• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Society for Photogrammetry and Remote Sensing Congress >IDENTIFYING BUILDING TYPES AND BUILDING CLUSTERS USING 3D-LASER SCANNING AND GIS-DATA
【24h】

IDENTIFYING BUILDING TYPES AND BUILDING CLUSTERS USING 3D-LASER SCANNING AND GIS-DATA

机译：使用3D-激光扫描和GIS数据识别建筑物类型和构建集群

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Power authorities are highly interested in figures that indicate the energy requirements and especially the heat requirements on a local, regional and country-wide level. Such numbers are needed for their planning of new sites of power plants or for planning alternative energy modes. Existing methods for estimating those requirements heavily rely on local sampling methods as well as on the use of statistical estimates and models. The traditional way of acquiring area wide data is to use statistics and punctually acquired data and extrapolate it to wider areas. E.g. several districts of a city are investigated based on aerial photos and classified into different building and settlement typologies; the cities, in turn are classified according to certain types, which in the end will lead to a country wide statistics. In order to determine more accurate base information, in this project we are using laser scanning as a basic data acquisition method to determine building volumes, i.e. the volumes to be heated. This is due to the fact that laser scanning potentially allows for an area-wide data capture, and also has a high potential of automated data analysis and interpretation. The heat demand of an individual building depends primarily on its age and its type. Therefore, in order to assign head demands to individual buildings measured from laser scanning, the building type first has to be inferred from the available geometric characteristics. The paper will present the results of the automatic extraction of building volumes, and concentrates on the identification of the given building and settlement types that can be used to link the building volumes with specific heat coefficients. The results achieved with our approach will be compared with results derived in the traditional way.
机译：权力当局对表明能源需求的数字非常感兴趣，特别是对当地，区域和全国范围内的热量要求。他们需要规划电厂新站点或用于规划替代能源模式所需的数量。估计这些要求的现有方法依赖于本地采样方法以及使用统计估算和模型。传统的获取区域范围广泛数据是使用统计数据并准时获得数据并将其推断到更广泛的区域。例如。一个城市的若干地区基于天线照片调查，并分为不同的建筑和结算类型;又根据某些类型对城市进行分类，最终将导致国家广泛的统计数据。为了确定更准确的基础信息，在该项目中，我们正在使用激光扫描作为基本数据采集方法来确定构建体积，即被加热的卷。这是由于激光扫描可能允许区域宽的数据捕获，并且还具有高潜力的自动化数据分析和解释。单个建筑的热需求主要取决于其年龄及其类型。因此，为了将头部要求分配给从激光扫描测量的各个建筑物，首先将建筑物从可用的几何特征推断出来。本文将介绍建筑卷的自动提取结果，并专注于可用于将建筑卷与特定热量系数联系起来的给定建筑物和结算类型的识别。通过我们的方法实现的结果将与以传统方式衍生的结果进行比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 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