Klaus I. Itten

Radiometric corrections of topographically induced effects on Landsat TM data in an alpine environment

Abstract Four radiometric correction methods for the reduction of slope-aspect effects in a Landsat TM data set are tested in a mountainous test site with regard to their physical soundness and their influence on forest classification, as well as on the visual appearance of the scene. Excellent ground reference information and fine-resolution DEM allowed precise assessment of the applicability of the methods under investigation. The results of the study presented here demonstrate the weakness of the classical cosine correction method for radiometric correction in rugged terrain. The statistical, Minnaert and C-correction approaches, however, yielded an improvement of the forest classification and an impressive reduction of the visual topography effect.

A field goniometer system (FIGOS) for acquisition of hyperspectral BRDF data

A new field goniometer system (FIGOS) is introduced that allows in situ measurements of hyperspectral bidirectional reflectance data under natural illumination conditions. Hyperspectral bidirectional reflectance distribution function (BRDF) data sets taken with FIGOS nominally cover the spectral range between 300 and 2450 nm in 704 bands. Typical targets are small-growing, dense, and homogeneous vegetation canopies, man-made surfaces, and soils. Field BRDF data of a perennial ryegrass surface reveal a strong spectral variability. In the blue and red chlorophyll absorption bands, BRDF effects are strong. Less-pronounced bidirectional reflectance effects are observed in the green and in most of the near-infrared range there surface reflectance is high. An anisotropy index (ANIX), defined as the ratio between the maximum and minimum bidirectional reflectance over the hemisphere, is introduced as a surrogate measurement for the extent of spectral BRDF effects. The ANIX data of the ryegrass surface show a very high correlation with nadir reflectance due to multiple scattering effects. Since canopy geometry, multiple scattering, and BRDF effects are related, these findings may help to derive canopy architecture parameters, such as leaf area index (LAI) or leaf angle distribution (LAD) from remotely sensed hyperspectral BRDF data. Furthermore, they show that normalized difference vegetation index (NDVI) data are strongly biased by the spectral variability of BRDF effects.

Geometric and radiometric correction of TM data of mountainous forested areas

Methodologies to improve Landsat TM (Thematic Mapper) forest classifications of alpine regions through the removal of some radiometric and geometric distortions are tested. Besides correcting for sensor and system induced errors, geometric errors are corrected using a digital elevation model. Then scene-related effects such as differences in illumination as well as the height dependent atmospheric influence and adjacency effects are corrected. The improvement of the accuracy of a forest classification is demonstrated by comparison with ground truth data. >

Atmospheric Precorrected Differential Absorption Technique to Retrieve Columnar Water Vapor

Abstract Differential absorption techniques are suitable to retrieve the total column water vapor contents from imaging spectroscopy data. A technique called Atmospheric Precorrected Differential Absorption (APDA) is derived directly from simplified radiative transfer equations. It combines a partial atmospheric correction with a differential absorption technique. The atmospheric path radiance term is iteratively corrected during the retrieval of water vapor. This improves the results especially over low background albedos. The error of the method for various ground reflectance spectra is below 7% for most of the spectra. The channel combinations for two test cases are then defined, using a quantitative procedure, which is based on MODTRAN simulations and the image itself. An error analysis indicates that the influence of aerosols and channel calibration is minimal. The APDA technique is then applied to two AVIRIS images acquired in 1991 and 1995. The accuracy of the measured water vapor columns is within a range of ±5% compared to ground truth radiosonde data.

APEX - the hyperspectral ESA Airborne Prism Experiment

The airborne ESA-APEX (Airborne Prism Experiment) hyperspectral mission simulator is described with its distinct specifications to provide high quality remote sensing data. The concept of an automatic calibration, performed in the Calibration Home Base (CHB) by using the Control Test Master (CTM), the In-Flight Calibration facility (IFC), quality flagging (QF) and specific processing in a dedicated Processing and Archiving Facility (PAF), and vicarious calibration experiments are presented. A preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user is presented for limnology, vegetation, aerosols, general classification routines and rapid mapping tasks. BRDF (Bidirectional Reflectance Distribution Function) issues are discussed and the spectral database SPECCHIO (Spectral Input/Output) introduced. The optical performance as well as the dedicated software utilities make APEX a state-of-the-art hyperspectral sensor, capable of (a) satisfying the needs of several research communities and (b) helping the understanding of the Earths complex mechanisms.

Inversion of a lidar waveform model for forest biophysical parameter estimation

Due to its measurement principle, light detection and ranging (lidar) is particularly suited to estimate the horizontal as well as vertical distribution of forest structure. Quantification and characterization of forest structure is important for the understanding of the forest ecosystem functioning and, moreover, will help to assess carbon sequestration within forests. The relationship between the signal recorded by a lidar system and the canopy structure of a forest can be accurately characterized by physically based radiative transfer models (RTMs). A three-dimensional RTM is capable of representing the complex forest canopy structure as well as the involved physical processes of the lidar pulse interactions with the vegetation. Consequently, the inversion of such an RTM presents a novel concept to retrieve biophysical forest parameters that exploits the full lidar signal and underlying physical processes. A synthetic dataset and data acquired in the Swiss National Park (SNP) successfully demonstrated the feasibility and the potential of RTM inversion to retrieve forest structure from large-footprint lidar waveform data. The SNP lidar data consist of waveforms generated from the aggregation of small-footprint lidar returns. Derived forest biophysical parameters, such as fractional cover, leaf area index, maximum tree height, and the vertical crown extension, were able to describe the horizontal and vertical forest canopy structure.

The spectral database SPECCHIO for improved long-term usability and data sharing

The organised storage of spectral data described by metadata is important for long-term use and data sharing with other scientists. Metadata describing the sampling environment, geometry and measurement process serves to evaluate the suitability of existing data sets for new applications. There is a need for spectral databases that serve as repositories for spectral field campaign and reference signatures, including appropriate metadata parameters. Such systems must be (a) highly automated in order to encourage users entering their spectral data collections and (b) provide flexible data retrieval mechanisms based on subspace projections in metadata spaces. The recently redesigned SPECCHIO system stores spectral and metadata in a relational database based on a non-redundant data model and offers efficient data import, automated metadata generation, editing and retrieval via a Java application. RSL is disseminating the database and software to the remote sensing community in order to foster the use and further development of spectral databases.

Hyperspectral remote sensing for estimating aboveground biomass and for exploring species richness patterns of grassland habitats

Dry grassland sites are amongst the most species-rich habitats of central Europe and it is necessary to design effective management schemes for monitoring of their biomass production. This study explored the potential of hyperspectral remote sensing for mapping aboveground biomass in grassland habitats along a dry-mesic gradient, independent of a specific type or phenological period. Statistical models were developed between biomass samples and spectral reflectance collected with a field spectroradiometer, and it was further investigated to what degree the calibrated biomass models could be scaled to Hyperion data. Furthermore, biomass prediction was used as a surrogate for productivity for grassland habitats and the relationship between biomass and plant species richness was explored. Grassland samples were collected at four time steps during the growing season to capture normally occurring variation due to canopy growth stage and management factors. The relationships were investigated between biomass and (1) existing broad- and narrowband vegetation indices, (2) narrowband normalized difference vegetation index (NDVI) type indices, and (3) multiple linear regression (MLR) with individual spectral bands. Best models were obtained from the MLR and narrowband NDVI-type indices. Spectral regions related to plant water content were identified as the best estimators of biomass. Models calibrated with narrowband NDVI indices were best for up-scaling the field-developed models to the Hyperion scene. Furthermore, promising results were obtained from linking biomass estimations from the Hyperion scene with plant species richness of grassland habitats. Overall, it is concluded that ratio-based NDVI-type indices are less prone to scaling errors and thus offer higher potential for mapping grassland biomass using hyperspectral data from space-borne sensors.

Accuracy assessment of automatically derived digital elevation models from aster data in mountainous terrain

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite was designed to generate along‐track stereo images. The data are available at low cost, providing a feasible opportunity for generating digital elevation models (DEMs) in areas where little or no elevation data are yet available. This study evaluates the accuracy of DEMs extracted from ASTER data covering mountainous terrain. For an assessment of the achieved accuracies in the Andean study site, comparisons were made to similar topographical conditions in Switzerland, where reference data were available. All raw DEMs were filtered and interpolated by the post‐processing tools included with PCI Geomatica, the software package used. After carefully checking the DEM quality, further post‐processing was undertaken to eliminate obvious artefacts such as peaks and sinks. Accuracy was tested by comparing the DEMs in the Swiss Alps to three reference models. The achieved results of the generated DEMs are promising, considering the extreme terrain. Given accurate and well‐distributed ground control points (GCPs), it is possible to generate DEMs with a root mean square (RMS) error between 15 m and 20 m in hilly terrain and about 30 m in mountainous terrain. The DEMs are very accurate in nearly flat regions and on smooth slopes with southern expositions: errors are generally within ±10 m in those cases. Larger errors do appear in forested, snow covered or shady areas and at steep cliffs and deep valleys with extreme errors of a few hundred metres. The evaluation showed that the quality of the DEMs is sufficient for enabling atmospheric, topographic and geometric correction to various satellite datasets and for deriving additional products.

Assessment of the influence of flying altitude and scan angle on biophysical vegetation products derived from airborne laser scanning

Airborne Laser Scanning (ALS) has been established as a valuable tool for the estimation of biophysical vegetation properties such as tree height, crown width, fractional cover and leaf area index (LAI). It is expected that the conditions of data acquisition, such as viewing geometry and sensor configuration influence the value of these parameters. In order to gain knowledge about these different conditions, we test for the sensitivity of vegetation products for viewing geometry, namely flying altitude and scanning (incidence) angle. Based on two methodologies for single tree extraction and derivation of fractional cover and LAI previously developed and published by our group, we evaluate how these variables change with either flying altitude or scanning angle. These are the two parameters which often need to be optimized towards the best compromise between point density and area covered with a single flight line, in order to reduce acquisition costs. Our test‐site in the Swiss National Park was sampled with two nominal flying altitudes, 500 and 900 m above ground. Incidence angle and local incidence angle were computed based on the digital terrain model using a simple backward geocoding procedure. We divided the raw laser returns into several different incident angle classes based on the flight path data; the TopoSys Falcon II system used in this study has a maximum scan angle of ±7.15°. We compared the derived biophysical properties from each of these classes with field measurements based on tachymeter measurements and hemispherical photographs, which were geolocated using differential GPS. It was found that with increasing flying height the well‐known underestimation of tree height increases. A similar behaviour can be observed for fractional cover; its respective values decrease with higher flying height. The minimum distance between first and last echo increases from 1.2 metres for 500 m AGL to more than 3 metres for 900 m AGL, which does alter return statistics. The behaviour for incidence angles is not so evident, probably due to the small scanning angle of the system used. fCover seems to be most affected by incidence angles, with significantly higher differences for locations further away from nadir. As expected, incidence angle appears to be of higher importance for vegetation density parameters than local incidence angle.