Understanding cities with machine eyes: A review of deep computer vision in urban analytics

MR Ibrahim, J Haworth, T Cheng - Cities, 2020 - Elsevier
Modelling urban systems has interested planners and modellers for decades. Different
models have been achieved relying on mathematics, cellular automation, complexity, and …

Computational socioeconomics

J Gao, YC Zhang, T Zhou - Physics Reports, 2019 - Elsevier
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic
status are significant for economic development. The understanding of socioeconomic …

Take a look around: using street view and satellite images to estimate house prices

S Law, B Paige, C Russell - ACM Transactions on Intelligent Systems …, 2019 - dl.acm.org
When an individual purchases a home, they simultaneously purchase its structural features,
its accessibility to work, and the neighborhood amenities. Some amenities, such as air …

Association between street greenery and walking behavior in older adults in Hong Kong

Y Yang, D He, Z Gou, R Wang, Y Liu, Y Lu - Sustainable Cities and Society, 2019 - Elsevier
Built environment interventions, such as creating green and walkable neighborhoods have
increasingly been recognized as an effective approach to promote physical activity and …

Using social media, machine learning and natural language processing to map multiple recreational beneficiaries

AS Gosal, IR Geijzendorffer, T Václavík, B Poulin… - Ecosystem Services, 2019 - Elsevier
Abstract Information and numbers on the use and appreciation of nature are valuable
information for protected area (PA) managers. A promising direction is the utilisation of …

Happiness is greater in more scenic locations

CI Seresinhe, T Preis, G MacKerron, HS Moat - Scientific reports, 2019 - nature.com
Does spending time in beautiful settings boost people's happiness? The answer to this
question has long remained elusive due to a paucity of large-scale data on environmental …

Street-Frontage-Net: urban image classification using deep convolutional neural networks

S Law, CI Seresinhe, Y Shen… - International Journal of …, 2020 - Taylor & Francis
Quantifying aspects of urban design on a massive scale is crucial to help develop a deeper
understanding of urban designs elements that contribute to the success of a public space. In …

Social media and deep learning capture the aesthetic quality of the landscape

I Havinga, D Marcos, PW Bogaart, L Hein, D Tuia - Scientific reports, 2021 - nature.com
Peoples' recreation and well-being are closely related to their aesthetic enjoyment of the
landscape. Ecosystem service (ES) assessments record the aesthetic contributions of …

Deep mapping gentrification in a large Canadian city using deep learning and Google Street View

L Ilic, M Sawada, A Zarzelli - PloS one, 2019 - journals.plos.org
Gentrification is multidimensional and complex, but there is general agreement that visible
changes to neighbourhoods are a clear manifestation of the process. Recent advances in …

Landscape aesthetics: Spatial modelling and mapping using social media images and machine learning

AS Gosal, G Ziv - Ecological Indicators, 2020 - Elsevier
Cultural ecosystem services such as aesthetic value are highly context-specific and often
present difficulties in their assessment. Here we present a case study in the northern English …