Smart City Gnosys

Smart city article details

Title	Advanced Spatial Categorization Of Buildings Based On Point Based Cloud Data Algorithms
ID_Doc	6549
Authors	Oh G.H.
Year	2025
Published	Journal of Machine and Computing, 5, 2
DOI	http://dx.doi.org/10.53759/7669/jmc202505083
Abstract	There is a tremendous horizontal and vertical growth, where an immediate demand for geospatial tools for precision urban planning and sustainable development is gaining more interest. Acquisition of high resolution, 3D spatial data through Light Detection and Ranging (LiDAR) technology is an exploitable medium. Traditional grid-based LiDAR methods, however, tend to have data loss and lower accuracy. An automated, point based classification methodology is introduced to further augment the classification of raw LiDAR data for urban areas in Tamil Nadu. Through spatial characteristics of point height, point density and local plane orientation, the proposed method efficiently classifies LiDAR points into ground, vegetation and building classes. By successfully reconstructing 3D urban models, the study was able to reflect large urban clusters in urban centres and sparse low-rise structures in rural areas. These models demonstrate the spatial relations between urban characteristics, they develop urban patterns and fluctuations in eco balances. Results show the capacity of this approach being potentially applicable to urban planning, smart city development, landslides and flooding management, and ecological conservation. This study aims to contribute to LiDAR's utility for urban analytics by overcoming current limitations of grid-based methods while enhancing classification in complex terrain. This research highlights the importance of LiDAR in making sustainable urban landscapes and beyond, significantly informed by data. © 2025 The Authors.
Author Keywords	3D City Model; Building Classification; Building Reconstruction; LiDAR; Point Cloud

Similar Articles

Id	Similarity	Authors	Title	Published
27797	0.892	Ortega S.; Santana J.M.; Wendel J.; Trujillo A.; Murshed S.M.	Generating 3D City Models From Open Lidar Point Clouds: Advancing Towards Smart City Applications	Lecture Notes in Intelligent Transportation and Infrastructure, Part F1384 (2021)
59331	0.881	Yang B.; Dong Z.; Liang F.; Mi X.	Ubiquitous Point Cloud: Theory, Model, And Applications	Ubiquitous Point Cloud: Theory, Model, and Applications (2024)
36391	0.88	Münzinger M.; Prechtel N.; Behnisch M.	Mapping The Urban Forest In Detail: From Lidar Point Clouds To 3D Tree Models	Urban Forestry and Urban Greening, 74 (2022)
13121	0.876	Jovanovic, D; Milovanov, S; Ruskovski, I; Govedarica, M; Sladic, D; Radulovic, A; Pajic, V	Building Virtual 3D City Model For Smart Cities Applications: A Case Study On Campus Area Of The University Of Novi Sad	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 9, 8 (2020)
31455	0.876	Vijaywargiya J.; Ramiya A.M.	Information Extraction System For Urban Planning And Governance Using Lidar Based 3D Repository	Journal of Spatial Science, 69, 1 (2024)
41134	0.873	Merkle D.; Reiterer A.	Overview Of 3D Point Cloud Annotation And Segmentation Techniques For Smart City Applications	Proceedings of SPIE - The International Society for Optical Engineering, 12269 (2022)
55088	0.871	Liu R.; Wang M.; Hou G.; Wu W.; Zhao C.; Ge Q.	The Classification Of Airborne Lidar Building Point Clouds Based On Multi-Scale And Multi-Level Cloth Simulation	Photogrammetric Record, 38, 182 (2023)
13123	0.87	Wang R.; Huang S.; Yang H.	Building3D: An Urban-Scale Dataset And Benchmarks For Learning Roof Structures From Point Clouds	Proceedings of the IEEE International Conference on Computer Vision (2023)
35097	0.87	Rahman S.A.F.S.A.; Maulud K.N.A.; Hassan H.	Leveraging Lidar For Smart Cities Climate Change Resilient: A Solar Potential Case Study In A Developing Area	IOP Conference Series: Earth and Environmental Science, 1167, 1 (2023)
27818	0.87	Dhruwa L.; Garg P.K.	Generation Of 3-D Large-Scale Maps Using Lidar Point Cloud Data	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48, 1/W2-2023 (2023)