research-article

Characterizing The Evolution Of Indian Cities Using Satellite Imagery And Open Street Maps

Authors:

Ankit Kumar Singh,

Hari Om Ahlawat,

Prashant Kumar,

Sakshi Taparia,

Shailesh Yadav,

Aaditeshwar SethAuthors Info & Claims

COMPASS '20: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies

Pages 87 - 96

https://doi.org/10.1145/3378393.3402258

Published: 01 July 2020 Publication History

Abstract

With growing urbanization, being able to track urban change is important to plan cities better. Land-use classification of satellite data has been actively used for this purpose. We augment this analysis through the use of crowd-sourced data about the road network in cities, obtained through the Open Street Maps platform. We develop several indicators to quantify the spatial layout of cities and how different localities have changed over time. We apply our methods to study seven Indian cities (Bangalore, Chennai, Delhi, Gurgaon, Hyderabad, Kolkata, and Mumbai) and relate our findings with that of other studies. Our contribution lies in synthesizing two freely available datasets of satellite imagery and road information to develop a series of standardized indicators for different aspects of urbanization, which can serve to compare various cities with one another and to track change happening in the cities over time.

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Cortes-Ramirez JWilches-Vega JCaicedo-Velasquez BParis-Pineda OSly P(2024)Spatiotemporal hierarchical Bayesian analysis to identify factors associated with COVID-19 in suburban areas in ColombiaHeliyon10.1016/j.heliyon.2024.e30182(e30182)Online publication date: Apr-2024
https://doi.org/10.1016/j.heliyon.2024.e30182
Presa-Reyes MTao YChen SShyu M(2022)Deep Learning With Weak Supervision for Disaster Scene Description in Low-Altitude ImageryIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2021.312944360(1-10)Online publication date: 2022
https://doi.org/10.1109/TGRS.2021.3129443
Bansal CAhlawat HJain MPrakash OMehta SSingh DBaheti HSingh SSeth A(2021)IndiaSat: A Pixel-Level Dataset for Land-Cover Classification on Three Satellite Systems - Landsat-7, Landsat-8, and Sentinel-2Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies10.1145/3460112.3471953(147-155)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3460112.3471953

Index Terms

Characterizing The Evolution Of Indian Cities Using Satellite Imagery And Open Street Maps
1. Applied computing
  1. Computers in other domains
    1. Computing in government
2. Computing methodologies
  1. Machine learning

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COMPASS '20: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies

June 2020

359 pages

ISBN:9781450371292

DOI:10.1145/3378393

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Cited By

Cortes-Ramirez JWilches-Vega JCaicedo-Velasquez BParis-Pineda OSly P(2024)Spatiotemporal hierarchical Bayesian analysis to identify factors associated with COVID-19 in suburban areas in ColombiaHeliyon10.1016/j.heliyon.2024.e30182(e30182)Online publication date: Apr-2024
https://doi.org/10.1016/j.heliyon.2024.e30182
Presa-Reyes MTao YChen SShyu M(2022)Deep Learning With Weak Supervision for Disaster Scene Description in Low-Altitude ImageryIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2021.312944360(1-10)Online publication date: 2022
https://doi.org/10.1109/TGRS.2021.3129443
Bansal CAhlawat HJain MPrakash OMehta SSingh DBaheti HSingh SSeth A(2021)IndiaSat: A Pixel-Level Dataset for Land-Cover Classification on Three Satellite Systems - Landsat-7, Landsat-8, and Sentinel-2Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies10.1145/3460112.3471953(147-155)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3460112.3471953

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