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Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation


Baltensweiler, Andri; Walthert, Lorenz; Ginzler, Christian; Sutter, Flurin; Purves, Ross S; Hanewinkel, Marc (2017). Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation. Environmental Modelling & Software, 95:13-21.

Abstract

Terrestrial Laser Scanning (TLS) has great potential in creating high resolution digital elevation models (DEMs). However, little is known about the properties of TLS derived DEMs covering several hectares in heterogeneous environments compared to conventional airborne laser scanning (ALS) based models and their influence on derived products. We investigated the accuracy of DEMs with different resolutions derived from TLS and high quality ALS on a study site with complex micro-topography covered by dense forest and ground vegetation. We further examined the effect of these DEMs on predicted topsoil pH using linear regression models built on terrain attributes. We show that at high resolutions (∼1 m), TLS based DEMs performed better than ALS DEMs, which directly translated into significantly better pH models, the best of which showing an R2 of 0.62. The use of TLS therefore improves the quality of terrain attributes, which are the foundation for many ecological and hydrological applications.

Abstract

Terrestrial Laser Scanning (TLS) has great potential in creating high resolution digital elevation models (DEMs). However, little is known about the properties of TLS derived DEMs covering several hectares in heterogeneous environments compared to conventional airborne laser scanning (ALS) based models and their influence on derived products. We investigated the accuracy of DEMs with different resolutions derived from TLS and high quality ALS on a study site with complex micro-topography covered by dense forest and ground vegetation. We further examined the effect of these DEMs on predicted topsoil pH using linear regression models built on terrain attributes. We show that at high resolutions (∼1 m), TLS based DEMs performed better than ALS DEMs, which directly translated into significantly better pH models, the best of which showing an R2 of 0.62. The use of TLS therefore improves the quality of terrain attributes, which are the foundation for many ecological and hydrological applications.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Uncontrolled Keywords:Ecological Modelling, Environmental Engineering, Software
Language:English
Date:2017
Deposited On:20 Dec 2017 16:10
Last Modified:19 Aug 2018 12:02
Publisher:Elsevier
ISSN:1364-8152
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.envsoft.2017.05.009

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