Hyperspectral Sensors Calibration, Operation and Maintenance

1. HyperspectralSensorsCalibration, Operation and Maintenance Jens Nieke, Daniel Schläpfer, Francesco Dell'Endice, Klaus Itten (RSL) Koen Meuleman (VITO) Michael Schaepman (WUR)

2. Introduction • Calibration (cal/val) activities: • Pre-launch (laboratory), in-flight and vicarious calibration, validation • Spectral, radiometric, spatial calibration • Higher product validation

3. Introduction • Operations & Services: • Spaceborne sensors: • ESA operations center ESRIN (e.g., CHRIS) • U.S. Geological Survey (USGS): EROS data center (e.g., HYPERION) • Airborne sensors: Vito, DLR, INTA, … • Maintenance : • Spaceborne sensors: no maintenance required • Airborne sensors: frequent maintenance recommended (combined with re-calibration activities)

4. Hyperspectral Sensors • Methodology of Sensor Calibration • Calibration of HYPERION / CHRIS • Pre-launch (TRW / SIRA) • Products: L1B, geocorrected • Calval not coordinated (except of WS) • Calibration of HYMAP • Pre-flight (however no visibility of calibration procedures) • Calval not coordinated • Validation Techniques at reference site Gilching

5. Hyperspectral Sensors • Operations Boundary conditions • Operations of HYPERION/ CHRIS • Dedicated data facilities (USGS/ESRIN) • Request via help desks / web • FAST DATA DELIVERY! • Operations of Airborne Sensors (Vito, DLR, INTA..) • Call for Requests (long preparation time) • Availability of sensor/aircraft (summer season) • FEW months for data delivery • Maintenance of (airborne) sensors • Methods (cleaning lenses?) • Techniques (spare part services)

6. Examples Operational spaceborne sensors, with open calibration record and exemplary cal/val activities: • MODIS and SeaWiFS • Best documented data descriptions and open data distribution policy (extraordinary funding resources are available). • MERIS • Well documented data restricted to a selection of data products due to funding limitations.

7. Examples Operations of MIVIS: The instrument was delivered as commercial off-the shelf solution, without visibility to the internal preprocessing. Scientific usability is restricted due to: • Unknown radiometric calibration stability/accuracy • Undocumented on-board processing routines (and no ability to switch off on-board processing).

8. Examples Operations of AVIRIS: for about 15 years, a team of ~10 people provided upgrades and calibration to the instrument. Calibration results were published in workshop proceedings. High scientific value because of… … very well known and accepted accuracy of the instrument. Open information and generous data policy.

9. Developments Example: APEX calibration methodology (SPIE paper*) * Nieke, Kaiser, Schläpfer, Brazile, Itten, Strobl, Schaepman, Ulbrich, SPIE Vol. 5570 (2004)

10. APEX-CHB APEX-IFC Developments Example: APEX calibration methodology (SPIE paper*) * Nieke, Kaiser, Schläpfer, Brazile, Itten, Strobl, Schaepman, Ulbrich, SPIE Vol. 5570 (2004)

11. Developments Challenges: (1) meeting the accuracy requirements of the user community, (2) the lack of standard methodologies for calibration and validation of hyperspectral methods and products, and (3) reliable (comparable) higher-level data products. Needs: • The introduction of standard methods and processing schemes • Hyperspectral data with known performance and error propagation • More efforts on data pre-processing, including ortho-rectification, atmospheric corrections and in-flight calibration. => Standard methods and processing schemes will also allow to compare higher-level data products in a better way.

12. Discussion Points Open Qs: • What are the minimum calibration requirements of end users? • Are the end users willing to pay more for better knowledge of calibration issues? • Who is able to provide independent system performance validation? • Is there a bigger market for cost-effective off-the shelf instruments (with less calibration information) ?

13. Discussion Points • Calibration of latest-generation hyperspectral sensors clearly requires new technological efforts: • Software: the complexity of data processing algorithms has created the need for improved computing infrastructure, and implies stronger requirements on memory/storage issues as well as advanced downlink and data transmission strategies. • Hardware: low-weight and low-power integrated components, along with calibration sources and fast electronics, are mandatory to reduce payload, data transmission overheads and satisfy other requirements in many planned and future Earth observing missions. • Reliable CalVal requires operational data retrieval (CalVal sites, ground-truth data) and processing.

14. Discussion Points • Operations & Services of latest-generation hyperspectral sensors clearly requires further efforts: • Fast delivery • User support • Additional data: quality flags, 3rd party data (ECMWF) • Further services: add-on modules, hotline • Automatic chain for standard products • Flexible exchange of research product codes

15. Discussion Points • Maintenance of latest-generation hyperspectral sensors clearly requires further efforts: • On-board data processing capabilities and programmability, • Standardization of laboratory calibration procedures, • Streamlined cross-calibration procedures for validation, • Sensor stability between calibration.