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In search for urban landscape development tools: Street View Imagery (SVI) Analysis

DOI

https://doi.org/10.7275/30gp-g924

Publication Date

August 2022

Abstract

Streets hold up to 90% of public space in densely built urban areas, they are ubiquitous and thus hold considerable spatial potential to fulfill various functions. This paper presents a comparative study on main streets, squares, or spaces on a micro scale within Budapest and compared to similar European streets.

A goal to transform streets into sufficient public spaces for a growing number of people are investigated along with how residents view those spaces from their own point of view. A motive and evidence for its importance is focused on how half of the world’s population is now covered by Street View Imagery (SVI), which provides a valuable large-scale source of urban data, often replacing field visits with virtual audits and it can be a vital resource to help us design and understand how we could perceive our landscape and urban spaces especially.

The questions of this paper are the following: Could we use street images and analysis for urban and landscape development? Are our perspectives and what we see from images efficient tools to develop our surroundings? Is Google Street View Imagery (GSVI) an effective tool to analyse, categorize and compare our public spaces and streets in relation to landscape and urban developments?

Finally, this paper will take a look at how GSVI works, its positives and negatives, then use previous literature and studies to apply a practical analysis using GSVI. A figure with an assessment method to see how we could use GSVI and image editing programs to end up with quantitative results that could be used for landscape development and comparative analysis within our streets and public spaces. The importance and historical use of GSVI is evident in research and literature, the questions lie in how and what methods could make it of good assistance and use in our profession and its applications.

Key words: Landscape assessment; Street greenery; Google Street View Imagery (GSVI); Visual quality, public participation

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