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

Sudaryatno | Zendy; Prima Widayani | Zendy; Totok Wahyu Wibowo | Zendy; Bayu Aji Sidiq Pramono | Zendy; Zulfa Nur’aini ‘Afifah | Zendy; Awit Dini Meikasari | Zendy; Muhammad Rizki Firdaus | Zendy

Open Access

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

Author(s) -

Sudaryatno,

Prima Widayani,

Totok Wahyu Wibowo,

Bayu Aji Sidiq Pramono,

Zulfa Nur’aini ‘Afifah,

Awit Dini Meikasari,

Muhammad Rizki Firdaus

Publication year - 2020

Publication title -

iop conference series earth and environmental science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.179

H-Index - 26

eISSN - 1755-1307

pISSN - 1755-1315

DOI - 10.1088/1755-1315/500/1/012046

Subject(s) - landslide , vegetation (pathology) , vulnerability (computing) , regression analysis , normalized difference vegetation index , elevation (ballistics) , variables , geology , geography , remote sensing , physical geography , hydrology (agriculture) , geomorphology , statistics , computer science , geotechnical engineering , mathematics , medicine , oceanography , geometry , computer security , pathology , climate change

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 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.

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