ESS 421 – Introduction to Geological Remote Sensing Prof: Alan Gillespie (JHN 343) Office hours: Wed - Fri or by arrangement TA: Iryna Danilina (JHN 330) Office hours: Wed/Fri 12: 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: Wednesday, 5 January 2011

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

Schedule LECTURESLABS Jan 051. Intro Jan 072. Images1 Jan 123. Photointerpretation2 Jan 144. Color theory Jan 195. Radiative transfer3 Jan 216. Atmospheric scattering Jan 267. Lambert’s Law4 Jan Volume interactions Feb 029. Spectroscopy5 Feb Satellites & Review Feb Midterm6 Feb Image processing Feb Spectral mixture analysis7 Feb Classification Feb Radar & Lidar8 Feb Thermal infrared Mar Mars spectroscopy (Matt Smith)9 Mar Forest remote sensing (Van Kane) Mar Thermal modeling (Iryna Danilina) Mar 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.

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

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

Examinations & Grading °Midterm and Final will both contain questions from the lectures, reading, and labs ° Midterm covers 1 st half of class °Final covers whole class with emphasis on 2 nd 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 Reading assignment: Lillesand, Kiefer & Chipman: Ch 1.1, 1.2radiation Ch 1.6reference data Ch 1.7GPS Ch 1.10GIS Ch 2.9 Multiband imaging For your reference App. A Concepts & terminology App. B Data and resources 1

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

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

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

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

6 NASA MASTER airborne 50-band multispectral image R=0.658  m G=0.542  m B=0.462  m and displayed as color pictures NASA MASTER airborne 50-band multispectral image X Y =8.735  m =9.205  m =  m =  m =  m =0.462  m =0.542  m =0.658  m =0.804  m =0.870  m

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

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

9 Images can be made at different wavelengths of light X Y =8.735  m =9.205  m =  m =  m =  m =0.462  m =0.542  m =0.658  m =0.804  m =0.870  m

10 They reveal different information about scene composition VISIBLE THERMAL INFRARED

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

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

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 ) [E ] Spectral radiance (W m -2 sr -1 µm -1 ) [L ]

In the spectrum, energy is dispersed by a grating or prism according to frequency or wavelength Gamma rays<10 -4 µm X rays µm Ultraviolet µm Visible blue B µm Visible green G µm Visible red R µm Near infrared NIR µm Shortwave infrared SWIR µm Mid-wave infrared MIR µm Longwave thermal infrared LWIR8-14 µm Microwave(Radar)0.1mm-1 m Radio1 m - 10 km Reflected sunlight Thermal radiation The electromagnetic spectrum Short High energy High frequency Long Low energy Low frequency

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

What will be covered in Friday’s lecture 14 imaging systems and some of their characteristics