Street view imagery in urban analytics and GIS: A review

https://doi.org/10.1016/j.cities.2022.103925

Unsupervised machine learning in urban studies: A systematic review of applications

The urban planning ideas proposed by Jane Jacobs in the 1960s remain relevant to this day, promoting a perspective on the relationship between urban morphology and the community that takes into consideration the experiences of the people themselves in the planning of cities. With Jacobs’ ideas in mind, this article seeks to explore the urban territory of Santiago, Chile, and to assess the vitality of its neighborhoods with their diversity of morphological, architectural, and spatial characteristics. The results reveal a spatial reality that differs considerably from typical interpretations of this and other cities across Latin America, characterized by a strong radial center–periphery dynamic interspersed with sub-centers of high vitality, mainly in the form of rural towns and villages that, over time, became absorbed into the urban fabric of Santiago, along with social housing estates located on what used to be the urban periphery.

/pdf/santiago-de-chile-through-the-eyes-of-jane-jacobs-analysis-14u9ibrmmt.pdf

Santiago de Chile through the eyes of jane jacobs. Analysis of the conditions for urban vitality in a latin American metropolis

The release of Google Street View in 2007 inspired several new panoramic street-level imagery platforms including Apple Look Around, Bing StreetSide, Baidu Total View, Tencent Street View, Naver Street View, and Yandex Panorama. The ever-increasing global capture of cities in 360° provides considerable new opportunities for data-driven urban research. This paper provides the first comprehensive, state-of-the-art review on the use of street-level imagery for urban analysis in five research areas: built environment and land use; health and wellbeing; natural environment; urban modelling and demographic surveillance; and area quality and reputation. Panoramic street-level imagery provides advantages in comparison to remotely sensed imagery and conventional urban data sources, whether manual, automated, or machine learning data extraction techniques are applied. Key advantages include low-cost, rapid, high-resolution, and wide-scale data capture, enhanced safety through remote presence, and a unique pedestrian/vehicle point of view for analyzing cities at the scale and perspective in which they are experienced. However, several limitations are evident, including limited ability to capture attribute information, unreliability for temporal analyses, limited use for depth and distance analyses, and the role of corporations as image-data gatekeepers. Findings provide detailed insight for those interested in using panoramic street-level imagery for urban research.

Panoramic Street-Level Imagery in Data-Driven Urban Research: A Comprehensive Global Review of Applications, Techniques, and Practical Considerations

A successful built environment is assumed to encourage street vitality in the time and space dimensions. The availability of mobile location data has made it possible to measure street vitality from a large-scale and multiperiod perspective. We used the mobile location data recorded in West Nanjing Road and the surrounding streets in Shanghai as a proxy for street activity, and introduced intensity and instability as indicators of street vitality to test whether there is still a correlation between street vitality and built environment in high-density cities, and whether there are applicable conditions. The results show that for spatial units with higher intensity, the street activities tend to be more unstable. It is more effective to promote street vitality by increasing the diversity of commercial formats. For the streets in high-intensity areas, increasing the mix degree of building functions and the development intensity of the surrounding blocks may not necessarily enhance the street vitality. The design of the external spaces is always an effective measure to maintain continuous vitality. Subway stations play a significant role in promoting street vitality.

Influence of Built Environment on Street Vitality: A Case Study of West Nanjing Road in Shanghai Based on Mobile Location Data

Street networks are considered to be one significant component of urban structures that serve various urban functions. Assessing the quality of each street is important for managing natural and public resources, organizing urban morphologies and improving city vitality. While current research focuses on particular street assessment indices, such as accessibility and connectivity, they ignore biases in street assessment caused by differences in urban functions. To address this issue, an adaptive approach to assessing street quality from the perspective of the variation in urban functions is proposed. First, an adaptive urban function detection model is established, with street-level element segmenting using PSPNet and semantic urban function extraction using LDA topic modelling. On this basis, an urban function-driven street quality assessment is proposed to adaptively evaluate multilevel urban streets. Taking Tianhe District in Guangzhou, Guangdong Province, as the study area, experiments using street view images and points of interest (POIs) are applied to validate the proposed approach. The experiment results in a model for adaptive urban function detection with an overall accuracy of 64.3%, showing that streets with different urban functions, including traffic, commercial, and residential functions, can be assessed. The experimental results can facilitate urban function organization and urban land-use planning.

Urban Function as a New Perspective for Adaptive Street Quality Assessment

Evolution of river network due to urbanization in the Southeast Yinzhou Plain of Yongjiang River Basin, China

A Combined Architecture Based on 1d Cnn and Gru for Type Prediction and Time Location of Shearer Tripping Fault

The invention discloses a street quality evaluation method. The method comprises the steps: obtaining a street view image and POI data of a to-be-evaluated street; extracting city function semantic information of the POI data, and constructing a spatial characteristic index of the streetscape image, wherein the spatial characteristic indexes comprise an opening degree index and a surrounding degree index; inputting the urban function semantic information and the spatial characteristic indexes into a pre-established adaptive urban function prediction model to obtain a street urban function prediction result of the to-be-evaluated street; and evaluating the street quality of the to-be-evaluated street based on the street city function prediction result. The invention further discloses a street quality evaluation device and system and a storage medium, the problem that the street quality cannot be evaluated through the urban function perspective in the prior art can be effectively solved,and the evaluation accuracy and efficiency can be effectively improved.

Junyu Lu

Papers

Urban Function as a New Perspective for Adaptive Street Quality Assessment

Evolution of river network due to urbanization in the Southeast Yinzhou Plain of Yongjiang River Basin, China

A Combined Architecture Based on 1d Cnn and Gru for Type Prediction and Time Location of Shearer Tripping Fault

Street quality evaluation method, device and system and storage medium