...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Building and Environment >GSV2SVF-an interactive GIS tool for sky, tree and building view factor estimation from street view photographs
【24h】

GSV2SVF-an interactive GIS tool for sky, tree and building view factor estimation from street view photographs

机译：GSV2SVF-Anteractive GIS工具，用于天空，树木和街景照片的天空，树木和建筑视图因素估计

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Sky View Factor (SVF) is a commonly used indicator of urban geometry. The availability of street-level SVF measurements has been fairly limited due to the high costs of field survey. The Google Street View (GSV) serves a massive storage of panorama data that can be utilized to obtain SVF measurements. Yet, automatic extraction of SVFs from panoramas is a complicated process that involves multiple sophisticated computation technologies including machine learning, big image data processing, SVF estimation and geographic information systems (GIS), which constitute major hurdles for the end users. In this light, we developed an easy-to-use GIS-integrated tool (GSV2SVF) to streamline the workflow of extracting SVFs from GSV images and therefore making this vast treasure trove of information conveniently available to everyone at a mouse click. As by-products in addition to the SVF, the results obtained from each GSV panorama are accompanied with the tree view factor (TVF) and the building view factor (BVF), which together can provide a more holistic characterization of the outdoor built environment. GSV2SVF is freely available with source code at https://github.com/jian9695/GSV2SVF. A video is available at https://github.com/jian9695/GSV2SVF/blob/master/Video.mp4 and https://youtu.be/k00 wCnuzuvE.
机译：天空视图因子（SVF）是城市几何形状的常用指标。由于现场调查的高成本，街道级SVF测量的可用性已经过分限制。 Google Street View（GSV）提供了全面存储的全景数据，可用于获得SVF测量。然而，从Panoramas的自动提取SVFS是一个复杂的过程，涉及多种复杂的计算技术，包括机器学习，大图像数据处理，SVF估计和地理信息系统（GIS），这些系统构成最终用户的主要障碍。在这种灯光下，我们开发了一种易于使用的GIS集成工具（GSV2SVF），用于简化从GSV图像中提取SVF的工作流程，从而使这个庞大的宝库可以在鼠标点击中方便地提供给每个人的信息。作为副产物除了SVF之外，从每个GSV全景获得的结果伴随着树视图因子（TVF）和建筑物视图因子（BVF），它们一起可以提供户外建筑环境的更全面的表征。 GSV2SVF在https://github.com/jian9695/gsv2svf上自由地提供源代码。一个视频在https://github.com/jian9695/gsv2svf/blob/master/video.mp4和https://youtu.be/k00 wcnuzuve。

著录项

  • 来源
    《Building and Environment》 |2020年第1期|106475.1-106475.7|共7页
  • 作者

    Liang Jianming; Gong Jianhua; Zhang Jinming; Li Yi; Wu Dong; Zhang Guoyong;

  • 作者单位

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Zhejiang CAS Applicat Ctr Geoinformat Jiashan 314100 Zhejiang Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Zhejiang CAS Applicat Ctr Geoinformat Jiashan 314100 Zhejiang Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Informat Engn Univ Inst Geospatial Informat Zhengzhou 450052 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Zhejiang CAS Applicat Ctr Geoinformat Jiashan 314100 Zhejiang Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

    Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China|Univ Chinese Acad Sci Beijing 100049 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sky view factor; Tree view factor; Building view factor; Google street view; Urban environment;

    机译：天空视图因素;树视图因素;建筑视图因素;谷歌街景;城市环境;

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号