GEOGRAPHY 477: INTRODUCTION TO REMOTE SENSING
LECTURES: 2:00 - 3:15 T/R – 204 SAUNDERS
LAB HOURS: M/T 8:00 - 11:00; W 1:00 - 4:00 322 SAUNDERS
FALL 2006 ● UNC-CHAPEL HILL
Aaron Moody
211 Saunders Hall
aaronm@email.unc.edu
Lindsay Berk
319 Saunders Hall
berk@email.unc.edu
COURSE CONTEXT
Remote sensing has fundamentally changed humanity. It has transformed our scientific
insight, geographic knowledge, and cultural perceptions of Earth. The highly symbolic
photograph “The Blue Marble” is not only a byproduct, or legacy of the space age, but the
promise of that synoptic view, afforded from above, was a primary force prompting the
investments necessary to access space beyond Earth’s atmosphere and gravitational
dominance. Access to space meant release from the limits imposed by the mismatch between
the individual human scale of experience and the geographic scope of the Earth system. In
fact, remote sensing has, in part, coevolved with the vast research domains enveloped within
“Earth System Science,” which will form the context for many of the examples and
applications discussed in this course.
Military and strategic interests, have, of course, been tantamount in the pursuit of space,
including the development of remote sensing technology. However that legacy is dying, if
not dead. Satellite remote sensing technology is now driven by federal and international
programs funding space and Earth system science research, by public and private land
management interests, by demand from extractive and recreational industry, federally funded
meteorological and climate observation, and by demand relating to management of human
infrastructure. We are approaching a critical threshold at which the Earth system – the
atmosphere, climate, ocean, ice, and land processes – will be replicated continuously and
digitally in real time using gargantuan hypervolumes of data generated through the
coalescence of what the National Academies has referred to as “an intelligent sensor web1.”
In the meantime, satellite remote sensing plays an extensive role in a wide range of fields,
including forestry, ecosystem ecology, geophysics, climatology and oceanography, to name a
few. Meanwhile, the quality, variety and availability of satellite- (and aircraft-) based data is
expanding rapidly, along with the computing technology necessary to integrate, analyze, and
synthesize them. Naturally, there is a corresponding demand for personnel who understand
and are able to work with these data: particularly those who combine remote sensing
expertise with a background in other systematic fields.
1
http://darwin.nap.edu/openbook.php?record_id=10658&page=35
COURSE DESCRIPTION
This course covers the basic theory and mechanics of the remote sensing process and related
theoretical aspects of radiation and the environment. We study a tiny bit of history, but will
focus on a selective subset of the network of currently active sensors on board Earthorbiting platforms. We will work with data from these sensors and learn their basic
characteristics and applications. Although we will focus on visible to near-infrared spectra,
we will also review RaDAR, LiDAR, and thermal-infrared methods and applications. In
order to extract information from satellite data, students will use software to apply the digital
image analysis methods discussed in class. This will also involve learning (or relearning)
some statistics. Topics will be covered in the context of a variety of environmental science
applications and examples.
Through this course, students should gain the basic concepts and language skills necessary
to understand and communicate with others about remote sensing, as well as the
background necessary to begin using remote sensing for research.
YOUR PROFESSOR
I am an associate professor in the Department of Geography at UNC-Chapel Hill. I arrived
here in 1994 after receiving my Ph.D. in Geography from Boston University under the
direction of Alan Strahler and Curtis Woodcock. Prior to that, I received bachelors and
masters degrees in Geography from UC Santa Barbara, and an associate degree in Music
from Santa Barbara City College. I study biogeography, landscape ecology, and ecosystem
ecology, and apply a variety of approaches, theories and tools in my research. My work has
examined processes and patterns across a broad range of geographic and temporal scales.
Some of the main themes in my research include plant-water relations in California
chaparral, ecosystem response to climate variability, geographic determinants of species
richness, and habitat conservation.
GOALS AND GRADING
Class lectures will be supplemented by readings, quizzes, lab exercises, one midterm
exam, and a cumulative final exam. Grading will be based on the following elements and
their corresponding percentages:
Labs: 20% Assigned on Tuesdays – Due upon assignment of following lab.
Quizzes: 30% Given on Tuesdays before lecture.
Midterm Exam: 20%
Final Exam: 25% (cumulative)
Participation and Engagement: 5%
See schedule below for important dates.
Review the following resource each week: http://earthobservatory.nasa.gov/.
CLASS SCHEDULE
WEEK
TOPICS
MAIN THEMES
NOTES
1 8/24 – 8/29 – 8/31
Jensen RSE Ch. 1, 3
Introduction & Background
Resolutions & Trends
Lab 1
2 9/5 – 9/7
Jensen RSE Chapter 2
Basics of EMR & Matter
3 9/12 – 9/14
Lillesand Ch. 1 and
appendix 1
4 9/19 – 9/21
Jensen RSE Ch. 7
Robinson Ch. 2 p26-51
5 9/26 – 9/28
Jensen DIP Ch. 2 to
p141
Radiative Transfer
Pigeons to Payloads, Current
Systems, Resolutions & Tradeoffs, State of the Art, Trends
Definitions, Units, Spectrum,
Major Spectral Regions, Laws,
Fates, Energy Balance
Atmosphere, Canopy, Water,
Terrain, BRDF
Sensors & Orbits
Types, Specs, Design, Orbital
Geometry, Space Junk
Quiz 1
Scene-to-Image; Image
Properties, Structures &
Formats
Lab 3
6 10/3 – 10/5
Jensen DIP Ch. 4
Image Statistics
Pixels, Bits/Bytes/Binary,
Scale, Spectral Mixing, Image
Data Properties, Image
Choice, Data Storage &
Formats, Data Access
Summary Statistics, Σ, μ,
PDFs, Set up for classification
7 10/10 – 10/12
Lab 2
Quiz 2
Lab 4
8 10/17 – Break
9 10/24 – 10/26
Jensen DIP Ch. 5, 7, 8
Exam I (through Week 7)
Display, Contrast &
Geometric Enhancement,
Geometric Correction
10 10/31 – 11/2
Jensen DIP Ch. 9, 13
11 11/7 – 11/9
Supervised Classification
Lab 5
Unsupervised Classification
& Change Detection
Quiz 3
12 11/14 – 11/16
Jensen RSE Ch. 9, 10
13 11/21 – Break
Other Sensor Types
14 11/28 – 11/30
Jensen RSE Ch. 11, 12
Advanced Products
15 12/5
Final: 12/11 @ 4:00
Wrap Up
Final Exam
Histogram Equalization Etc.,
Hi/Low Pass Filters, Moving
Window Operations, GCPs
and Polynomial Regression,
Resampling
LiDAR, RADAR, Thermal
Catch up
Vegetation Indices, LAI,
fAPAR, Pnet, NPP,
Atmosphere, Ocean,
Geophysics