PARE:Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

The proliferation of intelligent,connected Internet of Things(IoT)devices facilitates data collection.However,task workers may be reluctant to participate in data collection due to privacy concerns,and task requesters may be concerned about the validity of the collected data.Hence,it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing(SC)data collection tasks with IoT.To this end,this paper proposes a privacy-preserving data reliability evaluation for SC in IoT,named PARE.First,we design a data uploading format using blockchain and Paillier homomorphic cryptosystem,providing unchangeable and traceable data while overcoming privacy concerns.Secondly,based on the uploaded data,we propose a method to determine the approximate correct value region without knowing the exact value.Finally,we offer a data filtering mechanism based on the Paillier cryptosystem using this value region.The evaluation and analysis results show that PARE outperforms the existing solution in terms of performance and privacy protection.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires

Understanding the mechanisms and risks of forest fires by building a spatial prediction model is an important means of controlling forest fires.Non-fire point data are important training data for constructing a model,and their quality significantly impacts the prediction performance of the model.However,non-fire point data obtained using existing sampling methods generally suffer from low representativeness.Therefore,this study proposes a non-fire point data sampling method based on geographical similarity to improve the quality of non-fire point samples.The method is based on the idea that the less similar the geographical environment between a sample point and an already occurred fire point,the greater the confidence in being a non-fire point sample.Yunnan Province,China,with a high frequency of forest fires,was used as the study area.We compared the prediction performance of traditional sampling methods and the proposed method using three commonly used forest fire risk prediction models:logistic regression(LR),support vector machine(SVM),and random forest(RF).The results show that the modeling and prediction accuracies of the forest fire prediction models established based on the proposed sampling method are significantly improved compared with those of the traditional sampling method.Specifically,in 2010,the modeling and prediction accuracies improved by 19.1%and 32.8%,respectively,and in 2020,they improved by 13.1%and 24.3%,respectively.Therefore,we believe that collecting non-fire point samples based on the principle of geographical similarity is an effective way to improve the quality of forest fire samples,and thus enhance the prediction of forest fire risk.

Spatial Pattern of Compulsory Education Resources in Shijingshan District of Beijing under the Background of Big Data

With the continuous development of promoting high-quality and balanced basic education and the continuous advancement of research on spatial layout of school,it aims to ensure that the public enjoys educational resources fairly.Based on 63 items of POI data of primary and secondary schools in Shijingshan District,Beijing,this study analyzes the spatial layout,degree supply,and coverage of primary and secondary schools in Shijingshan District using three spatial analysis methods:ArcGIS average nearest neighbor,kernel density analysis,and standard deviation ellipse.The results show that the spatial layout of primary and secondary schools in Shijingshan District,Beijing is characterized by overall clustering:the central region is high-density distribution,while the eastern and western parts are scattered.Moreover,this spatial structure continues to develop along the northwest-southeast direction.Although the high-density population areas in the nine streets correspond to the high-density distribution of schools,the service scope of primary and secondary schools does not cover all residential areas,and the distribution of residential areas within the coverage range is uneven.At the same time,the actual degree supply in Shijingshan District is insufficient.

Research on Evaluation of Spatial Vitality and Influencing Factors of Guesthouses Public Areas Based on Rural Tourism Development

In recent years,China has continued to promote the strategy of rural revitalization.The rural tourism industry has developed rapidly in the context of rural revitalization.Now the rural B&B industry has become an important pillar in solving the problem of rural tourism accommodation.Most of the villages in China have begun to carry out the construction of rural lodging,for example,there are residents who use idle houses to carry out construction on their own initiative and projects developed by village collectives,so the rural lodging industry has been vigorously developed.The vitality of supporting industries and landscape resources around the distribution of rural lodging has become a hot spot of rural issues research in recent years.Therefore,we can use the method of data analysis to analyze the industry and function of the public area around the distribution of rural B&B.Through the comparison of data and the interpretation of related cases,the core elements affecting the spatial vitality of B&B public areas can be identified.We will analyze and improve the related elements to find a reasonable way to enhance the spatial vitality value.Finally,the article will put forward suggestions to improve the related spatial vitality as a way to promote the development of rural B&B industry and the progress of rural tourism.

The Study on the Evolution of Urban Spatial Structure in Zhuhai City Based on Spatial Syntax

With the deepening of the Guangdong-Hong Kong-Macao Greater Bay Area strategy and the accelerated integration and development of the east and west sides of the Pearl River Estuary,Zhuhai’s hub position is becoming more and more prominent.The city of Zhuhai has a dense water network and is divided into two urban areas,the east and the west,under the influence of the Mordor Gate waterway.Based on the theory of spatial syntax,this paper carries out an analytical study on the urban spatial structure of Zhuhai,identifies the distribution characteristics of urban POIs,and provides theoretical support for the urban development of Zhuhai.

A Semantic-Sensitive Approach to Indoor and Outdoor 3D Data Organization

Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.

Scaling up the DBSCAN Algorithm for Clustering Large Spatial Databases Based on Sampling Technique

Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.

Unified Platform About Information Issuing,Integration and Management of Meta-Database and Spatial-Database Based on Geology Metadata Standard

With the deepening informationization of Resources & Environment Remote Sensing geological survey conducted,some potential problems and deficiency are:(1) shortage of unified-planed running environment;(2) inconsistent methods of data integration;and(3) disadvantages of different performing ways of data integration.This paper solves the above problems through overall planning and design,constructs unified running environment, consistent methods of data integration and system structure in order to advance the informationization

Spatial Characteristics of Ancient Villages in Western Beijing Based on ASTER GDEM Data

There are hundreds of villages in the western mountainous area of Beijing,of which quite a few have a profound history and form the settlement culture in the western part of Beijing.Taking dozens of ancient villages in Mentougou District as the research sample,the village space as the research object,based on ASTER GDEM database and quantitative analysis tools such as Global Mapper and ArcGIS,this study analyzed from the perspectives of altitude,topography,slope direction,and building density distribution,made a quantitative study on the spatial distribution and plane structure of ancient villages so that the law of village space with the characteristics of western Beijing was summarized to supplement and improve the relevant achievements in the research field of ancient villages in western Beijing.

An Improved Hilbert Curve for Parallel Spatial Data Partitioning

一条新奇 Hilbert 曲线为划分的平行空间数据被介绍，与空间信息和向量数据项的可变长度的特征的巨大数量的性质的考虑。基于改进 Hilbert 弯曲，算法能被设计空间数据在平行空间数据库在多重磁盘之中划分完成几乎制服。因此，数据不平衡的现象能显著地被避免，搜索和询问效率能被提高。

Spatial Quantitative Analysis of Garlic Price Data Based on ArcGIS Technology

In order to solve the hidden regional relationship among garlic prices,this paper carries out spatial quantitative analysis of garlic price data based on ArcGIS technology.The specific analysis process is to collect prices of garlic market from 2015 to 2017 in different regions of Shandong Province,using the Moran's Index to obtain monthly Moran indicators are positive,so as to analyze the overall positive relationship between garlic prices;then using the geostatistical analysis tool in ArcGIS to draw a spatial distribution Grid diagram,it was found that the price of garlic has a significant geographical agglomeration phenomenon and showed a multi-center distribution trend.The results showed that the agglomeration centers are Jining,Dongying,Qingdao,and Yantai.At the end of the article,according to the research results,constructive suggestions were made for the regulation of garlic price.Using Moran’s Index and geostatistical analysis tools to analyze the data of garlic price,which made up for the lack of position correlation in the traditional analysis methods and more intuitively and effectively reflected the trend of garlic price from low to high from west to east in Shandong Province and showed a pattern of circular distribution.

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau:Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorological Forcing Data(PMFD)and the high spatial resolution and upscaled China Meteorological Forcing Data(CMFD)were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(SSiB4/TRIFFID)and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau(TP),a region with complex topography and sparse observations.By comparing the monthly Leaf Area Index(LAI)and Gross Primary Production(GPP)against observations,we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP,reducing RMSEs by 24.3%and 20.5%,respectively.The multi-year averaged GPP decreased from 364.68 gC m^(-2)yr^(-1)to 241.21 gC m^(-2)yr^(-1)with the percentage bias dropping from 50.2%to-1.7%.When using the high spatial resolution CMFD,the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5%and 9.5%,respectively.This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

Spatial Interpolation of Tidal Data Using a Multiple-Order Harmonic Equation for Unstructured Grids

A general spatial interpolation method for tidal properties has been developed by solving a partial differential equation with a combination of different orders of harmonic operators using a mixed finite element method. Numerically, the equation is solved implicitly without iteration on an unstructured triangular mesh grid. The paper demonstrates the performance of the method for tidal property fields with different characteristics, boundary complexity, number of input data points, and data point distribution. The method has been successfully applied under several different tidal environments, including an idealized distribution in a square basin, coamplitude and cophase lines in the Taylor semi-infiite rotating channel, and tide coamplitude and cophase lines in the Bohai Sea and Chesapeake Bay. Compared to Laplace’s equation that NOAA/NOS currently uses for interpolation in hydrographic and oceanographic applications, the multiple-order harmonic equation method eliminates the problem of singularities at data points, and produces interpolation results with better accuracy and precision.

Effect of FDI on China's environmental pollution: Evidence based on spatial panel data

It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.

THE INTEGRATED SPATIAL DATABASES OF GEOSTAR

GeoStar is the registered trademark of GIS software made by WTUSM in China.By means of the GeoStar,multi_scale images,DEMs,graphics and attributes integrated in very large seamless databases can be created,and the multi_dimensional dynamic visualization and information extraction are also available.This paper describes the fundamental characteristics of such huge integrated databases,for instance,the data models,database structures and the spatial index strategies.At last,the typical applications of GeoStar for a few pilot projects like the Shanghai CyberCity and the Guangdong provincial spatial data infrastructure (SDI) are illustrated and several concluding remarks are stressed.

Digital Watermark-based Security Technology for Geo-spatial Graphics Data

The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data, as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data. The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product, so as to effectively protect the data producer’s rights as well as to facilitate the secure sharing of geo-spatial graphics data. So far in the GIS field throughout the world, few researches have been made on digital watermarking. The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique. An application software employing the pro- posed technology has been developed. A number of experimental tests on the 1∶500,000 digital bathymetric chart of the South China Sea and 1∶10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.

Characteristics analysis on high density spatial sampling seismic data

中国的大陆人免职盆被复杂地质的结构和各种各样的水库岩性学描绘。因此，高精确探索方法被需要。高密度空间采样是一种新技术增加地震探索的精确性。我们简短讨论点来源和接收装置技术，分析高密度在 situ 方法的空间采样，介绍吉季斯· J · O 介绍的对称的采样原则。Vermeer，并且讨论高密度从波浪地连续性的观点的空间采样技术。我们强调高密度的分析空间采样特征，包括高密度，首先，裂缝为近的表面结构的调查有利，改善静态的修正精确，在到增加的短偏移量的稠密的接收装置间距的使用在浅深度的有效范围，和思考成像的精确性。协调噪音不是 aliased 和噪音分析精确，抑制作为结果增加。空间采样提高的高密度各种各样的数学变换的波浪地连续性和精确性，它受益飘动地分离。最后，我们指出空间采样技术是的高密度的困难的部分处理的数据。更多的研究需要在分析并且处理地震数据的巨大的数量的方法上被做。

OBJECT-ORIENTED SPATIAL DATA ORGANIZATION AND MANAGEMENT IN GEOSTAR

Spatial data, including geometrical data, attribute data, image data and DEM data, are huge in volume and relations among them are complex. How to effectively organize and manage those data is an important problem in GIS. Several problems about space data organization and management in GeoStar which is a basic GIS software made in China are discussed in this paper. The paper emphasizes on object model of spatial vector, data organization, data management and how to realize the goal, and the like.

Relationship of Uncertainty Between Polygon Segment and Line Segment for Spatial Data in GIS

The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error band model of ε_σ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of ε_m and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.