Improving models of urban greenspace: from vegetation surface cover to volumetric survey, using waveform laser scanning. Issue 11 (22nd May 2017)

• Record Type: Journal Article
• Authors: Casalegno, Stefano; Anderson, Karen; Hancock, Steven; Gaston, Kevin J.
• Editors: Kriticos, Darren
• Is Part Of: Methods in ecology and evolution. Volume 8:Issue 11(2017)
• Page Start: 1443
• Page End: 1452
• Publication Date: 2017-05-22
• Subjects: 3D -- airborne -- lidar -- mapping -- remote sensing -- voxel -- waveform laser; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12794
• Languages: English
• ISSNs: 2041-210X

Abstract

Summary: Urban greenspace has a major impact on human health and quality of life, and thus the way in which such green infrastructure is constructed, managed and maintained is of critical importance. A range of studies have demonstrated the relationship between the areal coverage and distribution of vegetation and the provision of multiple urban ecosystem services. It is not known how sensitive findings are to the spatial resolution of the underlying data relative to the grain size of urban land cover heterogeneity. Moreover, little is known about the three‐dimensional (3D) structure of urban vegetation and delivery of services, and addressing such questions is limited by the availability of data describing canopy structure from the tree tops to the ground. Waveform airborne laser scanning (lidar) offers a new way of capturing 3D data describing vegetation structure. We generated voxels (volumetric pixels) from waveform lidar (1·5 m resolution), differentiated vegetation layers using height as a determinant, and computed statistics on surface cover, volume and volume density per stratum. We then used a range of widely available remote sensing products with varying spatial resolution (1 to 100 m) to map the same greenspace, and compared results to those from the waveform lidar survey. We focused on data from three urban zones in the UK with distinct patterns of vegetation cover. We found −3%, +7·5% and +26·1% differences in green surface cover compared with, respectively, town planning maps (<10 m resolution), national land cover maps (25 m) and European land cover maps (100 m). There were differences of −59·1%, +12·4% and −2·4% in tree cover compared with global (30 m resolution), European (25 m) and national (1 m) estimates. Waveform lidar captured sub‐canopy structure and detected empty spaces in the understorey which contributed a 16% bias in the total green volume derived from non‐waveform lidar observations. We conclude that waveform lidar has a key role to play in estimating important quantitative metrics of urban green infrastructure, which is important because urban greenspace is highly fragmented and shows high levels of spatial and volumetric heterogeneity.