Vol. 11, No. 1, 44-51, 2012

Mapping the peri-urban forest of Thessaloniki after the big fire of 1997 using IKONOS imagery
Eleftheria K. Vrania, Miltiadis I. Meliadis, Christos G. Karydas, and Ioannis Z. Gitas

Abstract
This paper compares a pixel-based vs. an object-based classification (OBIA) of a multi-spectral IKONOS image for mapping Mediterranean forests after fire. The study area was a part of the aesthetic, peri-urban forest of Thessaloniki, Greece (Seich-Sou forest) after the big fire of 1997. The IKONOS image was acquired in 2001 and was classified with Maximum Likelihood Classification (MLC, per-pixel method) and with the Membership Function classifier (per-object method). The latter relies on the development of rules, which have the potential to support objective and standardised mapping. Five land use/cover classes were recognised in the forest according to the national legislation. Verified by visual photointerpretation and ancillary ground truth data, OBIA seems to give more realistic results than MLC, especially for grasslands, agricultural land and reforested areas. Future work will focus on testing OBIA in the entire extent of the forest towards an operational use of the rule-set for monitoring Mediterranean forests after fire.

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History
Submitted: 20 June 2011
Revised: 28 Jan 2012
Accepted: 31 Jan 2012
Published: 05 Mar 2012
Responsible editor: Rainer Reuter

Citation
Vrania E K, M I Meliadis, C G Karydas & I Z Gitas, 2012. Mapping the peri-urban forest of Thessaloniki after the big fire of 1997 using IKONOS imagery. EARSeL eProceedings, 11(1): 44-51

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EARSeL European Association of Remote Sensing Laboratories, Strasbourg, France

   
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BIS Library and Information System, Carl von Ossietzky University of Oldenburg

 

ISSN 1729-3782