Identifying the uneven distribution of health and education services in China using open geospatial data

Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.

Kenyan Counties Geospatial Data Knowledge to Monitor Crop Production

Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, resulting in reduced harvests and sometimes losses for farmers. Better availability of information such as weather patterns, suitable crops, nutrient requirements based on soil types and conditions would greatly alleviate these challenges. While geospatial information is being developed and improved continuously by researchers, its accessibility and use by the counties has not been established and cannot be identified as contributing to better crop production outcomes. The aim of this study, therefore, was to assess the awareness and status of geospatial data availability and use for crop production, and the level of the relevant capacities, both human and infrastructural, in selected Counties of Kenya. A survey was conducted in the four counties of Vihiga, Kilifi, Wajir and Nyeri and key informant interviews were conducted with both management and technical County Agricultural Officers, as well as sub-county agricultural extension officers. From the results of the survey, out of the four counties, only one has adequate infrastructure in terms of hard-ware, software and connectivity to conduct useful geospatial data acquisition and processing. While most indicated awareness of the existence of geospatial data, limited resources, low skills and knowledge have restricted any meaningful sourcing of and access to data, with only 38% moderately or highly skilled in acquisition, 48% in processing and 57% in interpretation and use of geospatial data. The study concludes that moderate skills and capacities available within the counties have considerable potential to make use the available geospatial data to inform farmers accordingly and improve their farming outcomes.

A Data-Intensive FLAC^3D Computation Model:Application of Geospatial Big Data to Predict Mining Induced Subsidence

Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimplifying geological mining conditions,ignoring the fluctuation of rock layers with space.In the context of geospatial big data,a data-intensive FLAC3D(Fast Lagrangian Analysis of a Continua in 3 Dimensions)model is proposed in this paper based on borehole logs.In the modeling process,we developed a method to handle geospatial big data and were able to make full use of borehole logs.The effectiveness of the proposed method was verified by comparing the results of the traditional method,proposed method,and field observation.The findings show that the proposed method has obvious advantages over the traditional prediction results.The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7%and the standard deviation of the prediction results(which was 70 points)decreased by 39.4%,on average.The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.

Design of similarity measure for discrete data and application to multi-dimension

Similarity measure design for discrete data group was proposed. Similarity measure design for continuous membership function was also carried out. Proposed similarity measures were designed based on fuzzy number and distance measure, and were proved. To calculate the degree of similarity of discrete data, relative degree between data and total distribution was obtained. Discrete data similarity measure was completed with combination of mentioned relative degrees. Power interconnected system with multi characteristics was considered to apply discrete similarity measure. Naturally, similarity measure was extended to multi-dimensional similarity measure case, and applied to bus clustering problem.

TOWARDS AN INTEGRAL STRATEGY FOR MODELLING UNCERTAIN GEOSPATIAL DATA

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continuous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continuous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzziness significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN(triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.

RESEARCH ON THE SECURITY OF NATIONAL GEOSPATIAL DATA CLEARINGHOUSE BASED ON ASP

On the basis of the authors’ experiences of setting up an NGDC Web site,this paper attempts to present some significant aspects about the security of NGDC based on ASP.They include data storing,database maintenance,new technical support and so on.Firstly,this paper discusses how to provide the security of data which is saved in the hosts of NGDC.The security model of "Networks_DB Server_DB_DB Object" is also presented.In Windows NT Server,Internet Information Server (i.e.,IIS) is in charge of transferring message and the management of Web sites.ASP is also based on IIS.The advantages of virtual directory technique provided by IIS are emphasized. An NGDC Web site,at the Research Center of GIS in Wuhan Technical University of Surveying and Mapping is also mentioned in this paper.Because it is only an analoge used for case study,the transmission of digital spatial products is not included in the functions in this NGDC Web site.However,the management of spatial metadata is more important and some functions of metadata query are implemented in it.It is illustrated clearly in the functional diagram of the NGDC Web site.

Quantitative versus Qualitative Geospatial Data in Spatial Modelling and Decision Making

In general, geospatial data can be divided into two formats, raster and vector formats. A raster consists of a matrix of cells where each cell contains a value representing quantitative information, such as temperature, vegetation intensity, land use/cover, elevation, etc. A vector data consists of points, lines and polygons representing location or distance or area of landscape features in graphical forms. Many raster data are derived from remote sensing techniques using sophisticated sensors by quantitative approach and many vector data are generated from GIS processes by qualitative approach. Among them, land use/cover data is frequently used in many GIS analyses and spatial modeling processes. However, proper use of quantitative and qualitative geospatial data is important in spatial modeling and decision making. In this article, we discuss common geospatial data formats, their origins and proper use in spatial modelling and decision making processes.

Creation of Data Specification for Geospatial Information in Albania on the Theme:“Geology”

The development of technology and the demands of groups of interest for standardized digital geospatial information are increasing daily.The necessity for referred geospatial information,according to a Referencing Coordinating System and European Standards,through a national GIS(Geographic Information System)system,requires a decision making of national and institutional importance.ASIG(State Authority for Geospatial Information)is the institution that administrates,implements,and maintains the NSDI(National Spatial Data Infrastructure).It is calculated that 80%of decision-making by public or private institutions uses geospatial data with a well-organized structure that enables efficiency.Thus,standardization of geospatial data by topic is one of the main objectives of implementing the NSDI in Albania.This is a complex task for the standard and the harmonization of geospatial data,which can be a good opportunity for professional awareness.This study shows in detail the methodology for the creation and implementation of data specification for geospatial information in Albania on the theme:Geology,adoption of the technical specification of the INSPIRE directive as well as the importance of ASIG as an institution that builds and maintains NSDI in Albania.

Analyzing and Modeling of Geo Spatial Effect on Radio Wave Propagation System Using Geospatial Technologies

The research presented in this thesis reveals the level of rightness of the recurrence Prediction systems by correlated with geospatial effect. The Geospatial technology elements split up: Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS) consolidated into this technique in light of the fact that the vast majority of the components in radio wave propagation are geographic highlights. In this exploration, ICEPAC remote arranging programming is tried in a field test completed in Tigray and Afar district. The consequence show that, the Prediction programming doesn’t put, day by day, regular and month to month topographical marvels into thought. Moreover, it doesn’t demonstrate the correct area of the radio stations. Furthermore, the new proposed ICEPAC Calibration algorithm anticipates a good Signal quality for frequencies in the vicinity of 1.5 MHz up to 30 MHz. The total result showed that Geographical Information Systems (GIS) are getting to be noticeably valuable apparatuses in accumulation, stockpiling, control and portrayal of Geo spatial information and also the RS and GIS situated Signal quality forecast can essentially enhance forecast quality contrasted with the hypothetical free space demonstration which does not consider any Geo spatial and neighborhood landscape highlights impacts.

Geospatial Information Service Based on Ad Hoc Network

The mobile geospatial information service involves the domain of mobile communication, mobile computing, geospatial information service and other techniques. This paper focuses on the integration of spatial information and mobile communication technologies. The author proposes the architecture of mobile geospatial information service based on the Ad Hoc network. On the basis of this architecture, a system is developed, and applied in correlative fields.

Developing Blue Spots Model for Tennessee Using GIS, and Advanced Data Analytics: Literature Review

Climate change and global warming results in natural hazards, including flash floods. Flash floods can create blue spots;areas where transport networks (roads, tunnels, bridges, passageways) and other engineering structures within them are at flood risk. The economic and social impact of flooding revealed that the damage caused by flash floods leading to blue spots is very high in terms of dollar amount and direct impacts on people’s lives. The impact of flooding within blue spots is either infrastructural or social, affecting lives and properties. Currently, more than 16.1 million properties in the U.S are vulnerable to flooding, and this is projected to increase by 3.2% within the next 30 years. Some models have been developed for flood risks analysis and management including some hydrological models, algorithms and machine learning and geospatial models. The models and methods reviewed are based on location data collection, statistical analysis and computation, and visualization (mapping). This research aims to create blue spots model for the State of Tennessee using ArcGIS visual programming language (model) and data analytics pipeline.

TGAIN:Geospatial Data Recovery Algorithm Based on GAIN-LSTM

Accurate geospatial data are essential for geographic information systems(GIS),environmental monitoring,and urban planning.The deep integration of the open Internet and geographic information technology has led to increasing challenges in the integrity and security of spatial data.In this paper,we consider abnormal spatial data as missing data and focus on abnormal spatial data recovery.Existing geospatial data recovery methods require complete datasets for training,resulting in time-consuming data recovery and lack of generalization.To address these issues,we propose a GAIN-LSTM-based geospatial data recovery method(TGAIN),which consists of two main works:(1)it uses a long-short-term recurrent neural network(LSTM)as a generator to analyze geospatial temporal data and capture its temporal correlation;(2)it constructs a complete TGAIN network using a cue-masked fusion matrix mechanism to obtain data that matches the original distribution of the input data.The experimental results on two publicly accessible datasets demonstrate that our proposed TGAIN approach surpasses four contemporary and traditional models in terms of mean absolute error(MAE),root mean square error(RMSE),mean square error(MSE),mean absolute percentage error(MAPE),coefficient of determination(R2)and average computational time across various data missing rates.Concurrently,TGAIN exhibits superior accuracy and robustness in data recovery compared to existing models,especially when dealing with a high rate of missing data.Our model is of great significance in improving the integrity of geospatial data and provides data support for practical applications such as urban traffic optimization prediction and personal mobility analysis.

我国地理空间数据资源开放现状、问题与对策研究

研究地理空间数据开放情况,有利于我国政府地理空间数据开放工作的全面开展,有利于促进地理空间数据价值的释放与利用。以20个地方政府数据开放平台为调查对象,对平台所发布的有关地理空间数据的内容进行搜集、整理和分析,从数据集数量、数据集主题分类、数据时效性、数据可获取性、数据集格式、元数据格式等方面进行综合评估。研究发现,目前我国地理空间数据的分类、发布和共享都还处于初级阶段,我国地方政府数据开放平台存在数据集分类混乱且数量较少、部分文件缺少数据接口、数据集更新频率较低、数据获取流程繁琐、元数据建设不完善等问题。基于此,提出相应的对策和解决方案,以期为我国地理空间领域的数据开放共享提供参考。

大数据的6种地理学应用范式

随着大数据时代的来临,多源大数据正在兴起,数据驱动研究范式与地理学日益融合。基于个体行为的地理空间大数据可提供对海量个体行为模式的观察,从而实现“由人及地”的社会感知,支持城市管理、交通、公共卫生等不同应用。本文从应用角度,以地理空间大数据为重点,梳理其支持的6种应用范式,按照层次从低到高依次为描述时空分布、识别异常对象、发现普适规律、揭示关联关系、预测未来趋势及优化空间决策。其中,第1个方向是对地理现象和地理要素时空特征的简单刻画;第2~4个方向则注重探寻时空分布特征背后的规律和机理;最后两项,则是在决策层面提供支持。继而,本文指出大数据应用中数据获取、分析方法和应用目标3方面的问题。

可编辑三维场景的动态3D Tiles构建方法

可编辑的大型三维WebGIS具有一定的应用场景需求,常见的3DTiles数据格式局限于静态场景渲染,在编辑的三维场景中,需要构建动态的3D Tile文件格式和多细节层次(level of detail,Lo D)渲染方法。本文从动态空间索引和多细节层次技术两方面研究Web在线编辑大型三维场景的构建方法,将动态松散八叉树和半边折叠LoD构建算法应用于3D Tiles构建流程中,实现支持可编辑场景的3D Tiles构建与更新。结果表明:(1)松散八叉树索引在计算量上能够实现动态更新的目标,且在视锥体剔除上有着良好的精度;(2)基于半边折叠法进行准实时LoD的构建,能够满足动态场景下实时计算LoD的需求;(3)所构建的3D Tiles场景,配合Three.js等成熟框架并应用WebWorker等技术,能够顺利完成3DTiles的高效调度和渲染。研究成果对城市三维模型在线编辑、动态地理三维场景的加载渲染等相关研究和应用具有一定的参考价值。

基础地理实体数据存储与交换模型研究

实景三维自提出以来,不断探索新模式新方法并取得了显著成效。然而由于建模方法和软件工具多样,不同地区基础地理实体数据格式、数据标准并不完全兼容,统一高效的存储格式标准还是空白,严重阻滞了数据在不同区域不同行业间的共享流通。本文以畅通不同格式、不同类型数据交互为重点,梳理分析当前用于存储地理实体数据模型现状,以当前地理实体数据交换格式标准为基础,研究统一、通用、开放的地理实体数据存储与交换模型,并结合实际生产数据进行探索试验,验证了本文方法的可行性,为形成可供广泛交流和共享的标准规范,促进实景三维数据的应用和推广提供参考。

WebGIS中地理空间Metadata管理系统研究与设计

为实现 Web GIS中地理空间信息的有效管理和网络共享 ,结合国际地理空间信息共享的标准规范 ,对Web GIS中地理空间 Metadata的定义、作用、内容、技术实现及其应用进行了详细的研究和设计 ,提出了与Web GIS集成的地理空间 Metadata管理系统解决方案 ,并给出了体现具体技术实现的原型系统 ,为国家空间信息基础设施和数字地球的建设提供了理论基础和技术原型 ,在当今信息化与数字地球时代 。

基于现代测绘技术的基础地理空间数据生产——以智慧滕州时空大数据平台建设为例

智慧城市时空大数据平台建设是构建数字中国的重要组成部分,而基础地理空间数据的生产是建设智慧城市时空大数据平台的关键步骤。以智慧滕州时空大数据平台建设项目为例,阐述了利用先进的现代测绘技术进行基础地理空间数据生产的技术方法和具体流程,包括实景三维模型数据生产、矢量数据生产和更新、地理实体数据生产、街景数据生产和地名地址数据更新等方面,为智慧城市的建设提供了科学、实用的技术方法,并积累了宝贵的经验。

数字地球建设中的地理空间Metadata研究

为解决数字地球建设中现有海量地理空间信息的共建共享、有效管理和利用 ,结合国际地理空间Metadata标准规范 ,对数字地球建设中所需的地理空间Metadata的定义、作用、分类、内容、实现模型与实例及其应用进行详细研究和设计 ,提出用于数字地球建设的地理空间Metadata网络管理系统解决方案 ,并设计实现了原型系统 ,为数字地球建设中现有海量地理空间信息的有效管理和共建共享提供了理论基础和切实可行的技术支撑。对国家空间信息基础设施建设与数字地球建设具有重要的推动作用和深远的社会意义。

北京市地理空间数据应用现状和产权框架体系

数据在我国经济社会发展中已经成为重要的生产要素和战略资源,地理空间数据作为数据重要组成类别,其重要性不言而喻。本文综合分析了国内外数据产权制度的建设,对北京市地理空间数据应用和产权现状进行详细分析并指出存在的问题,针对这些问题,提出了一种构建地理空间数据产权框架体系,明确了流通链路,并从五个方面提出了解决问题的建议,以期盘活地理空间数据资源,开拓地理空间数据作为新型生产要素的价值。