测绘通报 ›› 2022, Vol. 0 ›› Issue (6): 125-129.doi: 10.13474/j.cnki.11-2246.2022.0184.

• 技术交流 • 上一篇    下一篇

基于无人机影像和面向对象的中国西部地区农村宅基地面积快速估算

刘耀辉1,2,3, 于祥惠1, 范洁洁1, 周洁4, 程昊5, 姚国标1, 孟飞1, 靳奉祥3   

  1. 1. 山东建筑大学测绘地理信息学院, 山东 济南 250101;
    2. 河北省地震动力学重点实验室, 河北 三河 065201;
    3. 山东科技大学测绘与空间信息学院, 山东 青岛 266590;
    4. 中国地震局地质研究所, 北京 100029;
    5. 武汉大学遥感信息工程学院, 湖北 武汉 430079
  • 收稿日期:2021-07-07 发布日期:2022-06-30
  • 通讯作者: 姚国标。E-mail:yao7837005@163.com
  • 作者简介:刘耀辉(1991-),男,讲师,主要从事遥感信息提取、深度学习技术及地震灾害等方面的研究。E-mail:liuyaohui20@sdjzu.edu.cn
  • 基金资助:
    山东省自然科学基金(ZR2021QD074);河北省地震动力学重点实验室开放基金(FZ212203);国家自然科学基金(42177453);国家对地观测科学数据中心开放基金(NODAOP2020008)

Rapid estimation of rural homestead area in Western China based on UAV imagery and object-oriented method

LIU Yaohui1,2,3, YU Xianghui1, FAN Jiejie1, ZHOU Jie4, CHENG Hao5, YAO Guobiao1, MENG Fei1, JIN Fengxiang3   

  1. 1. School of Surveying and Geo-informatics, Shandong Jianzhu University, Jinan 250101, China;
    2. Hebei Key Laboratory of Earthquake Dynamics, Sanhe 065201, China;
    3. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China;
    4. Institute of Geology, China Earthquake Administration, Beijing 100029, China;
    5. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • Received:2021-07-07 Published:2022-06-30

摘要: 快速、准确地提取农村宅基地面积,对于城乡规划、房地一体化、美丽乡村建设等工作意义重大。本文以陕西省某村为研究区域,基于无人机高分辨率遥感数据,采用面向对象方法,对研究区进行多尺度分割和监督分类,提取建筑物轮廓;基于倾斜摄影测量方法,估算建筑物楼层数,并最终进行宅基地面积的快速估算。建筑物提取总体精度为95.8%,Kappa系数为0.892 5。将提取后的宅基地面积结合楼层数进行分析计算,得出该研究区建筑物宅基地总面积为36 417 m2。结果表明,本文方法能够准确、有效地提取宅基地面积,为无人机遥感在建筑物的提取识别及宅基地面积快速判定提供了参考。

关键词: 无人机, 遥感, 宅基地面积, 中国西部地区, 农村

Abstract: Rapid and accurate extraction of rural homestead area is of great significance for urban and rural planning, housing and land integration, and beautiful rural construction. In this paper, one village in Shaanxi province is taken as the research area. Based on UAV high-resolution remote sensing data, multi-scale segmentation and supervised classification are used to extract the building contour. The number of building floors is then estimated based on oblique photogrammetry. Finally, a fast estimation of homestead area is carried out. The overall accuracy of building extraction in the study area is 95.8%, and Kappa coefficient is 0.892 5. The total area of residential land in the study area is 36 417 m2. The results show that this method can accurately and effectively extract the homestead area, and provide a reference for UAV remote sensing in the extraction and identification of buildings and the rapid determination of homestead area.

Key words: UAV, remote sensing, homestead area, Western China, rural area

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