Chapter 0 Syllabus Introduction to Remote Sensing Instructor

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 • 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

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

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

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

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

Some questions § Who am I? • http: //myweb. ncku. edu. tw/~ccliu 88/ § 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, …

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%

Office hours § Monday: 15: 00 – 17: 00 § Friday: 10: 00 – 12: 00 § Anytime if necessary

Some issues § Representative • Textbook • Seat • Email to TA (conifer_6@hotmail. com) v. 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)

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

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

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 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 v word eyes brain meaning v data sensor processing information

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

Missions of satellite remote sensing Operation Sensor Platform Mission Type 1978 – 1986 CZCS (Coastal Zone Color Scanner) Nimbus-7 Ocean color Earth Resources 1978 – 1986 TOMS Nimbus-7 Mapping Ozone Earth Resources

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

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

Remote sensing in Taiwan ROC (cont. ) § ROCSAT-3 • Missions • Status • Applications § Yam. SAT

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 v. Our focus: electromagnetic energy distribution Ø Fig 1. 1: Generalized processes and elements involved in electromagnetic remote sensing of earth resources ü data acquisition: a-f (§ 1. 2 - § 1. 5) ü data analysis: g-i (§ 1. 6 - § 1. 10)

Basic concepts of remote sensing (cont. ) § Energy sources and radiation principles • Electromagnetic spectrum (Fig 1. 3) memorize v. Spectrum : Ø UV (ultraviolet) Ø Vis (visible) ü narrow range, strongest, most sensitive to human eyes ü blue: 0. 4~0. 5 mm ü green: 0. 5~0. 6 mm ü red: 0. 6~0. 7 mm Ø IR (infrared) ü near-IR: 0. 7~1. 3 mm ü mid-IR: 1. 3~3. 0 mm ü thermal-IR: 3. 0 mm~1 mm heat sensation Ø microwave: 1 mm~1 m v. Wave theory: c = nl Ø c : speed of light (3 x 108 m/s) Ø n : frequency (cycle per second, Hz) Ø l : wavelength (m) Ø unit: micrometer mm = 10 -6 m

Basic concepts of remote sensing (cont. ) § Energy sources and radiation principles (cont. ) • Electromagnetic spectrum (cont. ) v. Particle theory: Q = hn Ø Q: quantum energy (Joule) Ø h: Planck's constant (6. 626 x 10 -34 J sec) Ø n: frequency v. Q = hn = hc/l 1/l Ø implication in remote sensing: l Q viewing area enough area • Stefan-Boltzmann law: v M = s. T 4 Ø M: total radiant exitance from the surface of a material (watts m-2) Ø s: Stefan-Boltzmann constant (5. 6697 x 10 -8 W m-2 K-4) Ø T: absolute temperature (K) of the emitting material v. Blackbody: Ø A hypothetical, ideal radiator totally absorbs and reemits all incident energy

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) v Area total radiant exitance M Ø T M (graphical illustration of S-B law) v Wien's displacement law: Ø lm=A/T 1/T ü lm : dominant wavelength, wavelength of maximum spectral radiant (mm) ü A: 2898 (K) ü T: absolute temperature (K) of the emitting material ü e. g. heating iron: dull red orange yellow white v Sun: T 6000 K lm 0. 5 mm (visible light) v incandescent lamp: T 3000 K lm 1 mm Ø "outdoor" film used indoors� "yellowish“ v Earth: T 300 K lm 9. 7 mm thermal energy radiometer Ø l<3 mm: reflected energy predominates Ø l>3 mm: emitted energy prevails v Passive Active

Basic concepts of remote sensing (cont. ) § Energy interaction in the atmosphere • Path length v space photography: 2 atmospheric thickness v airborne thermal sensor: very thin path length v sensor-by sensor • Scattering v molecular scale: d << l Rayleigh scatter Ø Rayleigh scatter effect 1/l 4 Ø "blue sky" and "golden sunset" Ø Rayleigh "haze" imagery filter (Chapter 2) v wavelength scale: d l Mie scatter Ø influence longer wavelength Ø dominated in slightly overcast sky v large scale: d >> l Ø Ø e. g. water drop nonselective scatter f(l) that's why fog and clod appear white why dark clouds black?

Basic concepts of remote sensing (cont. ) § Energy interaction in the atmosphere (cont. ) • Absorption vabsorbers in the atmosphere: water vapor, carbon dioxide, ozone v. Fig 1. 5: Spectral characteristics of (a) energy sources (b) atmospheric effect (c) sensing systems Ø atmospheric windows Ø important considerations ü sensor: spectral sensitivity and availability ü windows: in the spectral range sense ü source: magnitude, spectral composition

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 v. EI(l) = ER(l) + EA(l) + ET(l) Ø incident = reflected + absorbed + transmitted Ø ER = ER(feature, l) distinguish features R. S. Ø in visible portion: ER(l) color Ø most R. S. reflected energy predominated ER important! • Fig. 1. 7: Specular versus diffuse reflectance vspecular diffuse (Lambertian) vsurface roughness incident wavelength: l. I vif l. I << surface height variations diffuse Ø for R. S. measure diffuse reflectance vspectral reflectance

Basic concepts of remote sensing (cont. ) § Energy interactions with earth surface features (cont. ) • Fig 1. 8: Spectral reflectance curve (SRC) vobject type ribbon (envelope) rather than a single line vcharacteristics of SRC choose wavelength vcharacteristics of SRC choose sensor Ø near-IR photograph does a good job (Fig 1. 9) v. Many R. S. data analysis mapping spectrally separable understand the spectral characteristics

Basic concepts of remote sensing (cont. ) § Energy interactions with earth surface features (cont. ) • Typical SRC (Fig 1. 10) • vegetation: v pigment chlorophyll two valleys (0. 45 mm: blue; o. 67 mm: red) green Ø if yellow leaves r(red) green + red v from 0. 7 mm to 1. 3 mm minimum absorption (< 5%) strong reflectance = f(internal structure of leaves) discriminate species and detect vegetation stress v l > 1. 3 mm three water absorption bands (1. 4, 1. 9 and 2. 7 mm) Ø water content r(l) Ø r(l) = f(water content, leaf thickness) • soil v moisture content r(lwab) v soil texture: coarse drain moisture v surface roughness r v iron oxide, organic matter r v These are complex and interrelated variables

Basic concepts of remote sensing (cont. ) § Energy interactions with earth surface features (cont. ) • Water vnear-IR: water r(lnear-IR) vvisible: very complex and interrelated Ø surface Ø bottom Ø material in the water ü clear water blue ü chlorophyll green ü CDOM yellow vp. H, [O 2], salinity, . . . (indirect) R. S.

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

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

Organization of this course § Image acquisition § Image processing and analysis § Applications

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

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