Comparative analysis of Landsat TM, ETM+, OLI and EO-1 ALI satellite images at the Tisza-tó area, Hungary

Satellite images are important information sources of land cover analysis or land cover change monitoring. We used the sensors of four different spacecraft: TM, ETM+, OLI and ALI. We classified the study area using the Maximum Likelihood algorithm and used segmentation techniques for training area...

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Bibliographic Details
Main Authors: Loránd Szabó, Márton Deák, Szilárd Szabó
Format: Article
Language:English
Published: Debrecen University Press. 2016-06-01
Series:Acta Geographica Debrecina. Landscape & Environment Series
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Online Access:http://landscape.geo.klte.hu/pdf/agd/2016/2016v10is2_1.pdf
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Summary:Satellite images are important information sources of land cover analysis or land cover change monitoring. We used the sensors of four different spacecraft: TM, ETM+, OLI and ALI. We classified the study area using the Maximum Likelihood algorithm and used segmentation techniques for training area selection. We validated the results of all sensors to reveal which one produced the most accurate data. According to our study Landsat 8’s OLI performed the best (96.9%) followed by TM on Landsat 5 (96.2%) and ALI on EO-1 (94.8%) while Landsat 7’s ETM+ had the worst accuracy (86.3%).
ISSN:1789-4921
1789-7556