Measurement of 2D and 3D Fractal Features of Urban Morphology from an Architectural View and Its Influencing Factors

被引:4
|
作者
Zhang, Chenming [1 ]
Ping, Xiaoying [2 ]
Fan, Qindong [1 ]
Li, Chunlin [3 ]
机构
[1] North China Univ Water Resources & Elect Power, Coll Architecture, Zhengzhou 450046, Peoples R China
[2] North China Univ Water Resources & Elect Power, Sch Publ Adm, Zhengzhou 450046, Peoples R China
[3] Chinese Acad Sci, Inst Appl Ecol, CAS Key Lab Forest Ecol & Management, Shenyang 110016, Peoples R China
关键词
fractal dimensions; box-counting dimension; urban morphology; architecture layout; road network; LAND-USE; FORM; SCALE; EVOLUTION; PATTERN; SHAPE;
D O I
10.3390/fractalfract8030138
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Urban morphology has been empirically demonstrated to be self-organized and can be quantified by fractal dimension. However, the spatial variation rule of fractal features at the sub-zone scale has yet to be uncovered, as well as the relationship between fractal dimension values and road network or land-use patterns. In this study, the urban area is partitioned into 158 grid units, with subsequent calculations conducted to determine the fractal dimensions (using 2D box-counting and 3D voxel-counting methods), road network characteristics, and land-use patterns within each individual unit. The pattern of how architectures fill into the 2D or 3D embedding space at the grid level is revealed. Moreover, the spatial relationship between the road network, land-use, and their impacts on the local architectural layout is elucidated by employing MGWR, a model that incorporates the principles of fitting localized spatial regression. The results are as follows: (1) urban morphology follows fractal laws at a sub-zone scale, both in a 2D plane and 3D volume; (2) the filling degree of architecture is high in the urban center but low in the periphery areas; (3) the selected variables fit well with the regression models; (4) there is spatial heterogeneity regarding the influence of each factor. The research findings provide valuable insights into the theoretical relationship between urban morphology and the composite structure of road networks and land use. This facilitates identifying crucial areas and priority directions for urban renewal construction, as well as optimizing architectural design to improve efficiency and functionality.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] The Effects of 2D and 3D Urban Morphology on Air Quality
    Yuyao Liu
    Hanqing Wang
    Water, Air, & Soil Pollution, 2023, 234
  • [2] The Effects of 2D and 3D Urban Morphology on Air Quality
    Liu, Yuyao
    Wang, Hanqing
    WATER AIR AND SOIL POLLUTION, 2023, 234 (09):
  • [3] Urban Geochemistry: from 2D to 3D
    Le Guern, C.
    URBAN SUBSURFACE - FROM GEOSCIENCE AND ENGINEERING TO SPATIAL PLANNING AND MANAGEMENT, 2017, 209 : 26 - 33
  • [4] A 3D view on 2D materials
    Novoselov, Kostya
    Demming, Anna
    PHYSICS WORLD, 2019, 32 (05) : 15 - 15
  • [5] 3D morphology reconstruction of rock joints from 2D profile measurement by a profilograph
    Liu, Songlin
    Wang, Changshuo
    Du, Shigui
    Yong, Rui
    Yu, Yang
    Sun, Hongyue
    MEASUREMENT, 2022, 203
  • [6] 3D morphology reconstruction of rock joints from 2D profile measurement by a profilograph
    Liu, Songlin
    Wang, Changshuo
    Du, Shigui
    Yong, Rui
    Yu, Yang
    Sun, Hongyue
    MEASUREMENT, 2022, 203
  • [7] Generation of 3D building models from 2D architectural plans
    Lewis, R
    Sequin, C
    COMPUTER-AIDED DESIGN, 1998, 30 (10) : 765 - 779
  • [8] Towards 3D face model from 2D view
    Skarbek, W
    Ignasiak, K
    Morgos, M
    Tomaszewski, M
    INTELLIGENT MEDIA TECHNOLOGY FOR COMMUNICATIVE INTELLIGENCE, 2005, 3490 : 158 - 162
  • [9] 3D morphology of a random field from its 2D cross-section
    Makarenko, Irina
    Fletcher, Andrew
    Shukurov, Anvar
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2015, 447 (01) : L55 - L59
  • [10] The effect of urban 2D and 3D morphology on air temperature in residential neighborhoods
    Tian, Yunyu
    Zhou, Weiqi
    Qian, Yuguo
    Zheng, Zhong
    Yan, Jingli
    LANDSCAPE ECOLOGY, 2019, 34 (05) : 1161 - 1178