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Why Hyperspectral Remote Sensing? Canadian National Working Groups Recommendations. Geoscience Working Group:Develop a spectral library representative of materials in the Canadian tundraSoftware and algorithm development to help industry to use hyperspectral dataAgriculture Working Group:Identify the potential of hyperspectral data for precision farmingEnvironment Working Group:Applications for the identification of bio-indicators and indexesEmphasis should be placed upon the simpler ca15
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Canadian Hyperspectral Imaging Program
3. Overview of Canadian Capabilities in Hyperspectral Remote Sensing: Program Objectives To develop advanced hyperspectral technologies as partner in foreign missions
To satisfy Canadian needs for high quality hyperspectral data products, and to provide better access to data for Canadian users
To provide advanced hyperspectral information products for:
exploration geology and prospecting
management of mine wastes
assessment of environmental stress in ecosystems and coastal zones
monitoring of water resources and aquaculture
management of forests and agriculture
4.
Canadian Investment in Hyperspectral activities
5. Canadian Expert Support Laboratory (CESL) Medium Resolution Imaging Spectrograph (MERIS) MERIS is a 15 band imager (designed as a visible imaging spectrometer) primarily for ocean/water monitoring ? 300 m footprint) and 3 day revisit cycle
Simulate and evaluate MERIS data in diverse Canadian landscape and seasons
Develop and test product generation algorithms for MERIS
Evaluate benefits of information products and initiate a science framework for Canada
6. Overview of Canadian Capabilities in Hyperspectral Remote Sensing Hyperspectral Mission:
Canada Space Agency (CSA) and Canada Centre for Remote Sensing (CCRS) are providing a coordinated approach to facilitate access to hyperspectral missions and related opportunities
Current activities :
Prepare options for Canadian participation in a hyperspectral mission
Data and instrument simulation to ensure that mission meets Canadian users needs and to influence payload design
Demonstration of applications to ensure that Canadian users can take full advantage of the data when a satellite is operational
7. Hyperspectral Imager Technology Assessment: Objectives Examine Canadian participation in all aspects of satellite based program and provide critical assessment of:
Technical constraints
Schedule
Budget
Leading to:
detailed design and fabrication
user application studies and user development
8. Hyperspectral SensorFunctional Block Diagram Foreoptics and Calibration Subsystems shown in Orange
Detectors and signal conditioning in Blue
Data Handling Electronics in Yellow
Data Formatter in Green
Spectrometer and instrument control computer in white.Foreoptics and Calibration Subsystems shown in Orange
Detectors and signal conditioning in Blue
Data Handling Electronics in Yellow
Data Formatter in Green
Spectrometer and instrument control computer in white.
9. Hyperspectral Imager Technology Assessment: ForeOptics and Calibration-
Examined a series of compact telescopes;
Evaluated signal level requirements for on-board and on-ground calibration systems
Detectors and Buffering- Identified candidate detectors VNIR and SWIR data rate constraints and data reformatting requyirements
Interfaces- Identified instrument data bus structures
Quality Assurance- Guidelines provided for Space Qualified programForeOptics and Calibration-
Examined a series of compact telescopes;
Evaluated signal level requirements for on-board and on-ground calibration systems
Detectors and Buffering- Identified candidate detectors VNIR and SWIR data rate constraints and data reformatting requyirements
Interfaces- Identified instrument data bus structures
Quality Assurance- Guidelines provided for Space Qualified program
10. Hyperspectral Imager Technology Assessment Modelling- examined the needs for overall system modelling
Lossless Compression- Summary of lossless compression algorithms and space qualified Lossless compression chips
Applications- Provided a status summary of algorithms and the applicability of candidate sensors characteristics to each appplication
Software Tools- Recommendations re development of COTS or customized S/W tools to satisfy Canadian needs.Modelling- examined the needs for overall system modelling
Lossless Compression- Summary of lossless compression algorithms and space qualified Lossless compression chips
Applications- Provided a status summary of algorithms and the applicability of candidate sensors characteristics to each appplication
Software Tools- Recommendations re development of COTS or customized S/W tools to satisfy Canadian needs.
11. Goals
1. Hyperspectral Data Cube management
2. Spectral interpretation (match to known or identify unknown)
3. Combining spectral-spatial algorithms
4. Visualization tools
5. Browse, archive, retrieval and dissemination
Some Developers (algorithms, proprietary and COTS tools)
- Canada Centre for Remote Sensing (CCRS) – Imaging Spectrometer Data Analysis System (ISDAS)
- Canadian Space Agency (CSA)
- MacDonald Dettwiler and Associates (MDA)
- Borstad
- Itres
- Universities Software Tools for Hyperspectral Imagers
12. Hyperspectral Imager Technology Assessment
13. #1 Optical Technology Advancement Demonstrate fabrication capabilities for a three-mirror anastigmatic (TMA) fore-optics and on-board calibration subsystem optical elements
Build and test breadboard optical components
Perform fabrication and materials trade-offs
Advance TMA and calibration-subsystem optical designs, considering e.g. stray light, scatter, opto - mechanical methods
14. #2 System Studies for a Hyperspectral Imager: Establish system-level and instrument-level requirements, based on applications needs
Develop system modeling tools, including applications algorithms, lumped-parameter models (LPMs) and data-flow models (DFMs)
Perform systems analysis using LPMs and DFMs
Models and analyses to include Cal/Val requirements and functional performance
Application algorithms should be well benchmarked including ground truth to distinguish instrument error from algorithm error
15. #3 Predictors for Lossless Compression of Hyperspectral Data: Investigate and Select optimum predictor for a satellite HSI program, considering performance and ease of hardware implementation
Assess predictor’s performance, using Hyperspectral datasets from a variety of available scenes and sensors
Examine benefits of on-board calibration to compression
Consolidate buffering and compression electronics design; identify critical components and implementation issues
16. ESA Explorer Core MissionLand Surface Processes and Interaction Mission Designed to meet research goals
Relies on intensive study of particular sites
Examines BRDF algorithms and Remote Sensing Science
17. Partnerships Ongoing discussions with:
Australia - Australian Resource Information and Environmental Satellite (ARIES)
European options
European Space Agency (ESA) Earth Explorer
Land Surface Processes and Interaction Mission (Core Mission)
SIMSA 'Spectral Imaging Mission for Science, and Application' (German Initiative)
Smart Spectral - Dornier Satellitensysteme (DSS) led commercial mission
18. Australian Resource Information and Environmental Satellite (ARIES) Goal: to develop and operate a commercially sustainable resource information satellite using the latest hyperspectral sensing technology
Outcome of 20 years of collaborative R&D between Australia’s leading research agency Commonwealth Scientific and Industrial Research Organization (CSIRO) and the mining industry
ARIES-1 Project Office created in October 1995
ARIES-1 feasibility study completed in March 1997
ARIES-1 launch in 2002 with operation starting in 2003
Australian consortium: CSIRO, Australian Centre for Remote Sensing (ACRES) , Auspace Limited
Other partners:
International groups of mining and exploration companies
Australian and European Geological Surveys consortia
UK Natural Environment Research Council
Canada Centre for Remote Sensing (with the participation of CSA)
19. Australian Resource Information and Environmental Satellite (ARIES) Satellite:
Australian design and weight less than 500 kg
Polar, sun synchronous 500 km above the Earth's surface
Design life: 5 years
Sensor:
32 contiguous bands in the VNIR (400 to 1100 nm)
32 contiguous bands in the SWIR (2000 to 2500 nm)
Optional coverage of 1000 to 2000 nm range with emphasis on atmospheric correction and calibration
Spatial resolution: Spectrometer - 30 meters at nadir Panchromatic - 10 meters at nadir
Ground swath: 15 km at nadir
Off-track pointing: to 30 degrees off vertical
Revisit time: 7 days at 30 degrees look angle
20. Status of ARIES ARIES Phase A and pre-Phase B completed by current partners
Australian Tax Office ruling critical to ARIES funding
Phase B set started June 1999
Preliminary discussions between Canada and ARIES started in March and December 1997
The first ARIES Data Analysis and Simulation Workshop was held in Sydney on 8 and 9 April, 1997
Major joint workshop held in June 1998
Work package alternatives discussed
Data rights discussed
Meetings with ARIES held 1999 - 2001
21. ARIES Consortium Currently there are three partners:
Auspace Limited (a wholly owned subsidiary of Matra - Marconi Space - UK)
CSIRO (Division of Exploration and Mining )
ACRES
ARIES Operating Company
Finances operations through data sales
Investors TBD
Space Segment Prime
Applications Prime
Ground Segment Prime
Owns Satellite and Data
Contracts with AUSPACE, CSIRO and ACRES for satellite development and operation