Forest attributes from multi-angle multi-date remotely sensed data

Date

2010-08-30T20:56:07Z

Authors

Dyk, Andrew

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Multi-Angle, Multi-Date, Hyperspectral imagery of forests have been used to provide accurate estimates of the canopy characteristics. This thesis investigated the influence of various forest attributes on the spectral reflectance over time and view direction. The Compact High Resolution Imaging Spectrometer (CHRIS) is aboard the ESA PROBA satellite. The revisits of the CHRIS multi-angle images have been used to improve the accuracies of forest species recognition and stand densities compared to a nadir view only. Multi-angle data for CHRIS analysis of forest species produced higher accuracy and were easier to obtain than multi-date date. 5-Scale, a radiative transfer model, and CHRIS data have been compared as inputs into Partial Least Squares (PLS), a fullspectrum analytical method that offers relations between forest stand parameters and the resulting spectra. The resulting coefficients highlight where (view angle and spectral regions) within the multi-angle spectra contributed to estimating the various forest parameters. Methodology of collecting spectral calibration data in the field and the unique pre-processing challenges have been described.

Description

Keywords

Remote Sensing, Hyperspectral, Forests, Bidirectional Reflectance

Citation