基于无人机影像的房屋信息提取技术初步研究

马建; 唐丽华; 吴国栋

doi:10.11899/zzfy20230210

基于无人机影像的房屋信息提取技术初步研究

doi: 10.11899/zzfy20230210

新疆维吾尔自治区地震局, 乌鲁木齐 830011

基金项目: 中国地震局地质研究所所长基金（JB-19-06）；新疆地震科学基金课题（202105）

详细信息

作者简介:
马建，男，生于1991年，工程师。主要从事活动构造及地震地质灾害研究工作。E-mali：492519640@qq.com

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出版历程
- 收稿日期: 2022-01-10
- 刊出日期: 2023-06-30

Preliminary Research on House Information Extraction Technology Based on UAV Images

Earthquake Agency of Xinjiang Uygur Autonomous Region, Urumqi 830011, China

摘要

摘要: 本文以新疆疏附县境内的无人机影像为基础，采用多种方法对研究区内的房屋进行自动提取。由于不同地物在无人机影像中的色彩差异不显著，基于像元的房屋信息提取效果不理想；面向对象的房屋信息提取方法能够识别出绝大部分房屋，但基于DOM影像的提取结果难以识别房屋数量及单栋房屋的面积，而nDSM数据具有房屋的高度信息，基于nDSM数据提取的房屋信息相对较好，提取的房屋信息与实际结果较为吻合，造成误差的原因主要是简易棚和树木的干扰。结果表明，无人机影像具有明显优势，可为区域房屋调查提供有效的基础信息。
- 无人机影像 /
- 房屋 /
- 信息提取
Abstract: Based on UAV images in Shufu county, Xinjiang Province, a variety of methods were used to automatically extract houses in the study area. Because the color difference of different objects in the drone image is not significant, the selected classification method is not suitable and the pixel-based house information extraction effect is not ideal. Object-oriented house information extraction methods can identify most houses, but it is difficult to identify the number of houses and the area of a single house due to its base on DOM image extraction. With the elevation information of houses, the house information extracted based on nDSM data is the best. The extracted house information is more consistent with the actual one. The main error is caused by simple sheds and the interference of trees. The results show that UAV images have obvious advantages and can provide effective basic information for regional house surveys.
- UAV image /
- Houses /
- Information extraction

HTML全文

图 1 分类样本的可分离性

Figure 1. Separability of classification samples

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图 2 房屋信息提取分类后的结果

Figure 2. The classification result of house information extraction

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图 3 不同阈值分割结果对比图

Figure 3. Comparison of segmentation results with different thresholds

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图 4 影像分类后的结果

Figure 4. The result of image classification

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图 5 数字表面模型图

Figure 5. Digital surface model

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图 6 nDSM归一化数字表面模型及房屋信息提取结果

Figure 6. Normalized nDSM surface digital model and extracted house information

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图 7 部分房屋的提取结果

Figure 7. Extraction results of some houses

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图 8 房屋信息提取结果及检验

Figure 8. Extracted house information and validation

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表 1 房屋提取精度评价

Table 1. Accuracy of evaluation of house extraction

评价区 S_m/m² S_a/m² S_c/m² C/%

1 6045 6324 4616 73
2 5074 5135 4313 84
3 5112 5226 3919 75

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