Mapping Forest Species in the Central Middle Atlas of Morocco (Azrou Forest) through Remote Sensing Techniques

被引：31

作者：

Mohajane, Meriame ^{[1
]}

Essahlaoui, Ali ^{[2
]}

Oudija, Fatiha ^{[1
]}

El Hafyani, Mohammed ^{[2
]}

Teodoro, Claudia ^{[3
,4
]}

机构：

[1] Moulay Ismail Univ, Fac Sci, Dept Biol, Soil & Environm Microbiol Team, BP11201 Zitoune Meknes, Meknes, Morocco

[2] Moulay Ismail Univ, Fac Sci, Dept Geol, Water Sci & Environm Engn Team, BP11201 Zitoune Meknes, Meknes, Morocco

[3] Univ Porto, Fac Sci, Earth Sci Inst ICT, P-4169007 Oporto, Portugal

[4] Univ Porto, Fac Sci, Dept Geosci Environm & Land Planning, P-4169007 Oporto, Portugal

来源：

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION | 2017年 / 6卷 / 09期

关键词：

Sentinel-2A; spectral angle mapper (SAM); QGIS; mapping; SPACEBORNE THERMAL EMISSION; SUPPORT VECTOR MACHINES; SPECTRAL ANGLE MAPPER; LAND-USE; ASTER DATA; COVER; CLASSIFICATION; IMAGERY; RECONSTRUCTION; CLASSIFIERS;

D O I：

10.3390/ijgi6090275

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：10

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