The estimation of stem diameters can be very useful in the study of forests, as together with height and tree specie, it is one of the most important parameters used in forest inventories. In this paper a system for the estimation of stem diameters with LIDAR and hyperspectral data (both separately and combined in a data fusion framework) is presented. An analysis on the effectiveness of these data in the estimation process and on the accuracy and robustness of different estimation algorithms is presented. Experimental results point out the effectiveness and the properties of the proposed system
Dalponte, M.; Bruzzone, L.; Gianelle, D. (2009). Fusion of hyperspectral and lidar remote sensing data for the estimation of tree stem diameters. In: 2009 IEEE International Geoscience& Remote Sensing Symposium, Cape Town (south Africa), July 12—17, 2009: 1008-1011. ISBN: 978-1-4244-3395-7. doi: 10.1109/IGARSS.2009.5418274 url: http://ieeexplore.ieee.org/xpl/abstractMetrics.jsp?reload=true&arnumber=5418274&contentType=Conference+Publications handle: http://hdl.handle.net/10449/22475
Fusion of hyperspectral and lidar remote sensing data for the estimation of tree stem diameters
Dalponte, Michele;Gianelle, Damiano
2009-01-01
Abstract
The estimation of stem diameters can be very useful in the study of forests, as together with height and tree specie, it is one of the most important parameters used in forest inventories. In this paper a system for the estimation of stem diameters with LIDAR and hyperspectral data (both separately and combined in a data fusion framework) is presented. An analysis on the effectiveness of these data in the estimation process and on the accuracy and robustness of different estimation algorithms is presented. Experimental results point out the effectiveness and the properties of the proposed system
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