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ISPRS Int. J. Geo-Inf. 2018, 7(8), 288; https://doi.org/10.3390/ijgi7080288

Task-Oriented Visualization Approaches for Landscape and Urban Change Analysis

Lab for Geoinformatics and Geovisualization (g2lab), HafenCity University Hamburg, Überseeallee 16, 20457 Hamburg, Germany
Received: 7 May 2018 / Revised: 13 July 2018 / Accepted: 20 July 2018 / Published: 24 July 2018
(This article belongs to the Special Issue Historic Settlement and Landscape Analysis)
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Abstract

Approaches to landscape and urban change analysis are still far away from being fully automatic or operational. For this reason, the concept of Geovisual Analytics is proposed, combining computational and visual/manual processing steps. This contribution concentrates on the latter part with the overall goal of improving its usability. For this purpose, a classification of tasks is created, which often occur in the context of change analysis. This serves as the basis for the assignment of suitable map types to change processing results. Beyond this, it is pointed out that in many cases an appropriate pre-processing of data is imperative to preserve or enhance certain spatial relationships or characteristics for visualization. This is demonstrated using the example of data classification prior to choropleth mapping. Methods are described which allow the preservation of local extreme values, large value differences between adjacent polygons, clusters, and hot/cold spots. Finally, discussing future research and developments, it will be stressed that the importance of visual methods in the context of big data change analysis will continue to increase, which is due to the particular ability of maps to generalize and reduce complex data to a minimum. View Full-Text
Keywords: change analysis; visualization; landscape analysis; geovisual analytics; data classification; choropleth mapping change analysis; visualization; landscape analysis; geovisual analytics; data classification; choropleth mapping
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Schiewe, J. Task-Oriented Visualization Approaches for Landscape and Urban Change Analysis. ISPRS Int. J. Geo-Inf. 2018, 7, 288.

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