Vegetation indices’ spatial prediction based novel algorithm for determining tsunami risk areas and risk values

PeerJ Computer Science

Yessica Nataliani¹  Kristoko Dwi Hartomo¹  Zainal Arifin Hasibuan² 

[1] Department of Information System, Faculty of Information Technology, Satya Wacana Christian University, Salatiga, Indonesia;Faculty of Computer Science, University of Dian Nuswantoro, Semarang, Indonesia;

关键词: Tsunami;    Spatial;    Vegetation index;    Risk areas;    Risk values;   

DOI  :  10.7717/peerj-cs.935

来源: DOAJ

【 摘 要 】

This paper aims to propose a new algorithm to detect tsunami risk areas based on spatial modeling of vegetation indices and a prediction model to calculate the tsunami risk value. It employs atmospheric correction using DOS1 algorithm combined with k-NN algorithm to classify and predict tsunami-affected areas from vegetation indices data that have spatial and temporal resolutions. Meanwhile, the model uses the vegetation indices (i.e., NDWI, NDVI, SAVI), slope, and distance. The result of the experiment compared to other classification algorithms demonstrates good results for the proposed model. It has the smallest MSEs of 0.0002 for MNDWI, 0.0002 for SAVI, 0.0006 for NDVI, 0.0003 for NDWI, and 0.0003 for NDBI. The experiment also shows that the accuracy rate for the prediction model is about 93.62%.

【 授权许可】

Unknown