{"id":7102,"date":"2022-09-19T19:55:20","date_gmt":"2022-09-19T19:55:20","guid":{"rendered":"https:\/\/oceanopticsconference.org\/?page_id=7102"},"modified":"2022-09-27T16:56:06","modified_gmt":"2022-09-27T16:56:06","slug":"poster-dinh","status":"publish","type":"page","link":"https:\/\/oceanopticsconference.org\/poster-dinh\/","title":{"rendered":"Poster: Dinh"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.16&#8243; background_image=&#8221;https:\/\/oceanopticsconference.org\/wp-content\/uploads\/2022\/01\/oo22-banner-bckd.jpg&#8221; background_position=&#8221;bottom_left&#8221; custom_padding=&#8221;54px||54px||true|&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;4.16&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_padding=&#8221;||22px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;header&#8221; _builder_version=&#8221;4.18.0&#8243; header_font=&#8221;|||on|||||&#8221; header_text_color=&#8221;#FFFFFF&#8221; header_font_size=&#8221;42px&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h1>Posters<\/h1>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.18.0&#8243; custom_padding=&#8221;||44px|||&#8221; border_width_top=&#8221;2px&#8221; border_color_top=&#8221;#e8e8e8&#8243; border_width_bottom=&#8221;2px&#8221; border_color_bottom=&#8221;#e8e8e8&#8243; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.17.4&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_padding=&#8221;2px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;Extended abstracts&#8221; _builder_version=&#8221;4.18.0&#8243; text_font=&#8221;|||on|||||&#8221; link_font=&#8221;||||on||||&#8221; header_3_font=&#8221;|800|||||||&#8221; header_3_text_color=&#8221;#057184&#8243; header_3_font_size=&#8221;20px&#8221; header_3_line_height=&#8221;1.3em&#8221; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;7px||2px|||&#8221; custom_padding=&#8221;||31px|||&#8221; use_border_color=&#8221;off&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221; link_text_color__hover=&#8221;#a5a5a5&#8243; link_text_color__hover_enabled=&#8221;on|hover&#8221;]<\/p>\n<p class=\"p1\"><a href=\"\/poster2\/\">Poster Session 2<\/a>, Tuesday,\u00a0 October\u00a0 4, 10:40\u201312:40<\/p>\n<p>[\/et_pb_text][et_pb_text admin_label=&#8221;Extended abstracts&#8221; _builder_version=&#8221;4.18.0&#8243; link_font=&#8221;||||on||||&#8221; header_3_font=&#8221;|800||on|||||&#8221; header_3_text_color=&#8221;#057184&#8243; header_3_font_size=&#8221;20px&#8221; header_3_line_height=&#8221;1.2em&#8221; header_5_font=&#8221;|||on|||||&#8221; header_5_text_color=&#8221;#545454&#8243; header_5_font_size=&#8221;17px&#8221; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;7px||15px|||&#8221; use_border_color=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221; link_text_color__hover=&#8221;#a5a5a5&#8243; link_text_color__hover_enabled=&#8221;on|hover&#8221;]<\/p>\n<h5>Poster 24<\/h5>\n<h3>Modification of WiPE (WiPE-2) for Land use\/Land cover mapping based on combination of statistical of spectral and unsupervised classification: An application to VNREDSat-1 satellite image<\/h3>\n<p>[\/et_pb_text][et_pb_text admin_label=&#8221;Extended abstracts&#8221; _builder_version=&#8221;4.18.0&#8243; link_font=&#8221;||||on||||&#8221; header_3_font=&#8221;|800||on|||||&#8221; header_3_text_color=&#8221;#057184&#8243; header_3_font_size=&#8221;20px&#8221; header_3_line_height=&#8221;1.2em&#8221; header_5_font=&#8221;|||on|||||&#8221; header_5_font_size=&#8221;17px&#8221; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;7px|||||&#8221; use_border_color=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221; link_text_color__hover=&#8221;#a5a5a5&#8243; link_text_color__hover_enabled=&#8221;on|hover&#8221;]<\/p>\n<p>Land use\/Land cover (LULC) map is a necessary product for intensive thematic studies such as water, forest, land cover change, etc. WiPE was developed to extract only natural water pixels that a lot of contaminated water pixels with land pixels are masked. The identification of contaminated water pixels is essential to propose restoration solutions for improving the water surface information from the satellite image. Spectral shape analysis performs well in WiPE algorithm but it difficult to separate contaminated water pixels (sunglint, whitecaps, etc.) with other objects such as thin cloud, sand etc. To avoid the difficulty in classifying each pixel when the spectral amplitude of each noise object region on each scene is quite wide, the classification technique will help group these regions to form a base feature in the form of regions. Unsupervised classification, K-Mean, is effective when grouping pixels in areas of water, vegetation, and bare land, but it is difficult to create pixel regions in residential areas. Quickshift segmentation is a technique of clustering pixels by defining the kernel size and spectral difference in that block and this is the solution for grouping pixels in a residential area. Zonal statistic (min, max, mean, median, standard deviation) for each Rayleigh corrected spectral band at each classified group pixels is used as spectral analysis in WiPE algorithm. New algorithm of WiPE is validated in independent dataset and manual checking based on Google map.<\/p>\n<p><a href=\"mailto:dndat@sti.vast.vn\"><strong>Dat Dinh Ngoc<\/strong><\/a>, dndat@sti.vast.vn, Space Technology Institute, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay, Hanoi, Vietnam<\/p>\n<p>Duong Dang Nguyen Hien, duongdnh.m21sa@st.usth.edu.vn, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay, Hanoi, Vietnam<\/p>\n<p>Hubert Loisel, hubert.loisel@univ-littoral.fr, Laboratoire d&#8217;Oc\u00e9anologie et de G\u00e9osciences, Universit\u00e9 du Littoral-C\u00f4te-d&#8217;Opale, Universit\u00e9 Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France<\/p>\n<p>C\u00e9dric Jamet, cedric.jamet@univ-littoral.fr, Laboratoire d&#8217;Oc\u00e9anologie et de G\u00e9osciences, Universit\u00e9 du Littoral-C\u00f4te-d&#8217;Opale, Universit\u00e9 Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France<\/p>\n<p>Vincent Vantrepotte, vincent.vantrepotte@univ-littoral.fr, Laboratoire d&#8217;Oc\u00e9anologie et de G\u00e9osciences, Universit\u00e9 du Littoral-C\u00f4te-d&#8217;Opale, Universit\u00e9 Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France<\/p>\n<p>Lucile Dufor\u00eat-Gaurier, lucile.duforet@univ-littoral.fr, Laboratoire d&#8217;Oc\u00e9anologie et de G\u00e9osciences, Universit\u00e9 du Littoral-C\u00f4te-d&#8217;Opale, Universit\u00e9 Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France<\/p>\n<p>Chung Doan Minh, dmchung@sti.vast.vn, Space Technology Institute, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay, Hanoi, Vietnam<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; 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