Calculation of the number of peaks in the Gunung Sewu area using DEMNAS, focal maximum function and slope position classification method

Sutanta, H. and Tiera, A. (2019) Calculation of the number of peaks in the Gunung Sewu area using DEMNAS, focal maximum function and slope position classification method. In: IOP Conference Series: Earth and Environmental Science, 2019.

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Abstract

Thousand Hills (Gunung Sewu) is a karst area in the southern Java island, stretches 85 km east to west covering around 1,300 km<sup>2</sup> and formed by thousands of conical hills. This research aims to calculate the number of peaks in the Gunung Sewu area using focal maximum function and slope position classification. The data for the calculation was the Indonesian national DEM (DEMNAS). It was used in its original spatial resolution at 8.25 m, and the resampled version at 10 m and 16.5 m. The processing consists of detection of peaks, selection of top of hills, and evaluation. Twenty four combinations of window types and size and spatial resolution of DEMNAS were evaluated. The accuracy of the calculation was assessed using ten test areas with 1,576 hills digitized manually. The best function to detect the peaks is a rectangle type window with a width of three pixels with a spatial resolution at 8.25 m. Types of hills can be identified: Conical and polygonal hills. The calculation found that there are 27,773 regional peaks, or hills, in the Thousand Hills area. The results were tested using a confusion matrix with overall accuracy is 86.2.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Library Dosen
Uncontrolled Keywords: Surveying; Best function; Classification methods; Confusion matrices; Karst areas; Overall accuracies; Slope positions; Spatial resolution; Image resolution
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
Divisions: Faculty of Engineering > Geodetic Engineering Department
Depositing User: Sri JUNANDI
Date Deposited: 29 Jun 2026 01:45
Last Modified: 29 Jun 2026 01:45
URI: https://ir.lib.ugm.ac.id/id/eprint/26643

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