{"created":"2021-03-01T06:34:08.548426+00:00","id":28343,"links":{},"metadata":{"_buckets":{"deposit":"32a7d177-5212-474d-867e-ae7b43f45c31"},"_deposit":{"id":"28343","owners":[],"pid":{"revision_id":0,"type":"depid","value":"28343"},"status":"published"},"_oai":{"id":"oai:niigata-u.repo.nii.ac.jp:00028343","sets":["453:456","485:872:1583:1594"]},"item_7_alternative_title_1":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Examination and Accuracy Assessment in the Extraction of Bamboo Stands by Object-based Image Analysis Using Remotely Sensed Data"}]},"item_7_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2011-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"69","bibliographicPageStart":"63","bibliographicVolumeNumber":"64","bibliographic_titles":[{"bibliographic_title":"新潟大学農学部研究報告"},{"bibliographic_title":"新潟大学農学部研究報告","bibliographic_titleLang":"en"}]}]},"item_7_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"比較的空間分解能の高い衛星リモートセンシングデータであるSPOT5/HRG、ALOS/AVNIR-2、WorldView-2データを用いて、オブジェクトベース画像分析による竹林抽出を検討し、それらの精度を比較した。全てのデータはセグメンテーションによりオブジェクトに分割し、その後Nearest Neighbor 法による分類とCART モデルによる分類を実行した。その結果、SPOT 画像に対してCART モデルを用いた場合、全体精度が78.1％、竹林のProducer’s Accuracy が89.5％、User’s Accuracy が70.8％と最も高い分類精度を達成できた。既往の研究結果と同様に、短波長赤外域の存在が小面積の竹林抽出においても有効であるということが示された。","subitem_description_type":"Abstract"},{"subitem_description":"In this study, using SPOT5/HRG, ALOS/AVNIR-2, and WorldView-2 data, which are remotely sensed data withrelatively highly spatial resolution, the detection of bamboo forests by object-based image analysis was considered, and theiraccuracies were assessed. All the data were divided into objects through segmentation, and classification with the NearestNeighbor method or CART model was performed. In the results, the classification with CART model applied to SPOT/HRGimagery achieved the highest classification accuracy: overall accuracy was 78.1%, producer’s and user’s accuracy in bamboostand was 89.5% and 70.8%, respectively. The shortwave infrared wavelength mainly contributed to detecting small bamboostands as previous research has mentioned.","subitem_description_type":"Abstract"}]},"item_7_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"162934","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Matsuzawa, Shota"}]},{"nameIdentifiers":[{"nameIdentifier":"162935","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Nakagawa, Kyohei"}]},{"nameIdentifiers":[{"nameIdentifier":"162936","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Mochizuki, Shota"}]},{"nameIdentifiers":[{"nameIdentifier":"162937","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Murakami, Takuhiko"}]}]},"item_7_publisher_7":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"新潟大学農学部"}]},"item_7_select_19":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"publisher"}]},"item_7_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00183393","subitem_source_identifier_type":"NCID"}]},"item_7_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"03858634","subitem_source_identifier_type":"ISSN"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松澤, 翔太"}],"nameIdentifiers":[{"nameIdentifier":"162930","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"中川, 恭兵"}],"nameIdentifiers":[{"nameIdentifier":"162931","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"望月, 翔太"}],"nameIdentifiers":[{"nameIdentifier":"162932","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"村上, 拓彦"}],"nameIdentifiers":[{"nameIdentifier":"162933","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-08-20"}],"displaytype":"detail","filename":"64(1)_63-69.pdf","filesize":[{"value":"942.7 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"64(1)_63-69.pdf","url":"https://niigata-u.repo.nii.ac.jp/record/28343/files/64(1)_63-69.pdf"},"version_id":"62f60a2a-f5aa-4bd8-86c6-598459211dcd"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"SPOT5/HRG","subitem_subject_scheme":"Other"},{"subitem_subject":"ALOS/AVNIR-2","subitem_subject_scheme":"Other"},{"subitem_subject":"WorldView-2","subitem_subject_scheme":"Other"},{"subitem_subject":"竹林抽出","subitem_subject_scheme":"Other"},{"subitem_subject":"オブジェクトベース画像分析","subitem_subject_scheme":"Other"},{"subitem_subject":"bamboo forests","subitem_subject_scheme":"Other"},{"subitem_subject":"object-based image analysis","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":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"衛星リモートセンシングデータを用いたオブジェクトベース画像分析による竹林抽出手法の検討とその精度比較","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"衛星リモートセンシングデータを用いたオブジェクトベース画像分析による竹林抽出手法の検討とその精度比較"},{"subitem_title":"衛星リモートセンシングデータを用いたオブジェクトベース画像分析による竹林抽出手法の検討とその精度比較","subitem_title_language":"en"}]},"item_type_id":"7","owner":"1","path":["456","1594"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-07-02"},"publish_date":"2012-07-02","publish_status":"0","recid":"28343","relation_version_is_last":true,"title":["衛星リモートセンシングデータを用いたオブジェクトベース画像分析による竹林抽出手法の検討とその精度比較"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-15T03:58:21.452856+00:00"}