COMPARISON OF KRIGING AND INVERSE DISTANCE WEIGHTED (IDW) INTERPOLATION METHODS IN LINEAMENT EXTRACTION AND ANALYSIS

https://doi.org/10.22146/jag.7204

Agung Setianto(1*), Tamia Triandini(2)

(1) Geological Engineering Department, Faculty of Engineering, Universitas Gadjah Mada
(2) Civil and Environmental Engineering, Ehime University, Matsuyama, Japan
(*) Corresponding Author

Abstract


Analysis that is based on geostatistics eliminates many corresponding defects and limitations compared to classical statistics which have been developed by random distribution theory of processes and variables. Interpolation is important for local analysis by GIS, because many maps used for GIS operation are made by interpolation. In this research, two different methods which is Kriging method and Inverse Distance Weighted (IDW) method was examined for developing Digital Elevation Model image. Each method’s advantages and disadvantages were considered. The study are, Kepil, is within Kulon Progo physiographic and stratigraphic area, located in the western part of Yogyakarta city. This area is located close to the Java Island Subduction Zone, hence influence of tectonic plate movement is relatively dominant. Geological structures become a main factor that shapes the recent morphology. This study area also has many settlements and has high weathering and erosion rate. Lineaments are extracted based on Digital Elevation Model to provide assistance in delineating geological structures. The structural geology analysis and an understanding of tectonic phase of the area provide useful information for geological map- ping. Accuracy of lineament depends on extraction and imagery parameters used. In this study, the extraction was conducted by two different raster methods, namely Kriging and Inverse Distance Weighted (IDW) with the same resolution of 30 meters. Lineament extracted automatically (digitally) with certain parameter settings. Keywords: Kriging, inverse distance weighted, interpolation, lineament, random distribution, digital elevation model.

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DOI: https://doi.org/10.22146/jag.7204

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