Abstract

AbstractOld-growth forests (OGFs) are extremely valuable relict ecosystems for studying natural disturbance dynamics. Small-scale disturbances caused by tree crown mortality of one or few individuals, i.e. gap dynamics, are the most frequent events occurring in OGFs. Understanding these processes requires information on the spatial arrangement of forest patches dominated by different tree species and forest canopy gaps at a fine spatial scale. Here, we aimed at mapping different land-cover classes including conifers, broad-leaved trees, and forest canopy gaps using two very-high-resolution satellite images, i.e. Pléiades images, in the mixed fir-spruce-beech OGF reserve of Biogradska Gora (Montenegro). Specifically, we coupled an Object-Based Image Analysis (OBIA) approach and a Random Forest classifier, trained with samples partly derived from field data. The adopted approach showed high accuracy for the main land-cover classes (conifers, broadleaved trees, grasslands, bare ground, and water), e.g. producer’s and user’s accuracy higher than 92% and 95%, respectively. Conversely, forest canopy gaps were classified with lower accuracy, e.g. minimum producer’s and user’s accuracies of 75% and 54%, respectively. Despite the exploitation of textural metrics during both image segmentation and classification, the lack of remote sensing data providing information on the vertical structure of the forest stand prevented us from accurately map forest canopy gaps.KeywordVery-high-resolution satellite imageryOld-growth forest. Land-cover mapObject-based image analysisForest canopy gaps

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.