INTRODUCTION TO Geological REMOTE SENSING
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The document outlines the syllabus for ESS 421 - Introduction to Geological Remote Sensing. The course covers topics such as the physical basis of remote sensing, spectra, image processing, and applications. It provides information on the professor, TA, class times, exams, labs, and grading. Remote sensing images can be made at different wavelengths and reveal different compositional information. Images can also show changes over time or derived parameters. Remote sensing and GIS work together in geospatial analysis of imagery.
![LKC App A: radiometric terminology (p. 742)
Radiant energy (J) [Q]
Radiant flux (J s-1
= W) [Ф]
Radiant intensity (W sr-1
) [I]
Irradiance (W m-2
) [E] Radiance (W m-2
sr-1
) [L]
Spectral irradiance (W m-2
µm-1
) [Eλ] Spectral radiance (W m-2
sr-1
µm-1
) [Lλ]](https://image.slidesharecdn.com/iitgtymrtglvsv4grr5k-signature-8dbde3c4dcca9e3d642395f3a7aad315577e37234540d7b5aab9c33dade3a242-poli-141220081611-conversion-gate01/85/INTRODUCTION-TO-Geological-REMOTE-SENSING-19-320.jpg)
INTRODUCTION TO Geological REMOTE SENSING
- 1. ESS 421 – Introduction to Geological Remote Sensing Prof: Alan Gillespie (JHN 343) arg3@uw.edu Office hours: Wed - Fri 1 - 3 or by arrangement TA: Iryna Danilina (JHN 330) danilina@uw.edu Office hours: Wed/Fri 12:30 - 2 or by arrangement Lectures: Wednesday/Friday 9:30-10:20 JHN-021 Labs: Wednesday/Friday 10:30-12:20 JHN-366 NO LAB TODAY – LAB 1 on FRIDAY Midterm: Wednesday, 9 February 9:30-10:20 JHN-021 Final: Wednesday, 16 March 10:30-12:20 JHN-021 Class website: http://gis.ess.washington.edu/keck/ess421_documents.html Wednesday, 5 January 2011
- 2. What topics are covered in ESS 421? - physical basis of remote sensing - spectra - radiative transfer - image processing - radar/lidar - thermal infrared - applications
- 3. Schedule • LECTURES LABS • Jan 05 1. Intro • Jan 07 2. Images 1 • Jan 12 3. Photointerpretation 2 • Jan 14 4. Color theory • Jan 19 5. Radiative transfer 3 • Jan 21 6. Atmospheric scattering • Jan 26 7. Lambert’s Law 4 • Jan 28 8. Volume interactions • Feb 02 9. Spectroscopy 5 • Feb 04 10. Satellites & Review • Feb 09 11. Midterm 6 • Feb 11 12. Image processing • Feb 16 13. Spectral mixture analysis 7 • Feb 18 14. Classification • Feb 23 15. Radar & Lidar 8 • Feb 25 16. Thermal infrared • Mar 02 17. Mars spectroscopy (Matt Smith) 9 • Mar 04 18. Forest remote sensing (Van Kane) • Mar 09 19. Thermal modeling (Iryna Danilina) • Mar 11 20. Review • Mar 16 Final Exam Lectures Reading Labs Class structure Ethics policy statement UW now requires an ethics policy statement. In ESS 421, we expect you to adhere to the following: •Labs: collaborative work in lab exercises is encouraged, but please write up the results yourself •Homework: Any homework assigned should be your own •Quizzes, Midterm, Final: All work should be your own •All assignments must be turned in. If some problem arises, please discuss with the TA or instructor •Grades: grading is on a curve.
- 4. Lab Exercises ° 9 lab exercises ° one lab per week, handed out Wednesdays (except today) ° due the following Wednesday, beginning of Lab period ° lab files (e.g., “Lab_1.doc”) are available from the website ° print only the “Answers” file of the lab (e.g., “Lab_1-answers.doc”) & turn in only this sheet to TA with your answers Unexcused late work will be docked 10% per day ° at the beginning of the lab on Wednesdays there will be a short one-page graded quiz on the lab just turned in, plus reading for the past week. Bring a sheet of paper for the answers and turn in to the TA. ° the labs just handed in will be reviewed after the quiz
- 5. Reading Assignments °Text is Lillesand, Kiefer, and Chipman “Remote Sensing and Image Interpretation” 6th ed. 2007, John Wiley ° Reading assignments in the text may be augmented with other material available on class website
- 6. Examinations & Grading °Midterm and Final will both contain questions from the lectures, reading, and labs ° Midterm covers 1st half of class °Final covers whole class with emphasis on 2nd half Labs - 30% Lab quizzes - 20% Midterm - 20% Final - 30% Failure to turn in all work in each of the 4 categories above will result in an incomplete
- 7. Lecture 1: Introduction Reading assignment: Lillesand, Kiefer & Chipman: Ch 1.1, 1.2 radiation Ch 1.6 reference data Ch 1.7 GPS Ch 1.10 GIS Ch 2.9 Multiband imaging For your reference App. A Concepts & terminology App. B Data and resources 1
- 8. What is remote sensing? 2 “Denied terrain” Measurement from a distance - Hazardous locales - Nodong, N. Korea
- 9. What is an image? 3 Y(latitude) X (longitude)
- 10. 4 Images in combination with maps add to interpretive power Geographic Information System (GIS)
- 11. Images can be made at different wavelengths of light 5 NASA MASTER airborne 50-band multispectral image X Y λ λ=8.735 µm λ=9.205 µm λ=10.275 µm λ=10.755 µm λ=11.405 µm λ=0.462 µm λ=0.542 µm λ=0.658 µm λ=0.804 µm λ=0.870 µm Image visualizations display only a subset of the data
- 12. 6 NASA MASTER airborne 50-band multispectral image R=0.658µm G=0.542µm B=0.462µm and displayed as color pictures NASA MASTER airborne 50-band multispectral image X Y λ λ=8.735 µm λ=9.205 µm λ=10.275 µm λ=10.755 µm λ=11.405 µm λ=0.462 µm λ=0.542 µm λ=0.658 µm λ=0.804 µm λ=0.870 µm
- 13. 7 X Y λ λ=8.735 µm λ=9.205 µm λ=10.275 µm λ=10.755 µm λ=11.405 µm λ=0.462 µm λ=0.542 µm λ=0.658 µm λ=0.804 µm λ=0.870 µm R=0.658µm G=0.542µm B=0.462µm Only 3 bands at a time can be visualized this way… but there is more information, and can be shown in a spectrum Spectrum
- 14. 8 R=0.658µm G=0.542µm B=0.462µm Spectra are different and convey information about composition Note the scale change!
- 15. 9 Images can be made at different wavelengths of light X Y λ λ=8.735 µm λ=9.205 µm λ=10.275 µm λ=10.755 µm λ=11.405 µm λ=0.462 µm λ=0.542 µm λ=0.658 µm λ=0.804 µm λ=0.870 µm
- 16. 10 They reveal different information about scene composition VISIBLE THERMAL INFRARED
- 17. Images are not limited to light reflected or emitted from a surface. They can be made over time, or of derived or calculated parameters. 12 Carbon monoxide at 500 mB pressure (elevation), from NASA’s Terra/Moppitt Increasing concentration of CO http://gis.ess.washington.edu/keck/lectures_ESS_421/mopit.MPE
- 18. How do remote sensing and GIS fit together in geospatial analysis? 13 Remote sensing GIS Engineering Analysis & Interpretation Operations & acquisition Image processing Calibration Validation sceneproject goals physics of remote sensing Knowledge Scanners & data
- 19. LKC App A: radiometric terminology (p. 742) Radiant energy (J) [Q] Radiant flux (J s-1 = W) [Ф] Radiant intensity (W sr-1 ) [I] Irradiance (W m-2 ) [E] Radiance (W m-2 sr-1 ) [L] Spectral irradiance (W m-2 µm-1 ) [Eλ] Spectral radiance (W m-2 sr-1 µm-1 ) [Lλ]
- 20. In the spectrum, energy is dispersed by a grating or prism according to frequency or wavelength Gamma rays <10-4 µm X rays 10-4 - 10-2 µm Ultraviolet 0.01-0.45 µm Visible blue B 0.47-0.48 µm Visible green G 0.51-0.56 µm Visible red R 0.63-0.68 µm Near infrared NIR 0.67-1.4 µm Shortwave infrared SWIR 1.4-2.5 µm Mid-wave infrared MIR 3.5-5.5 µm Longwave thermal infrared LWIR 8-14 µm Microwave (Radar) 0.1mm-1 m Radio 1 m - 10 km Reflectedsunlight Thermal radiation The electromagnetic spectrum Short λ High energy High frequency Long λ Low energy Low frequency
- 21. What was covered in today’s lecture? •Remote sensing •Images, maps, & pictures •Images and spectra •Time series images •Geospatial analysis framework •Useful parameters and units •The spectrum 14
- 22. What will be covered in Friday’s lecture 14 imaging systems and some of their characteristics