DBPapers
DOI:10.5593/SGEM2013/BB2.V1/S11.009

COMPARISON OF INTERPOLATION METHODS FOR ESTIMATING CLIMATOLOGICAL DATA

M. Gergelova, Z. Kuzevicova, S. Kuzevic, J. Palková
Monday 5 August 2013 by Libadmin2013

References: 13th SGEM GeoConference on Informatics, Geoinformatics And Remote Sensing, www.sgem.org, SGEM2013 Conference Proceedings, ISBN 978-954-91818-9-0 / ISSN 1314-2704, June 16-22, 2013, Vol. 1, 677 - 684 pp

ABSTRACT

Currently, the major climatic changes taking place that will affect the future character of the landscape and life. Monitoring climatological characteristics, their changes over time and the possibility of predicting future development is one of the fundamental tasks of climatology. To estimate values in areas without direct observation are using spatial interpolation methods. Interpolation is a procedure estimating unknown values from known values measured in a defined area. To estimate the unknown values, there are many different interpolation methods. The GIS environment the most common being inverse distance weighting (IDW), spline, kriging. Each of the methods has its mathematics, its advantages and disadvantages. In meteorology, the IDW method is further developed, trying to remove as much as possible the impact of terrain slope and altitude and was named gradient plus inverse distance squared (GIDS) method. In the present contribution compares the generated surfaces of selected climatic data - temperature, pressure, and analyzed in terms of accuracy.

Keywords: GIDS, interpolation methods, IDW, GIS

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