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Data Processing

Data Processing. Eduardo de Miguel Remote Sensing Laboratory INTA - Spain. Introduction. Data processing = Data calibration + quality control + data transformation + information retrieval Both at user side and provider side. Data Processing. Usual DP tasks at provider side:

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Data Processing

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  1. Data Processing Eduardo de Miguel Remote Sensing Laboratory INTA - Spain

  2. Introduction • Data processing = Data calibration + quality control + data transformation + information retrieval • Both at user side and provider side

  3. Data Processing • Usual DP tasks at provider side: • Radiometric calibration • Geometric correction • Atmospheric correction (might be included in radiometric correction) • Evaluating product accuracy (quality control) • Unusual DP tasks at provider side: • Data transformations (PCA, MNF, spectral resampling…)

  4. Data Processing • Usual DP tasks at user side: • Data transformations • Endmember selection • Spectral unmixing, spectral matching... • Classification • Feature detection • Running models • …

  5. Standard tools • Radiometric calibration: linear models • Geometric correction: direct geo-referencing • Atmospheric correction: MODTRAN and relatives (ATCOR, ACORN, FLAASH), ATREM, vicarious calibration (empirical line) • Temperature/emissivity separation: TES, others??

  6. Standard tools • Spectral tools: … • Transforms: … • Classification: … • Filters and convolutions: … (See ENVI as show-case of standard tools)

  7. Standard tools • Quality control & accuracy measures: ?? • Metadata definition: none (ISO19115??) • Metadata documentation/distribution: none • Data inventory/catalogues: none

  8. SWOT • Strengths and Weakness (I) • Geo-registration procedures satisfactory. (It is re-sampling correctly addressed?) • Radiometric/atmospheric correction is often close to 5% error in reflectance units. • Reporting geometric accuracy is not clear. • Reporting radiometric accuracy requires ground spectra / temperature.

  9. SWOT • Strengths and Weakness (II) • BRDF effects (and emission angular effects) are still outside of the standard processing pipeline. • Temperature/Emissivity algorithms far from being operational. • Metadata are not provided in a regular basis nor in a standard way

  10. Developments • A review of DP topics in the 2004 EARSel SIG IS workshop and the 2006 IGARSS. • Endmember extraction, spectral unmixing, advanced classification procedures… • BRDF modelling • Compression • Others • Nothing on quality/accuracy measures and metadata

  11. Discussion Points • It is geometric resampling a problem? • How to evaluate the geometric accuracy? • Which is the way to reduce the 5% error in atmospheric correction? • Should the spectral unmixing be performed at the provider side? (it is affected by instrument features, like PSF and spatial sampling)

  12. Discussion Points • It is worth to put effort on data compression? • When will be BRDF correction a common practice? • What is the users feeling about metadata? • … • (Your entry here)

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