基于Google Maps API的网络地图服务系统的研究与应用

以Google Maps为代表的地图服务的推出开创了全球化地理信息服务新的开端,GoogleMaps提供的API具有开放式、低成本和易用性的特点,使其应用更加广泛。通过介绍Google Maps的功能、特点和Google Maps API的使用方法,探讨了Google Maps API在网络地图服务中的应用。     

基于AJAX和Google Maps API的WebGIS开发研究

通过介绍AJAX技术的相关原理、Google Maps地图服务及其应用程序接口Google Maps API,提出了基于AJAX及Google Maps平台的WebGIS开发新技术。通过构建发布气象信息的WebGIS实例,探索在Google Maps平台上利用AJAX通过XMLHttpRequest对象异步调用XML数据实现动态加载地理信息和气象信息的关键步骤。研究结果表明,WebGIS实现的新模式,能够较好地解决传统WebGIS的固有缺点,如加快了响应速度、增强了用户体验和方便了服务扩充等。     

大连市旅游信息系统设计与开发

基于Google Maps API所提供的接口,把Google地图嵌入到自己的网页中,利用API提供的函数导入所需要的电子地图,实现了地图浏览和旅游信息显示等基本内容,并完成在电子地图上对旅游景点、旅游线路、旅游景区等信息的标注,使游客能够方便快捷地获取旅游景点及附近信息,从而合理安排旅游计划。     

瓦片式震中分布图生成及局部自动更新

针对目前在线震中分布图存在的问题,提出瓦片式地震震中分布图。使用ArcGIS Engine开发瓦片切图工具及局部瓦片自动更新程序,结合Google Maps实现瓦片式震中分布图的展示。基于Web GIS的瓦片式震中分布图在显示历史地震和最新地震方面较以往在线震中分布图有很大改善,瓦片局部自动更新程序也克服了瓦片式地图本身更新速度慢的缺陷。     

WebGIS开发方法的研究与实现

概述了传统WebGIS的特点和实现技术,在此基础上提出了以Google Maps API为WebGIS功能核心,结合恰当的地图发布平台和Web开发平台的WebGIS系统的新方案,阐述了新方案的原理及优势,并以长株潭地图浏览系统为例完成系统设计和功能实现。     

基于Google Map API的天气实况显示系统

谷歌地图应用程序开发包提供了各种向地图添加内容的服务,用户能够在网站上创建功能全面的地图应用程序。利用Google Maps API和Ajax技术,建立了气温、湿度等天气实况信息在Google Map中快速显示的WebGIS系统。实践证明,该方法提高了系统的开发速度,缩短了开发周期,优化了人机交互。     

期刊博览

Google Map API在网络地图服务中的应用 Google公司于2005年推出了免费网络地图服务Googte Map,同时也提供了一个基于dava Script技术的API接口,便于更多用户自行开发地图服务。     

基于Delphi+GoogleMapApi的地震信息显示平台的设计与应用

地震信息显示软件将Google Maps API技术与Delphi7.0开发环境结合,脱离了Google Maps Api技术在嵌入式网站服务器上的开发,相对避开了API密钥的申请和使用限制,实现了中国地震信息网和美国地震信息中心2个网站的震情数据的实时显示,并增设了全球震情动态和震情报警功能,达到虚拟地震台网功能。     

基于AJAX的Internet地图服务方法初探

2005年,AJAX技术被提出并开始成熟,已经迅速走向实际应用。短短1年间,基于AJAX技术的Intenet地图服务如雨后春笋般涌起,如Google Maps、百度地图、搜狗地图、Yahoo Maps和MSN Virtual Earth等。本文首先分析了Intetnet地图服务现状——人们对地图服务需求迫切和地图服务不够快速友好的矛盾,并简单介绍了AJAX技术及其优点,在此基础上,初步探讨了基于AJAX的Internet地图服务方法的相关原理,给出了地图服务框架,并简单讨论了地图服务AJAX引擎包含的若干对象,最后分析了其优势和前景,并对地理信息服务的发展方向进行了思考。     

基于SVG的专题地图与Google地图混搭研究

Google地图开放API后,将Google地图作为地理底图,由用户定制专题要素成为专题地图制作的一种新形式。文中研究如何在Google地图上制作精美生动的网络专题地图。SVG用于表达网络专题要素有其独特的优势,文中结合SVG的优点探讨以Google地图为地理底图的网络专题地图的表达、设计与实现方法,尝试解决网络地理底图与专题要素的一致性表达问题。     

基于Google Map API的校园电子地图开发

Google Map API为用户提供向Google地图添加各种个性化内容的功能,用户在此基础上进行二次开发,可实现各类网络地图服务。利用Google Map API开发校园电子地图,实现电子地图的各项基本功能,并探讨功能实现中的关键部分设计。     

A comparative analysis of routes generated by Web Mapping APIs

Web Mapping APIs (WMAs), such as Google Maps API, are widely used by researchers across different fields to develop geospatial Web applications. Among maps and map functionalities provided through WMAs, route and direction are prominent and commonly available. Given that each WMA uses a different map database and a different set of assumptions, the routes they generate, for the same pairs of origin and destination addresses, are different. Considering the current void in literature on WMAs and the routes they generate, in this paper, select common WMAs are compared and analyzed based on their routing techniques. The results of these comparisons will benefit researchers by helping them better understand the behavior of WMAs in producing routes, which in turn can be used for selecting suitable WMAs for research projects or developing applications (such as navigation and location-based services). The process in which routes are evaluated can also be used as a guideline to help researchers explore behavior of WMAs in generating routes.     

地理视频数据模型设计及网络视频GIS实现

在回顾地理视频与视频GIS的相关研究进展的基础上,提出了地理视频数据模型和视频GIS框架设计,包括地理视频的描述方法、数据处理流程,以及网络视频GIS技术标准、系统设计与实现技术方案,重点介绍了开发视频GIS的关键技术。基于Google Maps和ArcGIS Server平台,采用Flash视频,实现了网络地图环境中地理视频的查询、检索、播放和导航,表明本文提出的地理视频模型和网络视频GIS技术框架是可行的。     

基于Google Maps的气象全球眼视频监控系统

基于Google Maps设计和开发了气象全球眼视频监控系统,利用Google Maps API,以B/S方式灵活地实现了气象全球眼视频监控;实现了气象全球眼站点信息的叠加显示,对气象全球眼站点按高山、公路、沿海、航道、城市等分类进行浏览,气象全球眼视频的显示和查询等功能;为气象预报预警等提供了实时的资讯,也为浙江天气网、浙江气象影视及气象专题提供了丰富的视频信息和图像信息,大大增强了防灾减灾等气象服务能力。     

Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.     

Mining Trajectory Data and Geotagged Data in Social Media for Road Map Inference

As mapping is costly and labor‐intensive work, government mapping agencies are less and less willing to absorb these costs. In order to reduce the updating cycle and cost, researchers have started to use user generated content (UGC) for updating road maps; however, the existing methods either rely heavily on manual labor or cannot extract enough information for road maps. In view of the above problems, this article proposes a UGC‐based automatic road map inference method. In this method, data mining techniques and natural language processing tools are applied to trajectory data and geotagged data in social media to extract not only spatial information – the location of the road network – but also attribute information – road class and road name – in an effort to create a complete road map. A case study using floating car data, collected by the National Commercial Vehicle Monitoring Platform of China, and geotagged text data from Flickr and Google Maps/Earth, validates the effectiveness of this method in inferring road maps.