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
19 entries « ‹ 1 of 4
› » 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.
@article{nokey,
title = {Measurement of urban vitality with time-lapsed street-view images and object-detection for scalable assessment of pedestrian-sidewalk dynamics},
author = {Nathvani R and Cavanaugh A and Suel E and Bixby H and Clark SN and Metzler AB and Nimo J and Bedford-Moses J and Baah S and Arku RE and Robinson BE and Baumgartner J and Bennett JE and Arif AM and Long Y and Agyei-Mensah S and Ezzati M},
doi = {https://doi.org/10.1016/j.isprsjprs.2025.01.038},
year = {2025},
date = {2025-02-14},
urldate = {2025-02-14},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {221},
pages = {251-264},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{nokey,
title = {Using deep transfer learning and satellite imagery to estimate urban air quality in data-poor regions},
author = {Yadav N and Sorek-Hamer M and Von Pohle M and Asanjan AA and Sahasrabhojanee A and Suel E and Arku R and Lingenfelter V and Brauer M and Ezzati M and Oza N and Ganguly AR},
doi = {https://doi.org/10.1016/j.envpol.2023.122914},
year = {2024},
date = {2024-02-01},
urldate = {2024-02-01},
journal = {Environmental Pollution},
volume = {342},
pages = {122914},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{R2023b,
title = {Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning},
author = {Nathvani R and Vishwanath D and Clark SN and Alli AS and Muller E and Coste H and Bennett JE and Nimo J and Bedford-Moses J and Baah S and Hughes A and Suel E and Metzler AB and Rashid T and Brauer M and Baumgartner J and Owusu G and Agyei-Mensah S and Arku RE and Ezzati M
},
doi = {https://doi.org/10.1016/j.scitotenv.2023.166168},
year = {2023},
date = {2023-08-14},
urldate = {2023-08-14},
journal = {Science of the Total Environment},
volume = {903},
pages = {166168},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{AB2023,
title = {Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning},
author = {Metzler AB and Nathvani R and Sharmanska V and Bai W and Muller E and Moulds S and Agyei-Asabere C and Adjei-Boadi D and Kyere-Gyeabour E and Tetteh JD and Owuwu G and Agyei-Mensah S and Baumgartner J and Robinson BE and Arku RE and Ezzati M},
doi = {10.1016/j.scitotenv.2023.164794},
year = {2023},
date = {2023-06-13},
journal = {Science of the Total Environment},
volume = {893},
pages = {164794},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{E2023,
title = {Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images},
author = {Suel E and Muller E and Bennett JE and Blakely T and Doyle Y and Lynch J and Mackenbach JD and Middel A and Mizdrak A and Nathvani R and Brauer M and Ezzati M },
doi = {10.1140/epjds/s13688-023-00394-6},
year = {2023},
date = {2023-06-07},
journal = {EPJ Data Science},
volume = {12},
issue = {1},
pages = {19},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
19 entries « ‹ 1 of 4
› »
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