WEKO3
アイテム
{"_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": ["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_20": {"attribute_name": "その他キーワード", "attribute_value_mlt": [{"subitem_text_value": "資料請求非対応"}]}, "item_7_text_35": {"attribute_name": "JAXAカテゴリ", "attribute_value_mlt": [{"subitem_text_value": "JAXAカテゴリ: 学術雑誌論文"}]}, "item_7_text_36": {"attribute_name": "JAXAカテゴリ2", "attribute_value_mlt": [{"subitem_text_value": "JAXAカテゴリ2: AS"}]}, "item_7_text_43": {"attribute_name": "DSpaceコレクション番号", "attribute_value_mlt": [{"subitem_text_value": "DSpaceコレクション番号: 8"}]}, "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": [{"nameIdentifier": "210495", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "田殿, 武雄"}], "nameIdentifiers": [{"nameIdentifier": "210496", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "小野里, 雅彦"}], "nameIdentifiers": [{"nameIdentifier": "210497", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "堀, 雅裕"}], "nameIdentifiers": [{"nameIdentifier": "210498", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "塩見, 慶"}], "nameIdentifiers": [{"nameIdentifier": "210499", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Hashimoto, Shutaro", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "210500", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Tadono, Takeo", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "210501", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Onosato, Masahiko", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "210502", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Hori, Masahiro", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "210503", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Shiomi, Kei", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "210504", "nameIdentifierScheme": "WEKO"}]}]}, "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"], "permalink_uri": "https://jaxa.repo.nii.ac.jp/records/22446", "pubdate": {"attribute_name": "公開日", "attribute_value": "2015-03-26"}, "publish_date": "2015-03-26", "publish_status": "0", "recid": "22446", "relation": {}, "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_shared_id": -1}
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
https://jaxa.repo.nii.ac.jp/records/22446
https://jaxa.repo.nii.ac.jp/records/22446cdfed90f-7f92-4417-8bbe-8228fde6efa5
Item type | 学術雑誌論文 / Journal Article(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2015-03-26 | |||||
タイトル | ||||||
タイトル | 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 | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | land use and land cover (LULC); multi-temporal classification; optical multispectral sensor; ALOS/AVNIR-2 | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
その他のタイトル(英) | ||||||
その他のタイトル | A New Method to Derive Precise Land-use and Land-cover Maps Using Multi-temporal Optical Data | |||||
著者 |
橋本, 秀太郎
× 橋本, 秀太郎× 田殿, 武雄× 小野里, 雅彦× 堀, 雅裕× 塩見, 慶× Hashimoto, Shutaro× Tadono, Takeo× Onosato, Masahiko× Hori, Masahiro× Shiomi, Kei |
|||||
著者所属 | ||||||
北海道大学 | ||||||
著者所属 | ||||||
北海道大学 : 宇宙航空研究開発機構(JAXA) | ||||||
著者所属 | ||||||
北海道大学 | ||||||
著者所属 | ||||||
北海道大学 : 宇宙航空研究開発機構(JAXA) | ||||||
著者所属 | ||||||
北海道大学 : 宇宙航空研究開発機構(JAXA) | ||||||
著者所属(英) | ||||||
en | ||||||
Hokkaido University | ||||||
著者所属(英) | ||||||
en | ||||||
Hokkaido University : Japan Aerospace Exploration Agency(JAXA) | ||||||
著者所属(英) | ||||||
en | ||||||
Hokkaido University | ||||||
著者所属(英) | ||||||
en | ||||||
Hokkaido University : Japan Aerospace Exploration Agency(JAXA) | ||||||
著者所属(英) | ||||||
en | ||||||
Hokkaido University : Japan Aerospace Exploration Agency(JAXA) | ||||||
出版者 | ||||||
出版者 | 日本リモートセンシング学会 | |||||
出版者(英) | ||||||
出版者 | The Remote Sensing Society of Japan | |||||
書誌情報 |
日本リモートセンシング学会誌 en : Journal of The Remote Sensing Society of Japan 巻 34, 号 2, p. 102-112, 発行日 2014-10 |
|||||
抄録(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | 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. | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0289-7911 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AN10035665 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | http://dx.doi.org/10.11440/rssj.34.102 | |||||
関連名称 | info:doi/10.11440/rssj.34.102 | |||||
資料番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 資料番号: PA1410087000 |