Landscape Ecology

, Volume 33, Issue 1, pp 9–18 | Cite as

A practical method for creating a digital topographic surface for ecological plots using ground-based measurements

  • Jessie C. BuettelEmail author
  • Stefania Ondei
  • Barry W. Brook
Short Communication



Digital elevation models (DEMs) are widely used in landscape ecology to link topographic features with biotic and abiotic factors. However, to date, high-resolution, affordable, and easy to process elevation data are not available for many regions.


Here we propose a field-based method for efficiently and inexpensively collecting or analysing already existing slope data. We compare the field approach to two commonly used remote sensing techniques to test the similarly of the DEMs using different methods.


To provide an ecological example of the method, we selected four 1-ha forest plots and compared the DEM generated by using our field method with those derived from: (i) coarse (~ 30 m pixel) data from the Shuttle Radar Topography Mission and (ii) high-resolution (~ 1 m) data from Light Detection and Ranging devices (LiDAR).


Field- and LiDAR-based DEMs showed strong concordance in two of the four sites. The sites where field-based and LiDAR DEMs substantially differed, suffered from relatively few LiDAR sampling points. Diagnostic tests suggested that the field–LiDAR discrepancy was due to dense over-storey vegetation, which reduced LiDAR’s accuracy due to a failure to penetrate the forest canopy adequately in some areas.


Our method has the advantage of being quick and cheap to collect yet able to produce small-scale (plot-scale) DEMs of high quality. By using the R-code we have provided, ecologists will be able to use slope data (collected using any means) to generate a DEM without the need of specific skills in spatial sciences.


Digital elevation models DEM Topography Plots Algorithm Remote sensing Slope LiDAR SRTM Forests 



This study was supported by Australian Research Council Laureate Fellowship under award number FL160100101. Jessie C. Buettel and Barry W. Brook were supported by Centre of Excellence for Australian Biodiversity and Heritage under award number CE170100015.

Supplementary material

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Supplementary material 1 (TXT 5 kb)
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Supplementary material 2 (TXT 11 kb)
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Supplementary material 3 (DOCX 524 kb)
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Supplementary material 4 (PDF 3609 kb)


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© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Biological Sciences and ARC Centre of Excellence for Australian Biodiversity and HeritageUniversity of TasmaniaHobartAustralia

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