Influence of cell size on volume calculation using digital terrain models: A case of coastal dune fields

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.geomorph.2012.09.012. This is version 1 of this Preprint.

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Authors

Carlos Henrique Grohmann

Abstract

In this work, we analyze how variation in cell size influences the volume calculated from Digital Terrain Models (DTMs) derived from a LiDAR (Light Detection and Ranging) survey in two coastal Late Holocene dune fields in southern Brazil. Cell size varied from 1 to 100 m. The RMSE (Root Mean Square Error) of the resampled DTMs from the original LiDAR (with 0.5 m resolution) increases linearly with cell size, while the R-squared decreases following a second-order trend. The volume does not show simple linear or exponential behavior, but fluctuates with positive and negative deviations from the original DTM. This fluctuation can be explained by a random factor in the position of the cell with regard to landforms and a relationship between cell and landform size, wherein a small change in cell size can lead to an under- or overestimation of volume. ASTER GDEM (Global Digital Elevation Model) and X-SAR SRTM (Shuttle Radar Topography Mission) 1 arcsec Digital Elevation Models (DEMs) were not considered viable volume sources due to large deviations from the reference data, either as a consequence of noise in the SRTM X-SAR data or lack of bias elevation correction to a common reference base in the GDEM processing chain. Volumes from a 3-arcsec SIR-C SRTM deviated around +- 5% from the reference data and are considered suitable input for numerical simulations of Quaternary dune field evolution models because these values should be within the expected range of sediment volume changes over hundreds to millions of years.

DOI

https://doi.org/10.31223/osf.io/pr7um

Subjects

Earth Sciences, Geographic Information Sciences, Geography, Geomorphology, Other Earth Sciences, Physical Sciences and Mathematics, Remote Sensing, Sedimentology, Social and Behavioral Sciences, Spatial Science

Keywords

Quaternary, LiDAR, SRTM, ASTER GDEM, Coastal dune field, SIR-C, X-SAR

Dates

Published: 2017-11-01 03:55

License

CC BY Attribution 4.0 International