Yupeng Liu, Chong Chen, Jiajia Li, Wei-Qiang Chen
Context The key attributes of landscape pattern include composition and configuration, which can be depicted by landscape/spatial metrics. An emerging pathway is leveraging vertical data to advance three- dimensional (3-D) spatial metrics to interpret land- scape attributes and quantify 3-D patterns. Objectives We introduced a suite of spatial metrics to recognize 3-D morphological characteristics of residential communities and examine their temporal changes.
Methods Seventeen 3-D spatial metrics were designed and computed at patch-, class-, and land- scape-levels based on building footprints and height information in geographic information system (GIS). These metrics characterized 3-D forms of residential communities, including number, area, height, shape, and diversity. These 3-D features were further used to recognize five typical built types based on the scheme of local climate zone (LCZ) and quantify their 3-D morphological changes with rapid urbanization.
Results The 3-D spatial metrics performed well in describing vertical and volumetric characteristics of residential communities and distinguishing five typ- ical built types in Xiamen, China. Our results indicated that architectural styles of residential com- munities changed from homo- to mixed-rise buildings and from compact to open arrangement with rapid urbanization.
Conclusions Both 2-D and 3-D features are key attributes of the landscape. Our results showed that 3-D spatial metrics were not only useful tools for quantifying surface patterns but also key comple- ments to vertical feature characterization, offering advantages in representing urbanization over the existing indexes. Growing 3-D datasets have great potential to develop more valuable metrics for characterizing spatial features, capturing ecological processes, and understanding drivers in various landscape contexts.