Mohajane, M. and Essahlaoui, A. and Oudija, F. and El Hafyani, M. and Teodoro, A.C. (2017) Mapping forest species in the Central Middle Atlas of Morocco (Azrou Forest) through remote sensing techniques. ISPRS International Journal of Geo-Information, 6 (9).

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The studies of forest ecosystems from remotely-sensed data are of great interest to researchers because of ecosystem services provided by this ecosystem, including protection of soils and vegetation, climate stabilization, and regulation of the hydrological cycle. In this context, our study focused on the use of a spectral angle mapper (SAM) classification method for mapping species in the Azrou Forest, Central Middle Atlas, Morocco. A Sentinel-2A image combined with ground reference data were used in this research. Four classes (holm oak, cedar forest, bare soil, and others-unclassified) were selected; they represent, respectively, 27, 11, 24, and 38 of the study area. The overall accuracy of classification was estimated to be around 99.72. This work explored the potential of the SAM classification combined with Sentinel-2A data for mapping land cover in the Azrou Forest ecosystem. © 2017 by the Author.

Item Type: Article
Subjects: Earth and Planetary Sciences
Divisions: SCIENTIFIC PRODUCTION > Earth and Planetary Sciences
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46
URI: http://eprints.umi.ac.ma/id/eprint/2852

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