Voronoi tessellation on the ellipsoidal earth for vector data

Kastrisios, Christos; Tsoulos, Lysandros

doi:10.1080/13658816.2018.1434890

Cited by 9 publications

(8 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is unclear how users should proceed for large areas, with possible alternatives being techniques to correct scale deformations or avoiding projections altogether (Chrisman, 2017). Several recent studies have started to recognize and address these considerations, including appropriate interpretation of projection-based analysis (Battersby, Strebe, & Finn, 2017), inappropriate use of equal-angular 'grids' (Florinsky, 2017), and using spherical methods to improve Voronoi tessellations (Kastrisios & Tsoulos, 2018) and cartograms (Li & Aryana, 2018). Developing a robust method for assessing raster data distortion would be extremely beneficial, as would expanding the tool availability using Combined Index = 0.02375 Projection notes: -Conic (Albers, Lambert Conformal, Equidistant) -if distortion assessment is employed and one of these projections is the number one rank for the initial standard parallel and K value settings, then all remaining K values between 3 and 7 will be used to create and assess additional standard parallel options.…”

Section: Discussionmentioning

confidence: 99%

Automated map projection selection for GIS

Gosling

Symeonakis

2020

Cartography and Geographic Information Science

View full text Add to dashboard Cite

The selection of an appropriate map projection has a fundamental impact on the visualization and analysis of geographic information. Distortion is inevitable and the decision requires simultaneous consideration of several different factors; a process which can be confusing for many cartographers and GIS users. The last few decades have seen numerous attempts to create automated map projection selection solutions based on traditional classification and selection guidelines, but there are no existing tools directly accessible to users of GIS software when making projection selection decisions. This paper outlines key elements of projection selection and distortion theory, critically reviews the previous solutions, and introduces a new tool developed for ESRI's ArcGIS, employing an original selection method tailored to the specific purpose and geographical footprint characteristics of a GIS project. The tool incorporates novel quantitative projection distortion measures which are currently unavailable within existing GIS packages. Parameters are optimized for certain projections to further reduce distortions. A set of candidate projected coordinate systems are generated that can be applied to the GIS project; enabling a qualitative visual assessment to facilitate the final user selection. The proposed tool provides a straightforward application which improves understanding of the projection selection process and assists users in making more effective use of GIS.

show abstract

Section: Discussionmentioning

confidence: 99%

Automated map projection selection for GIS

Gosling

Symeonakis

2020

Cartography and Geographic Information Science

View full text Add to dashboard Cite

show abstract

“…Irregular Networks (TINs) - (Kastrisios and Tsoulos, 2018;Reuter et al, 2007) utilizadas em Sistemas de Informações Geográficas (SIGs) - (Kamel Boulos and Geraghty, 2020;Mollalo et al, 2020).…”

Section: Bdg Tais Métodos Permitem a Geração Das Redes Irregulares De...unclassified

“…As ciências geoespaciais (Kalyanam et al, 2019;Merlemis et al, 2021;Sikka et al, 2021) trabalham com aspectos geométricos e de Bancos de Dados Geográficos (BDGs). Na aquisição dos dados geométricos, a triangulação (Hegeman et al, 2014;Kastrisios and Tsoulos, 2018;Kim et al, 2010) e/ou a trilateração (Cheng et al, 2004;Mazuelas et al, 2009)…”

Section: Introductionunclassified

Simulação de Monte Carlo em redes triangulares irregulares / Monte Carlo simulation in triangular irregular networks

Penha¹,

Coelho²

2021

BJDV

View full text Add to dashboard Cite

Triangular Irregular Networks (TINs) are one of the most used ways to represent surface topology when working with Digital Terrain Models (DTM) or Geographic Information Systems (GIS). Given this form of representation, this article investigates one probabilistic demonstration to quantify how each point's accuracy σ (sigma) can be considered to have ambiguity, from the topological point of view, in any new 2D Delaunay Triangulation. To achieve it, this research designed an initial demonstration that, there is a maximum precision for which the network topology remains constant in a new Delaunay Triangulation, at each point and in the TIN as a whole. The methodological approach was experimental, with various mathematical experiments carried out using the Monte Carlo Simulation method. First, for each point of the network, and then for all network points for varied σ. The experiments culminate in helping to solve the problem of the existence of maximum σ for which the probability of occurrence in constant TIN topology is 100%. The mathematical results originated the following statement: Considering a TIN generated by Delaunay Triangulation, if any point of coordinates (x i , y i ) in a Triangular Irregular Network is disrupted (i.e., has its place altered), according to a Normal distribution N(μ, σ 2 ), then, exists a value σ max (sigma maximum) for which the topology of the network remains constant. For example, it was found that σ max.1 of one point exists and is obtained by σ max.1 = 0.30866, and at another point, σ max.2 = 0.2. The results also indicate the following for TIN: Every two-dimensional Triangular Irregular Network generated by the Delaunay Triangulation has a value σ * (sigma asterisk) to which the network topology remains constant. In this work, simulating the worst case of a Triangular Irregular Network: σ * = 0.2. Finally, it is concluded that the σ maximum for each point exists, as well as for the network as a whole. However, the results need to be tested in more extensive networks to prove (or not) if it always

show abstract

“…cluster analysis (Ahuja 1982), spatial interpolation (Watson 1992), maritime boundaries delimitation (Kastrisios and Tsoulos 2016), nearest service areas (Kastrisios and Tsoulos 2018), and cartographic generalization (Peters, Ledoux, and Meijers 2014).…”

Section: Background Informationmentioning

confidence: 99%

Towards automated validation of charted soundings: Existing tests and limitations

Kastrisios

Calder

Masetti

et al. 2019

Geo-spatial Information Science

Self Cite

View full text Add to dashboard Cite

The nautical chart is one of the fundamental tools in navigation used by mariners to plan and safely execute voyages. Its compilation follows strict cartographic constraints with the most prominent being that of the safety. Thereby, the cartographer is called to make the selection of the bathymetric information for portrayal on charts in a way that, at any location, the expected water depth is not deeper than the source information. To validate the shoal-biased pattern of selection two standard tests are used, i.e. the triangle and edge tests. To date, some efforts have been made towards the automation of the triangle test, but the edge test has been largely ignored. In the context of research on a fully automated solution for the compilation of charts at different scales from the source information, this paper presents an algorithmic implementation of the two tests for the validation of selected soundings. Through a case study with real-world data, it presents the improved performance of the implementation near and within depth curves and coastlines and points out the importance of the edge test in the validation process. It also presents the, by definition, intrinsic limitation of the two tests as part of a fully automated solution and discusses the need for a new test that will complement or supersede the existing ones.

show abstract

Voronoi tessellation on the ellipsoidal earth for vector data

Cited by 9 publications

References 26 publications

Automated map projection selection for GIS

Automated map projection selection for GIS

Simulação de Monte Carlo em redes triangulares irregulares / Monte Carlo simulation in triangular irregular networks

Towards automated validation of charted soundings: Existing tests and limitations

Contact Info

Product

Resources

About