Hyperlocal environmental data with a mobile platform in urban environments
Environmental data with a high spatio-temporal resolution is vital in informing actions toward tackling urban sustainability challenges. Yet, access to hyperlocal environmental data sources is limited due to the lack of monitoring infrastructure, consistent data quality, and data availability to the...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/153512 |
| _version_ | 1826193468719890432 |
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| author | Wang, An Mora, Simone Machida, Yuki deSouza, Priyanka Paul, Sanjana Oyinlola, Oluwatobi Duarte, Fábio Ratti, Carlo |
| author2 | Senseable City Laboratory |
| author_facet | Senseable City Laboratory Wang, An Mora, Simone Machida, Yuki deSouza, Priyanka Paul, Sanjana Oyinlola, Oluwatobi Duarte, Fábio Ratti, Carlo |
| author_sort | Wang, An |
| collection | MIT |
| description | Environmental data with a high spatio-temporal resolution is vital in informing actions toward tackling urban sustainability challenges. Yet, access to hyperlocal environmental data sources is limited due to the lack of monitoring infrastructure, consistent data quality, and data availability to the public. This paper reports environmental data (<jats:italic>PM</jats:italic>, <jats:italic>NO</jats:italic><jats:sub><jats:italic>2</jats:italic></jats:sub>, temperature, and relative humidity) collected from 2020 to 2022 and calibrated in four deployments in three global cities. Each data collection campaign targeted a specific urban environmental problem related to air quality, such as tree diversity, community exposure disparities, and excess fossil fuel usage. Firstly, we introduce the mobile platform design and its deployment in Boston (US), NYC (US), and Beirut (Lebanon). Secondly, we present the data cleaning and validation process, for the air quality data. Lastly, we explain the data format and how hyperlocal environmental datasets can be used standalone and with other data to assist evidence-based decision-making. Our mobile environmental sensing datasets include cities of varying scales, aiming to address data scarcity in developing regions and support evidence-based environmental policymaking. |
| first_indexed | 2024-09-23T09:40:00Z |
| format | Article |
| id | mit-1721.1/153512 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:40:00Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1535122024-09-20T18:01:12Z Hyperlocal environmental data with a mobile platform in urban environments Wang, An Mora, Simone Machida, Yuki deSouza, Priyanka Paul, Sanjana Oyinlola, Oluwatobi Duarte, Fábio Ratti, Carlo Senseable City Laboratory Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability Environmental data with a high spatio-temporal resolution is vital in informing actions toward tackling urban sustainability challenges. Yet, access to hyperlocal environmental data sources is limited due to the lack of monitoring infrastructure, consistent data quality, and data availability to the public. This paper reports environmental data (<jats:italic>PM</jats:italic>, <jats:italic>NO</jats:italic><jats:sub><jats:italic>2</jats:italic></jats:sub>, temperature, and relative humidity) collected from 2020 to 2022 and calibrated in four deployments in three global cities. Each data collection campaign targeted a specific urban environmental problem related to air quality, such as tree diversity, community exposure disparities, and excess fossil fuel usage. Firstly, we introduce the mobile platform design and its deployment in Boston (US), NYC (US), and Beirut (Lebanon). Secondly, we present the data cleaning and validation process, for the air quality data. Lastly, we explain the data format and how hyperlocal environmental datasets can be used standalone and with other data to assist evidence-based decision-making. Our mobile environmental sensing datasets include cities of varying scales, aiming to address data scarcity in developing regions and support evidence-based environmental policymaking. 2024-02-13T17:08:15Z 2024-02-13T17:08:15Z 2023-08-05 Article http://purl.org/eprint/type/JournalArticle 2052-4463 https://hdl.handle.net/1721.1/153512 Wang, A., Mora, S., Machida, Y. et al. Hyperlocal environmental data with a mobile platform in urban environments. Sci Data 10, 524 (2023). en_US 10.1038/s41597-023-02425-3 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ application/pdf Springer Science and Business Media LLC Springer Nature |
| spellingShingle | Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability Wang, An Mora, Simone Machida, Yuki deSouza, Priyanka Paul, Sanjana Oyinlola, Oluwatobi Duarte, Fábio Ratti, Carlo Hyperlocal environmental data with a mobile platform in urban environments |
| title | Hyperlocal environmental data with a mobile platform in urban environments |
| title_full | Hyperlocal environmental data with a mobile platform in urban environments |
| title_fullStr | Hyperlocal environmental data with a mobile platform in urban environments |
| title_full_unstemmed | Hyperlocal environmental data with a mobile platform in urban environments |
| title_short | Hyperlocal environmental data with a mobile platform in urban environments |
| title_sort | hyperlocal environmental data with a mobile platform in urban environments |
| topic | Library and Information Sciences Statistics, Probability and Uncertainty Computer Science Applications Education Information Systems Statistics and Probability |
| url | https://hdl.handle.net/1721.1/153512 |
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