Error in topographic attributes for volcanic hazard assessment of the Auckland Volcanic Field (New Zealand). Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Kereszturi, G; Procter, J
• Is Part Of: New Zealand journal of geology and geophysics. Volume 59:Issue 2(2016)
• Page Start: 286
• Page End: 301
• Publication Date: 2016-04-02
• Subjects: ASTER GDEM -- contour DEM -- lava flow -- LiDAR -- root-mean square error -- scoria cone -- slope angle -- SRTM -- topographic survey; Geology -- New Zealand -- Periodicals; Geology -- Periodicals; Geophysics -- Periodicals; Geofysica; Geologie; Geology; Geophysics; New Zealand; Periodicals; 559.3
• DOI: 10.1080/00288306.2015.1130155
• Languages: English
• ISSNs: 1175-8791

Abstract

ABSTRACT: Remotely sensed topographic datasets are a major source of information in modelling environmental and geomorphic processes. In this investigation, four of the most popular remotely sensed topographic datasets available for the Auckland Volcanic Field (AVF, New Zealand) were compared using high-accuracy control points, such as real-time kinematic global positioning system (RTK GPS) profiles as well as a terrestrial laser scanning (TLS) surface. The LiDAR (light detection and ranging) data were found to be the most accurate with a root-mean-square error (RMSE) of ±0.9 m, while other datasets such as contour-derived digital elevation model (DEM), Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global DEM (GDEM) were found to be accurate at 5–10 m levels. As part of the error assessment, an extensive comparison was carried out between a range of popular terrain attributes (e.g. elevation, volume and slope angle) to determine their variability as a function of input data properties (e.g. surveying technique and data structure). This study shows that the eruptive volumes of monogenetic volcanoes are sensitive to the input data type and its spatial resolution. The moderately vegetated lava flow fields of Rangitoto have an uncertainty in eruptive volume estimate by ±15% due to the overall surface roughness. For hazard assessment purposes in the AVF, resampled LiDAR datasets are reliable; however, other datasets such as contour-derived DEM and SRTM DTM can be used to estimate eruptive volumes of monogenetic volcanoes.