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作者

来源

LANDSCAPE AND URBAN PLANNING,Vol.165,P.93-101

语言

英文

关键字

Urban trees; Computer vision; Streetscapes; Tree cover; Greenspace; AESTHETICS; LANDSCAPE; QUALITY; CITIES; HEALTH; SPACE

作者单位

[Seiferling, Ian; Ratti, Carlo] MIT, Dept Urban Studies & Planning, Senseable City Lab, Room 10-485,77 Massachusetts Ave, Cambridge, MA 02139 USA. [Seiferling, Ian; Proulx, Raphael] Univ Quebec Trois Rivieres, Ctr Rech Interact Bassins Versants Ecosyst Aquat, Canada Res Chair Ecol Integr, 3351 Blvd Forges, Trois Rivieres, PQ G9A 5H7, Canada. [Naik, Nikhil] MIT, Media Lab, 75 Amherst St, Cambridge, MA 02139 USA. Seiferling, I (reprint author), MIT, Dept Urban Studies & Planning, Senseable City Lab, Room 10-485,77 Massachusetts Ave, Cambridge, MA 02139 USA. E-Mail: ianseifs@mit.edu

摘要

Traditional tools to map the distribution of urban green space have been hindered by either high cost and labour inputs or poor spatial resolution given the complex spatial structure of urban landscapes. What's more, those tools do not observe the urban landscape from a perspective in which citizens experience a city. We test a novel application of computer vision to quantify urban tree cover at the street-level. We do so by utilizing the open source image data of city streetscapes that is now abundant (Google Street View). We show that a multi-step computer vision algorithm segments and quantifies the percent of tree cover in streetscape images to a high degree of precision. By then modelling the relationship between neighbouring images along city street segments, we are able to extend this image representation and estimate the amount of perceived tree cover in city streetscapes to a relatively high level of accuracy for an entire city. Though not a replacement for high resolution remote sensing (e.g., aerial LiDAR) or intensive field surveys, the method provides a new multi-feature metric of urban tree cover that quantifies tree presence and distribution from the same viewpoint in which citizens experience and see the urban landscape.