|
|
多源数据融合：老旧小区改造中测量技术的对比与应用
|
Abstract:
为解决老旧小区改造中测量效率低、数据精度不足的行业痛点，本文以武汉市楚材社区为研究对象，构建涵盖激光测距仪、手持激光扫描仪、架站式三维激光扫描仪及无人机航测的多源测量技术评价体系，并通过实测数据展开分析对比。结果显示：毫米级精度的架站式扫描仪在建筑结构分析中具有显著优势(皮尔逊相关系数R = 0.98)，但单站覆盖范围受限；无人机航测可实现1:2000比例尺地形建模，却受限于低空地面采样距离；手持设备在室内狭窄空间测量中效率提升300%，但存在2 cm级系统性误差。进一步研究表明，采用多源数据融合策略可将总体测量误差降低约47%，大幅提升数据完整性与改造适配性。研究成果为老旧小区改造中测绘方案的优化提供了坚实的理论支撑与可靠的实证依据。
To address the critical challenges of low measurement efficiency and inadequate data precision in the renovation of old residential communities, this paper takes the Chucai Community in Wuhan City as the core research object, and constructs a multi-source measurement technology evaluation system covering laser rangefinders, handheld laser scanners, stationary 3D laser scanners, and unmanned aerial vehicle aerial surveying. The analysis and comparison are carried out through the collected field data. The results show that the stationary scanner with millimeter-level accuracy has a significant advantage in building structure analysis (the pearson correlation coefficient has a value of 0.98), but its single-station coverage is relatively limited; unmanned aerial vehicle aerial surveying can achieve 1:2000 scale terrain modeling, but is limited by the practical low-altitude ground sampling distance; handheld devices increase the measurement efficiency by 300% in indoor narrow spaces, but have a systematic error of 2 cm. Further research shows that the adoption of reasonable multi-source data fusion strategies can reduce the overall measurement error by approximately 47%, significantly improving data integrity and renovation adaptability. The research results provide a solid theoretical support and reliable empirical basis for the effective optimization of mapping schemes in the renovation of old residential areas.
| [1] | Li, Y., Teng, Y., Liu, K., Liu, S. and Tiong, R.L.K. (2026) Developing a Circular Regeneration Toolbox for the Public Space of Old Residential Area. Journal of Urban Management, 15, 436-449. https://doi.org/10.1016/j.jum.2025.05.009 |
| [2] | Wang, H., Shen, Q., Tang, B., Lu, C., Peng, Y. and Tang, L. (2014) A Framework of Decision-Making Factors and Supporting Information for Facilitating Sustainable Site Planning in Urban Renewal Projects. Cities, 40, 44-55. https://doi.org/10.1016/j.cities.2014.04.005 |
| [3] | He, H., Wang, H., Zheng, L., Zhao, T., Zhang, P. and Zheng, K. (2025) Factors and Pathways to Enhance Resident Satisfaction in Old Residential Neighbourhood Renovation: A Configuration Analysis of Cases in Central Nanchang, China. Buildings, 15, Article No. 1125. https://doi.org/10.3390/buildings15071125 |
| [4] | Li, X. (2026) Urban Renewal of Historic Districts: The Renovation of Lihuangpi Road Neighborhood in Wuhan. Journal of Urban Management, 15, 375-390. https://doi.org/10.1016/j.jum.2025.07.008 |
| [5] | Su, Y., Hu, M. and Wu, Y. (2026) Inclusive Urban Renewal: Housing Demolition and Gentrification. Cities, 168, Article ID: 106491. https://doi.org/10.1016/j.cities.2025.106491 |
| [6] | Li, Y., Qiu, J. and Gao, Z. (2024) Understanding the Spatially Heterogeneous Relationships between Urban Green Amenities and Residential Dynamics: Evidence from Wuhan, China. Applied Geography, 171, Article ID: 103396. https://doi.org/10.1016/j.apgeog.2024.103396 |
| [7] | Wang, Y. and Gou, Z. (2025) Evaluating Urban Heat Mitigation Strategies: Microclimate Effects and Energy Consumption in Residential Areas across Diverse Climates. Energy and Buildings, 343, Article ID: 115950. https://doi.org/10.1016/j.enbuild.2025.115950 |
| [8] | Suchocki, C., Nowak, R., Rutkowski, R. and Błaszczak-Bąk, W. (2025) Using Handheld 3D Laser Scanner and High-Resolution Handheld Digital Microscope for Hybrid Building Condition Measurements. Measurement, 253, Article ID: 117751. https://doi.org/10.1016/j.measurement.2025.117751 |
| [9] | Zhou, K. (2020) Combining LiDAR and Photogrammetry to Generate Up-to-Date 3D City Models. Dissertation, Technische Universiteit Delft. |
| [10] | Hu, W. and Hu, R. (2024) Creating Historical Building Models by Deep Fusion of Multi-Source Heterogeneous Data Using Residual 3D Convolutional Neural Network. International Journal of Architectural Heritage, 18, 1377-1393. https://doi.org/10.1080/15583058.2023.2229253 |
| [11] | Wang, T., Wang, Q., Ai, H. and Zhang, L. (2025) Semantics-and-Primitives-Guided Indoor 3D Reconstruction from Point Clouds. Remote Sensing, 14, Article No. 4820. |
| [12] | Zhou, P., An, L., Wang, Y., Geng, G. and Xu, Y. (2025) Cross-Domain Multi-Channel Transformer for Point Cloud Registration in Cultural Heritage Digital Preservation. NPJ Heritage Science, 13, Article No. 503. https://doi.org/10.1038/s40494-025-02064-4 |
| [13] | Chen, T., Wang, H., Li, D., Liu, J., Liu, P., Wu, Z., et al. (2026) An Automated Framework for converting Point Cloud Data to Building Information Modeling with Segmentation and Refinement. Engineering Applications of Artificial Intelligence, 163, Article 112915. https://doi.org/10.1016/j.engappai.2025.112915 |
| [14] | Liu, C., Liang, Y., Zhao, Y., Liu, S. and Huang, C. (2021) Simulation and Analysis of the Effects of Land Use and Climate Change on Carbon Dynamics in the Wuhan City Circle Area. International Journal of Environmental Research and Public Health, 18, Article No. 11617. https://doi.org/10.3390/ijerph182111617 |
| [15] | Luo, X., Ren, M., Zhao, J., Wang, Z., Ge, J. and Gao, W. (2022) Life Cycle Assessment for Carbon Emission Impact Analysis for the Renovation of Old Residential Areas. Journal of Cleaner Production, 367, Article ID: 132930. https://doi.org/10.1016/j.jclepro.2022.132930 |
| [16] | Huo, X., Xue, H. and Jiao, L. (2023) Risk Management of Retrofit Project in Old Residential Areas under Green Development. Energy and Buildings, 279, Article ID: 112708. https://doi.org/10.1016/j.enbuild.2022.112708 |
| [17] | Wang, J., Wen, L., Li, Y., Liu, J. and Che, S. (2025) Uncovering the Impacts of Social Comparative Information on Water Saving Behavior among Urban Residents: A Field Experiment in China. Journal of Cleaner Production, 492, Article ID: 144863. https://doi.org/10.1016/j.jclepro.2025.144863 |
| [18] | Theilig, K., Vollmer, M., Lang, W. and Albus, J. (2025) Multi-Criteria Decision-Making for Energy Building Renovation: Comparing Exterior Wall Structures with the AHP, ANP, Utility Analysis, and TOPSIS. Building and Environment, 280, Article ID: 113075. https://doi.org/10.1016/j.buildenv.2025.113075 |
| [19] | Bornmann, L. and Marx, W. (2015) Methods for the Generation of Normalized Citation Impact Scores in Bibliometrics: Which Method Best Reflects the Judgements of Experts? Journal of Informetrics, 9, 408-418. https://doi.org/10.1016/j.joi.2015.01.006 |
| [20] | García-Lapresta, J.L. and González del Pozo, R. (2023) Using Scoring Functions in a Group Decision-Making Procedure with Heterogeneous Experts and Qualitative Assessments. International Journal of Approximate Reasoning, 161, Article ID: 109004. https://doi.org/10.1016/j.ijar.2023.109004 |
| [21] | Zhang, P., Chen, S., Zheng, X., Li, P., Wang, G., Wang, R., et al. (2025) UAV Communication in Space-Air-Ground Integrated Networks (SAGINs): Technologies, Applications, and Challenges. Drones, 9, Article No. 108. https://doi.org/10.3390/drones9020108 |
| [22] | Bland, J.M. and Altman, D.G. (1999) Measuring Agreement in Method Comparison Studies. Statistical Methods in Medical Research, 8, 135-160. https://doi.org/10.1177/096228029900800204 |
| [23] | Zhang, Z. (1997) Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting. Image and Vision Computing, 15, 59-76. https://doi.org/10.1016/s0262-8856(96)01112-2 |
| [24] | Rusu, R.B. and Cousins, S. (2011) 3D Is Here: Point Cloud Library (pcl). 2011 IEEE International Conference on Robotics and Automation, Shanghai, 9-13 May 2011, 1-4. https://doi.org/10.1109/icra.2011.5980567 |
| [25] | Weinmann, M., Jutzi, B. and Mallet, C. (2014) Semantic 3D Scene Interpretation: A Framework Combining Optimal Neighborhood Size Selection with Relevant Features. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3, 181-188. https://doi.org/10.5194/isprsannals-ii-3-181-2014 |
| [26] | Κu, Η.Η. (1969) Notes on the Use of Propagation of Error Formulas. Journal of Research of the National Bureau of Standards—C. Engineering and Instrumentation, 70, 331. |
| [27] | Yang, J., Li, H., Campbell, D. and Jia, Y. (2016) Go-icp: A Globally Optimal Solution to 3D ICP Point-Set Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2241-2254. https://doi.org/10.1109/tpami.2015.2513405 |
| [28] | Yuan, H., Li, G., Wang, L. and Li, X. (2025) Research on the Improved ICP Algorithm for LiDAR Point Cloud Registration. Sensors, 25, Article No. 4748. https://doi.org/10.3390/s25154748 |
| [29] | Cheng, Y., Chu, H., Li, Y., Tang, Y., Luo, Z. and Li, S. (2024) A Hybrid Improved SAC-IA with a KD-ICP Algorithm for Local Point Cloud Alignment Optimization. Photonics, 11, Article No. 635. https://doi.org/10.3390/photonics11070635 |
| [30] | Lin, X., Zhang, B., Guo, L., Zhang, W., Sun, J., Liu, Y., et al. (2024) Multi-Source Fusion Deformation-Monitoring Accuracy Calibration Method Based on a Normal Distribution Transform-Convolutional Neural Network-Self Attention Network. Photonics, 11, Article No. 953. https://doi.org/10.3390/photonics11100953 |
| [31] | Ren, Y., Shen, Z., Liu, W. and Chen, X. (2025) An Enhanced Lidar-Based SLAM Framework: Improving NDT Odometry with Efficient Feature Extraction and Loop Closure Detection. Processes, 13, Article No. 272. https://doi.org/10.3390/pr13010272 |
| [32] | Liu, Y., Chen, X., Wang, K., Diao, S., Huang, Y., Li, H. and Wu, L. (2023) A Chebyshev Metamodel Based BnB Approach to Efficiently Search Global Optimum for 3D ICP Point Set Registration. Computer Aided Geometric Design, 101, Article 102178. https://doi.org/10.1016/j.cagd.2023.102178 |
| [33] | Chen, Y., Guo, F., Liu, J., Dai, S., Huang, J. and Cai, X. (2025) Overlapping Point Cloud Registration Algorithm Based on KNN and the Channel Attention Mechanism. PLOS One, 20, e0325261. https://doi.org/10.1371/journal.pone.0325261 |
| [34] | Remondino, F. and Rizzi, A. (2010) Reality-Based 3D Documentation of Natural and Cultural Heritage Sites—Techniques, Problems, and Examples. Applied Geomatics, 2, 85-100. https://doi.org/10.1007/s12518-010-0025-x |
| [35] | Doneus, M., Pierre, G. and Jose-Luis, L. (2016) Basics of Range-Based Modelling Techniques in Cultural Heritage 3D Recording. In: 3D Recording, Documentation and Management of Cultural Heritage, Whittles Publishing, 305-368. |
| [36] | Durrant-Whyte, H. and Bailey, T. (2006) Simultaneous Localization and Mapping: Part I. IEEE Robotics & Automation Magazine, 13, 99-110. https://doi.org/10.1109/mra.2006.1638022 |
| [37] | Hess, W., Kohler, D., Rapp, H. and Andor, D. (2016) Real-Time Loop Closure in 2D LIDAR SLAM. 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, 16-21 May 2016, 1271-1278. https://doi.org/10.1109/icra.2016.7487258 |
| [38] | Vosselman, G. and Maas, H.G. (2010) Airborne and Terrestrial Laser Scanning. Whittles Publishing. |
| [39] | Wu, Q., Luo, F., Wu, P., Wang, B., Yang, H. and Wu, Y. (2021) Automatic Road Extraction from High-Resolution Remote Sensing Images Using a Method Based on Densely Connected Spatial Feature-Enhanced Pyramid. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3-17. https://doi.org/10.1109/jstars.2020.3042816 |
| [40] | Lichti, D.D. (2010) Terrestrial Laser Scanner Self-Calibration: Correlation Sources and Their Mitigation. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 93-102. https://doi.org/10.1016/j.isprsjprs.2009.09.002 |
| [41] | Rietdorf, A., Gielsdorf, F. and Gruendig, L. (2004) A Concept for the Calibration of Terrestrial Laser Scanners. INGEO 2004 and FIG Regional Central and Eastern Conference on Engineering Surveying, Bratislava, 11-13 November 2004. |
