ARSF Data Processing Consequences of the Airborne Processing Library Mark Warren Plymouth Marine Laboratory, Plymouth, UK RSPSoc 2012 – Greenwich, London

RSPSoc 2012 – Greenwich Overview Airborne Research and Survey Facility (ARSF) –Who are we, what do we do Airborne Processing Library (APL) –Hyperspectral processing suite Geocorrection –Airborne hyperspectral images Potential error sources –Mapping using APL

RSPSoc 2012 – Greenwich ARSF: Who are we Airborne Research and Survey Facility (ARSF) NERC facility Supporting UK & European science –Dornier 228 aircraft Two hyperspectral sensors Full waveform LiDAR Medium format digital camera Plymouth / Gloucester

RSPSoc 2012 – Greenwich Hyperspectral Remote ARSF Specim Eagle sensor –Visible & Near Infra-Red 400nm nm –'Push-broom' sensor –Field of view ~37 degrees Specim Hawk sensor –Short Wave Infra-Red 1000nm – 2500nm –'Push-broom' sensor –Field of view ~24 degrees

RSPSoc 2012 – Greenwich Example data – Poole UK Left: EagleRight: Hawk

RSPSoc 2012 – Greenwich Airborne Processing Library (APL) Software suite developed to process ARSF hyperspectal data –Radiometric calibration –Geocorrection Cross purpose – in-house + end user –Windows, Linux –Graphical User Interface or Command Line

RSPSoc 2012 – Greenwich Point of View of ARSF user ARSF data delivered at “level 1” –Radiometric calibration –Navigation synchronisation –[2012 onwards also delivered mapped] User can apply additional algorithms –e.g. Atmospheric correction User can geocorrect the data with APL –Produce maps of data

RSPSoc 2012 – Greenwich Unmapped data Little Rissington Airfield Difficult to find targets –Distortions –Direction of flight –No fixed X,Y coordinates Geocorrection can help

RSPSoc 2012 – Greenwich Geocorrection – What? What is it? –Associating position information –Mapping to a real-world projection Benefits of geocorrecting / mapping –Easier to identify targets –Compare data from other map sources Limitations of geocorrecting / mapping –Can introduce different distortions –Can give misleading results

RSPSoc 2012 – Greenwich Geocorrected / Mapped data

RSPSoc 2012 – Greenwich Geocorrection – How? Stage 1 – create the mapping –Position / attitude / sensor pixel vectors –Per-pixel position information Stage 2 – resample data –Output pixel size –Interpolation –Fill the mapped grid using stage 1 mapping

RSPSoc 2012 – Greenwich Geocorrection Limitations for Airborne Data Airborne RS data usually localised areas –Projection internal distortion not big issue Platform stability –Wind / atmospheric buffeting –Roll / pitch / yaw Position accuracy –GPS constellation + ground stations Sensor –Stability of sensor head (internal movements) –Lens distortions

RSPSoc 2012 – Greenwich Potential Error Sources – In the Data Level 1 data –Navigation Position accuracy – lateral shift Synchronisation – distortions and shifts

RSPSoc 2012 – Greenwich Zoom – synchronisation error

RSPSoc 2012 – Greenwich Potential Error Sources – In the Data Auxiliary data –Digital Elevation Model – per-pixel positional errors –More accurate DEM the better

RSPSoc 2012 – Greenwich Potential limiting sources – Mapping 1 Pixel size –Try and stay similar to spatial resolution Related to aircraft height above surface –Size effects Too small - repeated data (not more data!) Too large - lost data 'Blocky' image

RSPSoc 2012 – Greenwich Pixel size 3 images at the same zoom level –10m pixel – shows lost data –2m pixel –0.5m pixel – shows repeated data

RSPSoc 2012 – Greenwich Potential limiting sources – Mapping 2 Interpolation –Required for transformation from 1 grid to another –Nearest neighbour Guarantees 'real' observed values 'blocky' image –Bilinear / Bicubic Unobserved (maybe unrealistic) values Smoothed data, visually pleasing image Problems with in-situ data comparisons

RSPSoc 2012 – Greenwich Interpolation Nearest Neighbour vs Cubic

RSPSoc 2012 – Greenwich Atmospheric Correction –Level 1 vs Mapped geometries –More spectral coverage the better Problem: separate Eagle / Hawk –Combine the spectra –Problems Different spatial resolution Different look vectors Different swath widths –Partial geocorrection of both and combine nearest points

RSPSoc 2012 – Greenwich Summary Intro to ARSF hyperspectral instruments Problems associated with geocorrecting RS data Potential error / limiting effects Future atmospheric correction products

RSPSoc 2012 – Greenwich Thank you for listening Any questions?

RSPSoc 2012 – Greenwich

Potential limiting sources – Mapping 3 Multiple bands and Masking –Masking data Insert a “null” value Interpolated over –Multiple bands Spectral analysis –incorrect profile if some bands masked Assumes sensor view vectors same for each band