Very high resolution digital elevation models: Do they improve models of plant species distribution?

2006 ◽  
Vol 198 (1-2) ◽  
pp. 139-153 ◽  
Author(s):  
Thierry Lassueur ◽  
Stéphane Joost ◽  
Christophe F. Randin
Author(s):  
T. Kramm ◽  
D. Hoffmeister

<p><strong>Abstract.</strong> The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000&amp;thinsp;km<sup>2</sup>. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30&amp;thinsp;m and 90&amp;thinsp;m, Advanced Land Observing Satellite (ALOS) World 3D 30&amp;thinsp;m and TanDEM-X WorldDEM&amp;trade; &amp;ndash; 12&amp;thinsp;m and 90&amp;thinsp;m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100&amp;ndash;400&amp;thinsp;km<sup>2</sup> for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12&amp;thinsp;m (RMSE: 2.3&amp;thinsp;m, NMAD: 0.8&amp;thinsp;m). The lowest accuracies were detected for the 30&amp;thinsp;m ASTER GDEM v3 (RMSE: 8.9&amp;thinsp;m, NMAD: 7.1&amp;thinsp;m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.</p>


2015 ◽  
Vol 6 (12) ◽  
pp. 1373-1383 ◽  
Author(s):  
Kevin Leempoel ◽  
Christian Parisod ◽  
Céline Geiser ◽  
Lucas Daprà ◽  
Pascal Vittoz ◽  
...  

2016 ◽  
Vol 57 (71) ◽  
pp. 273-281 ◽  
Author(s):  
Melanie Rankl ◽  
Matthias Braun

AbstractSnow cover and glaciers in the Karakoram region are important freshwater resources for many down-river communities as they provide water for irrigation and hydropower. A better understanding of current glacier changes is hence an important informational baseline. We present glacier elevation changes in the central Karakoram region using TanDEM-X and SRTM/X-SAR DEM differences between 2000 and 2012. We calculated elevation differences for glaciers with advancing and stable termini or surge-type glaciers separately using an inventory from a previous study. Glaciers with stable and advancing termini since the 1970s showed nearly balanced elevation changes of -0.09 ±0.12 m a-1 on average or mass budgets of -0.01 ±0.02Gt a-1 (using a density of 850 kg m-3). Our findings are in accordance with previous studies indicating stable or only slightly negative glacier mass balances during recent years in the Karakoram. The high-resolution elevation changes revealed distinct patterns of mass relocation at glacier surfaces during active surge cycles. The formation of kinematic waves at quiescent surge-type glaciers could be observed and points towards future active surge behaviour. Our study reveals the potential of the TanDEM-X mission to estimate geodetic glacier mass balances, but also points to still existing uncertainties induced by the geodetic method.


2013 ◽  
Vol 38 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Jean-Nicolas Pradervand ◽  
Anne Dubuis ◽  
Loïc Pellissier ◽  
Antoine Guisan ◽  
Christophe Randin

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species’ micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions – and therefore local management – compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.


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