Landscape value in urban neighborhoods: A pilot analysis using street-level images

Inoue, Tomoshige; Manabe, Rikutaro; Murayama, Akito; Koizumi, Hideki

doi:10.1016/j.landurbplan.2022.104357

Cited by 25 publications

(12 citation statements)

References 55 publications

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“…Hence, SVI can provide details seen on the ground that are not visible from aerial imagery (Hoffmann et al, 2019;Ning et al, 2022b;Cao et al, 2018;Rosenfelder et al, 2021;Barbierato et al, 2020). SVI is relatively cheaper to capture than aerial imagery thanks to free tiers of commercial companies and the emergence of crowdsourced SVI services such as Mapillary and KartaView (Barbierato et al, 2020;Inoue et al, 2022). What this means is that, even when mainstream services have no coverage of a particular area, SVI can be collected simply by mounting sensors on a backpack or a vehicle and moving around.…”

Section: Discussionmentioning

confidence: 99%

Comparing Street View Imagery and Aerial Perspectives in the Built Environment

Gaw

Chen

Chow

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Street view imagery (SVI) has gained prominence in the past decade, offering a new perspective to map and understand cities. It supports numerous studies in the built environment, by replacing or supplementing aerial and satellite imagery, where some studies have not yet been possible with traditional platforms and have now been enabled for the first time thanks to the increasing volume of SVI data. However, the two perspectives are often disconnected and there has not been an overarching paper to discuss the pros and cons of each. We provide an overview outlining and discussing the role of SVI in GIS and urban studies spanning six use cases. Our discourse is supported by a systematic literature review of more than 100 papers and our own experiments that reveal the added value and challenges of SVI in extracting information on buildings and other urban features, an increasingly important use case. We find that the key advantages of SVI over aerial imagery are that it represents more closely how streetscapes are perceived by people and that it enables extracting certain information that otherwise cannot be gathered from top-down perspectives. However, the spatial coverage of SVI tends to be limited to the vicinity of driveable roads, and its temporal coverage is comparatively sparse.

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Section: Discussionmentioning

confidence: 99%

Comparing Street View Imagery and Aerial Perspectives in the Built Environment

Gaw

Chen

Chow

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The original typology of landscape values was developed by Brown and Reed [20], who established a set of 13 values (aesthetic, recreation, biodiversity, life-supporting, economic, learning, historical, cultural, future, intrinsic, spiritual, therapeutic, subsistence) as part of a forest planning process. This typology has been adapted and used for different applications, such as public lands [21], country management [22][23][24], urban areas [25][26][27][28], rural landscapes [29,30], and coastal landscapes [31,32]. However, there is not a one-to-one correspondence when dealing with places and values [26].…”

Section: Landscape Valuesmentioning

confidence: 99%

“…This typology has been adapted and used for different applications, such as public lands [21], country management [22][23][24], urban areas [25][26][27][28], rural landscapes [29,30], and coastal landscapes [31,32]. However, there is not a one-to-one correspondence when dealing with places and values [26].…”

Section: Landscape Valuesmentioning

confidence: 99%

Landscape Values in a Marina in Granada (Spain): Enhancing Landscape Management through Public Participation

Martín

Piqueras

2023

Land

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Landscape values are related to the attributes that people assign to a perceived landscape. They reflect marina user perceptions, thus representing a feedback tool for marina managers to use to verify the degree of user satisfaction. This study focused on identifying and assessing a marina’s landscape values. We took Marina del Este (Granada, Spain) as a case study. We considered interviews and a questionnaire to devise methods to enhance the participation of stakeholders and users. First, the SWOT analysis from stakeholder interviews enabled us to collect management’s perceptions. Second, the survey gathered the marina’s landscape values, comprising 104 respondents from visitors and users. ANOVA and PCA methods were applied to check the suitability of the values. The results showed that the marina should be in keeping with an atmosphere of tranquility and well-being. Nevertheless, there was a need to improve values related to nautical tourism, such as hospitality and maintenance, dealing with the lack of space and an excess of urbanization in the surroundings. Marina managers should consider these outcomes and analyze the points of improvement to establish the causes of these disagreements and propose solutions for the established management model. The perception of stakeholders and users can enable more consensual policies with greater levels of acceptance and involvement.

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“…SVI data is commonly provided by commercial services such as Google Street View (GSV), and crowdsourced platforms such as Mapillary and KartaView. SVI has enabled and enhanced a wide spectrum of applications in urban-related topics including spatial data infrastructure, public health, urban greenery, transportation, mobility, perception, socioeconomics, and so on (Branson et al, 2018;Cheng et al, 2018;Zhang et al, 2019a;Pelizari et al, 2021;Li et al, 2021;Yao et al, 2021;Inoue et al, 2022;Qiu et al, 2022;Hosseini et al, 2022;Byun and Kim, 2022;Guan et al, 2022).…”

Section: Street View Imagery For Lcz Classificationmentioning

confidence: 99%

Local Climate Zones: Lessons From Singapore and Potential Improvement With Street View Imagery

Ignatius

Hou

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Urban heat island (UHI) is considered a serious environmental issue in highly urbanized cities such as Singapore. To better quantify the UHI intensity, the local climate zones (LCZ) classification scheme was adopted to characterize land covers, and describe and compare their thermal performance. There are three commonly used LCZ classification approaches: manual sampling,World Urban Database and Access Portal Tools (WUDAPT) processing method using remote sensing, and geographical information system (GIS)-based method. Based on the current implementation of WUDAPT Level 0 method in the classification work in Singapore, the principal limitations are expounded. To overcome the deficiencies, street view imagery (SVI), which carries substantial urban spatial information, is regarded as a promising data source. This paper reviews the potential of SVI to better estimate certain LCZrelated properties, such as sky view factor (SVF). As it allows a detailed view on the ground objects, SVI opens up the possibility of identifying surface properties such as albedo, as well as anthropogenic heat sources. Although it is not a novel idea, there has been a lack of a comprehensive use of SVI in assisting LCZ classification from the ground up, especially in a high-density city such as Singapore. This paper overviews potential ways to incorporate SVI and identifies challenges such as coarse temporal resolution and spatial coverage constrained to drivable roads.

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Landscape value in urban neighborhoods: A pilot analysis using street-level images

Cited by 25 publications

References 55 publications

Comparing Street View Imagery and Aerial Perspectives in the Built Environment

Comparing Street View Imagery and Aerial Perspectives in the Built Environment

Landscape Values in a Marina in Granada (Spain): Enhancing Landscape Management through Public Participation

Local Climate Zones: Lessons From Singapore and Potential Improvement With Street View Imagery

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