Transcript Introduction - National Cheng Kung University
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
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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, 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
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?
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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, …
Grade
Examination 40%
• •
Midterm exam 20% Final exam 20%
Homework 30%
• •
No late hand-in Email to TA
•
One day notice to present (once or twice) 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 ( [email protected]
)
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
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
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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
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 1978 – 1986 1978 – 1986 Sensor CZCS (Coastal Zone Color Scanner) TOMS Platform Nimbus-7 Nimbus-7 Mission Ocean color Mapping Ozone Type Earth Resources Earth Resources
Remote sensing in Taiwan ROC
• • •
National Space Project – phase 1
•
1991 – 2005
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19,700,000,000 NT dollars ROCSAT-1 ROCSAT-2 ROCSAT-3 YamSAT
National Space Project – phase 2
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2005 – 2018
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30,000,000,000 NT dollars
•
?
Remote sensing in Taiwan ROC (cont.)
ROCSAT-1
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Review
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News
• • •
Missions Status Applications ROCSAT-2
•
Characteristics
• • •
News Missions Scientific mission
• •
Status Applications
Remote sensing in Taiwan ROC (cont.)
ROCSAT-3
• • •
Missions Status Applications
YamSAT
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)
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: 0.4~0.5
m m green: 0.5~0.6
m m red: 0.6~0.7
m m IR (infrared) near-IR: 0.7~1.3 m m mid-IR: 1.3~3.0 m m thermal-IR: 3.0 m m~1mm heat sensation microwave: 1mm~1m
Wave theory: c =
nl
c
n l : speed of light (3x10 8 : wavelength (m) unit: micrometer m/s) : frequency (cycle per second, Hz) m m = 10 -6 m
Basic concepts of remote sensing (cont.)
Energy sources and radiation principles (cont.)
•
Electromagnetic spectrum (cont.)
Particle theory: Q = h
n
Q
: quantum energy (Joule)
h
: Planck's constant (6.626x10
-34 n : frequency
Q = h
n
= hc/
l
1/
l J sec) implication in remote sensing: l Q viewing area enough area •
Stefan-Boltzmann law:
M =
s
T 4
M: total radiant exitance from the surface of a material (watts m -2 ) s : Stefan-Boltzmann constant (5.6697x10
-8 W m -2 K -4 ) T: absolute temperature (K) of the emitting material
Blackbody:
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)
Area
total radiant exitance M
T M (graphical illustration of S-B law)
Wien's displacement law:
l m =A/T l m 1/T : 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
Sun: T
6000K
incandescent lamp: T
l
m
0.5
m
m (visible light) 3000K
"outdoor" film used indoors l
m
"yellowish“
1
m
m
Earth: T
300K
l
m
9.7
m
m
l <3 m m: reflected energy predominates l >3 m m: emitted energy prevails white
thermal energy
Passive
Active radiometer
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
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Scattering
molecular scale: d <<
Rayleigh scatter effect l 1/ l 4
Rayleigh scatter
"blue sky" and "golden sunset" Rayleigh "haze" imagery
wavelength scale: d
l filter (Chapter 2)
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?
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
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
E I (
l
) = E R (
l
) + E A (
l
) + E T (
l
)
incident = reflected + absorbed + transmitted E R = E R (feature, most R.S. l ) in visible portion: E R ( l distinguish features ) color R.S.
reflected energy predominated E R important!
•
Fig. 1.7: Specular versus diffuse reflectance
specular
diffuse (Lambertian)
surface roughness
if
l
I << surface height variations
for R.S.
incident wavelength:
measure diffuse reflectance
diffuse
l
I
spectral reflectance
l
E E R I
( ( l l ) )
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
separable
mapping
spectrally understand the spectral characteristics
Basic concepts of remote sensing (cont.)
Energy interactions with earth surface features (cont.)
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Typical SRC (Fig 1.10)
•
vegetation:
pigment
from 0.7
chlorophyll
if yellow leaves m
m to 1.3
(red) m
m
two valleys (0.45
green + red m
m: blue; o.67
minimum absorption (< 5%) f(internal structure of leaves)
m
m: red)
green strong reflectance = discriminate species and detect vegetation
stress
l
> 1.3
m
m
three water absorption bands (1.4, 1.9 and 2.7 mm)
water content ( l ) ( l ) = f(water content, leaf thickness) •
soil
moisture content
(lwab)
soil texture: coarse
surface roughness
drain
iron oxide, organic matter
moisture
These are complex and interrelated variables
Basic concepts of remote sensing (cont.)
Energy interactions with earth surface features (cont.)
•
Water
near-IR: water
(
l
near-IR )
visible: very complex and interrelated
surface bottom material in the water clear water blue chlorophyll CDOM green yellow
pH, [O2], salinity, ...
(indirect) R.S.
Basic concepts of remote sensing (cont.)
Spectral Response Pattern
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spectrally separable
recognize feature
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spectral signatures
absolute, unique
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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 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 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, 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