Investigation of Landslide and Flood Disasters by Using the Geographic Information System in Trenggalek

M. S. Purwanto*, Amelia Rosana Putri, Amien Widodo, Ulfa Ianati Sari

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Trenggalek Regency is an area that often experiences natural disasters, namely floods and landslides. Based on this, research was carried out, namely mapping flood and landslide-prone areas in each sub-district in Trenggalek Regency using a Remote Sensing and Geographic Information System (GIS). The data used to process flood-prone map and landslides-prone map is secondary data obtained from DEM data, soil type maps, BMKG Shapefile Ina-Geoportal data, Google Earth imagery, and Trenggalek Regency BPS data. The secondary data will be processed using ArcGis 10.7 software and produced parameter data for making flood-prone map and landslides-prone in slope, soil type, rainfall, land use, and exposed population in Trenggalek Regency. The parameter data will be used for classification, scoring, and overlay to produce a flood-prone map and landslides-prone map. The flood-prone map shows six districts with a high level of flood vulnerability, namely Tugu, Karangan, Trenggalek, Pogalan, Gandusari, and a small part of Kampak. In contrast, other districts have a moderate level of vulnerability. On the landslide-prone map, it is known that there are three sub-districts with a high level of landslide vulnerability, namely Trenggalek, Watulimo, and Panggul. In contrast, other sub-districts have an average level of landslide vulnerability. From the processing results, it can be concluded that sub-districts with a high population will be more prone to floods or landslides.

Original languageEnglish
Article number080003
JournalAIP Conference Proceedings
Volume3076
Issue number1
DOIs
Publication statusPublished - 5 Jun 2024
Event1st International Conference on Upstream Energy Technology and Digitalization, ICUPERTAIN 2022 - Jakarta, Indonesia
Duration: 6 Dec 20227 Dec 2022

Keywords

  • GIS
  • flood
  • landslide
  • mitigation disaster
  • remote sensing

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