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Chapter 0

Chapter 0. Syllabus Introduction to Remote Sensing Instructor: Dr. Cheng-Chien Liu Department of Earth Sciences National Cheng Kung University Last updated: 29 September 2004. Syllabus. Course name: Introduction to Remote Sensing Credit: 3 Prerequisite: Undergraduate students

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Chapter 0

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  1. Chapter 0 Syllabus Introduction to Remote Sensing Instructor: Dr. Cheng-Chien Liu Department of Earth Sciences National Cheng Kung University Last updated: 29 September 2004

  2. Syllabus • Course name: Introduction to Remote Sensing • Credit: 3 • Prerequisite: • Undergraduate students • Graduate students (approved by advisor) • Devoted and committed • Time: • Monday 14:10 – 15:00 • Thursday 10:10 – 12:00 • Place: • Department of Earth Sciences building room 3031 • Remote sensing laboratory • Teaching Assistant: Conifer Chang

  3. Objectives • Introduce students the fundamental concepts of remote sensing, as well as its limitation, characteristics and applications • Raising student’s interest in this subject, some video clips will be played in the class and an open discussion will be held afterwards • Encouraging students to ask questions and seek the answers as more as they can • Students are expected to complete some take-home questions and present the material they found in the class every week • Providing a roadmap for further study in the general field of Remote Sensing

  4. Textbook • Remote sensing and image interpretation, 5th edition, T.M. Lillesand, R.W. Kiefer. and J. W. Chipman, John Wiley & Sons, 2004 (textbook) • Introduction to remote sensing, 3rd edition, J.B. Campbell, Taylor & Francis, 2002. • Physical principles of remote sensing, 2nd edition, W.G. Rees, Cambridge University Press, 2001. • Introductory remote sensing - principles and concepts, 1st edition, P.J. Gibson and C.H. Power, Routledge, 2000. • Introductory remote sensing - digital image processing, 1st edition, P.J. Gibson and C.H. Power, Routledge, 2000

  5. Schedule – Foundation • Introduction • Space platform and orbit • Sensor • Digital data • Ground truth • Photogrammetry • Digital image processing • Geographic information system • Passive remote sensing • Active remote sensing

  6. Schedule – Application • Mapping • Water resource • Hydrology and oceanography • Land use • Agriculture • Environmental assessment • Natural disaster assessment

  7. Some questions • Who am I? • http://myweb.ncku.edu.tw/~ccliu88/ • Why are we here? • You and I, … • Why exams? • Acquire knowledge, … • Why taking lectures? • Save time and efforts, … • Why doing a project? • An interactive way of studying, …

  8. Grade • Homework 30% • No late hand-in • Email to TA • One day notice to present (once or twice) • Examination 40% • Midterm exam 20% • Final exam 20% • Project 30% • Report 15% • Presentation 15%

  9. Office hours • Monday: 15:00 – 17:00 • Friday: 10:00 – 12:00 • Anytime if necessary

  10. Some issues • Representative • Textbook • Seat • Email to TA (conifer_6@hotmail.com) • Name, Student ID number, Department/Year, Cell phone number, email address, (advisor’s name) • Introduce yourself • What you know about Remote Sensing • Why take this course • Background (education)

  11. Homework 1 • Job hunting in Remote Sensing • The courses that are related to Remote Sensing in NCKU and/or other institutes in Taiwan

  12. Chapter 1 Introduction Introduction to Remote Sensing Instructor: Dr. Cheng-Chien Liu Department of Earth Sciences National Cheng Kung University Last updated: 29 September 2004

  13. Definition • Satellite • Natural satellite • Man-made satellite • Type • Meteorology • Communication • Navigation and position • Earth resources • Remote sensing • The Science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand et al. 2004) • The practice of deriving information about the earth’s land and water surface sing images acquired from an overhead perspective, using electromagnetic radiation in one or more regions of the electromagnetic spectrum, reflected or emitted from the earth’s surface (Compbell 2002) • A complete collection of various definitions • Example • Reading process • word  eyes  brain  meaning • data  sensor  processing  information

  14. History • Milestone of remote sensing (see Table 1.2 in Campbell 2002) • 1800 • 1839 • 1850 – 1860 • 1873 • 1909 • 1939 – 1945 • 1957 • 1960 – 1970 • 1972 • 1978 • 1986 • 1990

  15. Missions of satellite remote sensing

  16. Remote sensing in Taiwan ROC • National Space Project – phase 1 • 1991 – 2005 • 19,700,000,000 NT dollars • ROCSAT-1 • ROCSAT-2 • ROCSAT-3 • YamSAT • National Space Project – phase 2 • 2005 – 2018 • 30,000,000,000 NT dollars • ?

  17. Remote sensing in Taiwan ROC (cont.) • ROCSAT-1 • Review • News • Missions • Status • Applications • ROCSAT-2 • Characteristics • News • Missions • Scientific mission • Status • Applications

  18. Remote sensing in Taiwan ROC (cont.) • ROCSAT-3 • Missions • Status • Applications • YamSAT

  19. Basic concepts of remote sensing • Methods of collecting data remotely • Variations in force distribution  e.g. gravity meter • Acoustic wave distribution  e.g. sonar • Electromagnetic energy distribution  e.g. eyes • Our focus: electromagnetic energy distribution • Fig 1.1: Generalized processes and elements involved in electromagnetic remote sensing of earth resources • data acquisition: a-f (§1.2 - §1.5) • data analysis: g-i (§1.6 - §1.10)

  20. Basic concepts of remote sensing (cont.) • Energy sources and radiation principles • Electromagnetic spectrum (Fig 1.3)  memorize • Spectrum : • UV (ultraviolet) • Vis (visible) • narrow range, strongest, most sensitive to human eyes • blue: 0.4~0.5mm • green: 0.5~0.6mm • red: 0.6~0.7mm • IR (infrared) • near-IR: 0.7~1.3 mm • mid-IR: 1.3~3.0 mm • thermal-IR: 3.0 mm~1mm  heat sensation • microwave: 1mm~1m • Wave theory: c = nl • c : speed of light (3x108 m/s) • n : frequency (cycle per second, Hz) • l : wavelength (m) • unit: micrometer mm = 10-6 m

  21. Basic concepts of remote sensing (cont.) • Energy sources and radiation principles (cont.) • Electromagnetic spectrum (cont.) • Particle theory: Q = hn • Q: quantum energy (Joule) • h: Planck's constant (6.626x10-34 J sec) • n: frequency • Q = hn = hc/l 1/l • implication in remote sensing:lQ  viewing areaenough area • Stefan-Boltzmann law: • M = sT4 • M: total radiant exitance from the surface of a material (watts m-2) • s: Stefan-Boltzmann constant (5.6697x10-8 W m-2K-4) • T: absolute temperature (K) of the emitting material • Blackbody: • A hypothetical, ideal radiator totally absorbs and reemits all incident energy

  22. Basic concepts of remote sensing (cont.) • Energy sources and radiation principles (cont.) • Spectral distribution of energy radiated from blackbodies of various temperatures (Fig 1.4) • Area  total radiant exitance M • T M (graphical illustration of S-B law) • Wien's displacement law: • lm=A/T  1/T • lm : dominant wavelength, wavelength of maximum spectral radiant (mm) • A: 2898 (K) • T: absolute temperature (K) of the emitting material • e.g. heating iron: dull red  orange  yellow  white • Sun: T6000K lm0.5mm (visible light) • incandescent lamp: T  3000K lm 1mm • "outdoor" film used indoors  "yellowish“ • Earth: T  300K lm9.7mm  thermal energy  radiometer • l<3mm: reflected energy predominates • l>3mm: emitted energy prevails • Passive Active

  23. Basic concepts of remote sensing (cont.) • Energy interaction in the atmosphere • Path length • space photography: 2 atmospheric thickness • airborne thermal sensor: very thin path length • sensor-by sensor • Scattering • molecular scale: d << l Rayleigh scatter • Rayleigh scatter effect  1/l4 • "blue sky" and "golden sunset" • Rayleigh  "haze" imagery  filter (Chapter 2) • wavelength scale: d l Mie scatter • influence longer wavelength • dominated in slightly overcast sky • large scale: d >> l • e.g. water drop • nonselective scatter  f(l) • that's why fog and clod appear white • why dark clouds black?

  24. Basic concepts of remote sensing (cont.) • Energy interaction in the atmosphere (cont.) • Absorption • absorbers in the atmosphere: water vapor, carbon dioxide, ozone • Fig 1.5: Spectral characteristics of (a) energy sources (b) atmospheric effect (c) sensing systems • atmospheric windows • important considerations • sensor: spectral sensitivity and availability • windows: in the spectral range  sense • source: magnitude, spectral composition

  25. Basic concepts of remote sensing (cont.) • Energy interactions with earth surface features • Fig 1.6: basic interactions between incident electromagnetic energy and an earth surface feature • EI(l) = ER(l) + EA(l) + ET(l) • incident = reflected + absorbed + transmitted • ER = ER(feature, l)  distinguish features  R.S. • in visible portion: ER(l)  color • most R.S.  reflected energy predominated  ER important! • Fig. 1.7: Specular versus diffuse reflectance • specular  diffuse (Lambertian) • surface roughness  incident wavelength: lI • if lI << surface height variations  diffuse • for R.S.  measure diffuse reflectance • spectral reflectance

  26. Basic concepts of remote sensing (cont.) • Energy interactions with earth surface features (cont.) • Fig 1.8: Spectral reflectance curve (SRC) • object type  ribbon (envelope) rather than a single line • characteristics of SRC  choose wavelength • characteristics of SRC  choose sensor • near-IR photograph does a good job (Fig 1.9) • Many R.S. data analysis  mapping  spectrally separable  understand the spectral characteristics

  27. Basic concepts of remote sensing (cont.) • Energy interactions with earth surface features (cont.) • Typical SRC (Fig 1.10) • vegetation: • pigment  chlorophyll  two valleys (0.45mm: blue; o.67mm: red)  green • if yellow leaves  r(red)  green + red • from 0.7 mm to 1.3 mm  minimum absorption (< 5%)  strong reflectance = f(internal structure of leaves)  discriminate species and detect vegetation stress • l > 1.3 mm  three water absorption bands (1.4, 1.9 and 2.7 mm) • water content r(l)  • r(l) = f(water content, leaf thickness) • soil • moisture content r(lwab)  • soil texture: coarse  drain  moisture  • surface roughness r • iron oxide, organic matter r • These are complex and interrelated variables

  28. Basic concepts of remote sensing (cont.) • Energy interactions with earth surface features (cont.) • Water • near-IR: water r(lnear-IR)  • visible: very complex and interrelated • surface • bottom • material in the water • clear water  blue • chlorophyll  green • CDOM  yellow • pH, [O2], salinity, ...  (indirect) R.S.

  29. Basic concepts of remote sensing (cont.) • Spectral Response Pattern • spectrally separable  recognize feature • spectral signatures  absolute, unique • reflectance, emittance, radiation measurements, ... • response patterns  quantitative, distinctive • variability exists! • identify feature types spectrally  variability causes problems • identify the condition of various objects of the same type  we have to rely on these variabilities • minimize unwanted spectral variabilitymaximize variability when required! • spatial effect: e.g. different species of planttemporal effect: e.g. growth of plant  change detection

  30. Trends of remote sensing • Technology • Application • Job market • Case 1 • Case 2 • Case 3

  31. Organization of this course • Image acquisition • Image processing and analysis • Applications

  32. Resources • Periodical journals • IEEE transaction on geosciences and remote sensing • International Journal of remote sensing • Remote sensing of environment • Web sites • Data/image

  33. Resources • Books • Remote sensing and image interpretation, 5th edition, T.M. Lillesand, R.W. Kiefer. and J. W. Chipman, John Wiley & Sons, 2004 (textbook) • Introduction to remote sensing, 3rd edition, J.B. Campbell, Taylor & Francis, 2002. • Physical principles of remote sensing, 2nd edition, W.G. Rees, Cambridge University Press, 2001. • Introductory remote sensing - principles and concepts, 1st edition, P.J. Gibson and C.H. Power, Routledge, 2000. • Introductory remote sensing - digital image processing, 1st edition, P.J. Gibson and C.H. Power, Routledge, 2000

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