Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery

Caglayan S. D., Leloğlu U. M., Ginzler C., Psomas A., Zeydanlı U. S., Bilgin C. C., ...More

GEOCARTO INTERNATIONAL, vol.37, no.6, pp.1587-1606, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 6
  • Publication Date: 2022
  • Doi Number: 10.1080/10106049.2020.1783581
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Environment Index, Geobase, INSPEC
  • Page Numbers: pp.1587-1606
  • Keywords: Mediterranean forests, maquis, random forest, Sentinel-2, image classification, VEGETATION INDEX, SPECTRAL DISCRIMINATION, ANCILLARY DATA, MANAGEMENT, ACCURACY, BIODIVERSITY, LANDSAT-8, PROGRESS, DYNAMICS, HOTSPOTS
  • Middle East Technical University Affiliated: Yes


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.