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All Journal International Journal of Remote Sensing and Earth Sciences (IJReSES)
Akmal Hafiudzan
Cartography and Remote Sensing Undergraduate Program, Faculty of Geography, Universitas Gadjah Mada
Earth & Planetary Sciences

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RESIDENTIAL CLASSIFICATION USING GEOBIA IN PART OF JAKARTA SUBURBAN AREA Akmal Hafiudzan; Prima Widayani; Nurwita Mustika Sari
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 20, No 2 (2023)
Publisher : Ikatan Geografi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3862

Abstract

The increasing of urban population followed by socioeconomic problems leads to emerging various number of researchs in urban area, especially in Jakarta Metropolitan Area. One of them are escalated tension-conflict due to rise of newly Gated Communities residential that sprawl across local residents (Kampung Kota). There is urgency to map all 3 types of residential (Kampung Kota, Perumnas, Cluster) through satellite imagery on a wide-scale. This study uses WorldView-2 imagery data recorded for 2020. The method used is an object-based method, namely GEOBIA using the eCognition Developer 64 software. The GEOBIA process is carried out through three stages, firstly the segmentation to separate residential blocks from surrounding land cover objects (bodies of water, vegetation, open land, non-residential built-up land) as well as exploring the variable values of each object, then sample-based classification using the SVM algorithm on Google Earth Engine application, and accuracy test to evaluate semantic and geometric accuracy levels. The results of the mapping are 3 classes of residential types followed by 4 classes of land cover. The overall accuracy of the three types of residential is 80% which means that the GEOBIA approach is able to show good performance.
Co-Authors Nurwita Mustika Sari Prima Widayani