Vertical Accuracy Assessment for SRTM V.4 and Aster Global Digital Elevation Models V.2: A Case Study of Padang Regency, West Sumatera

Abstract

<p>Digital elevation model (DEM) is an important element used to represent surface of The Earth. Generally, DEM has been utilized in many geographic science, for instance cartography, hydrology, geology, and remote sensing. It has been widely used since the advanced of technology in remote sensing. This research concerned to assess the vertical accuracy of SRTM v.4 and ASTER GDEM v.2. Topographic or also known as RBI map of Padang City, West Sumatera which has scale 1:10.000 was used as a reference map. RBI has 2.5 m vertical accuracy and 0.5 mm horizontal accuracy. Moreover, to gain the bias value, root mean square errors (RMSE) assessment was used to calculate the different value between them. Point height would be obtained through sampling method based on the distribution of land-use, slope, and relief. Land-use was classified digitally using maximum likelihood method from SPOT 6 imagery, slope and relief that were derived based on the reference map. Vertical accuracy assessment for both DEM was necessary in order to know the bias elevation prior to using them in a research or project. Assessment of DEM vertical accuracy also could help to generate contour in global region which should be used after the bias vertical was applied.</p>Keywords: SRTM v.2, ASTER GDEM v.2, DEM Generation, Accuracy Assessment, RBI Map

Enhancing Digital Elevation Model Accuracy for Flood Modelling – A Case Study of the Ciberes River in Cirebon Indonesia

“…Digital elevation model (DEM) data, which acts as topography input data, is a crucial element in accurately modelling flood inundation for both river channels and floodplains (Casas et al, 2006;Muthusamy et al, 2021). Currently, DEM data is extensively available to support flood inundation modelling, including open data sources that can be accessed for free, such as SRTM, ASTER GDEM, Sentinel, ALOS and Indonesia's very own DEMNAS (Ihsan & Sahid, 2021;Sahid et al, 2017).…”