Investigation of the potential of hyperspectral sensors for bathymetry applications using airborne HyMap data from Lake Constance

The potential of hyperspectral sensors in monitoring the bottom depth in shallow waters is investigated by numerical simulations and by analysis of hyperspectral data. The theoretically expected accuracy of bottom depth determination is studied by combining forward and inverse calculations for different conditions of the water medium and the bottom type. The parameters defining these conditions are changed in value starting from a clear-water scenario to various other optical situations. The spectral range of all calculations is 400 to 900 nm and the spectral sampling interval is 1 nm. All simulations are done with the Water Colour Simulator (WASI) software which is optimised to modelling and analyzing optical in situ measurements in aquatic environments. A physically based method for the inversion of hyperspectral remote sensing data is applied to data of the airborne sensor HyMap. The data were acquired during the HyEurope flight campaign in June 2004. HyMap spectra are inverted by adjusting modelled top-of-atmosphere radiance spectra to the measured ones by fitting the concentrations of 3 aerosol types (rural, maritime, urban) and 3 water constituents (suspended matter, chlorophyll, Gelbstoff). The determined concentrations of aerosols and water constituents are used to correct the HyMap images for atmospheric and air/water interface effects and for the angular dependency of the water body reflectance. In the final step bottom depth is determined for all pixels, with fixed concentrations of all water constituents at the deep-water average values. All data inversion and image processing is performed by use of the Modular Inversion and Processing System (MIP). These results are compared with bottom depth maps derived from echosounding measurements and aerial photography, and an assessment of error sources is given. WASI simulations proved that an accuracy of bottom depth better than 10 % is theoretically possible for low concentrations of water constituents between 2 and 8 m, independent from the bottom type. Errors in the concentration of the water constituents Gelbstoff and suspended matter may have a significant negative effect on the accuracy of bottom depth (ZB) determination if considered constant during the inversion. The results from the inversion technique by MIP showed that it is capable to estimate the bottom depth values from the HyMap image with a root mean square error of 20 cm after correction of systematic errors. The results on error propagation from the WASI simulations suggest that fixing of the water constituents during the inversion with MIP may be the main error source for the systematic error observed in the determination of bottom depth

Influence of gap fraction on coniferous needle optical properties measurements

Abstract of presentation at the 9th Swiss Geoscience Meeting, Zurich 2011, 11-13 November, ETH Hauptgebaude & Department of Earth Sciences, ETH Zurich

Geometrical and structural parameterization of forest canopy radiative transfer by LIDAR measurements

A forest canopy is a complex system with a highly structural multi-scale architecture. Physical based radiative transfer (RT) modelling has been shown to be an effective tool for retrieval of vegetation canopy biochemical/physical characteristics from optical remote sensing data. A high spatial resolution RT through a forest canopy requires several geometrical and structural parameters of trees and understory to be specified with an appropriate accuracy. Following attributes on forest canopy are required: i) basic tree allometric parameters (i.e., tree height, stem diameter and length, crown length and projection,simplified crown shape, etc.),ii)parameters describing distribution of green biomass (foliage) (e.g., leaf area index (LAI), leaf angle distribution (LAD) or average leaf angle (ALA), clumping of leaves and density of clumps, air gaps and defoliation, etc.), and iii) parameters describing distribution of woody biomass (branches and twigs) (e.g., number, position and angular orientation of the first order branches-branches growing directly from stem, twigarea index (TAI), twig angle distributi on (TAD)). At very high spatial resolution (airborne image data), an insufficiently characterized structure of the forest canopy can result in inaccurate RT simulations. Direct destructive methods of measuring canopy structure are unfeasible at large-scales, therefore, in this paper we review the non-in vasive Light Detection and Ranging (LIDAR) approaches. We also present some results on tree structure parameters acquired by a commercially available ground-based LIDAR scanner employed in scanning the matured Norway spruce trees

A geometric model for scaling between needle and shoot spectral albedos

Abstract of presentation at the 7th International Conference on Functional-Structural Plant Models, 9 -14 June 2013, Sarriselka, Finland

Minimizing measurement uncertainties of coniferous needle-leaf optical properties, part I: methodological review

Optical properties (OPs) of non-flat narrow plant leaves, i.e., coniferous needles, are extensively used by the remote sensing community, in particular for calibration and validation of radiative transfer models at leaf and canopy level. Optical mea- surements of such small living elements are, however, a technical challenge and only few studies attempted so far to investigate and quantify related measurement errors. In this paper we review current methods and developments measuring optical properties of narrow leaves. We discuss measurement shortcomings and knowledge gaps related to a particular case of non-flat nonbifacial coniferous needle leaves, e.g., needles of Norway spruce (Picea abies (L.) Karst.)

Minimizing measurement uncertainties of coniferous needle-leaf optical properties. Part II: experimental setup and error analysis

We present uncertainties associated with the measurement of coniferous needle-leaf optical properties (OPs) with an integrating sphere using an optimized gap-fraction (GF) correction method, where GF refers to the air gaps appearing between the needles of a measured sample. We used an optically stable artificial material simulating needle leaves to investigate the potential effects of: 1) the sample holder carrying the needles during measurements and 2) multiple scattering in between the measured needles. Our optimization of integrating sphere port configurations using the sample holder showed an underestimation of the needle transmittance signal of at least 2% in flat needles and 4% in nonflat needles. If the needles have a nonflat cross section, multiple scattering of the photons during the GF measurement led to a GF overestimation. In addition, the multiple scattering of photons during the optical measurements caused less accurate performance of the GF-correction algorithms, which are based on the assumption of linear relationship between the nonGF-corrected signal and increasing GF, resulting in transmittance overestimation of nonflat needle samples. Overall, the final deviation achieved after optimizing the method is about 1% in reflectance and 6% in transmittance if the needles are flat, and if they are nonflat, the error increases to 4%–6% in reflectance and 10%–12% in transmittance. These results suggest that formulae for measurements and computation of coniferous needle OPs require modification that includes also the phenomenon of multiple scattering between the measured needles

Estimation of spruce needle-leaf chlorophyll content based on DART and PARAS canopy reflectance models

Needle-leaf chlorophyll content (Cab) of a Norway spruce stand was estimated from CHRIS-PROBA images using the canopy reflectance simulated by the PROSPECT model coupled with two canopy reflectance models: 1) discrete anisotropic radia- tive transfer model (DART); and 2) PARAS. The DART model uses a detailed description of the forest scene, whereas PARAS is based on the photon recollision probability theory and uses a simplified forest structural description. Subsequently, statisti- cally significant empirical functions between the optical indices ANCB 670 − 720 and ANMB 670 − 720 and the needle-leaf Cab content were established and then applied to CHRIS-PROBA data. The Cab estimating regressions using ANMB 670 − 720 were more robust than using ANCB 670 − 720 since the latter was more sensitive to LAI, especially in case of PARAS. Comparison between Cab esti- mates showed strong linear correlations between PARAS and DART retrievals, with a nearly perfect one-to-one fit when using ANMB 670 − 720 (slope = 1.1, offset = 11 μ g · cm − 2 ). Further com- parison with Cab estimated from an AISA Eagle image of the same stand showed better results for PARAS (RMSE = 2.7 μ g · cm − 2 for ANCB 670 − 720 ;RMSE = 9.5 μ g · cm − 2 for ANMB 670 − 720 )than for DART (RMSE = 7.5 μ g · cm − 2 for ANCB 670 − 720 ;RMSE = 23 μ g · cm − 2 for ANMB 670 − 720 ). Although these results show the potential for simpler models like PARAS in estimating needle-lea

A note on upscaling coniferous needle spectra to shoot spectral albedo

Mutual shading of needles in coniferous shoots and small-scale variations in needle area density both within and between shoots violate conventional assumptions used in the definition of the elementary volume in radiative transfer models. In this paper, we test the hypothesis if it is possible to scale needle spectral albedo up to shoot spectral albedo using only one structural parameter: the spherically averaged shoot silhouette to total area ratio (STAR). To test the hypothesis, we measured both structural and spectral properties of ten Scots pine (Pinus sylvestris) shoots and their needles. Our results indicate that it is possible to upscale from needle to shoot spectral albedo using STAR. The upscaling model performed best in the VIS and SWIR regions, and for shoots with high STAR values. As STAR is linearly related to photon recollision probability, it is also possible to apply the upscaling model as integral part of radiative transfer models