Tools based on proprietary and free/open source geospatial software for CO emission maps analysis and comparison

The increasing availability of data monitoring the phenomena that occur on the Earth makes it necessary to provide ad hoc tools allowing the researchers to exploit efficiently all information. The study presented in this paper has been dedicated to the design and implementation in a GIS environment...

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Bibliographic Details
Published in:Applied geomatics Vol. 4; no. 2; pp. 105 - 112
Main Authors: Migliaccio, Federica, Carrion, Daniela, Zambrano, Cynthia
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer-Verlag 01.06.2012
Springer
Subjects:
Automation
Carbon monoxide
Computer programs
Earth and Environmental Science
Emission
Emission analysis
Freeware
Geographic information systems
Geographical Information Systems/Cartography
Geography
Geophysics/Geodesy
Measurement Science and Instrumentation
Original Paper
Public software
Remote Sensing/Photogrammetry
Software
Source code
Surveying
Data inter-comparison
GIS
ArcGIS
Statistical tools
CO emission
Python
ISSN:1866-9298, 1866-928X
Online Access:Get full text
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Summary:The increasing availability of data monitoring the phenomena that occur on the Earth makes it necessary to provide ad hoc tools allowing the researchers to exploit efficiently all information. The study presented in this paper has been dedicated to the design and implementation in a GIS environment of tools and indices for the analysis and inter-comparison of several datasets representing CO emissions at a global level. The objective of the work was to provide the scientists with an instrument for the consultation and processing of CO emission datasets, with as much automation as possible, besides guided setting of the parameters and interface for graph generation. Both proprietary and open source software have been considered, highlighting their advantages and disadvantages. The use of proprietary software (ArcGIS 9.3) was requested by the users; for a more efficient customisation the implementation involved also the use of Python 2.5 language and of the Matplotlib library. Then the same kind of tools were implemented in a new module of the GRASS software (version 6.4), developed in C language. In this paper the tools are presented together with examples of CO emission datasets inter-comparisons.
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ISSN:1866-9298
1866-928X
DOI:10.1007/s12518-011-0075-8