Physically-based land surface segmentation: Theoretical background and outline of interpretations

Minár, Jozef; Bandura, Peter; Holec, Juraj; Popov, Anton; Drăguţ, Lucian; Gallay, Michal; Hofierka, Jaroslav; Kaňuk, Ján; Evans, Ian S.

doi:10.7287/peerj.preprints.27075

Cited by 4 publications

(11 citation statements)

References 6 publications

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“…Further work will be focused on improving the approach by determination of variable segmentation step size and its combinations with partitioning the scene into separated domains. However, already the results presented here can be used for initial morphotectonic interpretations; see in [1].…”

Section: Discussionmentioning

confidence: 96%

“…These physically-based variables effectively replace pure geomorphometric variables elevation, vertical dissection of terrain and slope gradient used in [6], for more detail see [1].…”

Section: A Computation Of Input Data and Their Pre-processingmentioning

confidence: 99%

“…steady state) on their formation. This and more theoretical background is outlined in the specific contribution [1].…”

Section: Introductionmentioning

confidence: 99%

“…We adapted these principles in combination with selecting and setting apart distinct individuals that tend to influence the level of overall homogeneity in segmentation. Moreover, as improvement of [6] we consistently applied the theoretical principles of physicallybased land surface segmentation [1], which consists in use of physically-modified input data. This should make the subsequent morphotectonic interpretations more straightforward.…”

Section: Introductionmentioning

confidence: 99%

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Physically-based segmentation of the Western Carpathians (Central Europe)

Bandura

Minár

Drăguţ

2018

Preprint

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Results of a physically-based methodology to delineate morphometrical-morphostructural subdivision of the Western Carpathian region (Central Europe) from DEMs and their derivatives are presented. Previous suitability evaluation of an object-oriented methodology showed its potential in recognition of morphostructural features. In this study we moved towards a more complex object-oriented approach – fusion of segmentation and classification on several hierarchical levels. In addition, physicallybased geomorphometric variables were used as input data, resulting in enhancement of subsequent morphotectonic interpretations. Decrease of local variance of the delineated objects in comparison with simple segmentations without these upgrades confirms the efficiency of our approach.

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Section: Discussionmentioning

confidence: 96%

“…These physically-based variables effectively replace pure geomorphometric variables elevation, vertical dissection of terrain and slope gradient used in [6], for more detail see [1].…”

Section: A Computation Of Input Data and Their Pre-processingmentioning

confidence: 99%

“…steady state) on their formation. This and more theoretical background is outlined in the specific contribution [1].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Physically-based segmentation of the Western Carpathians (Central Europe)

Bandura

Minár

Drăguţ

2018

Preprint

Self Cite

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“…By this means, relative and absolute dating of glacial formation of the cirque and the through can be improved having implications to a wider context of the Tatry Mountains. The DEM also enabled experiments with new geomorphometric parameters as presented in [14]. Challenge for future research remains in distinguishing multiple hierarchies of landforms by using the high-resolution DEM or the original point clouds.…”

Section: Discussionmentioning

confidence: 99%

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Supplemental Information 1: Digital Elevation Model and Mask of the Area of Interest

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The alpine landscape is rugged, dominated by glacial morphogenesis, comprising specific landforms of different sizes and shapes with a marked vertical relief and hierarchical-ordering of the forms. Digital geomorphometric analyses of such a land surface in a high level of detail can exploit mainly data acquired by airborne laser scanning or photogrammetry. However, the level of detail captured is limited to several meters or decimetres in these datasets for the relatively high above ground flying heights. Terrestrial laser scanning (TLS) and close range photogrammetry generate 3-D point clouds of ultra-high spatial resolution but their application is limited by extreme environmental conditions. TLS data often contain data shadows in alpine landscape resulting in inhomogeneous spatial distribution of the acquired 3-D point cloud. Such data properties cause creation of overly smoothed surfaces or artefacts in digital elevation models (DEMs) interpolated into a grid (raster). The sub-horizontal field of view in TLS can be compensated by sub-vertical field of view of digital cameras installed on unpiloted aerial platforms (UAVs). Such a photogrammetric 3-D reconstruction of terrain with UAVs is based on structure-from-motion (SfM) image matching techniques. The measurement precision and accuracy of UAV-SfM is lower than with TLS but the UAV-SfM data can be used in filling the TLS data voids. In this paper, we present the results of combined use of TLS and UAV-SfM for high-resolution modelling of a glacial cirque in the Tatry Mountains, the Carpathians, Europe. The achieved accuracy (1 standard deviation) of mutual co-registration of 18 TLS positions was 4.2 mm. The accuracy of georeferencing the final TLS data in the national cartographic system was 33.2 mm based on 15 ground control points. The UAV-SfM dataset was spatially coregistered on the TLS dataset with the accuracy of 137 mm and point filling the TLS voids were used to generate the final DEM of 0.5 m cell size from the combined point clouds.

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