A New Algorithm for Cartographic Simplification of Streams and Lakes Using Deviation Angles and Error Bands

Gökgöz, Türkay; Sen, Alper; Memduhoğlu, Abdulkadir; Hacar, M A

doi:10.3390/ijgi4042185

Cited by 16 publications

(8 citation statements)

References 18 publications

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“…McMaster [19] presented a method of simplification lines based on the integration of smoothing and simplifying, which is to reduce the change of area. A similar idea is presented by T. Gökgöz et al [20]. Bose et al [21] proposed a method to simplify the boundaries of polygons.…”

Section: Related Workmentioning

confidence: 89%

Cartographic Line Generalization Based on Radius of Curvature Analysis

Kolanowski

Augustyniak

Latos

2018

IJGI

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Cartographic generalization is one of the important processes of transforming the content of both analogue and digital maps. The process of reducing details on the map has to be conducted in a planned way in each case when the map scale is to be reduced. As far as digital maps are concerned, numerous algorithms are used for the generalization of vector line elements. They are used if the scale of the map (on screen or printed) is changed, or in the process of smoothing vector lines (e.g., contours). The most popular method of reducing the number of vertices of a vector line is the Douglas-Peucker algorithm. An important feature of most algorithms is the fact that they do not take into account the cartographic properties of the transformed map element. Having analysed the existing methods of generalization, the authors developed a proprietary algorithm that is based on the analysis of the curvature of the vector line and fulfils the condition of objective generalization for elements of digital maps that may be used to transform open and closed vector lines. The paper discusses the operation of this algorithm, along with the graphic presentation of the generalization results for vector lines and the analysis of their accuracy. Treating the set of verification radii of a vector line as a statistical series, the authors propose applying statistical indices of position of these series, connected with the shape of the vector line, as the threshold parameters of generalization. The developed algorithm allows for linking the generalization parameters directly to the scale of the topographic map that was obtained after generalization. The results of the operation of the algorithm were compared to the results of the reduction of vertices with use of the Douglas-Peucker algorithm. The results demonstrated that the proposed algorithm not only reduced the number of vertices, but that it also smoothed the shape of physiographic lines, if applied to them. The authors demonstrated that the errors of smoothing and position of vertices did not exceed the acceptable values for the relevant scales of topographic maps. The developed algorithm allows for adjusting the surface of the generalized areas to their initial value more precisely. The advantage of the developed algorithm consists in the possibility to apply statistical indices that take the shape of lines into account to define the generalization parameters.

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Section: Related Workmentioning

confidence: 89%

Cartographic Line Generalization Based on Radius of Curvature Analysis

Kolanowski

Augustyniak

Latos

2018

IJGI

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“…During network pruning, the preserved rivers were also appropriately simplified. Considerable simplification algorithms can be used [22,46,47]; it has been noted that the well-known Douglas-Puecker (DP) algorithm, which selects the critical or shape-describing points globally and iteratively, has the best performance out of the other algorithms in terms of data accuracy and reduction [46,48]. Therefore, we applied a modified Douglas-Peucker algorithm advanced by Meijers [49] for the simplification of grouping lines.…”

Section: Hierarchical Construction For River Simplificationmentioning

confidence: 99%

A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales: The Case of River Network Data

Huang

Oosterom

et al. 2017

IJGI

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The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex generalization, we proposed a matrix model to combine different generalization operations into an integration. This study was carried on a set of river network data, where two operations, i.e., network pruning accompanied with river simplification, were hierarchically constructed as the rows and columns of a matrix. The correspondence between generalization operations and scale, and the scale linkage of multiple operations were also explicitly defined. In addition, we developed a vario-scale data structure to store the generalized river network data based on the proposed matrix. The matrix model was validated and assessed by a comparison with traditional methods that conduct generalization operations in sequence. It was shown that the matrix model enabled complex generalization with good generalization quality. Taking advantage of the corresponding vario-scale data structure, the river network data could be obtained at any arbitrary scale, and the vario-scale representation was achieved across a wide scale range.

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“…After a survey, the newly collected datasets are evaluated for evidence of substantial changes against the latest relevant nautical charts. This is an operation that must take into account the numerous transformations that a survey sounding has undergone from the moment that a sonar ping is emitted to its final representation on the chart, in particular when integrated on a statistically-based bathymetric surface and as the consequence of several possible cartographic adjustments (e.g., rounding and truncation, generalization) [7][8][9][10]. In addition, although ontologically distinct, disentangling inaccuracy and uncertainty adds complexity to the already challenging scenario [11].…”

Section: Introductionmentioning

confidence: 99%

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Masetti¹,

Faulkes²,

Kastrisios³

2018

Preprint

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Timely and accurate identification of change detection for areas depicted on nautical charts constitutes a key task for marine cartographic agencies in supporting maritime safety. Such a task is usually achieved through manual or semi-automated processes, based on best practices developed over the years requiring a substantial level of human commitment (i.e., to visually compare the chart with the new collected data or to analyze the result of intermediate products). This work describes an algorithm that aims to largely automate the change identification process as well as to reduce its subjective component. Through the selective derivation of a set of depth points from a nautical chart, a triangulated irregular network is created to apply a preliminary tilted-triangle test to all the input survey soundings. Given the complexity of a modern nautical chart, a set of feature-specific, point-in-polygon tests are then performed. As output, the algorithm provides danger-to-navigation candidates, chart discrepancies, and a subset of features that requires human evaluation. The algorithm has been successfully tested with real-world electronic navigational charts and survey datasets. In parallel to the research development, a prototype application implementing the algorithm was created and made publicly available.

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A New Algorithm for Cartographic Simplification of Streams and Lakes Using Deviation Angles and Error Bands

Cited by 16 publications

References 18 publications

Cartographic Line Generalization Based on Radius of Curvature Analysis

Cartographic Line Generalization Based on Radius of Curvature Analysis

A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales: The Case of River Network Data

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

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