{"created":"2023-03-31T02:09:23.711701+00:00","id":4980,"links":{},"metadata":{"_buckets":{"deposit":"6942011f-6d5f-4247-a92c-87e282285152"},"_deposit":{"id":"4980","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"4980"},"status":"published"},"_oai":{"id":"oai:nied-repo.bosai.go.jp:00004980","sets":[]},"author_link":[],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019-07","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicPageEnd":"1114","bibliographicPageStart":"1097","bibliographicVolumeNumber":"46","bibliographic_titles":[{"bibliographic_title":"ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as \"built-up area\"), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient (R-2) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"SAGE PUBLICATIONS LTD","subitem_publisher_language":"en"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1177/2399808317752926"}}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2399-8091","subitem_source_identifier_type":"EISSN"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hasi Bagan","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Habura Borjigin","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yoshiki Yamagata","creatorNameLang":"en"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_title":"Assessing nighttime lights for mapping the urban areas of 50 cities across the globe","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Assessing nighttime lights for mapping the urban areas of 50 cities across the globe","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"1","path":["1670839190650"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-03-30"},"publish_date":"2023-03-30","publish_status":"0","recid":"4980","relation_version_is_last":true,"title":["Assessing nighttime lights for mapping the urban areas of 50 cities across the globe"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-06-08T06:13:48.109448+00:00"}