三种测绘新技术在不动产测量中的对比研究
Comparative study for three new surveying and mapping technologies in real estate surveying
杨赞辉1
作者信息
- 1. 广东省地质局第七地质大队,广东 惠州 516000
- 折叠
摘要
如何快速、准确获取房屋地籍测量数据对于提升土地利用率以及不动产登记效率具有重要意义,然而,以往不动产测量主要利用全站仪等传统测量技术,存在作业效率低、费时费力等缺陷.近年来,三维测绘新技术不断发展与成熟,以无人机倾斜摄影测量技术、机载激光雷达技术、架站式激光雷达技术为代表的测绘新技术广泛应用于测绘项目生产中.但是不同测绘新技术在适用场景、成果精度等方面存在差异.研究选取台州市某地作为不动产测量试验区,分析基于三种测绘新技术的不动产测量方法与传统不动产测量方法的效率与精度,得出结论:制定了三种测绘新技术在不动产测量种的应用选择方案,为不动产测量相关项目生产的技术手段选择提供了有益借鉴.
Abstract
How to quickly and accurately obtain housing cadastral measurement data is of great significance for improving land use efficiency and real estate registration efficiency.However,due to the traditional measurement techniques such as total stations used in real estate measurement in the past,there were shortcomings such as low operational efficiency,time-consuming and laboriousness.In recent years,new 3D surveying and mapping technologies have continuously developed and matured,with new surveying and mapping technologies represented by unmanned aerial vehicle oblique photogrammetry,airborne LiDAR technology,and gantry LiDAR technology which are widely applied in surveying and mapping project production.As for different new surveying and mapping technologies,differences are still existed in terms of the applicable scenarios and result accuracy.A certain area in Taizhou City is selected in this article as a real estate measurement experimental area to analyze the efficiency and accuracy of real estate measurement methods based on three new surveying and mapping technologies and traditional real estate measurement methods,and it is concluded that the application selection schemes of three new surveying and mapping technologies have developed in the real estate measurement.It provides useful reference for the selection of technical means for the production of real estate measurement related projects.
关键词
不动产测量/无人机倾斜摄影测量/机载激光雷达/架站式激光雷达/测绘新技术Key words
real estate measurement/drone tilt photogrammetry/airborne laser radar/station mounted laser radar/new surveying and mapping technologies引用本文复制引用
出版年
2024
NETL
NSTL
万方数据