Multiple linear regression analysis of remote sensing data for determining vulnerability factors of landslide in PURWOREJO

  • Purworejo is one of the potential area that could be experiencing landslides, because the geomorphological conditions which are included in Menoreh Hills are geographically sloping to very steep. Based on the Indonesian Disaster Information Data (DIBI) and the National Disaster Management Agency (BNPB) in the last five years from 2014 to April 2019 there have been 64 landslides in Purworejo. The research on landslide vulnerability mapping has been done with various spatial modeling methods, one of them is using Information Value Model (IVM). There are four landslide factors arranging the model, such as elevation, slope, slope direction and vegetation index (NDVI). The purpose of this research is to determine the most influence factors towards landslide vulnerability levels thorugh remote sensing data. Multiple regression analysis is used to determine the most influential factors. In this research, dependent variable represented by eight landslide factors, and the independent variablePurworejo is one of the potential area that could be experiencing landslides, because the geomorphological conditions which are included in Menoreh Hills are geographically sloping to very steep. Based on the Indonesian Disaster Information Data (DIBI) and the National Disaster Management Agency (BNPB) in the last five years from 2014 to April 2019 there have been 64 landslides in Purworejo. The research on landslide vulnerability mapping has been done with various spatial modeling methods, one of them is using Information Value Model (IVM). There are four landslide factors arranging the model, such as elevation, slope, slope direction and vegetation index (NDVI). The purpose of this research is to determine the most influence factors towards landslide vulnerability levels thorugh remote sensing data. Multiple regression analysis is used to determine the most influential factors. In this research, dependent variable represented by eight landslide factors, and the independent variable is vurnerability level of landslide in Purworejo. The results of this study explain that the predictor variables that most influence the occurrence of landslides in Purworejo are elevations with regression values that are quite dominant among other variables.show moreshow less

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Metadaten
Author: Sudaryatno, Prima Widayani, Totok Wahyu Wibowo, Bayu Aji Sidiq Pramono, Zulfa Nur'aini AfifahORCiDGND, Awit Dini Meikasari, Muhammad Rizki Firdaus
URN:urn:nbn:de:bvb:384-opus4-1114862
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/111486
ISSN:1755-1307OPAC
ISSN:1755-1315OPAC
Parent Title (English):IOP Conference Series: Earth and Environmental Science
Publisher:IOP Publishing
Type:Article
Language:English
Year of first Publication:2020
Publishing Institution:Universität Augsburg
Release Date:2024/02/20
Volume:500
Issue:1
First Page:012046
Note:
The Fifth International Conferences of Indonesian Society for Remote Sensing 17-20 September 2019, West Java, Indonesia
DOI:https://doi.org/10.1088/1755-1315/500/1/012046
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Geographie
Fakultät für Angewandte Informatik / Institut für Geographie / Professur für Angewandte Geoinformatik
Dewey Decimal Classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Licence (German):CC-BY 3.0: Creative Commons - Namensnennung (mit Print on Demand)