Erik W. Grafarend Friedrich W. Krumm Map Projections Erik W
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A Law and Order Question
ALawandorder Relation preserving maps. Symmetric relations, asymmetric relations, and antisymmetry. The Cartesian product and the Venn diagram. Euler circles, power sets, partitioning or fibering. A-1 Law and order: Cartesian product, power sets In daily life, we make comparisons of type ... is higher than ... is smarter than ... is faster than .... Indeed, we are dealing with order. Mathematically speaking, order is a binary relation of type −1 xR1y : x<y (smaller than) , xR3y : x>y (larger than, R3 = R ) , 1 (A.1) ≤ ≥ −1 xR2y : x y (smaller-equal) , xR4y : x y (larger-equal, R4 = R2 ) . Example A.1 (Real numbers). x and y, for instance, can be real numbers: x, y ∈ R. End of Example. Question: “What is a relation?” Answer: “Let us explain the term relation in the frame of the following example.” Question. Example A.2 (Cartesian product). Define the left set A = {a1,a2,a3} as the set of balls in a left basket, and {a1,a2,a3} = {red,green,blue}. In contrast, the right set B = {b1,b2} as the set of balls in a right basket, and {b1,b2} = {yellow,pink}. Sequentically, we take a ball from the left basket as well as from the right basket such that we are led to the combinations A × B = (a1,b1) , (a1,b2) , (a2,b1) , (a2,b2) , (a3,b1) , (a3,b2) , (A.2) A × B = (red,yellow) , (red,pink) , (green,yellow) , (green,pink) , (blue,yellow) , (green,pink) . (A.3) End of Example. Definition A.1 (Reflexive partial order). Let M be a non-empty set. The binary relation R2 on M is called reflexive partial order if for all x, y, z ∈ M the following three conditions are fulfilled: (i) x ≤ x (reflexivity) , (ii) if x ≤ y and y ≤ x,thenx = y (antisymmetry) , (A.4) (iii) if x ≤ y and y ≤ z,thenx ≤ z (transitivity) . -
5–21 5.5 Miscellaneous Projections GMT Supports 6 Common
GMT TECHNICAL REFERENCE & COOKBOOK 5–21 5.5 Miscellaneous Projections GMT supports 6 common projections for global presentation of data or models. These are the Hammer, Mollweide, Winkel Tripel, Robinson, Eckert VI, and Sinusoidal projections. Due to the small scale used for global maps these projections all use the spherical approximation rather than more elaborate elliptical formulae. 5.5.1 Hammer Projection (–Jh or –JH) The equal-area Hammer projection, first presented by Ernst von Hammer in 1892, is also known as Hammer-Aitoff (the Aitoff projection looks similar, but is not equal-area). The border is an ellipse, equator and central meridian are straight lines, while other parallels and meridians are complex curves. The projection is defined by selecting • The central meridian • Scale along equator in inch/degree or 1:xxxxx (–Jh), or map width (–JH) A view of the Pacific ocean using the Dateline as central meridian is accomplished by running the command pscoast -R0/360/-90/90 -JH180/5 -Bg30/g15 -Dc -A10000 -G0 -P -X0.1 -Y0.1 > hammer.ps 5.5.2 Mollweide Projection (–Jw or –JW) This pseudo-cylindrical, equal-area projection was developed by Mollweide in 1805. Parallels are unequally spaced straight lines with the meridians being equally spaced elliptical arcs. The scale is only true along latitudes 40˚ 44' north and south. The projection is used mainly for global maps showing data distributions. It is occasionally referenced under the name homalographic projection. Like the Hammer projection, outlined above, we need to specify only -
A Pipeline for Producing a Scientifically Accurate Visualisation of the Milky
A pipeline for producing a scientifically accurate visualisation of the Milky Way M´arciaBarros1;2, Francisco M. Couto2, H´elderSavietto3, Carlos Barata1, Miguel Domingos1, Alberto Krone-Martins1, and Andr´eMoitinho1 1 CENTRA, Faculdade de Ci^encias,Universidade de Lisboa, Portugal 2 LaSIGE, Faculdade de Ci^encias,Universidade de Lisboa, Portugal 3 Fork Research, R. Cruzado Osberno, 1, 9 Esq, Lisboa, Portugal [email protected] Abstract. This contribution presents the design and implementation of a pipeline for producing scientifically accurate visualisations of Big Data. As a case study, we address the data archive produced by the European Space Agency's (ESA) Gaia mission. The satellite was launched in Dec 19 2013 and is repeatedly monitoring almost two billion (2000 million) astronomical sources during five years. By the end of the mission, Gaia will have produced a data archive of almost a Petabyte. Producing visually intelligible representations of such large quantities of data meets several challenges. Situations such as cluttering, overplot- ting and overabundance of features must be dealt with. This requires careful choices of colourmaps, transparencies, glyph sizes and shapes, overlays, data aggregation and feature selection or extraction. In addi- tion, best practices in information visualisation are sought. These include simplicity, avoidance of superfluous elements and the goal of producing esthetical pleasing representations. Another type of challenge comes from the large physical size of the archive, which makes it unworkable (or even impossible) to transfer and process the data in the user's hardware. This requires systems that are deployed at the archive infrastructure and non-brute force approaches. Because the Gaia first data release will only happen in September 2016, we present the results of visualising two related data sets: the Gaia Uni- verse Model Snapshot (Gums), which is a simulation of Gaia-like data; the Initial Gaia Source List (IGSL) which provides initial positions of stars for the satellite's data processing algorithms. -
A Bevy of Area Preserving Transforms for Map Projection Designers.Pdf
Cartography and Geographic Information Science ISSN: 1523-0406 (Print) 1545-0465 (Online) Journal homepage: http://www.tandfonline.com/loi/tcag20 A bevy of area-preserving transforms for map projection designers Daniel “daan” Strebe To cite this article: Daniel “daan” Strebe (2018): A bevy of area-preserving transforms for map projection designers, Cartography and Geographic Information Science, DOI: 10.1080/15230406.2018.1452632 To link to this article: https://doi.org/10.1080/15230406.2018.1452632 Published online: 05 Apr 2018. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=tcag20 CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE, 2018 https://doi.org/10.1080/15230406.2018.1452632 A bevy of area-preserving transforms for map projection designers Daniel “daan” Strebe Mapthematics LLC, Seattle, WA, USA ABSTRACT ARTICLE HISTORY Sometimes map projection designers need to create equal-area projections to best fill the Received 1 January 2018 projections’ purposes. However, unlike for conformal projections, few transformations have Accepted 12 March 2018 been described that can be applied to equal-area projections to develop new equal-area projec- KEYWORDS tions. Here, I survey area-preserving transformations, giving examples of their applications and Map projection; equal-area proposing an efficient way of deploying an equal-area system for raster-based Web mapping. projection; area-preserving Together, these transformations provide a toolbox for the map projection designer working in transformation; the area-preserving domain. area-preserving homotopy; Strebe 1995 projection 1. Introduction two categories: plane-to-plane transformations and “sphere-to-sphere” transformations – but in quotes It is easy to construct a new conformal projection: Find because the manifold need not be a sphere at all. -
View Preprint
1 Remaining gaps in open source software 2 for Big Spatial Data 1 3 Lu´ısM. de Sousa 1ISRIC - World Soil Information, 4 Droevendaalsesteeg 3, Building 101 6708 PB Wageningen, The Netherlands 5 Corresponding author: 1 6 Lu´ıs M. de Sousa 7 Email address: [email protected] 8 ABSTRACT 9 The volume and coverage of spatial data has increased dramatically in recent years, with Earth observa- 10 tion programmes producing dozens of GB of data on a daily basis. The term Big Spatial Data is now 11 applied to data sets that impose real challenges to researchers and practitioners alike. As rule, these 12 data are provided in highly irregular geodesic grids, defined along equal intervals of latitude and longitude, 13 a vastly inefficient and burdensome topology. Compounding the problem, users of such data end up 14 taking geodesic coordinates in these grids as a Cartesian system, implicitly applying Marinus of Tyre’s 15 projection. 16 A first approach towards the compactness of global geo-spatial data is to work in a Cartesian system 17 produced by an equal-area projection. There are a good number to choose from, but those supported 18 by common GIS software invariably relate to the sinusoidal or pseudo-cylindrical families, that impose 19 important distortions of shape and distance. The land masses of Antarctica, Alaska, Canada, Greenland 20 and Russia are particularly distorted with such projections. A more effective approach is to store and 21 work with data in modern cartographic projections, in particular those defined with the Platonic and 22 Archimedean solids. -
Portraying Earth
A map says to you, 'Read me carefully, follow me closely, doubt me not.' It says, 'I am the Earth in the palm of your hand. Without me, you are alone and lost.’ Beryl Markham (West With the Night, 1946 ) • Map Projections • Families of Projections • Computer Cartography Students often have trouble with geographic names and terms. If you need/want to know how to pronounce something, try this link. Audio Pronunciation Guide The site doesn’t list everything but it does have the words with which you’re most likely to have trouble. • Methods for representing part of the surface of the earth on a flat surface • Systematic representations of all or part of the three-dimensional Earth’s surface in a two- dimensional model • Transform spherical surfaces into flat maps. • Affect how maps are used. The problem: Imagine a large transparent globe with drawings. You carefully cover the globe with a sheet of paper. You turn on a light bulb at the center of the globe and trace all of the things drawn on the globe onto the paper. You carefully remove the paper and flatten it on the table. How likely is it that the flattened image will be an exact copy of the globe? The different map projections are the different methods geographers have used attempting to transform an image of the spherical surface of the Earth into flat maps with as little distortion as possible. No matter which map projection method you use, it is impossible to show the curved earth on a flat surface without some distortion. -
Adaptive Composite Map Projections
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 18, NO. 12, DECEMBER 2012 2575 Adaptive Composite Map Projections Bernhard Jenny Abstract—All major web mapping services use the web Mercator projection. This is a poor choice for maps of the entire globe or areas of the size of continents or larger countries because the Mercator projection shows medium and higher latitudes with extreme areal distortion and provides an erroneous impression of distances and relative areas. The web Mercator projection is also not able to show the entire globe, as polar latitudes cannot be mapped. When selecting an alternative projection for information visualization, rivaling factors have to be taken into account, such as map scale, the geographic area shown, the mapʼs height-to-width ratio, and the type of cartographic visualization. It is impossible for a single map projection to meet the requirements for all these factors. The proposed composite map projection combines several projections that are recommended in cartographic literature and seamlessly morphs map space as the user changes map scale or the geographic region displayed. The composite projection adapts the mapʼs geometry to scale, to the mapʼs height-to-width ratio, and to the central latitude of the displayed area by replacing projections and adjusting their parameters. The composite projection shows the entire globe including poles; it portrays continents or larger countries with less distortion (optionally without areal distortion); and it can morph to the web Mercator projection for maps showing small regions. Index terms—Multi-scale map, web mapping, web cartography, web map projection, web Mercator, HTML5 Canvas. -
Cylindrical Projections 27
MAP PROJECTION PROPERTIES: CONSIDERATIONS FOR SMALL-SCALE GIS APPLICATIONS by Eric M. Delmelle A project submitted to the Faculty of the Graduate School of State University of New York at Buffalo in partial fulfillments of the requirements for the degree of Master of Arts Geographical Information Systems and Computer Cartography Department of Geography May 2001 Master Advisory Committee: David M. Mark Douglas M. Flewelling Abstract Since Ptolemeus established that the Earth was round, the number of map projections has increased considerably. Cartographers have at present an impressive number of projections, but often lack a suitable classification and selection scheme for them, which significantly slows down the mapping process. Although a projection portrays a part of the Earth on a flat surface, projections generate distortion from the original shape. On world maps, continental areas may severely be distorted, increasingly away from the center of the projection. Over the years, map projections have been devised to preserve selected geometric properties (e.g. conformality, equivalence, and equidistance) and special properties (e.g. shape of the parallels and meridians, the representation of the Pole as a line or a point and the ratio of the axes). Unfortunately, Tissot proved that the perfect projection does not exist since it is not possible to combine all geometric properties together in a single projection. In the twentieth century however, cartographers have not given up their creativity, which has resulted in the appearance of new projections better matching specific needs. This paper will review how some of the most popular world projections may be suited for particular purposes and not for others, in order to enhance the message the map aims to communicate. -
MA3D9: Geometry of Curves and Surfaces
Geometry of Curves and Surfaces Weiyi Zhang Mathematics Institute, University of Warwick November 20, 2020 2 Contents 1 Curves 5 1.1 Course description . .5 1.1.1 A bit preparation: Differentiation . .6 1.2 Methods of describing a curve . .8 1.2.1 Fixed coordinates . .8 1.2.2 Moving frames: parametrized curves . .8 1.2.3 Intrinsic way(coordinate free) . .9 n 1.3 Curves in R : Arclength Parametrization . 11 1.4 Curvature . 13 1.5 Orthonormal frame: Frenet-Serret equations . 16 1.6 Plane curves . 18 1.7 More results for space curves . 20 1.7.1 Taylor expansion of a curve . 21 1.7.2 Fundamental Theorem of the local theory of curves . 21 1.8 Isoperimetric Inequality . 23 1.9 The Four Vertex Theorem . 25 3 2 Surfaces in R 29 2.1 Definitions and Examples . 29 2.1.1 Compact surfaces . 32 2.1.2 Level sets . 33 2.2 The First Fundamental Form . 34 2.3 Length, Angle, Area . 35 2.3.1 Length: Isometry . 36 2.3.2 Angle: conformal . 37 2.3.3 Area: equiareal . 37 2.4 The Second Fundamental Form . 38 2.4.1 Normals and orientability . 39 2.4.2 Gauss map and second fundamental form . 40 2.5 Curvatures . 42 2.5.1 Definitions and first properties . 42 2.5.2 Calculation of Gaussian and mean curvatures . 45 2.5.3 Principal curvatures . 47 3 4 CONTENTS 2.6 Gauss's Theorema Egregium . 49 2.6.1 Compatibility equations . 52 2.6.2 Gaussian curvature for special cases . -
Gaia Data Release 1: the Archive Visualisation Service A
Astronomy & Astrophysics manuscript no. arxiv c ESO 2017 August 2, 2017 Gaia Data Release 1: The archive visualisation service A. Moitinho1, A. Krone-Martins1, H. Savietto2, M. Barros1, C. Barata1, A.J. Falcão3, T. Fernandes3, J. Alves4, A.F. Silva1, M. Gomes1, J. Bakker5, A.G.A. Brown6, J. González-Núñez7; 8, G. Gracia-Abril9; 10, R. Gutiérrez-Sánchez11, J. Hernández12, S. Jordan13, X. Luri10, B. Merin5, F. Mignard14, A. Mora15, V. Navarro5, W. O’Mullane12, T. Sagristà Sellés13, J. Salgado16, J.C. Segovia7, E. Utrilla15, F. Arenou17, J.H.J. de Bruijne18, F. Jansen19, M. McCaughrean20, K.S. O’Flaherty21, M.B. Taylor22, and A. Vallenari23 (Affiliations can be found after the references) Received date / Accepted date ABSTRACT Context. The first Gaia data release (DR1) delivered a catalogue of astrometry and photometry for over a billion astronomical sources. Within the panoply of methods used for data exploration, visualisation is often the starting point and even the guiding reference for scientific thought. However, this is a volume of data that cannot be efficiently explored using traditional tools, techniques, and habits. Aims. We aim to provide a global visual exploration service for the Gaia archive, something that is not possible out of the box for most people. The service has two main goals. The first is to provide a software platform for interactive visual exploration of the archive contents, using common personal computers and mobile devices available to most users. The second aim is to produce intelligible and appealing visual representations of the enormous information content of the archive. Methods. The interactive exploration service follows a client-server design. -
Map Projections
Map Projections Map Projections A Reference Manual LEV M. BUGAYEVSKIY JOHN P. SNYDER CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business Published in 1995 by CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 1995 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group No claim to original U.S. Government works Printed in the United States of America on acid-free paper 1 International Standard Book Number-10: 0-7484-0304-3 (Softcover) International Standard Book Number-13: 978-0-7484-0304-2 (Softcover) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Catalog record is available from the Library of Congress Visit the Taylor & Francis Web site at http ://www. -
Adaptive Composite Map Projections in D3 Sukolsak Sakshuwong Gabor Angeli [email protected] [email protected]
Adaptive Composite Map Projections in D3 Sukolsak Sakshuwong Gabor Angeli [email protected] [email protected] ABSTRACT Selecting a map projection for a visualization is a challenging problem, as different projections are better suited for differ- ent purposes, and in particular for different scales. We im- plemented as an extension to D3 a recent paper on the topic, which produces a composite projection between zoom lev- els and latitudes. The implementation ensures that a reason- able projection is chosen for any given reference frame, and that the transition between these projections is seamless. We extended the method in the paper in two key ways: (1) We interpolate paths and handle edge cases more robustly than the paper’s proof-of-concept implementation, and (2) We im- plemented smooth animations between map locations which provide global context for the move. A demo can be found online at http://jitouch.com/map. INTRODUCTION A significant challenge in selecting an appropriate map pro- jection, and parametrization for that projection, for visualiz- ing geographic data. As no projection is good in every aspect, competing criteria include: • Equal area: A projection should preserve the areas of a polynomial. For instance, the Mercator projection presents Figure 1. A screenshot of our demo. The top screen shows the view that inaccurate areas near the poles. In contrast, projections the user of the map projection would see; the bottom screen shows the such as the Hammer, Lambert Azimuthal, or the Albers projection as it would look from a global perspective. The particular Conic projection preserve area. view being shown is an interpolated projection between Albers Conic and Mercator, centered on San Francisco.