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Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery
Date
2020-07-01
Author
Caglayan, Semiha Demirbas
Leloğlu, Uğur Murat
Ginzler, Christian
Psomas, Achilleas
Zeydanlı, Uğur Siyami
Bilgin, Cemal Can
Waser, Lars T.
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Essential forest ecosystem services can be assessed by better understanding the diversity of vegetation, specifically those of Mediterranean region. A species level classification of maquis would be useful in understanding vegetation structure and dynamics, which would be an indicator of degradation or succession in the region. Although remote sensing was regularly used for classification in the region, maquis are simply represented as one to three categories based on density or height. To fill this gap, we test the capability of Sentinel-2 imagery, together with selected ancillary variables, for an accurate mapping of the dominant maquis formations. We applied Recursive Feature Selection procedure and used a Random Forest classifier. The algorithm is tested using ground truth collected from site and reached 78% and 93% overall accuracy at species level and physiognomic level, respectively. Our results suggest species level characterization of dominant maquis is possible with Sentinel-2 spatial resolution.
Subject Keywords
Mediterranean forests
,
Maquis
,
Random forest
,
Sentinel-2
,
Image classification
URI
https://hdl.handle.net/11511/31827
Journal
GEOCARTO INTERNATIONAL
DOI
https://doi.org/10.1080/10106049.2020.1783581
Collections
Graduate School of Natural and Applied Sciences, Article
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S. D. Caglayan et al., “Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery,”
GEOCARTO INTERNATIONAL
, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31827.