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Finding potential tephra layers

Authors: Hao, Xu;

Finding potential tephra layers

Abstract

This paper aims to develop an Android application for gathering, analysing, and visualizing spatial and aspatial data stored in Tephrabase. Field based and GPS supported Geographic Information Science (GIS) plays an indispensable role in field data collection, such as tephra layers data collection. Two Mobile GIS architectures were achieved in this project: the Stand-Alone Client architecture and Client-Server architecture. Spatialite/SQLite is a spare database of Oracle Spatial stored in the local file when the system cannot connect to the server. A Google map generated by Google Map API was introduced in this project to render tephra sites stored in the database. The OpenGL ES API helps this application in generating strati-graphic columns based on existing data. Additionally, potential tephra layers can be estimated by this application together with the existing tephra layers which are within the user defined radius. Moreover, this application provides a practical function for collecting spatial data in field work.

Country
United Kingdom
Related Organizations
Keywords

Tephra, Android, GPS, MSc Geographical Information Science, Mobile GIS, Google Map API, OpenGL ES., Stratigraphic columns, GIS, OpenGL ES

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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