ARSF Data Processing Consequences of the Airborne Processing Library Mark Warren Plymouth Marine...

ARSF Data ProcessingConsequences 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


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


Hyperspectral Remote Sensing @ ARSF

• Specim Eagle sensor– Visible & Near Infra-Red

• 400nm - 1000nm

– '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


Example data – Poole UK

Left: Eagle Right: Hawk


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


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


Unmapped data

• Little Rissington Airfield

• Difficult to find targets– Distortions– Direction of flight– No fixed X,Y coordinates

• Geocorrection can help


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


Geocorrected / Mapped data


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


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


Potential Error Sources – In the Data

• Level 1 data– Navigation

• Position accuracy – lateral shift

• Synchronisation – distortions and shifts


Zoom – synchronisation error


Potential Error Sources – In the Data

• Auxiliary data– Digital Elevation Model – per-pixel positional errors– More accurate DEM the better


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


Pixel size

• 3 images at the same zoom level– 10m pixel – shows lost data– 2m pixel– 0.5m pixel – shows repeated data



• 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


Interpolation

• Nearest Neighbour vs Cubic


Atmospheric Correction

• 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


Summary

• Intro to ARSF hyperspectral instruments• Problems associated with geocorrecting RS

data• Potential error / limiting effects• Future atmospheric correction products


Thank you for listening

• Any questions?



• 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

ARSF Data Processing Consequences of the Airborne Processing Library Mark Warren Plymouth Marine...

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