Mapping forest structure and species composition using multi-source remote sensing data

a PhD project by Bechu KV Yadav

Measuring forest structure and species composition is vital for biodiversity studies, bushfire modelling, carbon stock estimation and sustainable management of forests. Particularly targeting the management needs of the Warra Supersite forests, and to contribute to replace the traditional forest inventory techniques, this PhD project focuses on developing an approach to map mature wet sclerophyll and mixed eucalypt forest structure and species composition exploiting remote sensing technologies. This project employs the combined airborne hyperspectral imagery and airborne LiDAR data in geographic object-based image analysis (GEOBIA) for forest species classification and attributes’ extraction eventually to develop models of Warra Supersite forests. This study scales up the developed models to large geographical areas using space-borne LiDAR data and medium resolution satellite imagery to test their robustness and transferability. Thus, this project should result in an objective and repeatable approach to forest biodiversity mapping and monitoring at local to regional scales.

Figure 1 Tree identification at Warra Supersite

Figure 1 Tree identification at Warra Supersite

Figure 2 Flux Tower at Warra Supersite forest

Figure 2 Flux Tower at Warra Supersite forest

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