A COMPARISON OF OBJECT-BASED AND PIXEL-BASED APPROACHES FOR LAND USE/LAND COVER CLASSIFICATION USING LAPAN-A2 MICROSATELLITE DATA

Authors

  • Jalu Tejo Nugroho Remote Sensing Applications Center, LAPAN Jl. Kalisari No.8 Kelurahan Pekayon Kecamatan Pasar Rebo Jakarta Timur
  • Zylshal Remote Sensing Applications Center, LAPAN Jl. Kalisari No.8 Kelurahan Pekayon Kecamatan Pasar Rebo Jakarta Timur
  • Nurwita Mustika Sari Remote Sensing Applications Center, LAPAN Jl. Kalisari No.8 Kelurahan Pekayon Kecamatan Pasar Rebo Jakarta Timur
  • Dony Kushardono Remote Sensing Applications Center, LAPAN Jl. Kalisari No.8 Kelurahan Pekayon Kecamatan Pasar Rebo Jakarta Timur

DOI:

https://doi.org/10.30536/j.ijreses.2017.v14.a2680

Keywords:

LAPAN-A2 microsatellite, LU/LC, object-based, pixel-based

Abstract

In recent years, small satellite industry has been a rapid trend and become important especially when associated with operational cost, technology adaptation and the missions. One mission of LAPAN-A2, the 2nd generation of microsatellite that developed by Indonesian National Institute of Aeronautics and Space (LAPAN), is Earth observation using digital camera that provides imagery with 3.5 m spatial resolution. The aim of this research is to compare between object-based and pixel-based classification of land use/land cover (LU/LC) in order to determine the appropriate classification method in LAPAN-A2 dataprocessing (case study Semarang, Central Java).The LU/LC were classified into eleven classes, as follows: sea, river, fish pond, tree, grass, road, building 1, building 2, building 3, building 4 and rice field. The accuracy of classification outputs were assessed using confusion matrix. The object-based and pixel-based classification methods result for overall accuracy are 31.63% and 61.61%, respectively. According to accuracy result, it was thought that blurring effect on LAPAN-A2 data may be the main cause ofaccuracy decrease. Furthermore, the result is suggested to use pixel-based classification to be applied inLAPAN-A2 data processing.

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Published

2025-11-26

Issue

Vol. 14 No. 1 (2017)

Section

Articles

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