Comparing global land cover datasets through the Eagle matrix land cover components for continental Portugal

• Author(s): Mozak, Selçuk
• Date: 2016
• Persistent ID: http://hdl.handle.net/10362/17653
• Origin: Repositório Institucional da UNL
• Subject(s): Semantic Uncertainty; Fuzzy Comparison; Globeland30; Map Comparison; Globe Land Cover - Share
• Document Type: Master thesis
• Language: English
• Advisor(s): Caetano, Mário Sílvio Rochinha de Andrade; Henriques, Roberto André Pereira; Guerrero, Ignacio
• Contributor(s): RUN

Description

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies

Global land cover maps play an important role in the understanding of the Earth's ecosystem dynamic. Several global land cover maps have been produced recently namely, Global Land Cover Share (GLC-Share) and GlobeLand30. These datasets are very useful sources of land cover information and potential users and producers are many times interested in comparing these datasets. However these global land cover maps are produced based on different techniques and using different classification schemes making their interoperability in a standardized way a challenge. The Environmental Information and Observation Network (EIONET) Action Group on Land Monitoring in Europe (EAGLE) concept was developed in order to translate the differences in the classification schemes into a standardized format which allows a comparison between class definitions. This is done by elaborating an EAGLE matrix for each classification scheme, where a bar code is assigned to each class definition that compose a certain land cover class. Ahlqvist (2005) developed an overlap metric to cope with semantic uncertainty of geographical concepts, providing this way a measure of how geographical concepts are more related to each other. In this paper, the comparison of global land cover datasets is done by translating each land cover legend into the EAGLE bar coding for the Land Cover Components of the EAGLE matrix. The bar coding values assigned to each class definition are transformed in a fuzzy function that is used to compute the overlap metric proposed by Ahlqvist (2005) and overlap matrices between land cover legends are elaborated. The overlap matrices allow the semantic comparison between the classification schemes of each global land cover map. The proposed methodology is tested on a case study where the overlap metric proposed by Ahlqvist (2005) is computed in the comparison of two global land cover maps for Continental Portugal. The study resulted with the overlap spatial distribution among the two global land cover maps, Globeland30 and GLC-Share. These results shows that Globeland30 product overlap with a degree of 77% with GLC-Share product in Continental Portugal.