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Remote Sens. 2015, 7(5), 5012-5041; doi:10.3390/rs70505012

Use of LUCAS LC Point Database for Validating Country-Scale Land Cover Maps

1
Lab of Forest Management and Remote Sensing, School of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2
Airbus Defence & Space, DE-88090 Immenstaad, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Parth Sarathi Roy and Prasad S. Thenkabail
Received: 16 January 2015 / Revised: 8 April 2015 / Accepted: 13 April 2015 / Published: 23 April 2015
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Abstract

In this study, the Land Use/Cover Area frame statistical Survey (LUCAS) of 2009 was used as a reference dataset for validating a Land Cover Map of Greece for 2007, produced with remote sensing by the Greek Office of the World Wildlife Fund (WWF Hellas). First, all class definitions were decomposed in terms of four vegetation parameters (type, height, density, and composition), considered as critical in indicating unconformities between LUCAS and the WWF Hellas map; their inter-class relations were described in a table of correspondence. Then, a two-tier methodology was applied: an “automated” process, where thematic agreement was based exclusively on the main land cover attribute of LUCAS (LC1); and a “supervised” process, where thematic agreement was based on the reinterpretation of LUCAS ground photos and use of ancillary earth observation imagery; non-square error matrix was deployed in both processes. For the supervised process specifically, a decision-tree was designed, using the critical vegetation parameters (mentioned above) as quantified criteria, thus allowing objective labelling of testing points in both systems. The results show that only a small proportion of the reassessed points verified the WWF Hellas map predictions and that the overall accuracy of the supervised process was reduced compared to that of the automated process. In conclusion, the LUCAS point database was found to be supportive, but not fully efficient, for identifying the various sources of error in country-scale land cover maps derived with remote sensing. Synergy with very high resolution satellite images and air photos, or a dedicated ground truth campaign, seems to be inevitable in order to validate their thematic accuracy, especially in highly heterogeneous environments. In this direction, LUCAS could be used as a verification, rather than a validation, dataset. View Full-Text
Keywords: WWF Hellas; ground truth; non-square error matrix; supervised validation; reinterpretation WWF Hellas; ground truth; non-square error matrix; supervised validation; reinterpretation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Karydas, C.G.; Gitas, I.Z.; Kuntz, S.; Minakou, C. Use of LUCAS LC Point Database for Validating Country-Scale Land Cover Maps. Remote Sens. 2015, 7, 5012-5041.

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