airborne hyperspectral imaging using the casi1500 · 2007-11-07 · with extremely sharp optics....

Copyright © ITRES 2006

Airborne Hyperspectral Imaging Using the CASI1500

AGRISAR/EAGLE 2006, ITRES Research


A class leading VNIR sensor with extremely sharp optics.

• 380 to 1050nm range

• 288 spectral bands

• ~1500 spatial pixels

• up to 30cm spatial resolution

Water Quality - Land Cover - Forestry

CASI 1500 overview


Sunlight- readable

Display

Sensor Head Unit

POS 410 v5.IMU

Instrument Control Unit

(PCU)

Keyboard w. tracking ball


Mission Parameters

• System to be installed coincident with AHS on CASA-212• AGRISAR -288 bands @ 1.1nm FWHM– 6 flight lines per sortie• EAGLE -60 Predetermined bands within 370-1050nm (VNIR).• Aircraft velocity slowed for maximum spatial resolution• Nominal pixel resolutions in raw data

– 288 band = 1.5 * 6 m– 60 band = 1.3 * 0.5m / 1.3 * 1.3m


CASI 1500 Installation(Quatro Vientos 060106)


Flight line configuration for AgriSAR acquisitions.

•High overlap = less bi-directional effects between flight lines

•Best-fit flightline design.

Acquisition Summary - Agrisar


Flight line configuration for EAGLE acquisitions, Speulderbos and LoobosBlocks

Flight line configuration for EAGLE acquisitions, Cabauw Block.

Acquisition Summary- EAGLE

•High overlap = less bi-directional effects between flight lines

•Best-fit flightline design.


June 01, 2006

•CASI integration with AHS in CASA-212-200

June 06, 2006 –AGRISAR 1st Mission

•6 lines @ 288b , acquired in afternoon (~13:00 UTC) due to Wx – isolated clouds in area.

•CASI Hardware problem does not allow for subsequent CASI images for 1st Agrisar campaign (no data June 10th)

June 13, 2006Eagle data acquisitions11 lines over three areas of interest @ 60bands , acquired in afternoon (~11:00 UTC) – Isolated clouds in area, increasing during the acquisition, hazy atmospheric conditions throughout.

July 04 & 05, 2006 –AGRISAR 2nd Mission

•6 lines /day @ 288b, acquired at solar noon (~10:00 UTC). Clear conditions on both days

•Bundle Adjustment Flight performed on July 06, 2006 over NeuBrandenburg.


Radiometric Corrections : Raw to Pix

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Raw vs. Radcorr Spectra Comparison (DN vs. SRU (1 SRU = 1.0 µW cm-2 sr-1 nm-1 )

•Removal of Instrument ‘Noise’ & Dark Current effects•Traceable Standard• ! Persistent Blue – end calibration source effect


Notes on Imagery Calibration

• CASI1500 imagery acquired at maximum spectral resolution & minimunintegration time can be expected to have some image artifacts (noise) in parts of the spectrum where the SNR is lower.

• Data sets where imagery is summed spectrally (i.e 48 spectral bands = 6 rows summed) do not contain the same noise effects due to the reduction of the SNR through summation.

• Calibration of CASI1500 done to standardized light source with an accuracy of ±2% over the spectral range of 470 to 800 nm.

• Below 470 nm and above 800 nm, the quoted accuracy is ± 5%.


Effects of Clouds in Imagery – L4 June 6th

Example of flight line illumination difference in mosaiced CASI1500 data (0705 – L5/6)BiDirectional effects minimized, not cancelled out


Geocorrection process involves the integration of four separate data streams:

Radiometric correction software

extracts GPS time stamp

from CASI data

Aircraft GPS data are differentially corrected (DGPS) using data from a nearby GPS base-station. DGPS positions with aircraft attitude data from the Inertial Measurement Unit (IMU) are generated.

A Digital Elevation Model (DEM) is applied during geocorrection to remove topographic effects and facilitate the final ortho-rectification of the CASI imagery.

Position and attitude data are optimized using sensor misalignments determined in bore-site calibration (bundle adjustment process) and applied to the CASI image data.

A north-up image with square fixed-sized pixels is populated using a nearest neighbor algorithm.

OR

Unaltered image pixels mapped to a Geographic Lookup Table

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= …


Bundle Adjustment : inputs

Ground Control Point (GCP) XYZ Coordinates with reference map

(Courtesy of University of Neubrandenburg )

Identify GCP in non-georeferenced imagery, record image X,Y values for each point

Through use of multiple points , each in +2 adjacent flight lines, Sensor/GPS/IMU angular offset parameters are iterated.

Any data flown during same installation can be solved using offsets.


Bundle adjustment : Output

Boundary between two flight lines – note building offsets due to coarse DEM

XYZ offsets, ωs, φs, κs values entered into navigation data refinement program > Geocorrection is done on these output files.

! DEM coarseness affects linear offsets between flight lines.

! Very high resolution DEMs slow down processing if integrating data into a CASI image.


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Radiometric-corrected CASI image

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Pos Data

SAR Data

Bundle Adjustment


Radiometric / Geocoded hyperspectral Imagery


Fused SAR/CASI mosaic- AgriSAR Optical 2 - 040706

2x Vertical Exaggeration

11x Vertical Exaggeration

Note CASI line boundary

N


Delivered Data format:

•16-bit unsigned integer image files (BIP)

•Accompanying .glu file ( with ENVI header file)

•.glu file : output Geographic lookup table file

•2 channels : Easting, Nothing values in UTM WGS84 for center of each pixel. No resampling!

•Average terrain Height used in Geocorrection due to extents of imagery being outside DEM range – introduces errors in .GLU file write out

~28 Gb delivered data


SENTINEL 2 Simulations

• CASI1500 288 imagery for July 5th , 2007 acquisition used to simulated Sentinel-2 VNIR band data. Imagery averaged over rows that best fit bandset using bandmath function in ENVI.

• Some non-noise image artifacts enhanced by summing, instrument noise averaged out

• Spatial resolution left at original setting for analyst manipulation. • Image files contain both bands 8 & 8a.


Conclusions & Acknowledgements

airborne hyperspectral imaging using the casi1500 · 2007-11-07 · with extremely sharp optics....

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