共查询到19条相似文献，搜索用时 78 毫秒
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以太原市地理编码基础库建设为例,深入分析和探讨了地理编码库建设中涉及的资料搜集、外业采集、内业整理及标准化编码入库工作,并以此为基础库将城市各类专题信息进行地理编码匹配和定位生成各类专题地理数据集,经过整合建库生成地理编码扩展库,二者统称地理编码库。地理编码库为城市资源信息"落地"和各类专题信息共享交换提供了空间定位的依据。 相似文献
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“数字湖北”中文地理编码数据库建设与服务共享 总被引：1，自引：1，他引：0
针对"数字湖北"地理空间框架建设,探讨了适合于湖北省省情的中文地理编码技术,将湖北省现有的地址实体进行空间化、规范化,建立标准化的地址数据库,并实现了湖北省中文地理编码服务共享。以标准地址数据库为基础,通过发布可供标准REST接口调用的中文地理编码服务来满足用户的需求。 相似文献
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不同地图服务商提供的地理编码规则和数据源不同,导致地理编码结果也有所差异。目前所有在线地理编码服务均提供JSON文本数据作为返回数据格式,但JSON文件并不是矢量文件格式,无法直接转换成矢量数据文件,给实际工作带来了不便。对比分析了高德地图、百度地图、天地图等地理编码服务接口的结果差异,针对该差异设计了一种地理编码结果优化算法,并利用ArcPy将最终优化的编码结果转换为矢量文件,实现了多种地理编码服务的整合优化和编码结果的直接矢量化,减小了地理编码差异带来的结果偏差,提高了地理编码工作效率。 相似文献
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高寒松 《测绘与空间地理信息》2017,40(Z1)
为了更好地整合统计地理空间信息,联合国成立了统计和地理信息整合专家组,目标是推进全球统计地理空间框架的实施.全球统计地理空间框架为各国提供了通用的标准和方法,以促进统计和地理空间信息的整合,并提高了结合空间信息的统计数据的可用性,让统计更好地服务于决策.本文介绍了构成统计地理空间框架五项原则的具体内容和相关国际经验,并分析了国内实施框架的基础条件、有利因素和困难.建议国家统计局在今后的普查和统计调查中,参照全球统计地理空间框架原则,加强统计和地理信息的整合,并提出了具体措施. 相似文献
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地理编码原理及其本地化解决方案 总被引：6，自引：0，他引：6
地理编码技术具有广阔的发展前景,使用它可以利用记录的属性数据直接定位出其地理坐标。完整阐述了地理编码的技术核心及实现方式,并对实现其本地化的关键技术-数据标准化提出了解决方案。在文章的最后阐述了相关的结论。 相似文献
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ArcGIS中地理编码方法的改进 总被引：2，自引：0，他引：2
城市管理部门对空间数据与非空间数据共享整合的要求日益迫切,急需利用地理编码技术把空间数据和非空间数据联系起来。但是由于中国的地名、地址体系异常复杂等原因的存在,使得地理编码技术没有国外成熟,应用也没有国外广泛。针对上述问题,笔者提出了解决ArcGIS中组合定位器不支持中文等问题的一种解决方案,并且通过应用于上海市青少年管理系统,提出了关于如何提高地址匹配成功率的几点建议。 相似文献
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地理编码数据库是地理编码技术的重要组成部分,它直接影响到地址匹配的效果。本文在青岛市地址体系的分析研究的基础上,详细阐述了青岛市地理编码数据库的建设流程,包括地址数据获取、地址数据标准化、地址数据入库和地址数据库组织的建设,并对地址数据的更新提出了建议。 相似文献
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《The Photogrammetric Record》1997,15(90):960-966
Books reviewed:
M. Araya, Isprs Highlights
N. Channing and M. Dunn, British Camera Makers
D. R. Wilson, The Care and Storage of Photographs. Recommendations for Good Practice
J. R. Smith, R. S. Webb (1892-1976). From Shropshire to Paarl Via Geodesy and Lesotho
D. Shirvanian. European Space Directory 1997
C. H. Wood and C. P. Keller, Cartographic Design: Theoretical and Practical Perspectives
O. Kö Lbl., Proceedings of the Oeepe Workshop on Application of Digital Photogrammetric Workstations
I. J. Dowman, The Oeepe Geosar Test of Geocoding ERS-1 Sar Data
J. Jaakola and T. Sarjakoski, Experimental Test on Digital Aerial Triangulation 相似文献
M. Araya, Isprs Highlights
N. Channing and M. Dunn, British Camera Makers
D. R. Wilson, The Care and Storage of Photographs. Recommendations for Good Practice
J. R. Smith, R. S. Webb (1892-1976). From Shropshire to Paarl Via Geodesy and Lesotho
D. Shirvanian. European Space Directory 1997
C. H. Wood and C. P. Keller, Cartographic Design: Theoretical and Practical Perspectives
O. Kö Lbl., Proceedings of the Oeepe Workshop on Application of Digital Photogrammetric Workstations
I. J. Dowman, The Oeepe Geosar Test of Geocoding ERS-1 Sar Data
J. Jaakola and T. Sarjakoski, Experimental Test on Digital Aerial Triangulation 相似文献
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K. S. Rao Manisha G. Naidu Jyoti Sakalley Santosh Phalke H. K. Aljassar 《Journal of the Indian Society of Remote Sensing》2005,33(2):267-276
The DEM of the Bhuj earthquake affected area of 50 x 50 km was generated using the ERS-1/2 SAR tandem data (May 15—16,1996).
Region growing algorithm coupled with path following approach was used for phase unwrapping. Phase to height conversion was
done using D-GPS control points. Geocoding was done using GAMMA software. A sample data of DEM of Shuttle Radar Topography
Mission (SRTM) of the Bhuj area is made available by DLR Germany. The intensity image, DEM and Error map are well registered.
The spatial resolution of this DEM is about 25 m with height accuracy of a few meters. The DEM derived through ERS SAR data
is prone to atmospheric affects as the required two images are acquired in different timings where as SRTM acquired the two
images simultaneously. An RMS height error of 12.06 m is observed with reference to SRTM though some of the individual locations
differ by as much as 35 m. 相似文献
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Geocoding has become a routine task for many research investigations to conduct spatial analysis. However, the output quality of geocoding systems is found to impact the conclusions of subsequent studies that employ this workflow. The published development of geocoding systems has been limited to the same set of interpolation methods and reference data sets for quite some time. We introduce a novel geocoding approach utilizing object detection on remotely sensed imagery based on a deep learning framework to generate rooftop geocoding output. This allows geocoding systems to use and output exact building locations without employing typical geocoding interpolation methods or being completely limited by the availability of reference data sets. The utility of the proposed approach is demonstrated over a sample of 22,481 addresses resulting in significant spatial error reduction and match rates comparable to typical geocoding methods. For different land‐use types, our approach performs better on low‐density residential and commercial addresses than on high‐density residential addresses. With appropriate model setup and training, the proposed approach can be extended to search different object locations and to generate new address and point‐of‐interest reference data sets. 相似文献
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As tools for collecting data continue to evolve and improve, the information available for research is expanding rapidly. Increasingly, this information is of a spatio‐temporal nature, which enables tracking of phenomena through both space and time. Despite the increasing availability of spatio‐temporal data, however, the methods for processing and analyzing these data are lacking. Existing geocoding techniques are no exception. Geocoding enables the geographic location of people and events to be known and tracked. However, geocoded information is highly generalized and subject to various interpolation errors. In addition, geocoding for spatio‐temporal data is especially challenging because of the inherent dynamism of associated data. This article presents a methodology for geocoding spatio‐temporal data in ArcGIS that utilizes several additional supporting procedures to enhance spatial accuracy, including the use of supplementary land use information, aerial photographs and local knowledge. This hybrid methodology allows for the tracking of phenomenon through space and over time. It is also able to account for reporting inconsistencies, which is a common feature of spatio‐temporal data. The utility of this methodology is demonstrated using an application to spatio‐temporal address records for a highly mobile group of convicted felons in Hamilton County, Ohio. 相似文献