Refining a hyperspectral and multiangle measurement concept for vegetation structure assessment

Abstract

The concept of combining multiangle and hyperspectral remote sensing has been developed and utilized in the compact high-resolution imaging spectrometer (CHRIS) satellite observation system onboard the project for on-board autonomy (PROBA) platform developed by the European Space Agency (ESA). Recent studies show that this technology is useful for extracting crop and soil information, and it is very promising for deriving forest structural and biochemical parameters. However, hyperspectral measurements at multiple angles appear to have much redundancy. Therefore, we attempt to refine this measurement concept by testing a new system that acquires hyperspectral signals only in the nadir direction but measures in two additional directions in two spectral bands, namely red and near-infrared (NIR). According to our recent research, we propose that the best two view angles are (i) the hotspot, where the Sun and view directions coincide; and (ii) the darkspot, where the sensor sees the maximum amount of vegetation structural shadows. Through model experiments, we demonstrate that the combination of the hotspot and darkspot reflectances has the strongest signals about the vegetation structure quantified using the foliage clumping index. The 5-Scale model is used in this study to simulate CHRIS data. Very good agreements are shown between modelled and CHRIS-measured spectra at the nadir and off-nadir view angles, except for the largest view angle (+55°), at which the atmospheric correction is uncertain. Furthermore, we successfully demonstrate that the off-nadir hyperspectral simulations could be brought in very close agreement with the CHRIS data once multispectral measurements at the same off-nadir angles are available. In other words, all hyperspectral bands can be closely reconstructed based on the nadir hyperspectral reflectance and off-nadir multispectral reflectance in the red and NIR bands. This is shown for black spruce and aspen forests using the CHRIS data acquired over the Sudbury region in Canada. The results suggest that the multiangle hyperspectral data exhibit much redundancy, and that the multispectral measurements at off-nadir angles in addition to the nadir hyperspectral data would be sufficient to reconstruct hyperspectral signatures at off-nadir angles. This proposed concept could be regarded as a refinement of the existing sensor. Remote sensing data acquired using this new measurement concept would provide the opportunity to analyze simultaneously vegetation structural and biochemical information.