Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Natural Disaster Identification and Mapping of Tsunami and Earthquake in Indonesia Using Satellite Imagery Analysis (Case Study: Aceh, Palu, and Yogyakarta)

Version 1 : Received: 17 February 2022 / Approved: 21 February 2022 / Online: 21 February 2022 (10:09:18 CET)

How to cite: Jundullah, M.R.; Wijayanto, A.W. Natural Disaster Identification and Mapping of Tsunami and Earthquake in Indonesia Using Satellite Imagery Analysis (Case Study: Aceh, Palu, and Yogyakarta). Preprints 2022, 2022020250 (doi: 10.20944/preprints202202.0250.v1). Jundullah, M.R.; Wijayanto, A.W. Natural Disaster Identification and Mapping of Tsunami and Earthquake in Indonesia Using Satellite Imagery Analysis (Case Study: Aceh, Palu, and Yogyakarta). Preprints 2022, 2022020250 (doi: 10.20944/preprints202202.0250.v1).

Abstract

Remote sensing technology, especially using satellite images, has become essential support in many aspects of decision-making, particularly in disaster risk management. It requires a shorter period of data updates and less cost compared to conventional field observations and surveys. Yet, the intensive processing and high-powered computing resources are necessary to analyze satellite imagery data through Geographic Information System (GIS). In this paper, we introduce the identification and mapping of natural disaster impact in Indonesia using the open-source collaborative tool of Google Earth Engine (GEE) application which analyzes the relative temporal difference of Earth surface from three major satellite images: Sentinel-1, Sentinel-2, and Landsat-8. Taking the advantage of the geographical, geological, and demographic conditions of Indonesia's disaster-prone areas, we analyze relative difference from normalized difference vegetation index (NDVI) out of months before and after natural disaster occurrence to measure the impact of natural disaster in focus study areas. Given the high-vegetation nature of three main natural disaster impacted areas in Indonesia: Aceh, Palu, and Yogyakarta, we are able to simplify the analysis by highlighting areas with vegetative loss or gain after the event. Using an open-source GEE application, namely HazMapper, we identify and visualize the aftermath of the tsunami disaster in Aceh and Palu as well as the earthquake in Yogyakarta. Our study is potentially beneficial for government and decision-makers to utilize publicly available satellite images for disaster recovery and mitigation policy.

Supplementary and Associated Material

https://s.id/IndonesiaDisasterMapping: Indonesia Disaster Mapping Apps

Keywords

satellite images; disaster mapping; GIS

Subject

EARTH SCIENCES, Geoinformatics

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