Open Data-Driven 3D Building Models for Micro-Population Mapping in a Data-Limited Setting

被引:0
|
作者
Maneepong, Kittisak [1 ]
Yamanotera, Ryota [1 ]
Akiyama, Yuki [2 ]
Miyazaki, Hiroyuki [3 ]
Miyazawa, Satoshi [4 ]
Akiyama, Chiaki Mizutani [5 ]
机构
[1] Tokyo City Univ, Grad Sch Integrat Sci & Engn, Tokyo 1580087, Japan
[2] Tokyo City Univ, Fac Architecture & Urban Design, Tokyo 1580087, Japan
[3] GLODAL Inc, Yokohama 2310062, Japan
[4] LocationMind Inc, Tokyo 1010048, Japan
[5] Reitaku Univ, Chiba, Japan
关键词
urban population mapping; building height estimation; building use classification; machine learning; DENSITY;
D O I
10.3390/rs16213922
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Urban planning and management increasingly depend on accurate building and population data. However, many regions lack sufficient resources to acquire and maintain these data, creating challenges in data availability. Our methodology integrates multiple data sources, including aerial imagery, Points of Interest (POIs), and digital elevation models, employing Light Gradient Boosting Machine (LightGBM) and Gradient Boosting Decision Tree (GBDT) to classify building uses and morphological filtration to estimate heights. This research contributes to bridging the gap between data needs and availability in resource-constrained urban environments, offering a scalable solution for global application in urban planning and population mapping.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] DATA-DRIVEN ALIGNMENT OF 3D BUILDING MODELS AND DIGITAL AERIAL IMAGES
    Jung, J.
    Armenakis, C.
    Sohn, G.
    100 YEARS ISPRS ADVANCING REMOTE SENSING SCIENCE, PT 2, 2010, 38 : 327 - 332
  • [2] Data-Driven Scene Understanding from 3D Models
    Satkin, Scott
    Lin, Jason
    Hebert, Martial
    PROCEEDINGS OF THE BRITISH MACHINE VISION CONFERENCE 2012, 2012,
  • [3] Data-Driven Sampling Method for Building 3D Anatomical Models from Serial Histology
    Salunke, Snehal Ulhas
    Ablove, Tova
    Danforth, Teresa
    Tomaszewski, John
    Doyle, Scott
    MEDICAL IMAGING 2017: DIGITAL PATHOLOGY, 2017, 10140
  • [4] SegMap: 3D Segment Mapping using Data-Driven Descriptors
    Dube, Renaud
    Cramariuc, Andrei
    Dugas, Daniel
    Nieto, Juan
    Siegwart, Roland
    Cadena, Cesar
    ROBOTICS: SCIENCE AND SYSTEMS XIV, 2018,
  • [5] Data-Driven Models for Building Occupancy Estimation
    Golestan, Shadan
    Kazemian, Sepehr
    Ardakanian, Omid
    E-ENERGY'18: PROCEEDINGS OF THE 9TH ACM INTERNATIONAL CONFERENCE ON FUTURE ENERGY SYSTEMS, 2018, : 277 - 281
  • [6] On the causality of data-driven building thermal models
    Jiang, Fuyang
    Driesen, Johan
    Kazmi, Hussain
    PROCEEDINGS OF THE 10TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION, BUILDSYS 2023, 2023, : 454 - 457
  • [7] EXPLORATION OF OPEN DATA IN SOUTHEAST ASIA TO GENERATE 3D BUILDING MODELS
    Biljecki, F.
    ISPRS TC IV 3RD BIM/GIS INTEGRATION WORKSHOP AND 15TH 3D GEOINFO CONFERENCE 2020, 2020, 6-4 (W1): : 37 - 44
  • [8] Building 3D GIS data models using open source software
    Scianna, Andrea
    APPLIED GEOMATICS, 2013, 5 (02) : 119 - 132
  • [9] Ground motion models for regions with limited data: Data-driven approach
    Sreenath, Vemula
    Basu, Jahnabi
    Raghukanth, S. T. G.
    EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, 2024, 53 (03): : 1363 - 1375
  • [10] Data-Driven 3D Neck Modeling and Animation
    Liu, Yilong
    Zheng, Chengwei
    Xu, Feng
    Tong, Xin
    Guo, Baining
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2021, 27 (07) : 3226 - 3237