Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

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.

Multi-scale spatial relationships between soil total nitrogen and influencing factors in a basin landscape based on multivariate empirical mode decomposition

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.

SPATIAL OBJECTS AND SPATIAL RELATIONSHIPS

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.

Image Retrieval Based on Objects’ Spatial Orientation Relationships

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.

Spatial relationship-assisted classification from high-resolution remote sensing imagery

Spatial information remains to be an important topic in geographic information system and in remote sensing fields,and spatial relationships have been increasingly incorporated into the image classification processes.Previous studies have employed multiple occurrences of spatial features(shape,texture,etc.,)to improve classification results.However,less attention has been focused on using higher-level spatial relationships for image classification.In this study,two novel spatial relationships,namely,maximum spatial adjacency(MSA)and directional spatial adjacency(DSA),were proposed to assist in image classification.The proposed methods were implemented to extract buildings,beach,and emergent vegetation land-cover classes according to their spatial relationships with their corresponding reference classes.The promising results obtained from this study suggest that the proposed MSA and DSA spatial relationships can be valuable information in defining rule sets for a more reasonable and accurate classification.

Development of Suburban New Towns in Shanghai: Jobs-Housing Spatial Relationship Analysis

This paper identifies the employment and housing locations of residents in Shanghai based on mobile phone signaling data, so as to obtain the employment density and commuting data and analyze the development of nine suburban new towns from the perspective of jobs-housing spatial relationship. Firstly, the paper defines employment-intensive areas and gets the average employment density of each new town according to the employment density data. Then it marks out the scope of the employment influence through analyzing the sources of workers in each new town in accordance with the commuting data. Finally, it analyzes the jobs-housing balance of each new town using independence index, finding that suburban new towns in Shanghai have become main clusters of economic activities, while the scope of employment influence in each new town is still concentrated in its administrative area, with less attraction to residents in other areas. The independence index demonstrates a law that the suburban new town which is farther from the central city sees a higher degree of jobs-housing balance. Among them, new towns located in the outer suburbs with a low independence index indicate their special development situation, the reason of which is worth further study.

Spatial relationship of high-speed transportation construction and land-use efficiency and its mechanism:Case study of Shandong Peninsula urban agglomeration

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.

The new multistage water adsorption model of Longmaxi Formation shale considering the spatial configuration relationship between organic matter and clay minerals

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.

Spatial coupling relationships of gas hydrate formation in the Tibetan Plateau

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.

Two new approaches for image registration based onspatial-temporal relationship

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.

PHYLETIC RELATIONSHIP OF PROTEIN STRUCTURES BASED ON SPATIAL PREFERENCE OF RESIDUES

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.

An efficient selectivity estimation method for spatial query optimization with topological relationships

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.

中国城乡融合空间关联网络结构及其影响因素

基于2001—2021年中国省际面板数据,运用熵值法测度中国省际城乡融合水平,并采用修正引力模型和社会网络分析法,探析中国城乡融合空间关联网络结构特征及其影响因素。结果表明:1) 2001—2021年中国省际城乡融合水平不断提升,但提升进程较为缓慢,空间上呈现由东向西梯度递减的分异特征,具有明显的空间非均衡性。2)中国城乡融合空间关联网络日趋稠密化、复杂化与紧密化,网络连接具有异配性,且网络具备成长性特征,但城乡融合的空间关联尚未达到最佳水平。3)地理空间邻近、经济发展水平差异与城镇化水平差异对城乡融合空间关联网络的优化与演进具有显著正向影响,农业现代化差异与产业结构高级化差异的作用方向和强度随时间变化呈现阶段性特征,而金融规模差异的影响并不显著。

An Effective Image Retrieval Mechanism Using Family-based Spatial Consistency Filtration with Object Region

How to construct an appropriate spatial consistent measurement is the key to improving image retrieval performance. To address this problem, this paper introduces a novel image retrieval mechanism based on the family filtration in object region. First, we supply an object region by selecting a rectangle in a query image such that system returns a ranked list of images that contain the same object, retrieved from the corpus based on 100 images, as a result of the first rank. To further improve retrieval performance, we add an efficient spatial consistency stage, which is named family-based spatial consistency filtration, to re-rank the results returned by the first rank. We elaborate the performance of the retrieval system by some experiments on the dataset selected from the key frames of ＂TREC Video Retrieval Evaluation 2005 （TRECVID2005）＂. The results of experiments show that the retrieval mechanism proposed by us has vast major effect on the retrieval quality. The paper also verifies the stability of the retrieval mechanism by increasing the number of images from 100 to 2000 and realizes generalized retrieval with the object outside the dataset.

空间措施干预疾病流行:融合公共卫生学原理的空间机制分析框架与预防途径

围绕近年来突显的城市疾病问题,既往研究主要聚焦于蓝绿空间的健康效益促进,而较少关注空间因素对于疾病扩散流行的阻断过程与干预途径,致使城市疾病问题的空间管控收效不佳。因此,通过梳理公共卫生学理论与风景园林实践的交叉融贯发展历程,基于公共卫生学“剂量-反应”关系原理提出“空间干预-环境因素-致病因素-疾病反应”的空间机制分析框架,形成融合公共卫生学原理的空间干预模式,构建公共卫生学理论研究向风景园林设计实践的转化途径。通过结合大气环境、水体环境、城市居住环境三类情境中城市疾病问题的空间机制框架应用解析,从空间角度分析城市疾病问题并给予解决策略,进一步展示空间机制框架在症疾生物传染病实际案例中的应用可行性。强调空间干预途径介人疾病初级流行阶段的重要性,旨在促进规划设计措施对城市疾病问题的有效管控,意为当前城市蓝绿空间规划与更新提供不同视角,以期提升后疫情时代健康城市的综合效益。

A LSA Based Image Classification Framework Utilizing Relative Spatial Arrangement

This paper focuses on the problem of automatic image classification （AIC） by proposing a framework based on latent semantic analysis （LSA） and image region pairs. The novel framework employs relative spatial arrangements for region pairs as the primary feature to capture semantics. The significance of this paper is twofold. Firstly, to the best our knowledge, this is the first study of the influence of region pairs as well as their relative spatial information in latent semantic analysis as applied to automatic image classification. Secondly, our proposed method for using the relative spatial information of region pairs show great promise in improving image semantic classi- fication compared with the classical latent semantic analysis method and 2D string representation algorithm.

Spatial Mismatch or Not?Evidence from Public Janitors in Xi’an,China

Research on the spatial mismatch experienced by low-income minority residents is US-centric.However,spatial mismatch is not necessarily an appropriate term when considering the situation of low-wage workers in cities of northwestern China where there is higher proximity between jobs and housing and lower levels of residential segregation.This paper empirically examines the jobs-housing spatial relationship for one of the most typical low-wage groups,namely,public janitors,in Xi’an,China.Also,the causes of the jobs-housing spatial relationship are discussed in detail.Individual-level data based on in-depth interviews and questionnaires,as well as the GIS network analysis method,are used to provide baseline analyses of the jobs-housing spatial relationship.Results indicate that there is no jobs-housing spatial mismatch for public janitors in Xi’an.This can be implied from the short commuting distance and time.A basic cause is that most public janitors rent low-cost accommodation in villages-in-the-city,and in old residential quarters,near to their places of work.Other causes lie in off-peak commuting and high sensitivity to commuting distance due to the greater extent of nonmotorized commuting modes.The conclusions,based on a large number of social surveys,are an illuminating analysis of the spatial mismatch issue among low-wage workers in Chinese cities.

Functional Brain Network Learning Based on Spatial Similarity for Brain Disorders Identification

Functional brain network (FBN) measures based on functional magnetic resonance imaging (fMRI) data, has become important biomarkers for early diagnosis and prediction of clinical outcomes in neurological diseases, such as Alzheimer’s diseases (AD) and its prodromal state (i.e., Mild cognitive impairment, MCI). In the past decades, researchers have developed numbers of approaches for FBN estimation, including Pearson’s correction (PC), sparse representation (SR), and so on. Despite their popularity and wide applications in current studies, most of the approaches for FBN estimation only consider the dependency between the measured blood oxygen level dependent (BOLD) time series, but ignore the spatial relationships between pairs of brain regions. In practice, the strength of functional connection between brain regions will decrease as their distance increases. Inspired by this, we proposed a new approach for FBN estimation based on the assumption that the closer brain regions tend to share stronger relationships or similarities. To verify the effectiveness of the proposed method, we conduct experiments on a public dataset to identify the patients with MCIs from health controls (HCs) using the estimated FBNs. Experimental results demonstrate that the proposed approach yields statistically significant improvement in seven performance metrics over using the baseline methods.

2023年甘肃白银平川区4.9级地震强地面运动特征分析

中国地震预警台网在甘肃白银平川区4.9级地震中获得197组三分向地面运动加速度记录,其中仅100 km范围内就有165组,这是首次在海原断裂带附近获得的大量近断层强震动观测记录。通过近场台站加速度反应谱与设计谱比较、不同周期地震动与预测模型对比,绘制出地震动的空间影响场,研究此次地震的强地面运动特征。结果表明:近场6个土层台的水平向加速度反应谱在卓越周期附近大于8度多遇地震的设计谱,其中GS.D003E台EW向反应谱在峰值处超过8度设防地震的设计谱值,但由于其卓越周期低于当地城乡普通建筑的自振周期,因此其对采取了抗震措施的建筑物的破坏程度较小。土层台观测的PGA、PGV、S_(a)(0.2 s)、S_(a)(0.5 s)等短周期地震动普遍大于地震动预测值,而S_(a)(1.0 s)、S_(a)(2.0 s)等中等周期地震动的观测值与预测值较一致,说明本次地震高频成分的地震动比较卓越。基本站和一般站的地震动观测值普遍大于基准站,结合相邻土层台和基岩台的谱比分析,表明土层场地和地形对地震动有放大作用。PGA、S_(a)(0.2 s)、S_(a)(0.5 s)等短周期地震动除沿断层走向上的幅值较大外,在垂直于断层走向的震中西南侧的幅值也较大。而S_(a)(1.0 s)、S_(a)(2.0 s)和S_(a)(3.0 s)等中等周期的地震动在震中西南侧幅值较大的特点更加明显,可能与震源破裂特性及台站所处局部场地对地震动的影响有关。

旅游产业效率与区域经济发展异速关系时空特征及机理分析——以湖南省为例

旅游产业效率是旅游业提质增效的关键因素,是由粗放型向高质量发展转变的着力点;旅游产业效率与区域经济异速关系分析是深层次解析城市产业结构转型的重要依据。选择湖南省14个市州为研究对象,采用熵值法和DEAMalmquist模型对湖南省2006—2019年间旅游产业效率进行测度,并进一步采用空间变差函数和异速增长模型分析旅游产业效率与区域经济发展的异速增长情况。结果表明:(1)湖南省旅游产业效率存在差异,总体上呈现上升趋势,但与经济增速相比,效率增长略慢。以第二产业为主的其他行业的发展速度超过了旅游业,导致经济增速高于旅游产业。(2)湖南省不同地级市的旅游产业效率存在明显的空间差异,部分地市的旅游产业增长速度低于经济增长速度,一些地市的旅游产业效率波动较大。(3)旅游产业效率演化受不同阶段生产单元利用水平及交通、资源、专业化、信息化、产业结构等因素的影响。