测绘通报 ›› 2023, Vol. 0 ›› Issue (4): 111-114,134.doi: 10.13474/j.cnki.11-2246.2023.0113

• 无人机测绘技术应用推广 • 上一篇    下一篇

无人机影像密集匹配点云在违法占地和违法建筑监测中的应用

全昌文1,2, 李正洪1,2, 庞百宁1, 熊毅飞1,2   

  1. 1. 广西壮族自治区自然资源调查监测院, 广西 南宁 530219;
    2. 自然资源部北部湾经济区 自然资源监测评价工程技术创新中心, 广西 南宁 530219
  • 收稿日期:2022-12-13 发布日期:2023-04-25
  • 通讯作者: 李正洪。E-mail:447128459@qq.com
  • 作者简介:全昌文(1987—),男,工程师,主要研究方向为自然资源调查监测和土地管理。E-mail:qcw148@163.com
  • 基金资助:
    广西重点研发计划(AB22080077);广西科技基地和人才专项(AD20238044);广西空间信息与测绘重点实验室基金(191851011);广西壮族自治区自然资源调查监测院“揭榜挂帅”项目(JBGS2022008)

Application of UAV image matching point clouds in monitoring of illegal land and illegal construction

QUAN Changwen1,2, LI Zhenghong1,2, PANG Baining1, XIONG Yifei1,2   

  1. 1. Guangxi Institute of Natural Resources Survey and Monitoring, Nanning 530219, China;
    2. Technology Innovation Center for Natural Resources Monitoring and Evaluation of Beibu Gulf Economic Zone, Ministry of Natural Resources, Nanning 530219, China
  • Received:2022-12-13 Published:2023-04-25

摘要: 当前城市违法占地和违法建筑监测大多基于遥感影像开展,无法有效发现建筑物加建、加盖等情况,利用影像密集匹配点云提取建筑物三维变化是“两违”精准监测的有效途径。本文以贵港市“两违”监测工作为例,以无人机影像密集匹配点云为基础数据,通过构建深度神经网络模型自动提取建筑物点云,并检测不同时相建筑物点云的变化,经叠加审批、规划等自然资源管理数据,快速提取出疑似“两违”图斑并开展监测。

关键词: 密集匹配点云, 两违, 无人机, 监测

Abstract: At present, the monitoring of illegal land and illegal construction is mostly based on remote sensing images, it can not effectively detect the situation of building addition and construction, and so on. The use of image densely matching point clouds for extracting 3D changes of buildings is an effective way to accurately monitor “two violations”. In Guigang city “two violations” monitoring as an example, using UAV image matching point clouds as the basic data, through the depth of neural network model to extract buildings point clouds, and to detect the change of the different temporal point clouds, after superimposing the management data of natural resources, such as approval and planning, extract the suspected “two violations” spots and monitoring.

Key words: densely matched point clouds, two violations, UAV, monitoring

中图分类号: