Overland Flow Analysis Using Time Series of Suas-Derived Elevation Models

Jeziorska, Justyna; Mitášová, Helena; Petrášová, Anna; Petras, Vaclav; Divakaran, D.; Zajkowski, T.

doi:10.5194/isprsannals-iii-8-159-2016

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…In particular, UAS‐derived imagery is utilized for producing high‐ and very high‐resolution DEMs, which are then used, for example, to study and model dynamics of slope, coastal, glacial, and fluvial processes, to reveal fine geological features (e.g., micro‐folds and fractures) etc. (Bemis et al, ; Brunier, Fleury, Anthony, Gardel, & Dussouillez, ; Dowling & Gallant, ; D'Oleire‐Oltmanns, Marzolff, Peter, & Ries, ; Eltner et al, ; Jeziorska et al, ; Johnson et al, ; Kraaijenbrink et al, ; Mancini et al, ; Smith, Chandler, & Rose, ; Syromyatina, Kurochkin, Bliakharskii, & Chistyakov, ).…”

Section: Introductionmentioning

confidence: 99%

Geomorphometry from unmanned aerial surveys

Florinsky

Курков

Bliakharskii³

2017

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Unmanned aerial systems (UASs) are widely used for remote sensing, including the production of high-resolution digital elevation models (DEMs). We study the possibilities of UAS-based aerial surveys to produce photogrammetrically sound, high-resolution DEMs intended for geomorphometric modeling. The study was conducted at the Zaoksky testing ground (Russia). To carry out an aerial survey, we used a UAS Geoscan-101 equipped with a Sony DSC-RX1 camera and a Topcon GNSS receiver. Aerial photographs were processed using Agisoft PhotoScan Professional software. Applying dense point cloud generation and classification, we produced DEMs with resolutions of 6 cm, 20 cm, and 1 m. Using a universal spectral analytical method, we derived models of several morphometric variables (i.e., slope gradient, horizontal, vertical, minimal, and maximal curvatures) from DEMs with resolutions of 20 cm and 1 m. We found that it is possible to produce noiseless models and well-readable maps of morphometric variables for grassy areas with separately standing groups of trees and shrubs. However, UAS-based DEMs cannot be applied for modeling of forested areas: there occur pronounced unrecoverable artifacts due to errors of automated classification of the dense point cloud. Finally, we present recommendations for the production of UAS-derived, photogrammetrically sound, high-resolution DEMs intended for geomorphometry.

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Section: Introductionmentioning

confidence: 99%

Geomorphometry from unmanned aerial surveys

Florinsky

Курков

Bliakharskii³

2017

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Identification of karst sinkholes in a forested karst landscape using airborne laser scanning data and water flow analysis

et al. 2018

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Fusion of high-resolution DEMs for water flow modeling

Petrášová

Mitášová

Petras

et al. 2017

Open geospatial data, softw. stand.

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Background: New technologies for terrain reconstruction have increased the availability of topographic data at a broad range of resolutions and spatial extents. The existing digital elevation models (DEMs) can now be updated at a low cost in selected study areas with newer, often higher resolution data using unmanned aerial systems (UAS) or terrestrial sensors. However, differences in spatial coverage and levels of detail often create discontinuities along the newly mapped area boundaries and subsequently lead to artifacts in results of DEM analyses or models of landscape processes. Methods: To generate a seamless updated DEM, we propose a generalized approach to DEM fusion with a smooth transition while preserving important topographic features. The transition is controlled by distance-based weighted averaging along the DEMs' blending overlap with spatially variable width based on elevation differences. Results: We demonstrate the method on two case studies exploring the effects of DEM fusion on water flow modeling in the context of precision agriculture. In the first case study, we update a lidar-based DEM with a fused set of two digital surface models (DSMs) derived from imagery acquired by UAS. In the second application, developed for a tangible geospatial interface, we fuse a georeferenced, physical sand model continuously scanned by a Kinect sensor with a lidar-based DEM of the surrounding watershed in order to computationally simulate and test methods for controlling storm water flow. Conclusions:The results of our experiments demonstrate the importance of seamless, robust fusion for realistic simulation of water flow patterns using multiple high-resolution DEMs.

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Overland Flow Analysis Using Time Series of Suas-Derived Elevation Models

Cited by 4 publications

References 18 publications

Geomorphometry from unmanned aerial surveys

Geomorphometry from unmanned aerial surveys

Identification of karst sinkholes in a forested karst landscape using airborne laser scanning data and water flow analysis

Fusion of high-resolution DEMs for water flow modeling

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