Abstract
Abstract. Soil erosion is a decisive earth surface process strongly influencing the fertility of arable land. Several options exist to detect soil erosion at the scale of large field plots (here 600 m²), which comprise different advantages and disadvantages depending on the applied method. In this study, the benefits of unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanning (TLS) are exploited to quantify soil surface changes. Beforehand data combination, TLS data is co-registered to the DEMs generated with UAV photogrammetry. TLS data is used to detect global as well as local errors in the DEMs calculated from UAV images. Additionally, TLS data is considered for vegetation filtering. Complimentary, DEMs from UAV photogrammetry are utilised to detect systematic TLS errors and to further filter TLS point clouds in regard to unfavourable scan geometry (i.e. incidence angle and footprint) on gentle hillslopes. In addition, surface roughness is integrated as an important parameter to evaluate TLS point reliability because of the increasing footprints and thus area of signal reflection with increasing distance to the scanning device. The developed fusion tool allows for the estimation of reliable data points from each data source, considering the data acquisition geometry and surface properties, to finally merge both data sets into a single soil surface model. Data fusion is performed for three different field campaigns at a Mediterranean field plot. Successive DEM evaluation reveals continuous decrease of soil surface roughness, reappearance of former wheel tracks and local soil particle relocation patterns.
Highlights
Soil erosion is an important process influencing the fertility of the earth surface, which is significant regarding its agricultural exploitation
1 Point clouds from terrestrial laser scanning (TLS) are reliable in regard to their geometric error behaviour (e.g. Vosselman & Maas, 2010) and may be assumed to be useful for the evaluation of digital elevation models (DEMs) obtained from unmanned aerial vehicle (UAV) photogrammetry (UAV DEM)
The UAV DEMs are suitable to evaluate the TLS point quality in regard to the scan geometry allowing for TLS point cloud filtering considering the parameters incidence angle, footprint size and surface roughness, which can be calculated utilising the UAV DEMs and scan positions (SP) of the TLS device
Summary
Soil erosion is an important process influencing the fertility of the earth surface, which is significant regarding its agricultural exploitation. The UAV DEMs are suitable to evaluate the TLS point quality in regard to the scan geometry allowing for TLS point cloud filtering considering the parameters incidence angle, footprint size and surface roughness, which can be calculated utilising the UAV DEMs and scan positions (SP) of the TLS device. The introduced approach automatically incorporates information about the data acquisition configurations as well as surface properties to utilise the potential of TLS and UAV data, respectively. Both high resolution topographic datasets are merged to estimate a precise digital soil surface model. Concluding, multi-temporal assessment of the processed data is performed for three field campaigns from September 2013 to February 2014 capturing single precipitation events revealing steady soil roughness decrease and locally varying height changes
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