GTECH 380/721 Introduction to Geovisualization Hunter College, CUNY Department of Geography
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Planar Maps: an Interaction Paradigm for Graphic Design
CH1'89 PROCEEDINGS MAY 1989 PLANAR MAPS: AN INTERACTION PARADIGM FOR GRAPHIC DESIGN Patrick Baudelaire Michel Gangnet Digital Equipment Corporation Pads Research Laboratory 85, Avenue Victor Hugo 92563 Rueil-Malmaison France In a world of changing taste one thing remains as a foundation for decorative design -- the geometry of space division. Talbot F. Hamlin (1932) ABSTRACT Compared to traditional media, computer illustration soft- Figure 1: Four lines or a rectangular area ? ware offers superior editing power at the cost of reduced free- Unfortunately, with typical drawing software this dual in- dom in the picture construction process. To reduce this dis- terpretation is not possible. The picture contains no manipu- crepancy, we propose an extension to the classical paradigm lable objects other than the four original lines. It is impossi- of 2D layered drawing, the map paradigm, that is conducive ble for the software to color the rectangle since no such rect- to a more natural drawing technique. We present the key angle exists. This impossibility is even more striking when concepts on which the new paradigm is based: a) graphical the four lines are abutting as in Fig. 2. We feel that such a objects, called planar maps, that describe shapes with multi- restriction, counter to the traditional practice of the designer, ple colors and contours; b) a drawing technique, called map is a hindrance to productivity and creativity. In this paper sketching, that allows the iterative construction of arbitrarily we propose a new drawing paradigm that will permit a dual complex objects. We also discuss user interface design is- interpretation of Fig. -
Texture / Image-Based Rendering Texture Maps
Texture / Image-Based Rendering Texture maps Surface color and transparency Environment and irradiance maps Reflectance maps Shadow maps Displacement and bump maps Level of detail hierarchy CS348B Lecture 12 Pat Hanrahan, Spring 2005 Texture Maps How is texture mapped to the surface? Dimensionality: 1D, 2D, 3D Texture coordinates (s,t) Surface parameters (u,v) Direction vectors: reflection R, normal N, halfway H Projection: cylinder Developable surface: polyhedral net Reparameterize a surface: old-fashion model decal What does texture control? Surface color and opacity Illumination functions: environment maps, shadow maps Reflection functions: reflectance maps Geometry: bump and displacement maps CS348B Lecture 12 Pat Hanrahan, Spring 2005 Page 1 Classic History Catmull/Williams 1974 - basic idea Blinn and Newell 1976 - basic idea, reflection maps Blinn 1978 - bump mapping Williams 1978, Reeves et al. 1987 - shadow maps Smith 1980, Heckbert 1983 - texture mapped polygons Williams 1983 - mipmaps Miller and Hoffman 1984 - illumination and reflectance Perlin 1985, Peachey 1985 - solid textures Greene 1986 - environment maps/world projections Akeley 1993 - Reality Engine Light Field BTF CS348B Lecture 12 Pat Hanrahan, Spring 2005 Texture Mapping ++ == 3D Mesh 2D Texture 2D Image CS348B Lecture 12 Pat Hanrahan, Spring 2005 Page 2 Surface Color and Transparency Tom Porter’s Bowling Pin Source: RenderMan Companion, Pls. 12 & 13 CS348B Lecture 12 Pat Hanrahan, Spring 2005 Reflection Maps Blinn and Newell, 1976 CS348B Lecture 12 Pat Hanrahan, Spring 2005 Page 3 Gazing Ball Miller and Hoffman, 1984 Photograph of mirror ball Maps all directions to a to circle Resolution function of orientation Reflection indexed by normal CS348B Lecture 12 Pat Hanrahan, Spring 2005 Environment Maps Interface, Chou and Williams (ca. -
Digital Mapping & Spatial Analysis
Digital Mapping & Spatial Analysis Zach Silvia Graduate Community of Learning Rachel Starry April 17, 2018 Andrew Tharler Workshop Agenda 1. Visualizing Spatial Data (Andrew) 2. Storytelling with Maps (Rachel) 3. Archaeological Application of GIS (Zach) CARTO ● Map, Interact, Analyze ● Example 1: Bryn Mawr dining options ● Example 2: Carpenter Carrel Project ● Example 3: Terracotta Altars from Morgantina Leaflet: A JavaScript Library http://leafletjs.com Storytelling with maps #1: OdysseyJS (CartoDB) Platform Germany’s way through the World Cup 2014 Tutorial Storytelling with maps #2: Story Maps (ArcGIS) Platform Indiana Limestone (example 1) Ancient Wonders (example 2) Mapping Spatial Data with ArcGIS - Mapping in GIS Basics - Archaeological Applications - Topographic Applications Mapping Spatial Data with ArcGIS What is GIS - Geographic Information System? A geographic information system (GIS) is a framework for gathering, managing, and analyzing data. Rooted in the science of geography, GIS integrates many types of data. It analyzes spatial location and organizes layers of information into visualizations using maps and 3D scenes. With this unique capability, GIS reveals deeper insights into spatial data, such as patterns, relationships, and situations - helping users make smarter decisions. - ESRI GIS dictionary. - ArcGIS by ESRI - industry standard, expensive, intuitive functionality, PC - Q-GIS - open source, industry standard, less than intuitive, Mac and PC - GRASS - developed by the US military, open source - AutoDESK - counterpart to AutoCAD for topography Types of Spatial Data in ArcGIS: Basics Every feature on the planet has its own unique latitude and longitude coordinates: Houses, trees, streets, archaeological finds, you! How do we collect this information? - Remote Sensing: Aerial photography, satellite imaging, LIDAR - On-site Observation: total station data, ground penetrating radar, GPS Types of Spatial Data in ArcGIS: Basics Raster vs. -
Geotime As an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations for the Boston Police Department Offeror: Uncharted Software Inc
GeoTime as an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations for the Boston Police Department Offeror: Uncharted Software Inc. 2 Berkeley St, Suite 600 Toronto ON M5A 4J5 Canada Business Type: Canadian Small Business Jurisdiction: Federally incorporated in Canada Date of Incorporation: October 8, 2001 Federal Tax Identification Number: 98-0691013 ATTN: Jenny Prosser, Contract Manager, [email protected] Subject: Acquiring Technology and Services of Social Media Threats for the Boston Police Department Uncharted Software Inc. (formerly Oculus Info Inc.) respectfully submits the following response to the Technology and Services of Social Media Threats RFP. Uncharted accepts all conditions and requirements contained in the RFP. Uncharted designs, develops and deploys innovative visual analytics systems and products for analysis and decision-making in complex information environments. Please direct any questions about this response to our point of contact for this response, Adeel Khamisa at 416-203-3003 x250 or [email protected]. Sincerely, Adeel Khamisa Law Enforcement Industry Manager, GeoTime® Uncharted Software Inc. [email protected] 416-203-3003 x250 416-708-6677 Company Proprietary Notice: This proposal includes data that shall not be disclosed outside the Government and shall not be duplicated, used, or disclosed – in whole or in part – for any purpose other than to evaluate this proposal. If, however, a contract is awarded to this offeror as a result of – or in connection with – the submission of this data, the Government shall have the right to duplicate, use, or disclose the data to the extent provided in the resulting contract. GeoTime as an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations 1. -
Arcgis® + Geotime®: GIS Technology to Support the Analysis Of
® ® In many application areas, this is not enough: Geo- spatial and temporal correlations between the data ArcGIS + GeoTime : GIS technology should be studied, so that, on the basis of this insight, the available data - more and more numerous - can to support the analysis of telephone be translated into knowledge and therefore in appropriate decisions . In the area of security, to name an example, all this results in the predictive traffic data analysis of the spatial-temporal occurrence of crimes. Lastly, a technologically advanced GIS platform must Giorgio Forti, Miriam Marta, Fabrizio Pauri ® ensure data sharing and enable the world of mobile devices (system of engagement). ® There are several ways to share data / information, all supported by ArcGIS, such as: sharing within a single Historical mobile phone traffic billboards analysis is organization, according to the profiles assigned becoming increasingly important in investigative Figure 2: Sample data representation of two (identity); the sharing of multiple organizations that activities of public security organizations around the cellphone users in GeoTime may / should share confidential data (a very common world, and leading technology companies have been situation in both Public Security and Emergency trying to respond to the strong demand for the most Other predefined analysis features are already Management); public communication, open to all (for suitable tools for supporting such activities. available (automatic cluster search, who attends sites example, to report investigative success, or to of investigation interest, mobility compatibility with communicate to citizens unsafe areas for the Originally developed as a project funded in the United participation in events, etc.), allowing considerable frequency of criminal offenses). -
Visual Highlighting Methods for Geovisualization
VISUAL HIGHLIGHTING METHODS FOR GEOVISUALIZATION Anthony C. Robinson GeoVISTA Center, Department of Geography 302 Walker Building The Pennsylvania State University University Park, PA 16802, USA [email protected] ABSTRACT A key advantage of interactive geovisualization tools is that users are able to quickly view data observations across multiple views. This is usually supported with a transient visual effect applied around the edges of an object during a mouse selection or rollover. This effect, commonly called highlighting, has not received much attention in geovisualization research. Today, most geovisualization tools rely on simple color-based highlighting. This paper proposes additional visual highlighting methods that could be used in geovisualizations. It also presents a typology of interactive highlighting behaviors that specify multiple ways in which highlighting techniques can be blended together or modified based on data values to enhance visual recognition in multiple coordinated view applications. INTRODUCTION The key analytical affordances of geovisualization tools include dynamic interactive behaviors and coordinated multiple views of geospatial data. Much attention in geovisualization research is devoted to developing new types of views, integrating new types of data, and designing customized systems for specific analytical tasks and domains (MacEachren and Kraak, 2001). This paper focuses on refining and extending the interactively-driven visual indication, known as highlighting, that allows users to make connections between data objects in multiple views in a geovisualization. As data and the number of views we use to explore those data become increasingly complicated (Andrienko et al., 2007), it is timely to consider new highlighting methods to ensure that visual discovery is efficient and effective. -
Techniques for Spatial Analysis and Visualization of Benthic Mapping Data: Final Report
Techniques for spatial analysis and visualization of benthic mapping data: final report Item Type monograph Authors Andrews, Brian Publisher NOAA/National Ocean Service/Coastal Services Center Download date 29/09/2021 07:34:54 Link to Item http://hdl.handle.net/1834/20024 TECHNIQUES FOR SPATIAL ANALYSIS AND VISUALIZATION OF BENTHIC MAPPING DATA FINAL REPORT April 2003 SAIC Report No. 623 Prepared for: NOAA Coastal Services Center 2234 South Hobson Avenue Charleston SC 29405-2413 Prepared by: Brian Andrews Science Applications International Corporation 221 Third Street Newport, RI 02840 TABLE OF CONTENTS Page 1.0 INTRODUCTION..........................................................................................1 1.1 Benthic Mapping Applications..........................................................................1 1.2 Remote Sensing Platforms for Benthic Habitat Mapping ..........................................2 2.0 SPATIAL DATA MODELS AND GIS CONCEPTS ................................................3 2.1 Vector Data Model .......................................................................................3 2.2 Raster Data Model........................................................................................3 3.0 CONSIDERATIONS FOR EFFECTIVE BENTHIC HABITAT ANALYSIS AND VISUALIZATION .........................................................................................4 3.1 Spatial Scale ...............................................................................................4 3.2 Habitat Scale...............................................................................................4 -
Connected 2D and 3D Visualizations for the Interactive Exploration of Spatial Information
CONNECTED 2D AND 3D VISUALIZATIONS FOR THE INTERACTIVE EXPLORATION OF SPATIAL INFORMATION S. Bleisch *, S. Nebiker FHNW, University of Applied Sciences Northwestern Switzerland, Institute of Geomatics Engineering, CH-4132 Muttenz, Switzerland - (susanne.bleisch, stephan.nebiker)@fhnw.ch KEY WORDS: Geovisualization, Three-dimensional representation, Interactive, Spatial Data Exploration, Virtual globe, Development ABSTRACT: This paper describes the concepts and the successful prototypal implementation of interactively connected 2D information visualizations and data displays in 3D virtual environments for the interactive exploration of spatial data and information. Virtual globes or earth viewers such as Google Earth have become very popular over the last few years. They are used for looking at holiday destinations but more importantly also for scientific visualizations. From a geovisualization point of view we might regard 3D data or information displays as yet another representation type that adds to the multitude of information visualization methods. Combining 3D views of data sets with traditional 2D displays offers the advantage of being able to use 3D if and when this type of representation is considered useful or effective for finding new insights into a data set. The traditional and newer displays of mainly 2D information visualization may be enhanced and new insights into the data may be generated by displays of the data in a 3D virtual environment. On the other hand, data in 3D displays might be better understood by simultaneously reading and querying connected 2D representations.The paper presents a prototypal implementation of the interactively connected visualizations of spatial information in 2D views and 3D virtual environments using the brushing technique. -
(Geo-)Visualization
Geographic Data Science - Lecture III (Geo-)Visualization Dani Arribas-Bel Today Visualization What and why History Examples Geovisualization What "A map for everyone" Dangers of geovisualization Visualization "Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, and color." The Visual Display of Quantitative Information. Edward R. Tufte. [Source] [Source] A bit of history Maps A bit of history Maps --> Data Maps (XVIIth.C.) A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) --> Scatter plots A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) --> Scatter plots Surprisingly recent: 1750-1800 approx. (much later than many other advances in math and stats!) William Playfair's "linear arithmetic": encode/replace numbers in tables into visual representations. Other relevant names throughout history: Lambert, Minard, Marey. Visualization The Visual Display of Quantitative Information. Edward R. Tufte. By encoding information visually, they allow to present large amounts of numbers in a meaninful way. If well made, visualizations provide leads into the processes underlying the graphic. Learning by seeing time... Time series [Source] XVIIIth. Cent. - Pytometrie by J. H Lambert Bar chart [Source] Playfair's bar chart in The Commercial and Political Atlas (1786) Abstract line plot [Source] Lambert - Evaporation rate against temperature, 1769 Minard - Napoleon army map (XIXth. Cent.) [Source] "It may well be the best statistical graphic ever drawn" (E. R. Tufte) Geovisualization Tufte (1983) "The most extensive data maps [...] place millions of bits of information on a single page before our eyes. -
Geovisualization: Integration and Visualization of Multiple Datasets Using Mapbox Cecilia Cadenas California Polytechnic State University, San Luis Obispo
Geovisualization: Integration and Visualization of Multiple Datasets Using Mapbox Cecilia Cadenas California Polytechnic State University, San Luis Obispo Abstract—The use of geovisualizations to different from information visualization dealing analyze multiple datasets can ease the with abstract data spaces. [3] research and investigation to find B. Mapbox & TileMill correlations between these datasets. However, making these visualizations with The creation of these visualizations can be multiple datasets can be challenging due to challenging due to the complexity and the lack of standardization within file formats differences between the geographical data types, and the software needed to render the and how easily they can be accessed and used. visualizations. In order to help with the creation of these visualizations, many cartographers and software This project investigates the making of engineers have created many different tools that these visualizations, maps in this case, using can make the creation of these visualizations an open source platforms like Mapbox. Using easier and accessible to anyone with a computer. Python scripts for the data parsing, For the creation of the maps in this project, CartoCSS for the designing of the maps, one of these tools was used. After some research JavaScript to make the maps interactive, and and testing different tools and platforms, HTML to combine all the layers together a Mapbox was selected as the best option for the set of maps were created. These maps customization level needed for the maps wanted. contained data regarding tons of wine grape Mapbox is an online platform that makes the data crushed and yearly heat accumulation viewing of these maps simple across multiple during the growing season that demonstrate platforms since it requires no extra software to how combining multiple data sets can lead to be downloaded. -
What Is Geovisualization? to the Growing Field of Geovisualization
This issue of GeoMatters is devoted What is Geovisualization? to the growing field of geovisualization. Brian McGregor uses geovisualiztion to by Joni Storie produce animated maps showing settle- ment patterns of Hutterite colonies. Dr. Marc Vachon’s students use it to produce From a cartography perspective, dynamic presentation options to com- videos about urban visualization (City geovisualization represents a change in municate knowledge. For example, at- Hall and Assiniboine Park), while Dr. how knowledge is formed and repre- lases require extra planning compared Chris Storie shows geovisualiztion for sented. Traditional cartography is usu- to individual maps, structurally they retail mapping in Winnipeg. Also in this issue Honours students describe their ally seen a visualization (a.k.a. map) could include hundreds of maps, and thesis projects for the upcoming collo- that is presented after the conclusion all the maps relate to each other. Dr. quium next March, Adrienne Ducharme is reached to emphasize or compliment Danny Blair and Dr. Ian Mauro, in the tells us about her graduate research at the research conclusions. Geovisual- Department of Geography, provide an ELA, we have a report about Cultivate ization changes this format by incor- excellent example of this integration UWinnipeg and our alumni profile fea- porating spatial data into the analysis with the Prairie Climate Atlas (http:// tures Michelle Méthot (Smith). (O’Sullivan and Unwin, 2010). Spatial www.climateatlas.ca/). The combina- Please feel free to pass this newsletter data, statistics and analysis are used to tion of maps with multimedia provides to anyone with an interest in geography. answer questions which contribute to for better understanding as well as en- Individuals can also see GeoMatters at the Geography website, or keep up with the conclusion that is reached within riched and informative experiences of us on Facebook (Department of Geog- the research. -
Visual Bandwidth Selection for Kernel Density Maps
Photogrammetrie • Fernerkundung • Geoinformation 5/2009, S. 445–454 Visual Bandwidth Selection for Kernel Density Maps Jukka M. krisp, stefan peters,Christian e. Murphy & hongChao fan, München Keywords: Kernel Density, Visualization, Visual Analytics, Geostatistics, Kernel Bandwidth, Cartography Summary: Within this paper we investigate the Zusammenfassung: Visuelle Radius Festlegung challenge to find an appropriate bandwidth in ker- für Kernel Dichte Abschätzungen. In dieser Arbeit nel density estimation. Kernel density estimation untersuchen wir die Möglichkeiten, um einen ange- methods can be used in visualizing and analyzing messenen Radius in der Kernel-Dichte Schätzung spatial data, with the objective of understanding zu erhalten. Kernel-Dichte Schätzung Methoden and potentially predicting event patterns. Our aim können in der Visualisierung und Analyse räumli- is to provide a computational tool to visually select cher Daten zum Verständnis und zur Vorhersage the bandwidth parameter and to visually investi- von räumlichen Mustern dienen. Unser Ziel ist es, gate the effect of different parameters within the ein Computer-Werkzeug zur visuellen Parameter kernel density calculations. With this tool the user Bestimmung zu entwickeln. Die Radien verschie- is able to visually find the most appropriate band- deneR Kernel werden visuell geprüft und können width foR the particular dataset and scale. The slid- experimentell untersucht werden. Mit diesem er-tool includes a graphical user interface and can Werkzeug kann der Anwender den am besten ge- read point datasets. A specific number of kernel eigneten Radius für den jeweiligen Datensatz be- density maps are generated by using a range of stimmen. Das Schieberegler-Werkzeug beinhaltet bandwidths. In the graphical interface these kernel eine grafische Benutzeroberfläche und kann Punkt- density maps can be drawn near real-time while the datensätze einladen.