{"id":1947,"date":"2021-01-02T07:55:14","date_gmt":"2021-01-02T00:55:14","guid":{"rendered":"http:\/\/research.binus.ac.id\/airdc\/?p=1947"},"modified":"2021-09-01T12:31:52","modified_gmt":"2021-09-01T05:31:52","slug":"supervised-conversion-from-landsat-8-images-to-sentinel-2-images-with-deep-learning","status":"publish","type":"post","link":"https:\/\/research.binus.ac.id\/airdc\/2021\/01\/supervised-conversion-from-landsat-8-images-to-sentinel-2-images-with-deep-learning\/","title":{"rendered":"Supervised Conversion from Landsat-8 Images to Sentinel-2 Images with Deep Learning"},"content":{"rendered":"<p style=\"text-align: justify\">In a specific remote sensing study design, the utilization of images from a particular satellite is necessary. However, the images might be unavailable in a certain time range. Therefore, a conversion method from available remote sensing images at the time range is required. In this paper, we proposed machine learning models that are capable to convert Landsat-8 images to Sentinel-2 images. The models are inspired by the advancement of super-resolution model based on Deep learning. The result of this study shows that the proposed models can predict Sentinel-2 images which are quantitatively and qualitatively similar to the original images.<\/p>\n<p>European Journal of Remote Sensing<\/p>\n<p><strong>Sani M. Isa, Suharjito, Gede Putera Kusuma, Tjeng Wawan Cenggoro<\/strong><\/p>\n<p><a href=\"https:\/\/www.researchgate.net\/publication\/350346788_Supervised_conversion_from_Landsat-8_images_to_Sentinel-2_images_with_deep_learning\">Read Full Paper<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In a specific remote sensing study design, the utilization of images from a particular satellite is necessary. However, the images might be unavailable in a certain time range. Therefore, a conversion method from available remote sensing images at the time range is required. In this paper, we proposed machine learning models that are capable to [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":2013,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1947","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications"],"_links":{"self":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1947","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/comments?post=1947"}],"version-history":[{"count":1,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1947\/revisions"}],"predecessor-version":[{"id":1949,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1947\/revisions\/1949"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/media\/2013"}],"wp:attachment":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/media?parent=1947"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/categories?post=1947"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/tags?post=1947"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}