[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-113361-en":3,"doc-seo-113361-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},113361,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Can we rely on VIIRS nightlights to estimate the short-term impacts of natural hazards? Evidence from five South East Asian countries","This paper utilizes Visible Infrared Imaging Radiometer Suite (VIIRS) nightlights to model damage from earthquakes, floods, and typhoons across five South East Asian countries: Indonesia, Myanmar, the Philippines, Thailand, and Vietnam. For each hazard type, it compares nightlight intensity between affected and non-affected cells using case studies and fixed-effects regression models resembling a double-difference approach. The analysis addresses VIIRS limitations such as noise, seasonality, and volatility with new statistical methods. Results show little to no significance across methodologies, suggesting researchers should use VIIRS nightlights cautiously when estimating natural-hazard impacts.","Public Disc losure Authorized  \nGeomatics, Natural Hazards and Risk  \nISSN: (Print) (Online) Journal homepage: [https://www.tandfonline.com/loi/tgnh20](https://www.tandfonline.com/loi/tgnh20)  \nPub lic Disc losure Authorized  \nCan we rely on VIIRS nightlights to estimate the short-term impacts of natural hazards? Evidence from five South East Asian countries  \nEmmanuel Skoufias, Eric Strobl & Thomas Tveit  \nTo cite this article: Emmanuel Skoufias, Eric Strobl & Thomas Tveit (2021) Can we rely on VIIRS nightlights to estimate the short-term impacts of natural hazards? Evidence from five South East Asian countries, Geomatics, Natural Hazards and Risk, 12:1, 381-404, DOI:  \n10. 1080/19475705 .2021.1879943  \nTo link to this article: [https://doi.org/10.1080/19475705.2021.1879943](https://doi.org/10.1080/19475705.2021.1879943)  \n© 2021 The Author(s) . Published by Informa UK Limited, trading as Taylor & Francis Group.  \n Published online: 03 Feb 2021.  \n\n|  Submit your article to this journal  |\n| --- |\n|  View related articles  |\n|  Citing articles: 2 View citing articles  |\n\n\n|  Article views: 1121 |\n| --- |\n|  View Crossmark data |\n\nFull Terms & Conditions of access and use can be found at [https://www.tandfonline.com/action/journalInformation?journalCode=tgnh20](https://www.tandfonline.com/action/journalInformation?journalCode=tgnh20)  \nCan we rely on VIIRS nightlights to estimate the shortterm impacts of natural hazards? Evidence from five South East Asian countries  \nEmmanuel Skoufiasa, Eric Stroblb and Thomas Tveitb  \naPoverty & Equity Global Practice, The World Bank Group, Washington, DC, USA; bDepartment of Economics, University of Bern, Bern, Switzerland  \nABSTRACT  \nThis paper utilizes Visible Infrared Imaging Radiometer Suite (VIIRS) nightlights to model damage caused by earthquakes, floods and typhoons in five South East Asian countries (Indonesia, Myanmar, the Philippines, Thailand and Vietnam). For each typeof hazard we examine the extent to which there is a difference in nightlight intensity between affected and non-affected cells based on (i) case studies of specific hazards; and (ii) fixed effect regression models akin to the double difference method to determine any effect that the different natural hazards might have had on the nightlight value. The VIIRS data has some shortcomings with regards to noise, seasonality and volatility that we try to correct for with new statistical methods. The results show little to no significance regardless of the methodology used. Possible explanations for the lack of significance could be underlying noise in the nightlight data and measurements or lack of measurements due to cloud cover. Overall, given the lack of consistency in the results, even though efforts were made to decrease volatility and remove noise, we conclude that researchers should be careful when analyzing natural hazard impacts with the help of VIIRS nightlights.  \nARTICLE HISTORY  \nReceived 30 October 2020 Accepted 15 January 2021  \nKEYWORDS  \nRemote sensing; VIIRS; natural hazard; earthquake; typhoon; flood  \n1. Introduction  \nNatural hazards and the damages caused by them has seen an increase in media coverage, partly due to the overall focus on climate and climate change, but also due to the larger economic damages compared to previous decades. The latter point is explained through a growing global population and the increasing economic value in settled places. With this value increase comes a need for updated local data on where people live and the economic activity there. This is particularly true in the wake of a devastating natural hazard when it can be difficult to assess damages quickly and accurately.  \nCONTACT Thomas Tveit  [Thomas.tveit@vwi.unibe.ch](Thomas.tveit@vwi.unibe.ch)  \n􀀁 2021 The Author(s) . Published by Informa UK Limited, trading as Taylor & Francis Group.  \nThis is an Open Access article distributed under the terms of the Creative Commons Attribution License ([http://creativecommons.or","cbCainMLQ3z6tstG","https://ap.wps.com/l/cbCainMLQ3z6tstG","pdf",3219755,1,25,"English","en",105,"# Introduction\n## Nightlights as a proxy for economic activity\n## Prior work and the shift from DMSP to VIIRS\n# Abstract (Study approach)\n## Data and hazards covered\n## Identification strategy and fixed-effects models\n## Noise, seasonality, volatility adjustments\n## Findings and implications","[{\"question\":\"How does the study use VIIRS nightlights to assess natural-hazard impacts?\",\"answer\":\"It models damage for earthquakes, floods, and typhoons by examining differences in nightlight intensity between affected and non-affected cells across five South East Asian countries.\"},{\"question\":\"What methods are used to test whether hazards affect nightlight values?\",\"answer\":\"For each hazard, the study combines hazard-specific case studies with fixed-effect regression models akin to a double-difference approach.\"},{\"question\":\"Why do the authors conclude that researchers should be cautious with VIIRS nightlights?\",\"answer\":\"The results show little to no statistical significance across methodologies, which the authors attribute to noise in nightlight data and measurement limitations such as cloud 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