Abstract
Monitoring progress of power restoration following extreme events is essential for situational awareness about spatiotemporal distribution of populations without power and to help with response efforts. Because of the proprietary nature of restoration data, and the difficulty in obtaining power outage data from utility companies in near real-time (e.g., during Hurricane Maria (2017)), this project used satellite derived nighttime lights data from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to (i) monitor wide area power outage and (ii) estimate impacted customers over time to assist with restoration. A discussion of the methodology and its implementation during hurricanes Maria (2017) and Eta (2020) is presented in this paper. Future work will focus on calibrating estimated customers based on light intensity and density distribution, and generation of restoration profiles for emergency response.
| Original language | English |
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| Pages | 566-569 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2021 |
| Event | 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium Duration: Jul 12 2021 → Jul 16 2021 |
Conference
| Conference | 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 |
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| Country/Territory | Belgium |
| City | Brussels |
| Period | 07/12/21 → 07/16/21 |
Funding
This material is based upon work supported by the U.S. Department of Energy’s (DoE) Office of Cybersecurity, Energy, Security, and Emergency Response. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US DOE. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan). This material is based upon work supported by the U.S. Department of Energy's (DoE) Office of Cybersecurity, Energy, Security, and Emergency Response. This manuscript has been authored by UT-Battelle, LLC, under contract DEAC05-00OR22725 with the US DOE. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan).
| Funders | Funder number |
|---|---|
| DOE Public Access Plan | |
| U.S. Department of Energy | DE-AC05-00OR22725 |
Keywords
- Geographic Information Science
- Monitoring of natural disasters and hazards