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Remotely sensed data characterization, classification, and accuracies / edited by Prasad S. Thenkabail, PhD United States Geological Survey (USGS).

Contributor(s): Thenkabail, Prasad Srinivasa, 1958- [editor.].
Material type: materialTypeLabelBookSeries: Remote sensing handbook ; volume I.Publisher: Boca Raton : Taylor & Francis, [2016]Copyright date: ©2016Description: 1 online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780429089398.Subject(s): Remote sensing -- Data processingAdditional physical formats: Print version: : No titleDDC classification: 621.36780285 Online resources: Click here to view.
Contents:
section 1. Satellites and sensors from different eras and their characteristics -- section 2. Fundamentals of remote sensing : evolution, state of the art, and future possibilities -- section 3. Remote sensing data normalization, harmonization, and intersensor calibration -- section 4. Vegetation index standardization and cross-calibration of data from multiple sensors -- section 5. Image processing methods and approaches -- section 6. Change detection -- section 7. Integrating geographic information systems (GIS) and remote sensing in spatial modeling framework for decision support -- section 8. Global navigation satellite systems (GNSS) remote sensing -- section 9. Crowdsourcing and remote sensing data -- section 10. Cloud computing and remote sensing -- section 11. Google earth for remote sensing -- section 12. Accuracies, errors, and uncertainties of remote sensing-derived products -- section 13. Space law and remote sensing -- section 14. Summary.
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Includes bibliographical references and indexes.

section 1. Satellites and sensors from different eras and their characteristics -- section 2. Fundamentals of remote sensing : evolution, state of the art, and future possibilities -- section 3. Remote sensing data normalization, harmonization, and intersensor calibration -- section 4. Vegetation index standardization and cross-calibration of data from multiple sensors -- section 5. Image processing methods and approaches -- section 6. Change detection -- section 7. Integrating geographic information systems (GIS) and remote sensing in spatial modeling framework for decision support -- section 8. Global navigation satellite systems (GNSS) remote sensing -- section 9. Crowdsourcing and remote sensing data -- section 10. Cloud computing and remote sensing -- section 11. Google earth for remote sensing -- section 12. Accuracies, errors, and uncertainties of remote sensing-derived products -- section 13. Space law and remote sensing -- section 14. Summary.

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