Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation. (September 2017)

• Record Type: Journal Article
• Authors: Baltensweiler, Andri; Walthert, Lorenz; Ginzler, Christian; Sutter, Flurin; Purves, Ross S.; Hanewinkel, Marc
• Is Part Of: Environmental modelling & software. Volume 95(2017)
• Page Start: 13
• Page End: 21
• Publication Date: 2017-09
• Subjects: Digital elevation model -- Terrestrial laser scanning -- Airborne LiDAR -- Accuracy -- Digital soil mapping -- Terrain attribute; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.05.009
• Languages: English
• ISSNs: 1364-8152

Abstract

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 R 2 of 0.62. The use of TLS therefore improves the quality of terrain attributes, which are the foundation for many ecological and hydrological applications. Highlights: Accuracy assessment of DEMs derived from terrestrial and airborne LiDAR. Effect of DEMs accuracies and resolutions on soil pH prediction models. Very high resolution DEMs derived from TLS were more accurate than ALS based DEMs. Most accurate topsoil pH models were derived from TLS data. TLS is the favorable option to derive DEMs for complex areas of a few hectares.