Abstract Street View Imagery (SVI) is crucial in estimating indicators such as Sky View Factor
(SVF) and Green View Index (GVI), but (1) approaches and terminology differ across fields …

Artificial intelligence technologies such as computer vision (CV), machine learning, Internet
of Things (IoT), and robotics have advanced rapidly in recent years. The new technologies …

Urban greening is vital for environmental sustainability and human welfare, but assessing its
impact can be challenging due to traditional methodologies' limitations. These methods …

To address the realistic problem of seriously reducing distribution efficiency and increasing
distribution cost caused by road traffic congestion, this paper constructs a time-dependent …

The provision of urban green spaces has been widely acknowledged to offer numerous
benefits to individuals and communities. Recently, there has been a growing recognition of …

This paper elucidates an approach that utilizes generative artificial intelligence (AI) to
develop alternative architectural design options based on local identity. The advancement of …

How do we quantify the levels of greenness within urban street networks? Numerous
attempts to quantify this factor have been made through survey methodologies, remote …

As the university campus is a place for learning, conducting scientific research, and
communication, campus street spatial quality has an impact on its users. Therefore …

This paper utilizes deep learning and street view images to extract visual variables and
explore the interactive effects and spatial impacts of the built environment on hotel prices …

In this paper, we took the urban roads in the Changsha downtown areas as an example to
identify the green view index (GVI) of urban roads based on street view images (SVIs). First …