Title :
Deforestation detection and monitoring in cedar forests of the moroccan Middle-Atlas mountains
Author :
Haboudane, Driss ; Bahri, El Mustapha
Author_Institution :
Univ. du Quebec a Chicoutimi, Chicoutimi
Abstract :
The main objective of this study was to identify areas of deforestation/reforestation in the Middle-Atlas cedar forest and monitor their temporal dynamics. The aim was to detect a detailed "from-to" change information; it targets a quantitative estimation of the extent and the magnitude of the changes affecting major identified species of the Moroccan cedar ecosystem: cedar, oak, and deciduous. The major challenge was to identify changes of interest such as identifying the change due to a selective logging which consists on cutting cedar canopy trees while sparing the understory oak trees. To address these issues and achieve our objectives, we adopted a methodology with two main stages. First, we mapped major forest species from multidate satellite images (Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) using maximum likelihood classification (MLQ and spectral mixture analysis (SMA). Second, we performed change detection assessment using two procedures: (i) image products differencing to assess the overall change in the forest cover, (ii) post-classification comparisons using the outputs of the MLC and the relative abundances of forest species as determined by SMA. Results have shown the following: logging has decreased cedar area in a proportion of 12% while reforestation has yielded an increase of 8% in cedar forest; in oak forest, the increment (21%) has exceeded the deforestation effect (17%); conversely, deciduous have either degraded (11%) or remained stable (21%).
Keywords :
forestry; maximum likelihood estimation; vegetation mapping; ASTER; Advanced Spaceborne Thermal Emission and Reflection Radiometer; ETM+; Enhanced Thematic Mapper Plus; MLC; Moroccan cedar ecosystem; Moroccan middle Atlas mountains; SMA; cedar forest; cedar trees; change detection assessment; deciduous trees; deforestation area identification; deforestation detection; deforestation monitoring; forest temporal dynamics; image products differentiation; major forest species mapping; maximum likelihood classification; multidate satellite images; oak trees; post classification comparison; reforestation area identification; selective logging; spectral mixture analysis; Degradation; Ecosystems; Image analysis; Maximum likelihood detection; Maximum likelihood estimation; Monitoring; Radiometry; Reflection; Satellite broadcasting; Spectral analysis; ASTER; Landsat (TM, ETM+); MSAVI; Spectral unmixing; change detection; deforestation; maximum likelihood;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423809