Dan Fisher

Remote Sensing and Image Processing

Climatology Generation

Validation of Remotely Sensed Observations

In June 2014, Daniel began working on the LSA SAF fire radiative power (FRP) products with Professor Martin Wooster.  In the first instance he will be looking at the impact of optically thin clouds on observations of FRP and assessing the suitability of the cloud clearing approaches currently employed in the operational products.  He will also be assessing the fidelity of the georeferencing of the SEVIRI imagery.      

Daniel defended his thesis at University College London, in February 2014.  Under the supervision of Professor Jan-Peter Muller, Daniel researched into novel stereo-photogrammetric techniques for application to the Along Track Scanning Radiometer instruments.  During this research he identified and applied a number of stereo matching algorithms and generated the first long-term stereo derived cloud climatology from AATSR.  Daniel also researched into the derivation of tropospheric winds using optical flow techniques applied to tandem stereo imagery from the ATSR-2 and AATSR instruments. Furthermore, he generated the first validated correction coefficients for improving the co-registration between the forward and nadir views of all three ATSR instruments.

Daniel has also worked on a number of other projects prior to joining King's.  He was a member of the ESA ALANIS smoke plumes project, where, in collaboration with Prof. Muller and Dr. Vladimir Yershov (MSSL), the first stereo derived smoke plume injection height measurements were made from AATSR.  He was a member of the GlobAlbedo project, where his work on multi-sensor image collocation, allowed the effective synergistic usage of AATSR and MERIS imagery for the determination of sea-ice albedo.  Most recently, he worked with Dr. Caroline Poulsen (RAL) and Prof. Muller on the integration of stereo a priori observations from AATSR into the ORAC cloud retrieval scheme in an attempt to improve the cloud parameter retrievals in radiometrically challenging conditions (e.g. cloud in the atmospheric boundary layer).