@article{
 title = {Introducing GeoVISTA Studio: an integrated suite of visualization and computational methods for exploration and knowledge construction in geography},
 type = {article},
 year = {2002},
 keywords = {EDA,ESDA,Geocomputation,Visualization,classification,exploratory data analysis,geographic visualization,inference mechanisms,knowledge discovery},
 volume = {26},
 id = {ba70ae04-42c1-3725-8d9b-11931ba79f9d},
 created = {2018-05-29T14:06:05.807Z},
 file_attached = {false},
 profile_id = {6d8d7993-9618-3f6c-983a-9f6761313797},
 group_id = {4f1d95d1-59ee-3ce8-85ce-055cfae2da74},
 last_modified = {2018-05-29T14:06:05.807Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {13764},
 source_type = {article},
 private_publication = {false},
 abstract = {One barrier to the uptake of geocomputation is that, unlike GIS, it has no system or toolbox that provides easy accessto useful functionality. This paper describes an experimental environment, GeoVISTA Studio, that attempts to addressthis shortcoming. Studio is a Java-based, visual programming environment that allows for the rapid development ofcomplex data exploration and knowledge construction applications to support geographic analysis. It achieves this byleveraging advances in geocomputation, software engineering, visualization and machine learning. At the time of writing,Studio contains full 3D rendering capability and has the following functionality: interactive parallel coordinate plots,scatterplot, visual classifier, 2D map and image viewer, sophisticated colour selection (including Munsell colour-space),spreadsheet, statistics package, and supervised and unsupervised neural networks. Through examples of Studio atwork, this paper demonstrates the roles that geocomputation and visualization can play throughout the scientific cycle ofknowledge creation, emphasising their supportive and mutually beneficial relationship. A brief overview of differenttypes of inference used in such knowledge creation activities is given, and related to the exploratory analysis toolsdescribed. By way of results, a detailed account of the use of these tools is presented, and various findings and insightsgenerated are pointed out. The domain of application is the process of uncovering useful categories by which ataxonomy of landuse/landcover can be created. The proposed categories are then evaluated using a combination ofneural and visual methods, to ensure their viability.},
 bibtype = {article},
 author = {Mark, Gahegan and Takatsuka, M and Mike, Wheeler and Hardisty, F},
 journal = {Computers, Environment and Urban SystemsComputers, Environment and urban Systems}
}

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