{"_buckets": {"deposit": "8d34d497-4e39-4b66-a29d-a13a6d33d002"}, "_deposit": {"id": "4726", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "4726"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00004726", "sets": []}, "author_link": [], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-03", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "1", "bibliographicPageEnd": "82", "bibliographicPageStart": "75", "bibliographicVolumeNumber": "4", "bibliographic_titles": [{"bibliographic_title": "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "A new method has been developed to automatically extract moving vehicles and subsequently determine their speeds from a pair of QuickBird (QB) panchromatic (PAN) and multispectral (MS) images. Since the PAN and MS sensors of QB have a slight time lag (approximately 0.2 s), the speed of a moving vehicle can be determined from the difference in the positions of the vehicle observed in the PAN and MS images due to the time lag. An object-based approach can be used to extract a vehicle from the PAN image, which has a resolution of 0.6 m. However, it is difficult to accurately extract the position of a vehicle from an MS image because its resolution is 2.4 m. Thus, an area correlation method is proposed to determine the location of a vehicle from an MS image at a sub-pixel level. The speed of the moving vehicle can then be calculated by using the vehicle extraction results. This approach was tested on several parts of a QB image covering central Tokyo, Japan, and the accuracy of the results is demonstrated in this study. c 2011, IEEE. All rights reserved.", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.1109/JSTARS.2010.2069555"}}]}, "item_10001_source_id_9": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "2151-1535", "subitem_source_identifier_type": "EISSN"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Wen Liu", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Fumio Yamazaki", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Tuong Thuy Vu", "creatorNameLang": "en"}]}]}, "item_title": "Automated Vehicle Extraction and Speed Determination From QuickBird Satellite Images", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Automated Vehicle Extraction and Speed Determination From QuickBird Satellite Images", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "1", "path": ["1670839190650"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/4726", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-03-30"}, "publish_date": "2023-03-30", "publish_status": "0", "recid": "4726", "relation": {}, "relation_version_is_last": true, "title": ["Automated Vehicle Extraction and Speed Determination From QuickBird Satellite Images"], "weko_shared_id": -1}