indicate the evolutionary relationship of protein structures has been developed based on spatial preference factors of residues. The spatial preference factor is a reflection of the e...A distance measure that infers to indicate the evolutionary relationship of protein structures has been developed based on spatial preference factors of residues. The spatial preference factor is a reflection of the environment of residues in tertiary structure. Compared with the phyletic relationships derived from sequence homologies and three-dimensional structures, we find that the two lines of evolution are similar in general. This approach is applied to a group of glins here.展开更多
How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image re...How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.展开更多
Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial...Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multi dimensional histogram and the transformation scheme. Proposed scheme applies two partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.展开更多
基金financially supported by the Research Project of Shanxi Scholarship Council of China (2017– 075)the Natural Science foundation for Young Scientists of Shanxi Province (201801D221103)the Innovation Grant of Shanxi Agricultural University (2017ZZ07)
文摘The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factors(elevation,slope and topographic wetness index),intrinsic soil factors(soil bulk density,sand content,silt content,and clay content)and combined environmental factors(including the first two principal components(PC1 and PC2)of the Vis-NIR soil spectra)along three sampling transects located at the upstream,midstream and downstream of Taiyuan Basin on the Chinese Loess Plateau.We separated the multivariate data series of STN and influencing factors at each transect into six intrinsic mode functions(IMFs)and one residue by multivariate empirical mode decomposition(MEMD).Meanwhile,we obtained the predicted equations of STN based on MEMD by stepwise multiple linear regression(SMLR).The results indicated that the dominant scales of explained variance in STN were at scale 995 m for transect 1,at scales 956 and 8852 m for transect 2,and at scales 972,5716 and 12,317 m for transect 3.Multi-scale correlation coefficients between STN and influencing factors were less significant in transect 3 than in transects 1 and 2.The goodness of fit root mean square error(RMSE),normalized root mean square error(NRMSE),and coefficient of determination(R2)indicated that the prediction of STN at the sampling scale by summing all of the predicted IMFs and residue was more accurate than that by SMLR directly.Therefore,the multi-scale method of MEMD has a good potential in characterizing the multi-scale spatial relationships between STN and influencing factors at the basin landscape scale.
文摘Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.
基金National Natural Science Foundation of China,No.41630644Innovative Think-tank Foundation for Young Scientists of China Association for Science and Technology,No.DXB-ZKQN-2017-048。
文摘The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions.Taking the proportion of urbanization zones,agricultural development zones and ecological security zones as the basic parameter,this paper explores the spatial structures of major function zoning at different scales using spatial statistics,spatial modeling and landscape metrics methods.The results show:First,major function zones have spatial gradient structures,which are prominently represented by latitudinal and longitudinal gradients,a coastal distance gradient,and an eastern-central-western gradient.Second,the pole-axis system structure and core-periphery structure exist at provincial scales.The general principle of the pole-axis structure is that as one moves along the distance axis,the proportion of urbanization zones decreases and the proportion of ecological security zones increases.This also means that the proportion of different function zones has a ring-shaped spatial differentiation principle with distance from the core.Third,there is a spatial mosaic structure at the city and county scale.This spatial mosaic structure has features of both spatial heterogeneity,such as agglomeration and dispersion,as well as of mutual,adjacent topological correlation and spatial proximity.The results of this study contribute to scientific knowledge on major function zones and the principles of spatial organization,and it acts as an important reference for China’s integrated geographical zoning.
基金funded by the Natural Science Foundation Committee,China(41364001,41371435)
文摘The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61601442,61605218,and 61575207)the National Key Research and Development Program of China(Grant No.2018YFB0504302)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant Nos.2015124 and 2019154)。
文摘Imaging quality is a critical component of compressive imaging in real applications. In this study, we propose a compressive imaging method based on multi-scale modulation and reconstruction in the spatial frequency domain. Theoretical analysis and simulation show the relation between the measurement matrix resolution and compressive sensing(CS)imaging quality. The matrix design is improved to provide multi-scale modulations, followed by individual reconstruction of images of different spatial frequencies. Compared with traditional single-scale CS imaging, the multi-scale method provides high quality imaging in both high and low frequencies, and effectively decreases the overall reconstruction error.Experimental results confirm the feasibility of this technique, especially at low sampling rate. The method may thus be helpful in promoting the implementation of compressive imaging in real applications.
基金the Key Research and Development Program of Hainan Province(Grant Nos.ZDYF2023GXJS163,ZDYF2024GXJS014)National Natural Science Foundation of China(NSFC)(Grant Nos.62162022,62162024)+2 种基金the Major Science and Technology Project of Hainan Province(Grant No.ZDKJ2020012)Hainan Provincial Natural Science Foundation of China(Grant No.620MS021)Youth Foundation Project of Hainan Natural Science Foundation(621QN211).
文摘Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion blur.To enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial context.We build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small objects.We replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small objects.Furthermore,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple scales.This module enhances the perception of spatial contextual features and the utilizationof multiscale feature information.On the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.
基金Major Program of National Natural Science Foundation of China,No.41590840,No.41590842.
文摘Land-use efficiency is low for the urban agglomeration of China. High-speed transportation construction has been an important factor driving land use change. It is critically important to explore the spatial relationship between the high-speed transportation superiority degree and land-use efficiency. We built a model to evaluate the benefits of convenient high-speed transportation using the relative density of highways and the distance from high-speed rail stations and airports as a metric. We used 42 counties of the Shandong Peninsula urban agglomeration as an example. Land-use efficiency was calculated by a DEA model with capital, labor, economic benefits and environmental benefits as input and output factors. We examined the spatial relationships between high-speed transport superiority degree and land-use efficiency and obtained the following results. First, there are significant spatial differences in the relationships between the high-speed transportation superiority degree and land-use efficiency. Taking the two major cities of Jinan and Qingdao as the hubs, the core surrounding counties show significant spatial relationship between land-use efficiency and the high-speed transportation superiority degree. Spatial correlation declines as the distance from the hubs increases. Land-use efficiency is less than high-speed transportation convenience in areas along the transportation trunks that are distant from the hub cities. Correlation is low in areas that are away from both hub cities and transportation trunk routes. Second, high-speed transportation has a positive relationship with land-use efficiency due to the mechanism of element agglomeration exogenous growth. Third, high-speed transportation facilitates the flow of goods, services and technologies between core cities and peripheral cities as space spillover(the hub effect). This alters the spatial pattern of regional land-use efficiency. Finally, the short-board effect caused by decreased high-speed transport construction can be balanced by highway construction and the proper node layouts of high-speed rail stations and airports, resulting in a well-balanced spatial pattern of land-use efficiency.
基金Under the auspices of National Natural Science Foundation of China(No.41271132)
文摘With the urban expansion and economic restructuring, the jobs-housing relationship has become an important issue in studies on urban spatial structure. This paper employed a job accessibility model, which is an evaluation instrument to measure the jobs-housing relationship in Beijing Metropolitan Area from a job accessibility perspective. The results indicate that the population in the central city is declining, whereas the population in the suburbs is consistently growing and forming new population centers. However, the distribution pattern of employment is still highly centralized. Job accessibility varies in different locations, but the inner-city areas(within the Third Ring road) have seen improved job accessibility over time while job accessibility in the suburbs(especially outside the Fourth Ring road) has decreased, and this has led it to become a primary area of residential and employment mismatch. At the same time, the new towns in the outer suburbs have not yet demonstrated great potential to attract more jobs. In addition we find that, to some extent, urban planning changes the jobs-housing relationship, but a polycentric urban spatial structure is not yet evident. The floating population and related housing policy also affect the jobs-housing relationship. We propose some measures to resolve the spatial mismatch as well as some future research directions.
基金supported by the National Natural Science Foundation of China(No.41972145)National Science and Technology Major Project of China(No.2017ZX05035—002)+1 种基金the Foundation(No.PRP/indep-2-1904,PRP/indep-3-1707 and No.PRP/indep-3-1615)of State Key Laboratory of Petroleum Resources and Prospecting from China University of Petroleum in Beijingfundamental Research Funds for China University of Geosciences under Award Number 35832019035。
文摘The water adsorption by shale significantly affects shale gas content and its seepage capacity.However,the mechanism of water adsorption by shale is still unclear due to its strong heterogeneity and complicated pore structure.The relationship between the adsorbed water content at different relative humidities(RHs)and shale compositions,as well as shale pore structure and the spatial configuration relationship between organic matter(OM)and clay minerals,was investigated to clarify the controlling factors and mechanisms of water adsorption by Longmaxi Formation shale from the Southern Sichuan Basin in China.Consequently,the water adsorption process could be generally divided into three different stages from 0%RH to 99%RH.Furthermore,the Johnston’s clay mine ral interlayer pore structure model(JCM),the Freundlich model(FM)and the Dubinin-Astakhov model(DAM)were tested to fit the three water adsorption stages from low RH to high RH,respectively.The fitting results of the JCM and FM at lower RHs were far from good,while the fitting results of DAM at higher RHs were acceptable.Accordingly,two revised models(LRHM and MRHM)considering the spatial configuration relationship between OM and clay minerals were proposed for the two stages with lower RHs,and performed better fitting results indicating the pronounced effect of the spatial configuration relationship between OM and clay minerals on the water adsorption process of Longmaxi Formation shale.The outcomes of this study will contribute to clarifying the water distribution characteristics in the pore network of shale samples with variable water contents.
基金supported by the National Natural Science Foundation of China(Grant No.41971201).
文摘Numerous studies deal with spatial analysis of green innovation(GI).However,researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China.This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000-2019.We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales,including regional,provincial,and prefectural.Additionally,we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development.The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale,with significant spatial differences of GI decreasing in each scale.Furthermore,the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales,exhibiting the“club convergence”effect and a tendency to transfer to higher levels of proximity.This effect is more pronounced on a larger scale,but it is increasingly challenging to transfer to higher levels.The study also indicates a steady and sustained growth of GI in China,which concentrates on higher levels over time.These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.
基金Project supported by the National Natural Science Foundation of China (No.50809058)the International Science and Technology Cooperation Program of China (No.2010DFA24320)
文摘Regional drought analysis provides useful information for sustainable water resources management.In this paper,a standardized precipitation index(SPI) at multiple time scales was used to investigate the spatial patterns and trends of drought in the Han River Basin,one of the largest tributaries of Yangtze River,China.It was found that,in terms of drought severity,the upper basin of the Han River is the least,while the growing trend is the most conspicuous;a less conspicuous growing trend can be observed in the middle basin;and there is an insignificant decreasing trend in the lower basin.Meanwhile,the impact of drought on the Middle Route of the South-to-North Water Transfer Project was investigated,and it is suggested that water intake must be reduced in times of drought,particularly when successive or simultaneous droughts in the upper and middle basins of the Han River Basin occur.The results can provide substantial information for future water allocation schemes of the South-to-North Water Transfer Project.
基金funded by the Major Scientific and Technological Innovation Project of Shandong Province,Grant No.2022CXGC010609.
文摘Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.
文摘Spatial object and spatial relationship are two basic concepts of GIS.Spatial object is the digital representation of geographical entity or phenomenon,which forms the basis for data management and analysis;spatial relationship is theconnexion between spatial objects when geometric properties are considered.Thecommonly used classification of spatial objects as points,lines and areas is mathe-matically strict,and suitable for data management,but a bit too generalized forrepresenting real entities and extracting spatial relationships.A good classificationmodel should not only be good for representing real entities,but also good for re-vealing spatial relationships,therefore good for formalizing spatial analyses.
文摘A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of relative distance and relative direction are derived torepresent the spatial orientation relationships among objects of the image. A novel image retrievalalgorithm is presented using these two CASs. The proposed retrieval approach not only satisfies thetransformational invariance, butalso attains the quantitative comparison of matching. Experimentsidentify the effectiveness and efficiency of the algorithm adequately.
基金supported by the National High-Tech Research & Development Program of China (No. 2009AA062802) the Fundamental Research Funds for the Central Universities of China (No. 12CX06001A)Shandong Provincial Natural Science Foundation, China (No. ZR2011DQ011)
文摘A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.
基金supported by Re-search Project No.200420140001 of China Geological Survey
文摘At present, gas hydrates are known to occur in continental high latitude permafrost regions and deep sea sediments. For middle latitude permafrost regions of the Tibetan Plateau, further research is required to ascertain its potential development of gas hydrates. This paper reviewed pertinent literature on gas hydrates in the Tibetan Plateau. Both geological and ge- ographical data are synthesized to reveal the relationship between gas hydrate formation and petroleum geological evo- lution, Plateau uplift, formation of permafrost, and glacial processes. Previous studies indicate that numerous residual basins in the Plateau have been formed by original sedimentary basins accompanied by rapid uplift of the Plateau. Ex- tensive marine Mesozoic hydrocarbon source rocks in these basins could provide rich sources of materials forming gas hydrates in permafrost. Primary hydrocarbon-generating period in the Plateau is from late Jurassic to early Cretaceous, while secondary hydrocarbon generation, regionally or locally, occurs mainly in the Paleogene. Before rapid uplift of the Plateau, oil-gas reservoirs were continuously destroyed and assembled to form new reservoirs due to structural and thermal dynamics, forcing hydrocarbon migration. Since 3.4 Ma B.P., the Plateau has undergone strong uplift and extensive gla- ciation, periglacier processes prevailed, hydrocarbon gas again migrated, and free gas beneath ice sheets within sedi- mentary materials interacted with water, generating gas hydrates which were finally preserved under a cap formed by frozen layers through rapid cooling in the Plateau. Taken as a whole, it can be safely concluded that there is great temporal and spatial coupling relationships between evolution of the Tibetan Plateau and generation of gas hydrates.
基金financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil(CAPES)-Finance Code 001.Anderson C.Carniel was supported by Google as a recipient of the 2022 Google Research Scholar program.
文摘Spatial relationships are core components in the design and definition of spatial queries.A spatial relationship determines how two or more spatial objects are related or connected in space.Hence,given a spatial dataset,users can retrieve spatial objects in a given relationship with a search object.Different interpretations of spatial relationships are conceivable,leading to different types of relationships.The main types are(i)topological relationships(e.g.overlap,meet,inside),(ii)metric relationships(e.g.nearest neighbors),and(iii)direction relationships(e.g.cardinal directions).Although spatial information retrieval has been extensively studied in the literature,it is unclear which types of spatial queries can be defined using spatial relationships.In this article,we introduce a taxonomy for naming,describing,and classifying types of spatial queries frequently found in the literature.This taxonomy is based on the types of spatial relationships that are employed by spatial queries.By using this taxonomy,we discuss the intuitive descriptions,formal definitions,and possible implementation techniques of several types of spatial queries.The discussions lead to the identification of correspondences between types of spatial queries.Further,we identify challenges and open research topics in the spatial information retrieval area.
文摘A distance measure that infers to indicate the evolutionary relationship of protein structures has been developed based on spatial preference factors of residues. The spatial preference factor is a reflection of the environment of residues in tertiary structure. Compared with the phyletic relationships derived from sequence homologies and three-dimensional structures, we find that the two lines of evolution are similar in general. This approach is applied to a group of glins here.
文摘How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.
基金This work is supported by University IT Research Center Project in Korea
文摘Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multi dimensional histogram and the transformation scheme. Proposed scheme applies two partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.
