Retrieving vegetation cover types in the complex natural ecosystem of the Pollino National Park (South Italy) through Hyperion data

Lorenzo Fusilli; Cristiana Bassani; Simone Pascucci; Stefano Pignatti

doi:10.1117/12.739076

30 October 2007 Retrieving vegetation cover types in the complex natural ecosystem of the Pollino National Park (South Italy) through Hyperion data

Lorenzo Fusilli, Cristiana Bassani, Simone Pascucci, Stefano Pignatti

Author Affiliations +

Proceedings Volume 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII; 674930 (2007) https://doi.org/10.1117/12.739076
Event: SPIE Remote Sensing, 2007, Florence, Italy

Abstract

In this paper the potential of the Hyperion spaceborne hyperspectral data in discriminating land covers in complex natural ecosystems was evaluated according to the hierarchical structure of the European standard legend (CORINE Land Cover 2000). Furthermore, the ability of the Hyperion data in retrieving land cover information at sub-pixel level was assessed by exploiting the vegetation classes' distribution as obtained by aerial-photos. Four standard supervised classifiers have been compared in terms of algorithm performance and class accuracy by applying statistical metric; the best results were achieved with the Minimum Distance (MD) classifier. In those areas exhibiting mixed pixels at the Hyperion spatial resolution a Linear Spectral Unmixing technique was applied for deriving abundance fractions of the endmembers (i.e. land covers) previously identified. Accuracy of the un-mixing analysis was evaluated using a Residual Error index calculated by relating Hyperion fractional abundances and reference aerial-photos. Results show the capability of Hyperion data to map land covers and vegetation diversity even at sub-pixel level within a complex natural landscape.

Citation Download Citation

Lorenzo Fusilli, Cristiana Bassani, Simone Pascucci, and Stefano Pignatti "Retrieving vegetation cover types in the complex natural ecosystem of the Pollino National Park (South Italy) through Hyperion data", Proc. SPIE 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 674930 (30 October 2007); https://doi.org/10.1117/12.739076

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