The Demographic Impact on Credit Scores＂ Evidence From Statistical Methods and Geographic Information Systems （GIS） Mapping

Average credit scores for people in the United States （US） differ from state to state. Some states have high, and some states have low average credit scores. Since lenders and employers use credit scores to make loan and employment decisions, people living in states where average credit scores are high should experience the benefits of living where credit scores tend to allow more favorable loan and employment decisions. Although credit scores are the direct result of credit histories, credit histories may be impacted by demographic factors. If the demographic factors that impact credit histories are identified, ways to improve credit scores are likely to be discovered and available to people and state government policymakers. This study looks for demographic factors to indirectly explain the average credit scores for people living in each state of the US. The methodology includes statistical analyses and geographic information systems （GIS） mapping. Statistical analyses provide evidence to suggest that state average credit scores are explained by the demographic factors of education, family, income, and health. GIS mapping reveals clusters of states with similar demographics and credit scores.

Using Geographic Information Systems (GIS) for Targeted National Recruitment of Community-Dwelling Caregivers Managing Dementia-Related Behavioral and Psychological Symptoms: A Recruitment Approach for a Randomized Clinical Trial

Over 16 million caregivers of people living with dementia require support in a range of issues, including self-care, disease education, and guidance for how to manage behavioral and psychological symptoms of dementia (BPSD). Non-pharmacological interventions are needed to address these areas, and online applications have been shown to be safe and effective. To ensure the efficacy of such interventions, racially, ethnically, geographically, and socioeconomically diverse participants must be recruited to increase the generalizability of study outcomes. This protocol paper describes a recruitment plan using Geographic Information Systems (GIS) to reach a representative sample of caregivers across the United States for a national Phase III clinical study. Using publicly available census data from the American Community Survey (ACS), combined with location data for local aging resources such as Area Agencies on Aging (AAA), recruitment will be derived from data analysis conducted in ESRI ArcGIS v10.7.1. Datasets including age, gender, income, and education will be assessed nationally at the county and census tract spatial scale in a nine-step process to develop recruitment priority areas containing high concentrations of eligible participants living in the community. Overall, the current protocol will demonstrate the value of GIS in tailoring targeted outreach strategies to recruit community-dwelling populations through local resource institutions. This novel approach may have far-reaching implications in future recruitment initiatives and help to secure racially/ethnically diverse samples.

基于GIS的灌区土壤投入品残留污染监测预警系统

为了解决工业发展导致的灌区土壤投入品残留污染问题,给出一种基于地理信息系统(geographic information system,GIS)的土壤污染监测预警系统。该系统结合VOC-PF1型传感器、STM32主控芯片和GSM通信模块,实现了高效的数据采集和通信功能。通过反距离加权(inverse distance weighted,IDW)插值法进行空间分析,并设立预警阈值,实现对灌区土壤投入品残留污染的实时监测和预警。实验结果表明:该系统的监测精度高达98%,监测时长最高为49 s,具有很高的实用性和效率。研究结果不仅为灌区土壤投入品残留污染监测提供了有效手段,也为环境保护和农业可持续发展提供有力支持。

基于GIS的青岛市绿地景观生态格局与网络构建

定量化研究绿地景观生态格局和网络构建能够为城市绿地系统和国土空间的科学规划提供理论依据与方法支撑。研究基于无线电高空测候(RS)和地理信息系统(GIS)技术,运用总体景观生态格局分析和梯度分析方法,选取12个景观指数,对沿海城市——青岛市的绿地景观生态格局从斑块类型水平和景观水平两方面进行了定量研究。结果表明:斑块类型水平上,区域绿地以大型斑块为主且占优势地位,防护绿地以大中型斑块为主,二者虽空间分布不均匀,但生态效益较好;附属绿地以中小型斑块为主,缺乏大面积绿地建设,景观破碎度高但符合公众游憩需求;公园绿地以小型斑块为主且数量较少,在城区集中分布。景观水平上,城市绿地景观类型较齐全,但整体破碎度高,中部地区景观破碎度高,南部与中北部地区绿地类型多样,景观破碎度高且景观形状较复杂。在此基础上,进而分析了青岛城市绿地景观生态格局存在的问题,提出了“一轴、三核、廊汇成网、节点密布”的城市绿地生态网络优化与构建方案,以提高各类城市绿地连接度水平,发挥绿地生态系统的整体效益。

基于GIS的历史文化街区应急疏散能力可视化评估研究

为评估历史文化街区在旅游高峰期的应急疏散能力,探究街区的应急疏散风险区域。研究从点-线-面的角度出发,考虑行人特征因素、街巷路网因素和建筑结构因素,构建应急疏散能力评价模型。采用ANP-EWM综合评估方法确定各因素权重值,应用GIS技术进行因素可视化分级处理。在此基础上,采用空间分析方法,对单因素分级分析赋权重后进行加权叠加处理,得到历史文化街区应急疏散能力的可视化数据。以西安回民街为例进行实证分析,探究街区应急疏散能力风险区域。研究结果表明:所构建模型可以实现对研究区界的应急疏散能力可视化分级评估,反映回民街不同等级疏散风险情况。研究结果可为景区应急疏散与制定安全管理措施提供参考。

基于GIS的空间TOPSIS模型的安徽省休宁县滑坡易发性评价

文章在常规TOPSIS(technique for order preference by similarity to ideal solution)模型的基础上提出空间TOPSIS模型,以安徽省休宁县为例,采用地理信息系统(geographic information system,GIS)技术对安徽省休宁县的滑坡易发性进行评价。研究表明:基于GIS的空间TOPSIS模型的滑坡易发性评价,能够处理和分析滑坡评价因子以及滑坡易发性的空间变化特征;评价结果与休宁县境内已经发生滑坡的空间分布较为吻合,评价结果较好。基于GIS的空间TOPSIS模型在滑坡易发性评价中具有较好的适用性。

GIS技术在洪水灾害中的应用研究综述

地理信息系统(GIS)是一种专用于处理地理和空间信息的计算机系统。当前,随着计算机技术的逐渐成熟,GIS技术的空间分析等特点对于水资源的规划与管理有着重要的研究意义,其中在洪水灾害中的应用是近年来研究发展的一个重点。通过GIS技术建立洪水模拟模型,进行预测预警,以此为防洪抗涝提出更加科学的决策建议,降低频发的洪涝灾害事件所带来的损失。该文针对其在洪水灾害中的预测、风险图绘制、模型建立及避险路线进行评述,提出当前存在的问题,并对今后GIS在洪水灾害中的应用进行展望。

基于GIS+BIM的地铁工程实景三维可视化关键技术及应用

针对地铁工程项目可视化管理中存在的模型精细化不足、数据集成与展示不充分及真实性欠缺等问题,本研究提出了利用GIS和BIM技术作为解决方案,提升地铁工程实景三维建设的效果。首先研究构建了地铁工程实景三维平台的建设框架,分析了数据集成与融合、动态层次加载、模型轻量化与显示等关键技术。随后以深圳地铁14号线工程为案例,进行了实景三维可视化平台的建设与功能应用。案例涵盖了工程建设管理图、空间分析可视化、多视角场景漫游及BIM可视化与属性查询等内容,实现了地铁工程项目多源异构数据与模型的集成,提供了多尺度的实景三维可视化展示,为项目管理与决策提供了有力支持。

基于GIS格网模型的广州市土地生态安全格局演化

以公里格网为评价单元,构建基于PSR-NES(压力-状态-响应和经济-环境-社会)模型的土地生态安全测度指标体系,运用突变级数法动态识别2010—2020年广州市土地生态安全格局。结果表明:广州土地生态安全水平空间异质性较为明显,整体呈现“中间低,四周高”的分布格局;2010—2020年,广州市土地生态安全水平先下降后提高,其中,北部生态涵养区土地生态安全水平呈下降趋势,南部生态调节区土地生态安全状况逐渐好转,中部建成区土地生态安全状况不容乐观。未来城镇扩张应尽量避免侵占土地生态安全水平较高的区域,可通过分区治理,科学布局生产、生活、生态空间,优化产业结构,加强生态用地保护力度等措施持续改善土地生态安全状况。

基于GIS的林业调查技术研究

随着地理信息系统(GIS)技术的不断发展和应用,基于GIS的林业调查技术在林业资源管理、生态环境保护、林火监测和森林病虫害监测等方面得到了广泛应用。该文通过概述GIS的基本概念和定义,介绍了GIS在林业调查中的应用重要性和现状,并总结了林业调查中常用的GIS技术,比如,遥感、GPS和DEM技术。同时,通过实际案例阐述了GIS在林业调查中的应用技术,并探讨了GIS在林业调查中的优势和挑战。最后,提出了加强技术研究和应用推广的建议,以促进GIS在林业调查中的进一步应用和发展,实现更科学、可持续的林业资源管理和保护。

基于GIS的城市扩张监测与驱动力分析

准确的城市建设用地信息,能够反映城市扩张的动态变化,对于提供决策指导城市化建设和规划具有非常重要的意义。本文以南昌市作为研究区域,选取2000年、2010年、2020年三期30m全球地表覆盖数据(GlobeLand30)影像数据作为主要数据源,利用土地利用转移矩阵模型对城市用地变化情况的变化量和动态度进行定量分析,利用扩张指数模型等研究了南昌市20年间的扩张面积、速度、强度、紧凑度、分形维数、重心转移距离和扩张方位等,对城市扩张的驱动力进行了定性分析,并利用灰色关联分析法进行了定量分析。结果表明,南昌市经济和人口因素与城市扩张显著相关,研究内容在土地管理与合理利用土地、城市发展和规划以及城市的健康发展方面为管理部门提供了支持。

Application of Geographic Information Systems to Analyses and Modeling of Hydrocarbons Anomaly in Yakla,North Tarim Basin,Xinjiang,China

Yakla area is a very important and typical region in North Tarim, because it is the region that leads to a breakthrough in North Tarim oil/gas exploring. Therefore, a lot of exploration work has been already carried out in the area aiming at assessing the hydrocarbon anomaly and some techniques for anomaly delineation are being suggested. Yakla covers about 312 km 2 and lies 20 km south to Luntai Kuche road and displays as a long rectangular, with the length of 24 km in ENE and the width of 13 km in WSW. The surface is desert covered with saline akali, sand ribbon and sand dune. Samples collected from Yakla were analyzed for their hydrocarbon mass fractions and the spatial distribution of the concentrations of selected hydrocarbons C 1, C 2, C 3, i C 4, n C 4, i C 5, n C 5 and UF365 were estimated from these data sets. Multivariate statistical techniques including Kriging, moving average, factor analyses, cluster analyses and furrier filtering are used. The statistical techniques, spatial data analysis and transformation capabilities of geographic information systems, combined with geophysical and geological data, helped the authors to identify the hydrocarbon anomaly in Yakla.

基于地理信息系统(GIS)的地质灾害评价现状

近年来,地理信息系统(GIS)已成为评估和管理地质灾害风险的关键工具。地质灾害危险性评价是识别、分析和预测地质灾害潜在威胁的过程,它对于防灾减灾策略的制定和执行至关重要。本文基于GIS的地质灾害危险性评价方法的研究现状,探讨了其发展趋势。首先,从国内和国外两个方面回顾了GIS技术在地质灾害管理中的应用历史,分析了基于GIS的地质灾害调查。其次,探讨了地质易发性评价、危险性评价、易损性评价、地质灾害风险性之间的关系,详细分析了易发性和危险性评价的主要评价方法、计算逻辑、优缺点、应用场景和主要评价指标,对地质灾害易损性和风险性进行分析并指出目前主要几种分级类型,并指出了地质灾害评价过程的问题及未来的发展方向。

沙特NEOM隧道项目BIM与GIS关键技术研究

利用数字仿真模拟方法,在保障施工安全的基础上优化爆破方案。提出了大断面隧道大孔距设计的理论方法,有效控制隧道断面和保留岩体的损伤,并降低成本。通过模拟二维、三维路线的联动,可以对比剖切地质体,按里程桩号实时查询地质体产状及地质风险信息,根据围岩等级对施工方案进行分析,辅助施工决策。通过将项目的BIM模型接入GIS数据平台,可以将地质超前预报的信息与项目进度进行动态关联。采用BIM4D进度管理手段,采用BIM技术和数字化手段管理项目的计划和进度,帮助项目在高质量的基础上合理压缩工期,达到降本增效的目的。

Safety Evaluation Method of Evacuation Routes in Areas in Case of Earthquake Disasters Using Ant Optimization Algorithm and Geographic Information Systems

The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.

Governance of Marine Protected Areas： An Approach Using Public Participation Geographic Information Systems--The MARGov Project

The MARGov Project consisted in strengthening the interaction among the Professor Luiz Saldanha Marine Park stakeholders, and to collaboratively construct, with social and institutional actors, a governance model for the Marine Park, located in the municipality of Sesimbra （Portugal）. To pursue this goal, a PPGIS （public participation geographic information system） was developed, allowing the interaction, discussion and public participation of the stakeholders and actors involved. This PPGIS emerged as a crowdsourcing tool, with the purpose of assisting the georeferenced contributes from the local users of the Marine Park, regarding several relevant subjects, such as pollution, economic activities, opportunities and threats to the Marine Park, providing visual, analytical, and demonstrative qualities.

Water Runoff Estimation Using Geographical Information System (GIS) for Alrakhmah Basin Valley Northeast of Iraq

The lack of water resources in many regions is the main challenge for the human being and to extended investigations. Water resources controlling and management is essential in the areas depending on the seasonal rainfall. This research aims to estimate the surface water runoff for Basin of Alrakhmah Valley located in the southwestern part of Kirkuk Province in northeastern of Iraq. Analyzing of Spatial data and Digital Elevation Model (DEM) data has been conducted using Geographic Information System (GIS) to estimate the hydrological properties for the watershed valley with 158.5 km2 surface area. The results showed that watershed valley type is from the fifth rank with a longitudinal shape and topography percentage of 0.568. The watershed textures found to be 3.24 and the drain density 1.5 at 3.49 river branching. Finally, the annual estimated surface water retreat according to the morpho-hydro climatic elements found to be 0.01286233 milliard cubic meter.

基于GIS的广西食品抽样系统设计与实现

目的:设计基于地理信息系统(Geographic Information System,GIS)的广西食品抽样系统建设方案,清洗抽样数据建立大数据仓库,开发建设基于GIS的广西食品抽样系统。方法:通过运用GIS技术,建立大数据基础库,梳理从抽样计划制订,到实地抽样,再到抽样结果检测,提供区域安全风险等级图、区域抽样进度图、区域抽样覆盖完成实况;通过与实验室信息管理系统(Laboratory Information Management System,LIMS)的数据共享,实现抽样记录自动更新,数据自动完成清洗;通过Web Service接口技术实现抽、检数据互联互通,信息实时共享,消除信息孤岛。结果:优化了目前的国家食品安全抽样检验信息系统,生成区域安全风险等级图、区域抽样进度图、区域抽样覆盖完成实况等更直观的图像,实现抽样记录自动更新,数据自动完成清洗,提高了数据利用率,大幅缩短了抽样路程所需时间。结论:基于GIS的广西食品抽样系统为我区食品安全监管提供了数据信息保障,并大大减少了广西食品抽样的人力物力成本,成为食品安全智慧化监管不可或缺的工具。

煤矿GIS一张图快速构建平台研究

目前,煤矿使用的工程专题地图基本都是CAD制图,高效提取CAD图件中的数据并快速组织成地理信息系统(GIS)服务,进而支持矿井空间对象创建和业务属性扩展,集成安全生产实时数据,是构建煤矿GIS一张图的关键。基于ArcGIS平台将CAD图件转为GIS服务的方法实现过程较为繁琐,且ArcGIS平台成本较高,无法较好地跨平台运行。针对该问题,设计了一种煤矿GIS一张图快速构建平台。该平台包括CAD图件管理、地图服务发布、专题地图管理3大功能模块:CAD图件管理模块用于图件基础信息管理和状态跟踪,地图服务发布模块用于地图打包发布和在线预览,专题地图管理模块用于地图服务管理、矿井对象创建及属性扩展。基于开放设计联盟(ODA)的Teigha for Java SDK实现CAD图件全要素精确识别与快速准确提取;通过构建基于GIS数据特征的煤矿CAD图件数据分层描述模型,实现了CAD图件全要素数据快速存储;按照面向对象设计思路,开发了Spring Cloud框架下的Web端煤矿CAD图件数据集存储接口及专题地图服务发布平台,实现了煤矿GIS一张图快速构建。以某煤矿采掘工程平面图为例,分别采用传统方法和快速构建平台进行煤矿GIS一张图的构建,对比结果表明,快速构建平台可大幅提高煤矿GIS一张图的构建效率,为煤矿智能化建设提供时空数字底座。

Quantifying River Bank Erosion and Accretion Patterns along the Gorai River in Kushtia, Bangladesh: A Geospatial Analysis Utilizing GIS and Remote Sensing Techniques

River bank erosion is a natural process that occurs when the water flow of a river exceeds the bank’s ability to withstand it. It is a common phenomenon that causes extensive land damage, displacement of people, loss of crops, and infrastructure damage. The Gorai River, situated on the right bank of the Ganges, is a significant branch of the river that flows into the Bay of Bengal via the Mathumati and Baleswar rivers. The erosion of the banks of the Gorai River in Kushtia district is not a recent occurrence. Local residents have been dealing with this issue for the past hundred years, and according to the elderly members of the community, the erosion has become more severe activities. Therefore, the main objective of this research is to quantify river bank erosion and accretion and bankline shifting from 2003 to 2022 using multi-temporal Landsat images data with GIS and remote sensing technique. Bank-line migration occurs as a result of the interplay and interconnectedness of various factors such as the degree of river-related processes such as erosion, transportation, and deposition, the amount of water in the river during the high season, the geological and soil makeup, and human intervention in the river. The results show that the highest eroded area was 4.6 square kilometers during the period of 2016 to 2019, while the highest accreted area was 7.12 square kilometers during the period of 2013 to 2016. However, the erosion and accretion values fluctuated from year to year.