Introducing elevation models for geoscience

Abstract

Elevation data are a critical element in any geoscience application. From the fundamentals of geological mapping to more advanced three-dimensional (3D) modelling of Earth systems there must be an understanding of the shape of the Earth's surface. Vast amounts of digital elevation data exist, from large-scale global datasets to smaller-scale regional datasets, and in many cases datasets have been merged to improve scale and accuracy. For each application decisions must be made on which elevation data are appropriate. This will depend on many factors including the cost, resolution and accuracy of the data. The types of data discussed in this special publication include: ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), LiDAR (Light Detection And Ranging) – terrestrial and airborne, NEXTMap, SRTM (Shuttle Radar Topography Mission) and multibeam bathymetry. Applications covered include: landslide mapping, coastal erosion, glacial deposits and hazard mapping, and some of the issues discussed include: accuracy analysis, derived product creation, software comparisons and copyright considerations (Table 1 ). Since some of the papers were written for the Special Publication certain datasets have evolved and been created; for example, the GDEM global elevation dataset derived from ASTER data. This illustrates the fast moving nature of this field. View this table:In this windowIn a new windowTable 1. Summary of applications and sensors discussed in this Special Publication With the proliferation in data available for the production of digital elevation models (DEMs) it is increasingly important to understand how to use the raw data correctly and effectively. Giglierano discusses the use of LiDAR for natural resource mapping applications, and states how a ‘black box’ approach is dangerous and that knowledge of the data being used is essential, especially as more non-specialists begin to use the data. Many users reduce the resolution of the DEM to shorten processing time and also decrease the amount of space required to store the data.