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Proceedings Paper

The role of spatial resolution in landscape analysis
Author(s): Ruggero Casacchia; Alessandra Grignetti; Stefania Mandrone; Rosamaria Salvatori
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Paper Abstract

In this paper a study carried out by airborne hyperspectral data is presented. Image data concern a forest area (60 km North of Rome -Italy), to evaluate how different spatial resolutions can affect vegetation spectral response and therefore the discrimination among the different communities. MIVIS images were acquired at different flight altitudes (2000 m and 5000 m), in the same day and on the same surface targets. A radiometric field survey was carried out in order to radiometrically calibrate the airborne images. Classification were performed on each image by two different techniques: Maximum Likelihood and Spectral Angle Mapper. The results of these classification methods were analysed to evaluate how different spatial resolution can affect vegetation spectral response. In particular the relationship between spectral and spatial resolution of hyperspectral images was investigated by resampling the 2000 m image (4m/pxl) in order to simulate the radiometric response of surface targets in the MIVIS image acquired at 5000 m of altitude (10m/pxl). The result suggest that the spatial resolution of aerial images must be decided when the overflight is planned, because the resampled data keeps the original spectral characteristics and upscaling methods do not provide meaningful data in heterogeneous area.

Paper Details

Date Published: 24 February 2004
PDF: 12 pages
Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); doi: 10.1117/12.510695
Show Author Affiliations
Ruggero Casacchia, Istituto sull'Inquinamento Atmosferico, CNR (Italy)
Alessandra Grignetti, Istituto sull'Inquinamento Atmosferico, CNR (Italy)
Stefania Mandrone, Istituto sull'Inquinamento Atmosferico, CNR (Italy)
Rosamaria Salvatori, Istituto sull'Inquinamento Atmosferico, CNR (Italy)


Published in SPIE Proceedings Vol. 5232:
Remote Sensing for Agriculture, Ecosystems, and Hydrology V
Manfred Owe; Guido D'Urso; Jose F. Moreno; Alfonso Calera, Editor(s)

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