{"created":"2023-06-20T14:54:10.458190+00:00","id":22446,"links":{},"metadata":{"_buckets":{"deposit":"8e20ef15-eca8-400c-a315-03a7d417681d"},"_deposit":{"created_by":1,"id":"22446","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"22446"},"status":"published"},"_oai":{"id":"oai:jaxa.repo.nii.ac.jp:00022446","sets":["1887:1888"]},"author_link":["210495","210496","210497","210501","210500","210503","210504","210498","210499","210502"],"item_7_alternative_title_2":{"attribute_name":"その他のタイトル（英）","attribute_value_mlt":[{"subitem_alternative_title":"A New Method to Derive Precise Land-use and Land-cover Maps Using Multi-temporal Optical Data"}]},"item_7_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2014-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"112","bibliographicPageStart":"102","bibliographicVolumeNumber":"34","bibliographic_titles":[{"bibliographic_title":"日本リモートセンシング学会誌"},{"bibliographic_title":"Journal of The Remote Sensing Society of Japan","bibliographic_titleLang":"en"}]}]},"item_7_description_17":{"attribute_name":"抄録（英）","attribute_value_mlt":[{"subitem_description":"Here we propose an accurate and robust method for large-area land-use and land-cover (LULC) mapping using multi-temporal optical data. The conventional method for LULC classification usually uses time-series data at regular intervals to consider the seasonality of LULC. However, high-resolution optical data have considerable seasonal biases, making it difficult to use time-series data. Our basic idea for the accurate classification of LULC using high-resolution optical satellite data is to implement a classification for each scene considering seasonality first, and to then integrate multi-temporal classification results. In the per-scene classification, we accurately estimated the class-conditional spectral-seasonal densities of observation values from training data by conducting a kernel density estimation (KDE), and we used the densities in a Bayesian inference to obtain the class posterior probability. After the multi-temporal per-scene classification, we calculated the classification score by integrating class posterior probabilities in multi-temporal scenes. We conducted an 8-class classification for the entirety of Japan with 10-m spatial resolution using 1,876 scenes from the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) low-cloud-cover data, and we evaluated the accuracy of the classification by conducting a cross validation test and comparing the results to that obtained with existing methods: maximum likelihood classifier (MLC) and support vector machines (SVMs). The evaluation results showed that the overall accuracy of the proposed method is the best of all of the methods examined.","subitem_description_type":"Other"}]},"item_7_description_32":{"attribute_name":"資料番号","attribute_value_mlt":[{"subitem_description":"資料番号: PA1410087000","subitem_description_type":"Other"}]},"item_7_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本リモートセンシング学会"}]},"item_7_publisher_9":{"attribute_name":"出版者（英）","attribute_value_mlt":[{"subitem_publisher":"The Remote Sensing Society of Japan"}]},"item_7_relation_25":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"info:doi/10.11440/rssj.34.102"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://dx.doi.org/10.11440/rssj.34.102","subitem_relation_type_select":"DOI"}}]},"item_7_source_id_21":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0289-7911","subitem_source_identifier_type":"ISSN"}]},"item_7_source_id_24":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10035665","subitem_source_identifier_type":"NCID"}]},"item_7_text_6":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海道大学"},{"subitem_text_value":"北海道大学 : 宇宙航空研究開発機構(JAXA)"},{"subitem_text_value":"北海道大学"},{"subitem_text_value":"北海道大学 : 宇宙航空研究開発機構(JAXA)"},{"subitem_text_value":"北海道大学 : 宇宙航空研究開発機構(JAXA)"}]},"item_7_text_7":{"attribute_name":"著者所属（英）","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Hokkaido University"},{"subitem_text_language":"en","subitem_text_value":"Hokkaido University : Japan Aerospace Exploration Agency(JAXA)"},{"subitem_text_language":"en","subitem_text_value":"Hokkaido University"},{"subitem_text_language":"en","subitem_text_value":"Hokkaido University : Japan Aerospace Exploration Agency(JAXA)"},{"subitem_text_language":"en","subitem_text_value":"Hokkaido University : Japan Aerospace Exploration Agency(JAXA)"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"橋本, 秀太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田殿, 武雄"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小野里, 雅彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"堀, 雅裕"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"塩見, 慶"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hashimoto, Shutaro","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tadono, Takeo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Onosato, Masahiko","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hori, Masahiro","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shiomi, Kei","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"land use and land cover (LULC); multi-temporal classification; optical multispectral sensor; ALOS/AVNIR-2","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"多時期光学観測データを用いた高精度土地被覆分類手法の開発","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"多時期光学観測データを用いた高精度土地被覆分類手法の開発"}]},"item_type_id":"7","owner":"1","path":["1888"],"pubdate":{"attribute_name":"公開日","attribute_value":"2015-03-26"},"publish_date":"2015-03-26","publish_status":"0","recid":"22446","relation_version_is_last":true,"title":["多時期光学観測データを用いた高精度土地被覆分類手法の開発"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-06-21T03:21:01.509899+00:00"}