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Edinburgh Research Archive >
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MSc Geographical Information Science thesis collection >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1842/2459
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Files in This Item:
| File |
Description |
Size | Format |
A_RUSHFORTH_RESEARCH.doc | File only available to GIS staff and students | 21.54 MB | Microsoft Word | | A_RUSHFORTH_TECHNICAL.doc | File only available to GIS staff and students | 24.34 MB | Microsoft Word | | A_RUSHFORTH_TECHNICAL_CONTENTS.doc | File only available to GIS staff and students | 46 kB | Microsoft Word | |
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| Title: | 3D visualisation techniques for communicating forest change information in Google Earth |
| Authors: | Rushforth, Alex |
| Supervisor(s): | Woodhouse, Iain |
| Issue Date: | 5-Dec-2008 |
| Abstract: | Techniques for visualising forest change information using the ‘Google Earth’ online virtual globe were developed as a method of communicating remote sensing analysis to policy-makers and other non-technical audiences. For study areas in Malawi, GIS and RS were used to produce datasets representing areas of change - modelled as either simplified polygons or as a sample of points, which were then stored within a spatial database, and rendered as KML overlays using server-side scripts.
Two visualisation methods are explored. The first layers polygons representing areas of forest change over the top of Google's own high-resolution imagery. For each polygon, area attributes are also made available (for example number of hectares deforestation, tonnes of carbon lost...). The second method attempts to replicate small-scale landscape visualisations using simple 3D tree models (COLLADA) placed over areas of forest change (point locations from the data table). Rather than using descriptions, more intuitive techniques are used such as changing tree model colour or using animation sequences to show how forests have disappeared. |
| Keywords: | KML Google Earth Malawi GIS Deforestation Virtual Globe |
| URI: | http://hdl.handle.net/1842/2459 |
| Appears in Collections: | MSc Geographical Information Science thesis collection
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