An Improved Hilbert Curve for Parallel Spatial Data Partitioning

A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.

Multi-threaded Fast Distance Field Computation Using Spatial Partition

This article describes three algorithms for distance field generation on triangulated model: brute force algorithm, single-threaded algorithm based on spatial partition and multi-threaded algorithm based on spatial partition. Spatial partition algorithm use equidistant network divide the bounding box into equal-sized cubes, calculates the maximum and minimum distances between the sample point and each of the small cubes,taking the minimum value from the maximum distance as the minimum distance from the sample point to the model named d1, comparing d1 with the distance from sample point to every little cube's minimum distance d2, if d1 <d2, the sample point's distance to all triangles inside this cube are greater than d1, skip this cube, otherwise, calculated the distance from the point to all the triangles intersect with the cube, then alternative d1 with the minimum value, circulate all small cubes intersect with the model. Comparing the calculation results, it can be seen that the algorithm about the multi-threaded distance field relative to the other two algorithms in computational speed is greatly improved especially for complex models.

Slope deformation partitioning and monitoring points optimization based on cluster analysis

The scientific and fair positioning of monitoring locations for surface displacement on slopes is a prerequisite for early warning and forecasting.However,there is no specific provision on how to effectively determine the number and location of monitoring points according to the actual deformation characteristics of the slope.There are still some defects in the layout of monitoring points.To this end,based on displacement data series and spatial location information of surface displacement monitoring points,by combining displacement series correlation and spatial distance influence factors,a spatial deformation correlation calculation model of slope based on clustering analysis was proposed to calculate the correlation between different monitoring points,based on which the deformation area of the slope was divided.The redundant monitoring points in each partition were eliminated based on the partition's outcome,and the overall optimal arrangement of slope monitoring points was then achieved.This method scientifically addresses the issues of slope deformation zoning and data gathering overlap.It not only eliminates human subjectivity from slope deformation zoning but also increases the efficiency and accuracy of slope monitoring.In order to verify the effectiveness of the method,a sand-mudstone interbedded CounterTilt excavation slope in the Chongqing city of China was used as the research object.Twenty-four monitoring points deployed on this slope were monitored for surface displacement for 13 months.The spatial location of the monitoring points was discussed.The results show that the proposed method of slope deformation zoning and the optimized placement of monitoring points are feasible.

A heuristic clustering algorithm based on high density-connected partitions

Clustering data with varying densities and complicated structures is important,while many existing clustering algorithms face difficulties for this problem. The reason is that varying densities and complicated structure make single algorithms perform badly for different parts of data. More intensive parts are assumed to have more information probably,an algorithm clustering from high density part is proposed,which begins from a tiny distance to find the highest density-connected partition and form corresponding super cores,then distance is iteratively increased by a global heuristic method to cluster parts with different densities. Mean of silhouette coefficient indicates the cluster performance. Denoising function is implemented to eliminate influence of noise and outliers. Many challenging experiments indicate that the algorithm has good performance on data with widely varying densities and extremely complex structures. It decides the optimal number of clusters automatically.Background knowledge is not needed and parameters tuning is easy. It is robust against noise and outliers.

Relative Contributions of Spatial and Environmental Processes and Biotic Interactions in a Soil Collembolan Community

Understanding the underlying processes of how communities are structured remains a central question in community ecology. However, the mechanisms of the soil animal community are still unclear, especially for communities on a small scale. To evaluate the relative roles of biotic interactions and environmental and spatial processes in a soil collembolan community, a field experiment was carried out on a small scale(50 m) in the farmland ecosystem of the Sanjiang Plain, Northeast China. In August and October, 2011, we took 100 samples each month in a 50 m × 50 m plot using a spatially delimited sampling design. Variation partitioning was used to quantify the relative contributions of the spatial and environmental variables. A null model was selected to test for the non-randomness pattern of species co-occurrence and body size in assemblages of collembolans and to test whether the pattern observed was the result of environmental or biotic processes that structured the community on a small scale. The results showed that large variance was accounted for by spatial variables(18.99% in August and 21.83% in October, both were significant). There were relatively lower effects of environmental variation(3.56% in August and 1.45% in October, neither was significant), while the soil water content, soil p H and soybean height explained a significant portion of the variance that was observed in the spatial pattern of the collembolan community. Furthermore, the null model revealed more co-occurrence than expected by chance, suggesting that collembolan communities had a non-random co-occurrence pattern in both August and October. Additionally, environmental niche overlap and the body size ratio of co-occurrence showed that interspecific competition was not influential in collembolan community structuring. Considering all of the results together, the contributions of spatial and environmental processes were stronger than biotic interactions in the small-scale structuring of a soil collembolan community.

Environmental and spatial contributions to tree community assembly across life stages and scales in evergreen-deciduous broadleaf karst forests,southwest China

Spatial and environmental processes are two ecological processes that have attracted considerable attention in plant community assembly,depending on sampling scale and life history.However,the processes that determine community assembly have not been studied in the karst region of southwest China.In this study,a 25-ha(500 m×500 m)monitoring plot within the subtropical climax forest in the karst region was established and canonical correspondence analysis was used to reveal the effects of topography and soil on the spatial patterns of tree community assembly.Our study suggests that spatial processes dominate species composition and the combined effects of spatial and environmental processes play an important role.Overall interpretation rate increases with enlarging the sampling scale.However,the pattern of variation partitioning was similar in different life stages.Environmental variables significantly affected species composition at different sampling sizes and life histories and had a higher interpretation rate of species composition on larger s ampling sizes.Topographic wetness index was the most important variable to explain species composition of the environmental variables.These results suggest that it is necessary to consider the relative importance of environmental and spatial factors on community assembly to better understand,conserve,and manage subtropical karst forests.

Temporal and Spatial Scale Dependence of Precipitation Analysis over the Tropical Deep Convective Regime

Data from Goddard cumulus ensemble model experiment are used to study temporal and spatial scale dependence of tropical rainfall separation analysis based on cloud budget during Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment （TOGA COARE）. The analysis shows that the calculations of model domain mean or time-mean grid-scale mean simulation data overestimate the rain rates of the two rainfall types associated with net condensation but they severely underestimate the rain rate of the rainfall type associated with net evaporation and hydrometeor convergence.

Improved Super-Orthogonal Trellis-Coded Spatial Modulation Using STBC-CSM

Trellis coded modulation (TCM) is a scheme that enhances the error performance without extra power not bandwidth. This paper presents a modified Super-Orthogonal Trellis-Coded Spatial Modulation (SOTC-SM) based on a cyclic structure of the Space Time Coding. The developed code benefits from expanded codebook of the Space Time Block Coded Spatial Modulation (STBC-SM) to enhance the coding gain. The set-partitioning and the code design based on the expanded codebook was given for codes with rate of 2 and 3 bps and can be easily extended to higher rates. The Bit-Error Rate (BER) performance of the proposed scheme was evaluated via computer simulation. It was shown that the proposed scheme outperforms the SOTC-SM performance for the same number of transmit antennas.

SPATIALLY SCALABLE RESOLUTION IMAGE CODING METHOD WITH MEMORY OPTIMIZATION BASED ON WAVELET TRANSFORM

This letter exploits fundamental characteristics of a wavelet transform image to form a progressive octave-based spatial resolution. Each wavelet subband is coded based on zeroblock and quardtree partitioning ordering scheme with memory optimization technique. The method proposed in this letter is of low complexity and efficient for Internet plug-in software.

年龄分层下儿童友好型游乐空间设计研究

在“儿童友好”社会背景下,儿童的全面发展成为关注焦点。目的:探索年龄段分层下的社区游乐空间的营造方法,以满足不同年龄段儿童的社区活动需求。方法:在分析不同年龄段儿童个体特征及游戏特征的基础上,引入交互设计理念对社区游乐空间进行交互性分析,进一步定位儿童需求,确保社区游乐空间功能分区更具针对性和有效性。结果:提出关于社区游乐空间的适龄性分区、色彩搭配及空间布局等方面的相关建议。结论:通过合理的空间功能分区,满足不同年龄段儿童在游乐空间中的需求,并提升其互动体验。

“两山”理论视角下县域“三生”功能评价与分区研究——以广西为例

国土空间功能具有复杂的权衡/协同关系,基于广西区县“三生”功能评价与空间分析,结合“两山”理论实现广西国土空间功能分区及优化。文章以广西111个区县为研究单元,构建“三生”功能评价体系,借助空间自相关模型探究“三生”功能空间格局及权衡/协同关系,采用两维图论聚类法实现广西国土空间功能分区。结果表明:(1)广西区县“三生”功能空间格局具有显著规律性与差异性。生产功能呈“南高北低”空间格局,生活功能整体以南宁为中心向桂西与桂北区县衰减,生态功能高值区于桂西连片分布。(2)生产-生活低-低协同型区县于桂北、桂西北连片,二者权衡型区县分布在桂西南或集聚于南宁、柳州和桂林市区;生产-生态高-高协同型区县集聚于桂西南,权衡型区县在桂中聚集或零星分布在桂东南;生活-生态功能以权衡关系为主,于桂西呈连片分布或零星散布在桂中、桂东南。(3)广西国土空间分为功能协同发展区、功能提升区。共包括北部湾生产-生活-生态协同发展区,桂中生产-生态协同发展区,桂东生态功能提升区,桂东北工业生产-生态协同发展区,桂北生产、生活功能提升区,桂西南工业生产-生态协同发展区,桂西工业生产-生态协同发展区,桂西北生产、生活功能提升区8个分区。本研究为国土空间高质量协调发展提供了科学依据。

一种面向精细化地理分区的空间约束聚类方法

在空间分区的相关研究中,虽然已有经典聚类算法k均值聚类(k-means)结合空间约束的成果,但其对于连续平铺面状地理要素的空间聚类适用性不高。因此,本文开展对k-means算法进行空间约束的探讨。通过改进SKATER算法的空间约束方式,构建一种包含自然扩张与次优扩张过程的空间约束的k-means算法;并在两个公共数据集上与已有研究方法进行比较评价。结果表明:本文方法尤其适用于处理连续平铺面状地理要素的分区;通过轮廓系数、DB指数及总残差平方和三个评价指标知,本文方法优于已有的SKATER、AZP及SC k-means方法。研究成果不仅能够为地理信息系统中的空间数据处理提供新的工具,也为聚类算法的研究提供了新的视角。

Partitioning the effects of environmental and spatial heterogeneity on distribution of plant diversity in the Yellow River Estuary

For successful conservation and restoration of biodiversity,it is important to understand how diversity is regulated.In the ecological research community,a current topic of interest is how much of the variation in plant species richness and composition is explained by environmental variation(niche-based model),relative to spatial processes(neutral theory).The Yellow River Estuary(YRE) is a newly formed and fragile wetland ecosystem influenced by both the Yellow River and Bohai Bay.Here,we applied variance partitioning techniques to assess the relative effects of spatial and environmental variables on species richness and composition in the YRE.We also conducted a species indicator analysis to identify characteristic species for three subestuaries within the YRE.Partial redundancy analysis showed that the variations in species richness and composition were explained by both environmental and spatial factors.The majority of explained variation in species richness and composition was attributable to local environmental factors.Among the environmental variables,soil salinity made the greatest contribution to species abundance and composition.Soil salinity was the most important factor in the Diaokou subestuary,while soil moisture was the most important factor influencing species richness in the Qingshui and Chahe subestuaries.The combined effects of soil salinity and moisture determined species richness and composition in the wetlands.These results increase our understanding of the organization and assembly of estuarine plant communities.

A process monitoring method for autoregressive-dynamic inner total latent structure projection

As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.

碳中和目标下长三角城市群碳收支时空分异与碳补偿量化研究

碳补偿是促进区域低碳转型、实现碳中和目标的有效手段。在核算长三角城市群碳吸收量和碳补偿量的基础上分析其时空演化特征,并通过核算碳补偿金额、生态承载系数与经济贡献系数识别支付区与受偿区以及相关功能区,制定科学合理的空间补偿方案。结果表明在2009—2019年:(1)研究区域碳排放量阶段式增长,增量波动较大,呈“增—缓—增”的势态,空间上以沿江高值区城市为中轴,向南北两区削弱;(2)研究区域碳吸收量以2亿吨为平衡点上下浮动,呈增速缓慢、增量较少、整体稳定态势,空间上表现为明显的“外围—中心”特征;(3)支付区和受偿区在城市数量、补偿金额方面不够协调,补偿金额压力较大。因此,需要做好总体谋划,强化顶层设计,控制能源消耗,丰富补偿方式,拓宽补偿渠道。

自适应网络演化视角下公共设施服务半径测算方法——以东莞市小学为例

城市公共服务设施的服务半径直接影响着居民生活的便利程度。目前研究将城市视为均质空间,对初始阈值设置依赖较高,且忽略了其空间复杂性及人口分布情况。因此,本文结合新城市科学思想提出自适应网络演化视角下的设施服务半径测算方法,通过模拟人与设施交互关系,揭示微观基本单元到宏观统计规律的涌现机制;以东莞市小学为研究对象,探索基于供需总量平衡条件下的小学服务半径和学校规模适宜尺度,为城市规划中公共服务设施的合理配置提供路径方法建议。结果表明:①东莞市小学的实际平均服务半径为960 m,大于500 m的国家标准和800 m的地方规范要求;②不同主导功能区的设施服务半径存在较为明显的差异,产业区的小学服务半径相比居住主导型地区的大200 m;③不同规制学校的用地效率不同,54班制小学可作为土地资源紧约束地区的推荐值;④设施配置标准应结合城市或区域的功能分区、人口特征和发展阶段进行动态评估优化,来提升公共服务设施供给与社会需求的匹配度。

Examining residual spatial correlation in variation partitioning of beta diversity in a subtropical forest

Aims The relative roles of ecological processes in structuring beta diver-sity are usually quantified by variation partitioning of beta diversity with respect to environmental and spatial variables or gamma di-versity.However,if important environmental or spatial factors are omitted,or a scale mismatch occurs in the analysis,unaccounted spatial correlation will appear in the residual errors and lead to re-sidual spatial correlation and problematic inferences.Methods Multi-scale ordination(MSO)partitions the canonical ordination results by distance into a set of empirical variograms which charac-terize the spatial structures of explanatory,conditional and residual variance against distance.Then these variance components can be used to diagnose residual spatial correlation by checking assump-tions related to geostatistics or regression analysis.In this paper,we first illustrate the performance of MSO using a simulated data set with known properties,thus making statistical issues explicit.We then test for significant residual spatial correlation in beta diversity analyses of the Gutianshan(GTS)24-ha subtropical forest plot in eastern China.Important Findings Even though we used up to 24 topographic and edaphic variables mapped at high resolution and spatial variables representing spa-tial structures at all scales,we still found significant residual spatial correlation at the 10 m×10 m quadrat scale.This invalidated the analysis and inferences at this scale.We also show that MSO pro-vides a complementary tool to test for significant residual spatial correlation in beta diversity analyses.Our results provided a strong argument supporting the need to test for significant residual spatial correlation before interpreting the results of beta diversity analyses.

背景分区增强下的超高压典型AR运维场景重建方法

运维场景融合度过高,增加了子图间的冗余度。为了提升运维场景的清晰度、饱和度等,提出背景分区增强下的超高压典型AR运维场景重建方法。引入一个场景包围盒,搭建场景空间分割代价函数,生成运维场景包围盒列表,通过计算分割平面选择因子,分割AR运维场景空间。利用VR渲染方法分区增强AR运维场景的背景,将背景分区增强与模糊隶属度松弛迭代相结合,采用可视化定位检测方法融合AR运维场景,进行运维场景的三维重构,增强AR运维场景。根据运维场景重建的空间分布结构,完成超高压典型AR运维场景重建。实验结果表明,AR运维场景的漫游帧率在40~50帧/s,在清晰度、饱和度、亮度等方面具有更好的重建效果,为提高AR运维场景重建的可视化性能和人机交互能力提供了新思路。

基于地理空间适宜性指数自相关的农村居民点整理分区

农村居民点整理是提高建设用地节约集约利用水平的重要手段,为研究基于地理空间属性的区域农村居民点差异化整理方向和模式,提高整理效率,该文以甘肃省临夏县北塬地区为例,从农村居民点地理环境、空间区位、空间分布和空间形态4个方面构建居民点整理地理空间适宜性评价指标体系,通过对各指标标准化值加权求和并进行空间自相关分析,获取适宜性程度的空间聚集特征并结合各行政村超标可整理面积进行农村居民点整理分区,针对不同分区特征提出差异化的整理方向和模式。结果表明：1）地理空间适宜性值为32.093-85.226,空间分异明显,指标体系可较好地反映区域农村居民点地理空间属性差异;2）全局Moran指数为0.66,在0.01显著水平上极显著,呈显著正空间自相关性,LISA图显示只存在显著高高、低低聚集,与全局分析一致;3）分区划为优先整理区、次级整理区、并点整理区和选择性整理区,包含空间聚集特征,可较好地识别居民点整理适宜性和整理效益差异。研究可为农村居民点整理实践作参考,为农村居民点整理分区研究提供新的思路和方法。

多尺度空间单元区域划分方法

传统空间单元的区域划分通常仅以属性数据作为划分依据，而对单元之间空间依赖关系考虑不周。在尺度空间理论基础上，提出多尺度空间单元区域划分方法，在考虑空间单元属性信息的同时，增加了空间单元的相互依赖关系，使得在空间尺度在由小变大过程中，具有高度空间相互依赖关系的空间单元相互融合，得到不同空间尺度下的区域划分。以江苏省从１９７８年到１９９５年的１８年社会经济发展数据为基础，进行了全省社会经济发展水平的区域划分的试验，结果表明与实际发展水平的分布情况相吻合。