{"_buckets": {"deposit": "29cef3fa-d00d-4418-acf8-01ef8ff8e2db"}, "_deposit": {"id": "28819", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "28819"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00028819"}, "item_10_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2018-05-10", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "87", "bibliographicPageStart": "83", "bibliographicVolumeNumber": "66", "bibliographic_titles": [{"bibliographic_title": "\u4e2d\u90e8\u68ee\u6797\u7814\u7a76"}]}]}, "item_10_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "In order to monitor changes of tree areas after the 2004 tsunami, the aptitude of the pixel based and the object based image analysis for Google Earth images were compared. Satellite images, which taken in 2004, 2009 and 2013, were downloaded from Google Earth Pro as maximum resolution. They were georeferenced based on a topographic map. The land cover/use was classified to 9 classes by the pixel based and the object based image analysis with supervised learning. The overall accuracy by the pixel based image analysis was 0.65-0.71. By the object based image analysis, it was 0.65-0.71. Although tree areas were misclassified to paddy field, ponds and grassland by methods, user\u2019s and producer\u2019s accuracy by the object based image analysis were higher accuracy than the pixel based.", "subitem_description_type": "Abstract"}]}, "item_10_identifier_registration": {"attribute_name": "ID\u767b\u9332", "attribute_value_mlt": [{"subitem_identifier_reg_text": "10.18999/chufr.66.83", "subitem_identifier_reg_type": "JaLC"}]}, "item_10_publisher_32": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "\u4e2d\u90e8\u68ee\u6797\u5b66\u4f1a\u4e8b\u52d9\u5c40"}]}, "item_10_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_61": {"attribute_name": "ISSN\uff08print\uff09", "attribute_value_mlt": [{"subitem_source_identifier": "1342-971X", "subitem_source_identifier_type": "ISSN"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "ARIEF, Mochamad Candra Wirawan"}], "nameIdentifiers": [{"nameIdentifier": "94798", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "ITAYA, Akemi"}], "nameIdentifiers": [{"nameIdentifier": "94799", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2019-12-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "chufr_66_83.pdf", "filesize": [{"value": "855.3 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 855300.0, "url": {"label": "chufr_66_83.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/28819/files/chufr_66_83.pdf"}, "version_id": "c43f8b6a-1547-4408-92c6-4a15d45979f1"}]}, "item_keyword": {"attribute_name": "\u30ad\u30fc\u30ef\u30fc\u30c9", "attribute_value_mlt": [{"subitem_subject": "Classification", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Land cover/use", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Monitoring", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Recovery", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Supervised learning", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Detection of tree areas using Google Earth images in Banda Aceh Indonesia : Comparison between the pixel based and the object based image analysis", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Detection of tree areas using Google Earth images in Banda Aceh Indonesia : Comparison between the pixel based and the object based image analysis"}]}, "item_type_id": "10", "owner": "1", "path": ["2113/2449/2450/2451"], "permalink_uri": "https://doi.org/10.18999/chufr.66.83", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2019-12-19"}, "publish_date": "2019-12-19", "publish_status": "0", "recid": "28819", "relation": {}, "relation_version_is_last": true, "title": ["Detection of tree areas using Google Earth images in Banda Aceh Indonesia : Comparison between the pixel based and the object based image analysis"], "weko_shared_id": null}