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
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
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
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
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
The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the infl...The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the influences of indicators,contexts,and scales.Yet,another potential factor,which has been overlooked,may be the mixed use of spatial and temporal approaches.Using twelve ES and seven well-being indicators and multiple statistical methods,we quantified and compared the spatial and temporal ES–HWB relationships for Inner Mongolia,China.The spatial and temporal relationships differed in both correlation direction and strength.Most relationships of economic and employment-related indicators with food provisioning and supporting services were temporally positive but spatially nonsignificant or negative.Some relationships of economic and employmentrelated indicators with water retention,sandstorm prevention,and wind erosion were temporally negative but spatially complex.However,the spatial and temporal ES–HWB relationships could also be similar in some cases.We conclude that although both the spatial and temporal approaches have merits,space generally cannot substitute for time in the study of ES–HWB relationship.Our study helps reconcile the seemingly conflicting findings in the literature,and suggests that future studies should explicitly distinguish between the spatial and temporal ES–HWB relationships.展开更多
The uneven distribution of medical resources has led to increasingly frequent patient mobility;however, the interaction between this phenomenon and the healthcare supply-demand relationship remains underexplored. The ...The uneven distribution of medical resources has led to increasingly frequent patient mobility;however, the interaction between this phenomenon and the healthcare supply-demand relationship remains underexplored. The present study constructed the 2023Cross-City Patient Mobility Network in China using one million patient mobility data records obtained from online healthcare platforms. We applied urban network analysis to uncover mobility patterns and used the coupling coordination degree model to assess healthcare supply-demand relationships before and after patient mobility. Explainable machine learning further revealed the impact of supply-demand coupling on patient mobility. The results indicated the following: Patient mobility followed administrative boundaries, although megacities serve areas beyond provincial borders;The scale of healthcare supply and demand displayed a multi-centric spatial pattern with a general decline from east to west, and these characteristics of demand distribution were further solidified by patient mobility;Cities with low supply-demand coupling and undersupply experienced patient outflows, while cities with high coupling and oversupply attracted them. In turn, patient mobility helped balance healthcare supply and demand, optimising the coupling relationship across cities. Thus, this research not only provides a methodological reference for understanding the interaction between patient mobility and healthcare systems but also offers empirical insights for public health policy.展开更多
【目的】当前在微地图的内容检索领域尚缺乏系统性的研究。为了填补这一研究空白,本文提出了一种YOLOv8l-FMSC-Spatial (You Only Look Once v8l-Fewer Multi-Scale Convolution-Spatial, YOLOv8l-FMSC-Spatial)模型,实现在手绘地图场...【目的】当前在微地图的内容检索领域尚缺乏系统性的研究。为了填补这一研究空白,本文提出了一种YOLOv8l-FMSC-Spatial (You Only Look Once v8l-Fewer Multi-Scale Convolution-Spatial, YOLOv8l-FMSC-Spatial)模型,实现在手绘地图场景下地理要素的提取及检索。【方法】首先通过对比YOLO系列模型,选取最优的YOLOv8l模型,引入C2f-FMSC模块改进最优模型,建立应用于微地图的YOLOv8l-FMSC训练模型,利用该模型实现栅格地图的地理要素提取;其次针对地理要素的检索需要,建立地理要素的空间关系数据库,设计空间计算检索模块Spatial,通过Spatial模块实现地理要素信息的传递与筛选,进一步地计算用户检索信息与数据库地理要素信息的空间关系关联程度;最后根据空间关系关联程度,从微地图数据库中索引包含相关地理要素信息的地图,实现基于空间关系的地理要素检索模型构建。依据上述方法,在手绘校园地图检索场景中进行验证。实验数据源自各个学校发布内容以及学生自由制作,共计493幅手绘校园地图,在全国范围内研究学校代表性地理要素检索,此类要素包括水体、操场、特色建筑,确保准确识别和检索这些特征元素,验证所提模型的实际适用性。【结果】实验结果表明:训练后的YOLOv8l模型可有效识别手绘地图中的地理要素,并在收集的数据集上验证了模型的有效性和鲁棒性;引入FMSC模块后的YOLOv8l-FMSC模型精确率可达0.8、召回率可达0.764,为实际对比中的最优模型;引入Spatial模块计算模型度量空间关系,可有效捕捉到相关地理要素的空间信息,减少与正射地图检索的差距。【结论】综上,提出的YOLOv8l-FMSC-Spatial模型可根据顾及空间关系的地理要素条件,快速准确地检索到内容相关的手绘地图,从而填补微地图在内容检索方面的研究空缺。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
Rising frequency,intensity,and geographic scope of extreme heat profoundly impede global sustainable economic development.However,existing climate econometric models are limited in capturing the spatial processes thro...Rising frequency,intensity,and geographic scope of extreme heat profoundly impede global sustainable economic development.However,existing climate econometric models are limited in capturing the spatial processes through which extreme heat affects the global economy,often resulting in downward-biased estimates of total economic losses.This study develops a novel multi-scale spatio-temporal model that integrates classic multi-level modeling with spatial statistics,explicitly addressing key challenges faced by climate econometrics.A Bayesian Markov chain Monte Carlo simulation algorithm is derived for model implementation.Using this model,we present the first quantitative assessment of the impacts of extreme heat on global economic production and their scale-dependent spatial processes.Our findings reveal that,at the national scale,economic losses caused by input–output economic linkages initially decline slowly,then drop sharply with increasing connectivity,with an inflection point around 0.1.When accounting for spatial propagation effects,a 1℃increase in extreme heat intensity leads to an average loss of 2.54%[0.90%,4.19%]of annual GDP per capita—substantially higher than estimates assuming economic losses are locally confined.Moreover,the economic impacts of extreme heat exhibit significant spatial heterogeneity,with positive marginal effects detected in colder regions and negative effects in warmer regions,with a turning point around 33.7℃.This study offers a new methodology to evaluate the impact of climate change from a multi-scale and spatial perspective.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
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
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
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
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
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
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.
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.
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.
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supported by the Fundamental Research Funds for the Central Universities(Grant No.B240201068)the National Natural Science Foundation of China(Grant No.42361144861)the National Basic Research Program of China(Grant No.2014CB954303).
文摘The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the influences of indicators,contexts,and scales.Yet,another potential factor,which has been overlooked,may be the mixed use of spatial and temporal approaches.Using twelve ES and seven well-being indicators and multiple statistical methods,we quantified and compared the spatial and temporal ES–HWB relationships for Inner Mongolia,China.The spatial and temporal relationships differed in both correlation direction and strength.Most relationships of economic and employment-related indicators with food provisioning and supporting services were temporally positive but spatially nonsignificant or negative.Some relationships of economic and employmentrelated indicators with water retention,sandstorm prevention,and wind erosion were temporally negative but spatially complex.However,the spatial and temporal ES–HWB relationships could also be similar in some cases.We conclude that although both the spatial and temporal approaches have merits,space generally cannot substitute for time in the study of ES–HWB relationship.Our study helps reconcile the seemingly conflicting findings in the literature,and suggests that future studies should explicitly distinguish between the spatial and temporal ES–HWB relationships.
基金Humanities and Social Sciences Fund of Ministry of Education of China,No.24YJA630097National Natural Science Foundation of China,No.42471304。
文摘The uneven distribution of medical resources has led to increasingly frequent patient mobility;however, the interaction between this phenomenon and the healthcare supply-demand relationship remains underexplored. The present study constructed the 2023Cross-City Patient Mobility Network in China using one million patient mobility data records obtained from online healthcare platforms. We applied urban network analysis to uncover mobility patterns and used the coupling coordination degree model to assess healthcare supply-demand relationships before and after patient mobility. Explainable machine learning further revealed the impact of supply-demand coupling on patient mobility. The results indicated the following: Patient mobility followed administrative boundaries, although megacities serve areas beyond provincial borders;The scale of healthcare supply and demand displayed a multi-centric spatial pattern with a general decline from east to west, and these characteristics of demand distribution were further solidified by patient mobility;Cities with low supply-demand coupling and undersupply experienced patient outflows, while cities with high coupling and oversupply attracted them. In turn, patient mobility helped balance healthcare supply and demand, optimising the coupling relationship across cities. Thus, this research not only provides a methodological reference for understanding the interaction between patient mobility and healthcare systems but also offers empirical insights for public health policy.
文摘【目的】当前在微地图的内容检索领域尚缺乏系统性的研究。为了填补这一研究空白,本文提出了一种YOLOv8l-FMSC-Spatial (You Only Look Once v8l-Fewer Multi-Scale Convolution-Spatial, YOLOv8l-FMSC-Spatial)模型,实现在手绘地图场景下地理要素的提取及检索。【方法】首先通过对比YOLO系列模型,选取最优的YOLOv8l模型,引入C2f-FMSC模块改进最优模型,建立应用于微地图的YOLOv8l-FMSC训练模型,利用该模型实现栅格地图的地理要素提取;其次针对地理要素的检索需要,建立地理要素的空间关系数据库,设计空间计算检索模块Spatial,通过Spatial模块实现地理要素信息的传递与筛选,进一步地计算用户检索信息与数据库地理要素信息的空间关系关联程度;最后根据空间关系关联程度,从微地图数据库中索引包含相关地理要素信息的地图,实现基于空间关系的地理要素检索模型构建。依据上述方法,在手绘校园地图检索场景中进行验证。实验数据源自各个学校发布内容以及学生自由制作,共计493幅手绘校园地图,在全国范围内研究学校代表性地理要素检索,此类要素包括水体、操场、特色建筑,确保准确识别和检索这些特征元素,验证所提模型的实际适用性。【结果】实验结果表明:训练后的YOLOv8l模型可有效识别手绘地图中的地理要素,并在收集的数据集上验证了模型的有效性和鲁棒性;引入FMSC模块后的YOLOv8l-FMSC模型精确率可达0.8、召回率可达0.764,为实际对比中的最优模型;引入Spatial模块计算模型度量空间关系,可有效捕捉到相关地理要素的空间信息,减少与正射地图检索的差距。【结论】综上,提出的YOLOv8l-FMSC-Spatial模型可根据顾及空间关系的地理要素条件,快速准确地检索到内容相关的手绘地图,从而填补微地图在内容检索方面的研究空缺。
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(42471467 and 42293270).
文摘Rising frequency,intensity,and geographic scope of extreme heat profoundly impede global sustainable economic development.However,existing climate econometric models are limited in capturing the spatial processes through which extreme heat affects the global economy,often resulting in downward-biased estimates of total economic losses.This study develops a novel multi-scale spatio-temporal model that integrates classic multi-level modeling with spatial statistics,explicitly addressing key challenges faced by climate econometrics.A Bayesian Markov chain Monte Carlo simulation algorithm is derived for model implementation.Using this model,we present the first quantitative assessment of the impacts of extreme heat on global economic production and their scale-dependent spatial processes.Our findings reveal that,at the national scale,economic losses caused by input–output economic linkages initially decline slowly,then drop sharply with increasing connectivity,with an inflection point around 0.1.When accounting for spatial propagation effects,a 1℃increase in extreme heat intensity leads to an average loss of 2.54%[0.90%,4.19%]of annual GDP per capita—substantially higher than estimates assuming economic losses are locally confined.Moreover,the economic impacts of extreme heat exhibit significant spatial heterogeneity,with positive marginal effects detected in colder regions and negative effects in warmer regions,with a turning point around 33.7℃.This study offers a new methodology to evaluate the impact of climate change from a multi-scale and spatial perspective.
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.
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.
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 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.
