14 results match your criteria Cartography And Geographic Information Science[Journal]

  • Page 1 of 1

Composition of place: towards a compositional view of functional space.

Cartogr Geogr Inf Sci 2020 6;47(1):28-45. Epub 2019 Jun 6.

Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.

A long-standing question in GIScience is whether geographic information systems (GIS) facilitates an adequate quantifiable representation of the concept of place. Considering the difficulties of quantifying elusive concepts related to place, several researchers focus on more tangible dimensions of the human understanding of place. The most common approaches are semantic enrichment of spatial information and holistic conceptualization of the notion of place. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2019.1598894DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6999190PMC

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies.

Cartogr Geogr Inf Sci 2018 30;45(3):205-220. Epub 2017 Mar 30.

Doctoral College GIScience, Department of Geoinformatics-Z_GIS, University of Salzburg, Austria.

Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2017.1304243DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978938PMC
March 2017
1 Read

A heuristic multi-criteria classification approach incorporating data quality information for choropleth mapping.

Cartogr Geogr Inf Sci 2017 25;44(3):246-258. Epub 2016 Feb 25.

Department of Geology/Geography, Eastern Illinois University, Charleston, IL, USA.

Despite conceptual and technology advancements in cartography over the decades, choropleth map design and classification fail to address a fundamental issue: estimates that are statistically indifferent may be assigned to different classes on maps or vice versa. Recently, the class separability concept was introduced as a map classification criterion to evaluate the likelihood that estimates in two classes are statistical different. Unfortunately, choropleth maps created according to the separability criterion usually have highly unbalanced classes. Read More

View Article

Download full-text PDF

Source
https://www.tandfonline.com/doi/full/10.1080/15230406.2016.1
Publisher Site
http://dx.doi.org/10.1080/15230406.2016.1145072DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5342899PMC
February 2016
13 Reads

Spatial Collective Intelligence? credibility, accuracy, and Volunteered Geographic Information.

Authors:
Seth E Spielman

Cartogr Geogr Inf Sci 2014 ;41(2):115-124

Department of Geography, University of Colorado, 110 Guggenheim Hall/260 UCB, Boulder, CO, USA.

Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group (Suroweiki 2004), that is a group has an "intelligence" that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of "volunteered" or crowdsourced geographic information. Literature from a variety of fields makes clear that not all groups possess collective intelligence, this paper identifies four pre-conditions for the emergence of collective intelligence and then examine the extent to which collectively generated mapping systems satisfy these conditions. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2013.874200DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4238431PMC
January 2014
4 Reads

How to compare movement? A review of physical movement similarity measures in geographic information science and beyond.

Cartogr Geogr Inf Sci 2014 May 7;41(3):286-307. Epub 2014 Mar 7.

Fraunhofer FKIE , Fraunhoferstr. 20, 53343 Wachtberg , Germany.

In geographic information science, a plethora of different approaches and methods is used to assess the similarity of movement. Some of these approaches term two moving objects similar if they share akin paths. Others require objects to move at similar speed and yet others consider movement similar if it occurs at the same time. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2014.890071DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786848PMC
May 2014
1 Read

Geo-located Twitter as proxy for global mobility patterns.

Cartogr Geogr Inf Sci 2014 May 26;41(3):260-271. Epub 2014 Feb 26.

SENSEable City Laboratory, Massachusetts Institute of Technology , Cambridge , MA , USA.

Pervasive presence of location-sharing services made it possible for researchers to gain an unprecedented access to the direct records of human activity in space and time. This article analyses geo-located Twitter messages in order to uncover global patterns of human mobility. Based on a dataset of almost a billion tweets recorded in 2012, we estimate the volume of international travelers by country of residence. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2014.890072DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786829PMC
May 2014
4 Reads

The GeoCitizen-approach: community-based spatial planning - an Ecuadorian case study.

Cartogr Geogr Inf Sci 2014 May 10;41(3):248-259. Epub 2014 Mar 10.

Universidad San Francisco de Quito , Av. Diego de Robles y Via Interoceánica, Cumbaya , Ecuador.

Over the last years, geospatial web platforms, social media, and volunteered geographic information (VGI) have opened a window of opportunity for traditional Public Participatory GIS (PPGIS) to usher in a new era. Taking advantage of these technological achievements, this paper presents a new approach for a citizen-orientated framework of spatial planning that aims at integrating participatory community work into existing decision-making structures. One major cornerstone of the presented approach is the application of a social geoweb platform (the platform) that combines geo-web technologies and social media in one single tool allowing citizens to collaboratively report observations, discuss ideas, solve, and monitor problems in their living environment at a local level. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2014.890546DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786845PMC
May 2014
1 Read

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts.

Authors:
Dirk Tiede

Cartogr Geogr Inf Sci 2014 May 28;41(3):227-234. Epub 2014 Mar 28.

Department of Geoinformatics - Z_GIS, University of Salzburg , Schillerstr. 30, 5020 Salzburg , Austria.

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is - if at all - calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from-to class intersection. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2014.901900DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786846PMC
May 2014
4 Reads

What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System.

Cartogr Geogr Inf Sci 2013 ;40(2):90-102

( ), NIH Center for Advancing Translational Science, Rockville, MD, 20850.

Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1080/15230406.2013.776210DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4128420PMC
January 2013
18 Reads

Bicomponent Trend Maps: A Multivariate Approach to Visualizing Geographic Time Series.

Cartogr Geogr Inf Sci 2010 Jul;37(3):169-187

Minnesota Population Center, University of Minnesota, 225 19 Avenue South, Minneapolis, MN 55455.

The most straightforward approaches to temporal mapping cannot effectively illustrate all potentially significant aspects of spatio-temporal patterns across many regions and times. This paper introduces an alternative approach, bicomponent trend mapping, which employs a combination of principal component analysis and bivariate choropleth mapping to illustrate two distinct dimensions of long-term trend variations. The approach also employs a bicomponent trend matrix, a graphic that illustrates an array of typical trend types corresponding to different combinations of scores on two principal components. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1559/152304010792194930DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3595555PMC
July 2010
3 Reads

Delineating West Nile Virus Transmission Cycles at Various Scales: The Nearest Neighbor Distance-Time Model.

Cartogr Geogr Inf Sci 2010 Apr;37(2):149-163

Department of Geography, 413 McGilvrey Hall, Kent State University, Kent, OH 44242. < >.

Various approaches are used to identify West Nile virus (WNV) exposure areas, including unusual sightings of infected dead birds, mosquito pools or human cases both prospectively and retrospectively. A significant and largely unmet need in WNV research is to incorporate the temporal characterization of virus spread and locational information of the three components of transmission cycle-i.e. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1559/152304010791232208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491911PMC
April 2010
4 Reads

Supporting the Process of Exploring and Interpreting Space-Time Multivariate Patterns: The Visual Inquiry Toolkit.

Cartogr Geogr Inf Sci 2008 Jan;35(1):33-50

Jin Chen and Alan M. MacEachren, GeoVISTA Center and Department of Geography, Pennsylvania State University, 302 Walker Building, University Park, Pennsylvania16802. Email:< >;< >. Tel: 814-865-1633;

While many data sets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and tool scalability issues. This study develops a visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets. We develop and apply a variety of methods for data clustering, pattern searching, information visualization, and synthesis. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1559/152304008783475689DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2786075PMC
January 2008
2 Reads
4 Citations

Combining Usability Techniques to Design Geovisualization Tools for Epidemiology.

Cartogr Geogr Inf Sci 2005 Oct;32(4):243-255

GeoVISTA Center, Department of Geography, 302 Walker Building, The Pennsylvania State University University Park, PA 16802, USA. Tel: (814-865-3433);

Designing usable geovisualization tools is an emerging problem in GIScience software development. We are often satisfied that a new method provides an innovative window on our data, but functionality alone is insufficient assurance that a tool is applicable to a problem in situ. As extensions of the static methods they evolved from, geovisualization tools are bound to enable new knowledge creation. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1559/152304005775194700DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2786201PMC
October 2005
7 Reads

Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach.

Cartogr Geogr Inf Sci 2005 Apr;32(2):113-132

Department of Geography, University of South Carolina, 709 Bull Street, Columbia, SC 29208. E-mail: < >

The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial patterns. The integrated approach is able to: (1) perform multivariate analysis, dimensional reduction, and data reduction (summarizing a large number of input data items in a moderate number of clusters) with the Self-Organizing Map (SOM); (2) encode the SOM result with a systematically designed color scheme; (3) visualize the multivariate patterns with a modified Parallel Coordinate Plot (PCP) display and a geographic map (GeoMap); and (4) support human interactions to explore and examine patterns. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1559/1523040053722150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2786224PMC
April 2005
13 Reads
8 Citations
  • Page 1 of 1