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Open AccessFeature PaperArticle

Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions

Department of Land, Environment, Agriculture and Forestry, University of Padova, viale dell’Università 16, 35020 Legnaro, Italy
Tromso University Museum, UiT The Artic University of Norway, Kvaløyen 30, 9013 Tromsø, Norway
Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, UCLouvain, 1348 Louvain-la-Neuve, Belgium
Department of Archaeology, The Kings Manor, University of York, York YO1 7EP, North Yorkshire, UK
Geography and Environmental Science, University of Southampton, Highfield SO17 1BJ, Southampton, UK
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(12), 1946;
Received: 14 May 2020 / Revised: 8 June 2020 / Accepted: 15 June 2020 / Published: 17 June 2020
Agricultural terraced landscapes, which are important historical heritage sites (e.g., UNESCO or Globally Important Agricultural Heritage Systems (GIAHS) sites) are under threat from increased soil degradation due to climate change and land abandonment. Remote sensing can assist in the assessment and monitoring of such cultural ecosystem services. However, due to the limitations imposed by rugged topography and the occurrence of vegetation, the application of a single high-resolution topography (HRT) technique is challenging in these particular agricultural environments. Therefore, data fusion of HRT techniques (terrestrial laser scanning (TLS) and aerial/terrestrial structure from motion (SfM)) was tested for the first time in this context (terraces), to the best of our knowledge, to overcome specific detection problems such as the complex topographic and landcover conditions of the terrace systems. SfM–TLS data fusion methodology was trialed in order to produce very high-resolution digital terrain models (DTMs) of two agricultural terrace areas, both characterized by the presence of vegetation that covers parts of the subvertical surfaces, complex morphology, and inaccessible areas. In the unreachable areas, it was necessary to find effective solutions to carry out HRT surveys; therefore, we tested the direct georeferencing (DG) method, exploiting onboard multifrequency GNSS receivers for unmanned aerial vehicles (UAVs) and postprocessing kinematic (PPK) data. The results showed that the fusion of data based on different methods and acquisition platforms is required to obtain accurate DTMs that reflect the real surface roughness of terrace systems without gaps in data. Moreover, in inaccessible or hazardous terrains, a combination of direct and indirect georeferencing was a useful solution to reduce the substantial inconvenience and cost of ground control point (GCP) placement. We show that in order to obtain a precise data fusion in these complex conditions, it is essential to utilize a complete and specific workflow. This workflow must incorporate all data merging issues and landcover condition problems, encompassing the survey planning step, the coregistration process, and the error analysis of the outputs. The high-resolution DTMs realized can provide a starting point for land degradation process assessment of these agriculture environments and supplies useful information to stakeholders for better management and protection of such important heritage landscapes. View Full-Text
Keywords: data fusion; coregistration; TLS; SfM; terrace; direct georeferencing data fusion; coregistration; TLS; SfM; terrace; direct georeferencing
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Cucchiaro, S.; Fallu, D.J.; Zhang, H.; Walsh, K.; Van Oost, K.; Brown, A.G.; Tarolli, P. Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions. Remote Sens. 2020, 12, 1946.

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