EOMAP GmbH

Seefeld, Germany

EOMAP GmbH

Seefeld, Germany

Time filter

Source Type

Odermatt D.,University of Zürich | Giardino C.,CNR Institute for Electromagnetic Sensing of the Environment | Heege T.,EOMAP GmbH
Remote Sensing of Environment | Year: 2010

Semi-analytical remote sensing applications for eutrophic waters are not applicable to oligo- and mesotrophic lakes in the perialpine area, since they are insensitive to chlorophyll concentration variations between 1 and 10 mg/m3. The neural network based Case-2-Regional algorithm for MERIS was developed to fill this gap, along with the ICOL adjacency effect correction algorithm. The algorithms are applied to a collection of 239 satellite images from 2003-2008, and the results are compared to experimental and official water quality data collected in six perialpine lakes in the same period. It is shown that remote sensing estimates can provide an adequate supplementary data source to in situ data series of the top 5 m water layer, provided that a sufficient number of matchups for a site specific maximum temporal offset are available. © 2009 Elsevier Inc. All rights reserved.


Richter R.,EOMAP GmbH | Heege T.,EOMAP GmbH | Kiselev V.,EOMAP GmbH | Schlapfer D.,ReSe Applications
International Journal of Remote Sensing | Year: 2014

An accurate atmospheric correction (AC) of Earth remote-sensing data in the spectral region 450–800 nm has to account for the ozone gas absorption influence. Usual operational AC codes employ a fixed ozone concentration corresponding to a climatologic average for a certain region and season, e.g. the mid-latitude summer atmosphere of the Moderate Resolution Atmospheric Transmission (MODTRAN) code. The reasons for a fixed ozone column are that ozone does not vary rapidly on a spatial and temporal scale, and additionally, the look-up table (LUT) size for AC is already big. This means that another degree of freedom for the ozone parameter would dramatically increase the size of the LUT database and the time required for LUT interpolation. In order to account for this effect, we use already existing LUTs that were calculated for a certain ozone reference level, e.g. an ozone column of g = 330 Dobson Units (DU) for MODTRAN’s mid-latitude summer atmosphere. Then the deviation of the top-of-atmosphere (TOA) radiance ΔL(g) from the reference level L(g = 330) is calculated as a function of solar and view geometries. The calculation is performed for a set of 36 wavelengths in the ozone-sensitive spectrum (450–800 nm) and five ozone columns. The last step computes the linear regression coefficients for each wavelength and geometry. The results are stored in a small table (11 kB). It is shown that the ozone influence is accurately accounted for by multiplying the modelled radiance L(g = 330) with a factor depending on g and wavelength yielding TOA radiance relative errors smaller than 0.5% for a wide range of ozone concentrations between 180 and 500 DU. Selected examples of a sensitivity study of the ozone effect on the retrieval of water constituents demonstrate the need to account for ozone in the AC step. © 2014, © 2014 Taylor & Francis.


Geisler T.,University of Kiel | Oppelt N.,University of Kiel | Heege T.,EOMAP GmbH
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

Numerous approaches characterising the radiation field of a water column have been developed and correction attempts for remote sensing data have been applied successfully. Various algorithms describe the complex interaction of biophysical parameters with down- and upwelling radiation in a water body and form the basis for water column correction. Parameters such as varying bottom reflectances and bathymetry aggravate an accurate parameterization of water column correction models. Applying these models, special interest lies in their sensitivity to both quality and accuracy of model input parameters. In this paper we discuss the sensitivity of the water column correction model MIP2 to bio-physical parameters, i.e. suspended matters (SM) and chlorophyll (CHL), in case 2 waters. In August 2010, hyperspectral AISAeagle data have been acquired; in-situ measurements were conducted concurrently to the airborne campaign. The study was conducted at the rocky shores of the island Helgoland (North Sea, Germany). The study area is characterised by a heterogeneous water body resulting in varying and spatially uncorrelated concentrations of SM and CHL, which aggravate an accurate water column correction. During analysis, special focus is set on areas with varying water characteristics such as vegetated bedrock, shallow sandy spots and deep water areas. Water column correction is performed using a sub-module of MIP, i.e. WATCOR. Reflectance deviation results show that variations of SM concentrations have a stronger influence than variations of CHL within the water column correction. Whereas, the shallow sandy spots reveal the highest sensitivity at constituent concentration variation followed by the deep water and the vegetated bedrock areas. © 2012 SPIE.

Loading EOMAP GmbH collaborators
Loading EOMAP GmbH collaborators