Automatic mapping of river canyons using a digital elevation model and vector river data

Xu, Shi-Yu; Li, Anbo; Dong, Tian-Tian; Xie, Xinglong

doi:10.1007/s12145-020-00551-9

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…In this paper, the standard missed alarm rate (MAR) and the false alarm rate (FAR) was used to quantitatively evaluate the effectiveness of the identification results [42].…”

Section: Evaluation Of Experimental Resultsmentioning

confidence: 99%

Automatic Identification and Mapping of Cone-Shaped Volcanoes Based on the Morphological Characteristics of Contour Lines

Li¹,

Nong

et al. 2023

Sustainability

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Cone-shaped volcanoes have important research significance and application value due to their typical cone shape and unique structural features. The existing methods for recognizing volcanoes are mainly morphological feature matching and machine learning. In general, the former has low recognition accuracy, while the latter requires a large number of training samples. The contour lines of cone-shaped volcanoes are distributed in concentric circles. Furthermore, from the center outwards, the elevation of the contour lines increases first and then decreases. Based on the morphological characteristics of cone-shaped volcanoes and the Hough transform algorithm, the main algorithm includes (1) preliminary filtering of contour lines, (2) filtering circular contour lines based on random Hough transform, (3) grouping contour lines based on contour trees, (4) recognizing cone-shaped volcanoes based on concentric-circle contour lines, and (5) automatically mapping cone-shaped volcanoes. Case studies demonstrate the effectiveness of this method for detecting cone-shaped volcanoes in the Western Galapagos shield volcanoes and the Mariana Trench submarine volcano group. The proposed algorithm has low missed and false alarm rates, which is basically consistent with the manual recognition results. This method can effectively automatically recognize cone-shaped volcanoes and cone-shaped landscapes and is a powerful means to support deep-space and deep-sea exploration.

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“…In this paper, the standard missed alarm rate (MAR) and the false alarm rate (FAR) was used to quantitatively evaluate the effectiveness of the identification results [42].…”

Section: Evaluation Of Experimental Resultsmentioning

confidence: 99%

Automatic Identification and Mapping of Cone-Shaped Volcanoes Based on the Morphological Characteristics of Contour Lines

Li¹,

Nong

et al. 2023

Sustainability

Self Cite

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Remeasurement method of power engineering pipe position based on tilt photography 3D reconstruction technology

Zhu

2022

Second International Conference on Testing Technology and Automation Engineering (TTAE 2022)

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To effectively establish the three-dimensional model of the pipe laying process, reduce the three-dimensional coordinate positioning error of pipe laying and realize pipe position remeasurement, the pipe position remeasurement method of power engineering based on tilt photography three-dimensional reconstruction technology is studied. The UAV is equipped with four tilt cameras and a vertical camera, combined with a GPS receiver and high-precision inertial sensor to collect the pipe laying image and more accurate position information. Tube images are normalized to uniform light and color. The aerial triangulation method extracts the accurate pipe laying position information in the more accurate position. According to the processed pipe laying image and accurate position information, the polygonal pipe laying three-dimensional model is reconstructed and the pipe position information is retested. Experiments show that this method can effectively establish the three-dimensional model of the pipe laying process and retest the pipe position. In different routes, this method can accurately extract the three-dimensional coordinates of the pipeline, and the maximum absolute coordinate error is only 18cm.

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Automated identification and mapping of geological folds in cross sections

Huang

Wang

et al. 2023

Open Geosciences

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Cross sections carry information on the spatial distribution of rock strata and the development of geological structures, and it is an important data source for three-dimensional (3D) geological modeling. However, the interpretation and mapping of geological structures in sections by means of manual interpretation are inefficient and costly, and the performance varies greatly with the experts’ ability and experience. The objective of this article is to develop an automatic recognition and mapping method for folds in cross sections. This method mainly includes identifying folds based on stratigraphic sequence characteristics (symmetrical and repetitive), classifying fold types based on geometric attributes of folds (interval scheduling, strike, and section morphology), optimizing strata based on the superposition principle and area conservation principle, and constructing the polygon features of folds. Based on experiments in the Parallel Fold Belt of Eastern Sichuan and the central Appalachian fold-thrust belt in the Appalachian Mountains, the method presented in this article can effectively be used for automatic recognition and high-quality mapping of folds in the cross sections. The method provides a good source of geological cross-sectional data for the 3D modeling of geologic bodies.

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Automatic mapping of river canyons using a digital elevation model and vector river data

Cited by 4 publications

References 26 publications

Automatic Identification and Mapping of Cone-Shaped Volcanoes Based on the Morphological Characteristics of Contour Lines

Automatic Identification and Mapping of Cone-Shaped Volcanoes Based on the Morphological Characteristics of Contour Lines

Remeasurement method of power engineering pipe position based on tilt photography 3D reconstruction technology

Automated identification and mapping of geological folds in cross sections

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