<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ridha, Syafiq Muhammad</style></author><author><style face="normal" font="default" size="100%">Kamal, Muhammad</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An object-based approach for vegetation and non-vegetation discrimination using WorldView-2 image</style></title><secondary-title><style face="normal" font="default" size="100%">Seventh Geoinformation Science Symposium 2021</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12082/120820U/An-object-based-approach-for-vegetation-and-non-vegetation-discrimination/10.1117/12.2619373.short?SSO=1</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">SPIE</style></publisher><volume><style face="normal" font="default" size="100%">12082</style></volume><pages><style face="normal" font="default" size="100%">295-301</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;table id=&quot;UsageTable0&quot;&gt;
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					The emergence of remote sensing images with high spatial resolution has increased the advancement of image-based information extraction methods. One of the rapidly developing approaches for mapping and analyzing high spatial resolution images is the object-based approach, also known as geographic object-based image analysis (GEOBIA). This development makes it possible to quickly and accurately distinguish between vegetated and non-vegetated objects in vegetation study. This study aims to (1) create a ruleset to discriminate vegetated and non-vegetated objects from a high spatial resolution image, (2) apply the GEOBIA approach to map vegetated and non-vegetated objects, and (3) calculate the accuracy of the mapping results. The GEOBIA approach was applied to a WorldView-2 image (2 m pixel size and eight multispectral bands) of the Clungup Mangrove Conservation area, Malang, East Java, Indonesia. We assessed the ability of all of the WorldView-2 image bands for discriminating the targeted objects. The segmentation process in GEOBIA used a multi-resolution segmentation algorithm using the normalized difference vegetation index (NDVI), and the image classification used a rule-based classification technique. The green, red, and near-infrared bands can effectively distinguish the targeted objects based on the developed ruleset. The classification result shows that the vegetated and non-vegetated classes fall within their corresponding objects on the image. We implemented an area-based accuracy assessment that assesses both positional and thematic accuracy of the mapping result, based on the visual interpretation of the pansharpened WV-2 image (0.5 m pixel size) as a reference for the accuracy assessment. This process results in a 74,06% accuracy, meaning that the combination of GEOBIA and WorldView-2 image produces high accuracy of vegetated and non-vegetated objects map.
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