Ecological Processes (Oct 2020)

Integrating structure and function: mapping the hierarchical spatial heterogeneity of urban landscapes

  • Yuguo Qian,
  • Weiqi Zhou,
  • Steward T. A. Pickett,
  • Wenjuan Yu,
  • Dingpeng Xiong,
  • Weimin Wang,
  • Chuanbao Jing

DOI
https://doi.org/10.1186/s13717-020-00266-1
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 11

Abstract

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Abstract Background Cities are social-ecological systems characterized by remarkably high spatial and temporal heterogeneity, which are closely related to myriad urban problems. However, the tools to map and quantify this heterogeneity are lacking. We here developed a new three-level classification scheme, by considering ecosystem types (level 1), urban function zones (level 2), and land cover elements (level 3), to map and quantify the hierarchical spatial heterogeneity of urban landscapes. Methods We applied the scheme using an object-based approach for classification using very high spatial resolution imagery and a vector layer of building location and characteristics. We used a top-down classification procedure by conducting the classification in the order of ecosystem types, function zones, and land cover elements. The classification of the lower level was based on the results of the higher level. We used an object-based methodology to carry out the three-level classification. Results We found that the urban ecosystem type accounted for 45.3% of the land within the Shenzhen city administrative boundary. Within the urban ecosystem type, residential and industrial zones were the main zones, accounting for 38.4% and 33.8%, respectively. Tree canopy was the dominant element in Shenzhen city, accounting for 55.6% over all ecosystem types, which includes agricultural and forest. However, in the urban ecosystem type, the proportion of tree canopy was only 22.6% because most trees were distributed in the forest ecosystem type. The proportion of trees was 23.2% in industrial zones, 2.2% higher than that in residential zones. That information “hidden” in the usual statistical summaries scaled to the entire administrative unit of Shenzhen has great potential for improving urban management. Conclusions This paper has taken the theoretical understanding of urban spatial heterogeneity and used it to generate a classification scheme that exploits remotely sensed imagery, infrastructural data available at a municipal level, and object-based spatial analysis. For effective planning and management, the hierarchical levels of landscape classification (level 1), the analysis of use and cover by urban zones (level 2), and the fundamental elements of land cover (level 3), each exposes different respects relevant to city plans and management.

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