Big Data

The Big Data group applies deep learning methods to various big data sources, especially high resolution satellite data and street imagery, to characterise urban environmental features and exposures, including housing, the social environment, air quality, noise and the transportation environment (mode, street safety, etc.) and to evaluate how urban land use and service delivery policies could impact health.  The group also advances methodologies for the use of big data, such as how best to combine satellite and street level images, transferability of prediction models trained in one city to others, and the use of images to evaluate temporal change.


Related Publications

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Nathvani R, Cavanaugh A, Suel E, Bixby H, Clark SN, Metzler AB, Nimo J, Bedford-Moses J, Baah S, Arku RE, Robinson BE, Baumgartner J, Bennett JE, Arif AM, Long Y, Agyei-Mensah S, Ezzati M

Measurement of urban vitality with time-lapsed street-view images and object-detection for scalable assessment of pedestrian-sidewalk dynamics

ISPRS Journal of Photogrammetry and Remote Sensing, vol. 221, pp. 251-264, 2025.

Yadav N, Sorek-Hamer M, Von Pohle M, Asanjan AA, Sahasrabhojanee A, Suel E, Arku R, Lingenfelter V, Brauer M, Ezzati M, Oza N, Ganguly AR

Using deep transfer learning and satellite imagery to estimate urban air quality in data-poor regions

Environmental Pollution, vol. 342, pp. 122914, 2024.

Nathvani R, Vishwanath D, Clark SN, Alli AS, Muller E, Coste H, Bennett JE, Nimo J, Bedford-Moses J, Baah S, Hughes A, Suel E, Metzler AB, Rashid T, Brauer M, Baumgartner J, Owusu G, Agyei-Mensah S, Arku RE, Ezzati M

Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning

Science of the Total Environment, vol. 903, pp. 166168, 2023.

Metzler AB, Nathvani R, Sharmanska V, Bai W, Muller E, Moulds S, Agyei-Asabere C, Adjei-Boadi D, Kyere-Gyeabour E, Tetteh JD, Owuwu G, Agyei-Mensah S, Baumgartner J, Robinson BE, Arku RE, Ezzati M

Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning

Science of the Total Environment, vol. 893, pp. 164794, 2023.

Suel E, Muller E, Bennett JE, Blakely T, Doyle Y, Lynch J, Mackenbach JD, Middel A, Mizdrak A, Nathvani R, Brauer M, Ezzati M

Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images

EPJ Data Science, vol. 12, iss. 1, pp. 19, 2023.

19 entries « 1 of 4 »