SYLLABUS: PRINCIPLES OF REMOTE SENSING
GTECH 712, 321 (4 cr/6 hr) M,Th 9:20-12:00 N, 1090B HN
Dr. Karl-Heinz Szekielda
LAB Thursdays: Hyo Jin Ahn
The course covers the principal concepts and applications of remote sensing for Earth Sciences. The course will have a lecture/projects format with emphasis on interpretation of satellite data in connection with a remote sensing website.
OBJECTIVES:
1. Understanding of spectral signatures to be demonstrated with samples throughout the electromagnetic spectrum.
2. Interpretation of unknown reflectance spectra in relation to features in spectra of minerals, water, vegetation and atmospheric targets.
3. Understanding of principles of remote sensing techniques by outlining a sensor design according to spectral responses of Earth’s surfaces and the atmosphere.
4. Defining the advantages and needs for orbit selection according to acquired ground resolution, spectral characteristics and temporal changes.
5. Demonstration of capability to interpret remote sensing data in order to:
a. Understand the processing and enhancement of satellite images for identifying geological structures and vegetation coverage,
b. Recognize coastal morphology from space,
c. Recognize global changes and environmental monitoring with data from special sensors.
COURSE REQUIREMENTS AND EVALUATION
1. Mid-term examination based on reading assignments, research proposal, and presentations with power point of the first research results.
2. Research on a remote sensing topic in the vicinity of New York, chosen by the student
3. Formal presentation by each student’s research with use of power point projection, to be presented during the last two weeks of classes.
4. Grades will be based on the following distribution of 100 points:
a. Mid-term examination/oral presentation 30
b. Research documentation 40
c. Oral presentation of final research 30
LECTURE TOPICS
I. Introduction and History
II. Basic Principles of Imaging Spectrometry
1. The electromagnetic spectrum and atmospheric considerations
2. Imaging spectrometry
III. Spectral Characteristics
1. Spectral characteristics and principles of spectroscopy
2. Spectroscopy of water
3. Spectroscopy of rocks and minerals
4. Spectroscopy of soil
5. Spectroscopy of vegetation
IV. Analysis and Interpretation
1. Spectral analysis for Earth science investigations
2. Integration and visualization of geoscience data
3. Concepts in data and image interpretation
V. Sensors and platforms
1. Visible and infrared sensors
2. Radar technology
3. Remote sensing platforms
VI. Applications
1. Geosphere: Imaging spectrometry and geological applications
2. Hydrosphere: Imaging spectrometry of water
3. Biosphere: Imaging spectrometry of vegetation
4. Atmosphere
5. Thermal imaging
6. Global cycles and change detection
Lab Exercises
Using ENVI, the students will study remote sensing data related to the lecture topics and will select a research topic over an area in the vicinity of New York.
Reading requirement for graduate students, recommended for undergraduates
IMAGING SPECTROMETRY: BASIC PRINCIPLES AND PROSPECTIVE APPLICATIONS
Edited by F. D. van der Meer and S.M. de Jong (2002)
A CDROM accompanies the book "Imaging Spectrometry: Basic principles
and prospective applications" by F. van der Meer and S. de Jong.
Kluwer Academic Publishers, 425 pp.
ISBN 1-4020-0194-0
US$ 40
Fall 2002 Principles of Remote Sensing Lab Schedule
Lab Class Time: Thur. 9:20 am to 12 noon, N 1090B
Lab Instructor : Hyo Jin Ahn (email: intjin@yahoo.com),
web http://geo.hunter.cuny.edu/~hyojin/rslabschedule.html
DATA ACCESS FOR LAB EXERCISES:
1.The Data files for tutorial exercises are contained in
D: driver /RSI/Idl55/products/envi35/data/ and
Window NT Explorer>Tools>Map Network Driver>Path>\\Samba\scratch\>envi3.5.data
2.The Data files for projects or assignments are contained in \\Samba\scratch\rsproject.
**Please email me (intjin@yahoo.com) your web site address which you post your lab results by Sep 19th.
OTHER REMOTE SENSING SITES ONLINE:
NASA'S Remote Sensing Tutorial http://rst.gsfc.nasa.gov/start.html
Remote Sensing Core Curriculum http://www.research.umbc.edu/~tbenjai/
REMOTE SENSING DATA SOURCES & ACQUISITION:
EROS (Earth Resources Observation Systems) Data Center http://edc.usgs.gov/index.html
EROS Data Center DAAC_land processes http://edcdaac.usgs.gov/dataproducts.html
JPL PO.DAAC - physical oceanography http://podaac-www.jpl.nasa.gov/
EARTH SCIENCE DATA INTERFACE http://gorgonzola.umiacs.umd.edu:8811/glcf/esdi?command=search
ACCESS TO LANDSAT DATA http://geo.arc.nasa.gov/sge/landsat/daccess.html
| LAB # | DATE | CONTENT |
Ass. Due |
| Lab1 | 9/5 | Int. to ENVI 3.5:Quick Start Tutorial (tutorial.pdf: p 35 – 45); Data file in envi3.5/data/can_tmr, & envi35/data/vector | |
| Lab2 | 9/12 | INT 2. ENVI Tutorial
#1 (p. 47-71): Data file in envi35/data/can_tmr File format, Basic functions |
|
| Lab3 | 9/19 | INT 3: ENVI Tutorial
#2 (p. 74-87): Data file in \\Samba\scratch\>envi3.5.data
/ enfidavi (14 files) : Introduction to using Panchromatic data, including display, contrast enhancement, filtering, overlay DXF vector file, & mapping with annotation. |
Post Lab2 result, the last image "annotated image with a grid overlaid" in your web site by 9/19 |
| Lab4 | 9/26 | Tutorial 4.
Image Georeferencing and Registeration (p. 125-131) :
Data file in \\Samba\scratch\>envi3.5.dat>envidata>bldr_reg
:Image to Image Registeration (do all procedures) Assignment 2 : Using the georeferenced Landsat 7ETM+ iamge (Data in \\Samba\scratch\rsproject \L7070599)as the Base image, wrap the pixel-based GER g63 aircraft image (Data in \\Samba\scratch\rsproject\Gerg63) into a registered image. |
|
| Lab5 | 10/3 | Tutorial 4.
Image Georeferencing and Registeration (p. 139-142) :
Data file in \\Samba\scratch\>envi3.5.dat>envidata>bldr_reg
: HSV Merge of Different Resolution Georeferenced Data Sets Ass #3 : Merge the Panchromatic band (resolution 15 m) of Landsat7 ETM+ (\\Samba\scratch\rsproject \L7070599) and the band 6 H (Thermal band) to enhance spatial resolution of thermal band. |
Post Ass. 2 result in your web by 9/26 |
| Lab6 | 10/10 | Tutorial
3 : Multispectral Classification I (p.
89-100) : Data file in \\Samba\scratch\>envi3.5.data>envidata>
can_tm : examines supervised & unsupervised classification methods |
Post the result
of Ass. #3 in your web by 10/10 |
| Lab7 | 10/17 | Mid-Term Review | |
| Lab8 | 10/24 | Continue
Multispectral Classification II (p. 100-112) :Data
file in \\Samba\scratch\>envi3.5.data>envidata>
can_tm : Spectral Classification Methods |
|
| Lab9 | 10/31 | Tutorial 12.
Hyperspectral Data & Analysis (p.264-286):Samba\scratch\>envi3.5.data> envidata>c95avs |
Post the final result images from Lab 6 & Lab 8 by 10/31 |
| Lab10 | 11/7 | Continue Tutorial 12. Hyperspectral Data & Analysis | |
| Lab11 | 11/14 | Tutorial 8. Data Fusion (p. 191-200) : Data file in \\Samba\scratch\>envi3.5.dat>envidata> lontmsp, and ….> brestsp | |
| Lab12 | 11/21 | Tutorial 9. Landsat TM & SAR Data Fusion (p. 201-206) : Data file in \\Samba\scratch\>envi3.5.dat>envidata>rometm_ers | Post the final image of Lab 11 by 11/21 |
| Lab13 | 12/5 | Tutorial 20.Near-Shore Marine Hyperspectral Case History (AVIRIS image :Moffett Field, CA) :DATA in \\Samba\scratch\>envi3.5.dat>envidata>M97avsub | |
| Lab14 | 12/12 | FINAL |