ESS 421 – Introduction to Geological Remote Sensing

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Presentation transcript:

ESS 421 – Introduction to Geological Remote Sensing Tuesday, 5 January 2010 ESS 421 – Introduction to Geological Remote Sensing Prof: Alan Gillespie (JHN 343) arg3@uw.edu Office hours: T, W, Th 1-3 or by arrangement TA: Iryna Danilina (JHN 330) danilina@uw.edu Office hours: Mon-Wed-Fri 2-3 or by arrangement Lectures: Tuesday/Thursday 9:30-10:20 JHN-111 Labs: Tuesday/Thursday 10:30-12:20 JHN-366 Midterm: Tuesday, 9 February 9:30-10:20 JHN-111 Final: Wednesday, 17 March 10:30-12:20 JHN-111 Class website: http://gis.ess.washington.edu/keck/ess421_documents.html

Class structure Model 2 (ESS 421) Model 1 Lectures Lectures Reading Labs Lectures Labs Reading

Lab Exercises ° one lab per week, handed out Tuesdays ° due the following Tuesday (or as noted in outline) in class ° 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 late work will be docked 10% per day ° at the beginning of the lab on Tuesdays 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

Reading Assignments °Text is Lillesand, Kiefer, and Chipman “Remote Sensing and Image Interpretation” 6th ed. 2007, John Wiley ° Reading assignments in the text are augmented with other material available on class website

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

Lecture 1: Introduction Tuesday, 5 January 2010 Lecture 1: Introduction Reading assignment: Lillesand, Kiefer & Chipman: Ch 1.1, 1.2, 1.6, 1.7, 1.10, 1.11 Ch 2.9 – Multiband imaging App. A – Concepts & terminology (p. 727-731) App. B – Data and resources (p. 732-735) 1

Measurement from a distance - What is remote sensing? Measurement from a distance - Hazardous locales - “Denied terrain” Nodong, N. Korea 2

What is an image? X (longitude) Y (latitude) 3

Images in combination with maps add to interpretive power Geographic Information System (GIS) 4

Image visualizations display only a subset of the data Images can be made at different wavelengths of light l=11.405 mm l=10.755 mm l=10.275 mm l=9.205 mm l=8.735 mm l l=0.870 mm l=0.804 mm l=0.658 mm l=0.542 mm l=0.462 mm Y Image visualizations display only a subset of the data X NASA MASTER airborne 50-band multispectral image 5

and displayed as color pictures l=11.405 mm l=10.755 mm l=10.275 mm l=9.205 mm l=8.735 mm l l=0.870 mm l=0.804 mm l=0.658 mm l=0.542 mm l=0.462 mm Y R=0.658mm G=0.542mm B=0.462mm X NASA MASTER airborne 50-band multispectral image NASA MASTER airborne 50-band multispectral image 6

Spectrum l Only 3 bands at a time can be visualized this way… but there is more information, and can be shown in a spectrum Spectrum l=11.405 mm l=10.755 mm l=10.275 mm l=9.205 mm l=8.735 mm l l=0.870 mm l=0.804 mm l=0.658 mm l=0.542 mm l=0.462 mm Y R=0.658mm G=0.542mm B=0.462mm X 7

Spectra are different and convey information about composition Note the scale change! R=0.658mm G=0.542mm B=0.462mm 8

different wavelengths of light Images can be made at different wavelengths of light l=11.405 mm l=10.755 mm l=10.275 mm l=9.205 mm l=8.735 mm l l=0.870 mm l=0.804 mm l=0.462 mm l=0.658 mm l=0.542 mm Y X 9

They reveal different information about scene composition THERMAL INFRARED VISIBLE 10

Images are not limited to light reflected or emitted from a surface. They can be made over time, or of derived or calculated parameters. Increasing concentration of CO Carbon monoxide at 500 mB, from NASA’s Terra/Moppitt 12

physics of remote sensing How do remote sensing and GIS fit together in geospatial analysis? Remote sensing GIS Image processing Analysis & Interpretation Operations & acquisition Engineering Calibration Validation physics of remote sensing Scanners & data project goals scene Knowledge 13

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) [El] Spectral radiance (W m-2 sr-1 µm-1) [Ll]

The electromagnetic spectrum Short l High energy High frequency Long l Low energy Low frequency 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 Reflected sunlight Thermally emitted radiation

What topics are covered in ESS 421? physical basis of remote sensing spectra radiative transfer image processing radar/lidar thermal infrared applications 14