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Damm A.,University of Zurich | Guanter L.,Free University of Berlin | Verhoef W.,University of Twente | Schlapfer D.,ReSe Applications Schlapfer | And 2 more authors.
Remote Sensing of Environment | Year: 2015

Imaging spectroscopy (IS) provides an efficient tool to assess vegetation status and functioning at ecologically relevant scales. Reliable extraction of vegetation information from spatial and spectral high resolution spectroscopy data requires accurate retrieval schemes to account for the complex radiative transfer in the coupled vegetation-atmosphere system. Particularly the coupling of the atmosphere and vegetation considering combined effects of anisotropy, absorption and scattering typically relies on many assumptions, rendering estimates of direct (Edir) and diffuse (Edif) surface irradiance error prone. This impacts the reliability of retrieved vegetation properties.In this study we discuss and quantify the retrieval sensitivity of vegetation information using high resolution IS data to inaccurate assumptions of direct and diffuse surface irradiance. We use observations and simulations and focus on the two vegetation indices normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI), and on sun-induced chlorophyll fluorescence (Fs). Our results indicate that, even if the irradiance field (E) is exactly known, reflectance based vegetation indices show an inherent variation of 9% (NDVI) and 12% (PRI) respectively. These variations are caused by complex interactions of surface irradiance and reflectance anisotropy. The emitted Fs signal was found to be almost unaffected by those variations, if the retrieval considers surface anisotropy. Further, estimation of vegetation properties is subject to large uncertainties if instantaneous E fields are unknown. In that case, they range up to 13% for the NDVI, up to 32% for the PRI, and up to 58% for Fs. We conclude that retrieval sensitivities of vegetation indices and Fs to illumination effects must be carefully considered in data interpretation and suggest using coupled surface-atmosphere models to exploit the full information content of IS data. © 2014 Elsevier Inc. Source

Markelin L.,Finnish Geodetic Institute | Honkavaara E.,Finnish Geodetic Institute | Schlapfer D.,ReSe Applications Schlapfer | Bovet S.,Land Survey of Switzerland | Korpela I.,University of Helsinki
Photogrammetrie, Fernerkundung, Geoinformation | Year: 2012

This article presents the results of an assessment of radiometric correction methods of images taken by the large-format aerial, photo-grammetric, multispectral pushbroom camera Leica Geosystems ADS40. The investigation was carried out in the context of the multi-site EuroSDR project "Radiometric aspects of digital photogram-metric images". Images were collected at the forestry research test site Hyytiälä, Finland, in August 2008. Tw o processing workflows were evaluated: one based on the photogrammetric software Leica XPro, which in radiometric processes relies on physical modelling and information collected from the imagery only, and one based on ATCOR-4, which is software dedicated to physical atmospheric correction of airborne multi-, hyperspectral and thermal scanner data, and can be operated either with or without in-situ reflectance and atmospheric observations. Outputs of these processes are reflectance images. Three participants processed the data with several processing options which resulted in a total of 12 different radiometrically corrected reflectance images. The data analysis was based on field and laboratory reflectance measurements of reference reflectance targets and field measurements of permanent targets (asphalt, grass, gravel). Leica XPro provided up to 5% reflectance accuracy without any ground reference and ATCOR-4 provided reflectance accuracy better than 5% with vicarious in-flight radiometric calibration of the sensor. The results show that the radiometric correction of multispectral aerial images is possible in an efficient way in the photogrammetric production environment. © 2012 E. Schweizerbart'sche Ve rlagsbuchhandlung. Source

Schlapfer D.,ReSe Applications Schlapfer | Richter R.,German Aerospace Center | Kellenberger T.,Swisstopo
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

The new method for cast shadow detection has shown to significantly improve the topographic image correction. This method will be used for operational processing of remote sensing products based on the ADS systems operated by the Swiss Federal Institute of Topography (swisstopo) and will be available in future releases of the ATCOR software packages. © 2012 IEEE. Source

Schlapfer D.,ReSe Applications Schlapfer | Richter R.,German Aerospace Center | Feingersh T.,Israel Aerospace Industries
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

The radiometric correction of airborne imagery aims at providing unbiased spectral information about the Earth's surface. Correction steps include system calibration, geometric correction, and the compensation for atmospheric effects. Such preprocessed data are affected by the bidirectional reflectance distribution function (BRDF), which requires an additional compensation step. We present a novel method for a surface-cover-dependent BRDF effects correction (BREFCOR). It uses a continuous index based on bottom-of-atmosphere reflectances to tune the Ross-Thick Li-Sparse BRDF model. This calibrated model is then used to correct for observation-angle-dependent anisotropy. The method shows its benefits specifically for wide-field-of-view airborne systems where BRDF effects strongly affect image quality. Evaluation results are shown for sample data from a multispectral photogrammetric Leica ADS camera system and for HYSPEX imaging spectroscopy data. The scalability of the procedure for various kinds of sensor configurations allows for its operational use as part of standard processing systems. © 2014 IEEE. Source

Schaepman M.E.,University of Zurich | Jehle M.,University of Zurich | Hueni A.,University of Zurich | D'Odorico P.,University of Zurich | And 19 more authors.
Remote Sensing of Environment | Year: 2015

Wepresent the Airborne PrismExperiment (APEX), its calibration and subsequent radiometric measurements as well as Earth science applications derived from this data. APEX is a dispersive pushbroom imaging spectrometer covering the solar reflected wavelength range between 372 and 2540 nmwith nominal 312 (max. 532) spectral bands. APEX is calibrated using a combination of laboratory, in-flight and vicarious calibration approaches. These are complemented by using a forward and inverse radiative transfer modeling approach, suitable to further validate APEX data. We establish traceability of APEX radiances to a primary calibration standard, including uncertainty analysis. We also discuss the instrument simulation process ranging from initial specifications to performance validation. In a second part, we present Earth science applications using APEX. They include geometric and atmospheric compensated as well as reflectance anisotropy minimized Level 2 data. Further, we discuss retrieval of aerosol optical depth as well as vertical column density of NOx, a radiance data-based coupled canopy-atmosphere model, and finallymeasuring sun-induced chlorophyll fluorescence (Fs) and infer plant pigment content. The results report on all APEX specifications including validation. APEX radiances are traceable to a primary standard with <4% uncertainty and with an average SNR of N625 for all spectral bands. Radiance based vicarious calibration is traceable to a secondary standard with ≤6.5% uncertainty. Except for inferring plant pigment content, all applications are validated using in-situmeasurement approaches andmodeling. Even relatively broad APEX bands (FWHM of 6 nm at 760 nm) can assess Fs with modeling agreements as high as R2 = 0.87 (relative RMSE=27.76%).Weconclude on the use of high resolution imaging spectrometers and suggest further development of imaging spectrometers supporting science grade spectroscopy measurements. © 2014 The Authors. Source

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