Quantification of urban greenery using hemisphere-view panoramas with a green cover index

Abstract

Urban greenery has positive impacts on the well-being of residents and provides vital ecosystem services. A quantitative evaluation of full-view green coverage at the human scale can guide green space planning and management. We developed a still camera to collect hemisphere-view panoramas (HVPs) to obtain in situ heterogeneous scenes and established a panoramic green cover index (PGCI) model to measure human-scale green coverage. A case study was conducted in Xicheng District, Beijing, to analyse the quantitative relationships of PGCI with the normalized difference vegetation index (NDVI) and land surface temperature (LST) in different land use scenarios. The results show that the HVP is a useful quantization tool: (1) the method adaptively distinguishes the green cover characteristics of the four functional areas, and the PGCI values are ranked as follows: recreational area (29.6) > residential area (19.0) > traffic area (15.9) > commercial area (12.5); (2) PGCI strongly explains NDVI and LST, and for each unit (1%) increase in PGCI, NDVI tends to increase by 0.007, and (3) LST tends to decrease by 0.21 degrees Celsius. This research provides government managers and urban planners with tools to evaluate green coverage in complex urban environments and assistance in optimizing human-scale greenery and microclimate.

Keywords

• urban greenery
• hemisphere-view panorama
• panoramic green cover index
• green vegetation threshold segmentation algorithm