292
F. Giittsche. F.-S. Olesen
atmospheric correction of IR satellite data with neural networks and the modelling
and analysis of the thermal behaviour of single pixels, also apply to MSG. These
investigations of the Forschungszentrum Karlsruhe - IMK will be complemented by
investigations of vegetation and albedo performed by the FU-Berlin.
References
Chinnaswamy A (1999) Parameterisation of Retrieval of SST from Geostationary Satellites. 3rd
Symposium on Integrated Observing Systems, January 11-15, University of Oklahoma, USA.
Braun H, Ragg T (1996) ENZO: Evolution of neural networks (Internal report. Fakultat flir
Informatik, Universitat Karlsruhe. 1996,21). University of Karlsruhe, Institute for Logic,
Complexity, and Deduction Systems, Germany.
Dash P, Giittsche F-M, Olesen, F-S, Fischer H (2001) Land surface temperature and emissivity
estimation from passive sensor data: theory and practice; current trends. Int. 1. Remote Sens.
(accepted).
DefenceMapping Agency (DMA) (1986) Defence Mapping Agency Product Specifications for Digital
Terrain Elevation Data (DTED). DMA Aerospace Centre, St. Louis
EUMETSAT (1998) http://www.eumetsat.de/en
Giittsche F-M, Olesen F-S (2001) Modelling of diurnal cycles of brightness temperature extracted
from METEOSAT data. Remote Sens. Environ. 76(3):337-348
Giittsche F-M, Olesen F-S (2002) Evolution of neural networks for radiative transfer calculations in
the terrestrial infrared. Remote Sens. Environ. 80(1):157-164 (accepted)
Koslowsky D (1996) Langjahrige validierte und homogenisierte Reihen des Reflexionsgrades und des
Vegetationsindexes von Landoberflachen aus taglichen A VHRR-Daten hoher Aufliisung. Institut
flir Meteorologie, Freie Universitat Berlin, Wiss.Met.Abh., Neue Folge, Serie A 9,1, Dissertation
Olesen F-S, Kind 0, Reutter H (1995) High resolution time series of IR data from a combination of
AVHRR and METEOSAT. Advances in Space Research, VoL 16:141-146
Riedmiller M (1993) A direct adaptive method for faster back-propagation learning: The RPROP
algorithm. Proceedings of the IEEE International Conference on Neural Networks (lCNN), I,
pp.586-591
Reutter H, Olesen F-S, Fischer H (1994) Distribution of the brightness temperature of land surfaces
determined from AVHRR data. Int. J. Remote Sens., IS: 95-104
Schadlich S, Giittsche F-M, Olesen F-S (2001) Influence ofland surface parameters and atmosphere
on METEOSAT brightness temperatures and generation of land surface temperature maps by
temporally and spatially interpolating atmospheric correction. Remote Sens. Environ., 75(1): 3946
Schroedter M, Olesen F-S, Fischer H (200 I) Determination of land surface temperature distributions
from single channel IR measurements: An effective spatial interpolation method for the use of
TOVS, ECMWF and radiosonde profiles in the atmospheric correction scheme. Int. J. Remote
Sens. (accepted)
Vollmer M, Giittsche F-M, Olesen F-S (2000) Correction of the atmospheric influence on IR
measurements by satellite with neural networks. The 2000 EUMETSAT Meteorological Satellite
Data Users' Conference. Bologna, Italy, pp. 506-511
Zell A (1994) Simulation neuronaler Netze. Olden bourg-Verlag, Miinchen, Germany
F. Giittsche. F.-S. Olesen
atmospheric correction of IR satellite data with neural networks and the modelling
and analysis of the thermal behaviour of single pixels, also apply to MSG. These
investigations of the Forschungszentrum Karlsruhe - IMK will be complemented by
investigations of vegetation and albedo performed by the FU-Berlin.
References
Chinnaswamy A (1999) Parameterisation of Retrieval of SST from Geostationary Satellites. 3rd
Symposium on Integrated Observing Systems, January 11-15, University of Oklahoma, USA.
Braun H, Ragg T (1996) ENZO: Evolution of neural networks (Internal report. Fakultat flir
Informatik, Universitat Karlsruhe. 1996,21). University of Karlsruhe, Institute for Logic,
Complexity, and Deduction Systems, Germany.
Dash P, Giittsche F-M, Olesen, F-S, Fischer H (2001) Land surface temperature and emissivity
estimation from passive sensor data: theory and practice; current trends. Int. 1. Remote Sens.
(accepted).
DefenceMapping Agency (DMA) (1986) Defence Mapping Agency Product Specifications for Digital
Terrain Elevation Data (DTED). DMA Aerospace Centre, St. Louis
EUMETSAT (1998) http://www.eumetsat.de/en
Giittsche F-M, Olesen F-S (2001) Modelling of diurnal cycles of brightness temperature extracted
from METEOSAT data. Remote Sens. Environ. 76(3):337-348
Giittsche F-M, Olesen F-S (2002) Evolution of neural networks for radiative transfer calculations in
the terrestrial infrared. Remote Sens. Environ. 80(1):157-164 (accepted)
Koslowsky D (1996) Langjahrige validierte und homogenisierte Reihen des Reflexionsgrades und des
Vegetationsindexes von Landoberflachen aus taglichen A VHRR-Daten hoher Aufliisung. Institut
flir Meteorologie, Freie Universitat Berlin, Wiss.Met.Abh., Neue Folge, Serie A 9,1, Dissertation
Olesen F-S, Kind 0, Reutter H (1995) High resolution time series of IR data from a combination of
AVHRR and METEOSAT. Advances in Space Research, VoL 16:141-146
Riedmiller M (1993) A direct adaptive method for faster back-propagation learning: The RPROP
algorithm. Proceedings of the IEEE International Conference on Neural Networks (lCNN), I,
pp.586-591
Reutter H, Olesen F-S, Fischer H (1994) Distribution of the brightness temperature of land surfaces
determined from AVHRR data. Int. J. Remote Sens., IS: 95-104
Schadlich S, Giittsche F-M, Olesen F-S (2001) Influence ofland surface parameters and atmosphere
on METEOSAT brightness temperatures and generation of land surface temperature maps by
temporally and spatially interpolating atmospheric correction. Remote Sens. Environ., 75(1): 3946
Schroedter M, Olesen F-S, Fischer H (200 I) Determination of land surface temperature distributions
from single channel IR measurements: An effective spatial interpolation method for the use of
TOVS, ECMWF and radiosonde profiles in the atmospheric correction scheme. Int. J. Remote
Sens. (accepted)
Vollmer M, Giittsche F-M, Olesen F-S (2000) Correction of the atmospheric influence on IR
measurements by satellite with neural networks. The 2000 EUMETSAT Meteorological Satellite
Data Users' Conference. Bologna, Italy, pp. 506-511
Zell A (1994) Simulation neuronaler Netze. Olden bourg-Verlag, Miinchen, Germany