Classification of limestone mining site using multi-sensor remote sensing data and OBIA approach: A case study: Biak Island, Papua

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Most of Soil Type in Biak Island, Papua is Coral Limestone. This limestone is used as building material. Limestone mining is one of the income sources for local people. This study tries to map limestone mining sites using multi-sensor remote sensing data fusion and Object-Based Image Analysis (OBIA) classification approach. 1.5 meters resolution SPOT-6 data acquired in 2015 and 2017 used as spectral and geometric parameters in OBIA classification process. Surface deformation points obtained from the PS-InSAR technique on Sentinel-IA SLC SAR data acquired from November 2017 to May 2018 is used as the structural variable for OBIA classification process to determine whether mining site is active or inactive. The overall accuracy of classification result is 84.7% for 2015 SPOT-6 data and 74.9% for 2017 SPOT-6 data.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages417-422
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 17 Jan 2019
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
CountryIndonesia
CityYogyakarta
Period27/10/1828/10/18

Keywords

  • Biak
  • Coral limestone
  • Data-fusion
  • Mining
  • OBIA
  • Papua
  • Remote sensing
  • SAR-interferometry
  • Sentinel-IA
  • SPOT-6

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