GEOGRAPHY 477: INTRODUCTION TO REMOTE SENSING
LECTURES: 9:30 - 10:45 T/R – 204 SAUNDERS
LAB HOURS: M 9:00-10:30 SA 322
FALL 2007 ● UNC-CHAPEL HILL
Aaron Moody
211 Saunders Hall
aaronm@email.unc.edu
Matt C. Simon
319 or 322 Saunders Hall
msimon@email.unc.edu
COURSE CONTEXT
Remote sensing has led to profound changes in society’s world view. It has transformed
scientific insight, geographic knowledge, and cultural perceptions of Earth and her
inhabitants. The photograph “The Blue Marble” is not merely a symbol, byproduct, or
legacy of the space age. Rather, the promise of that synoptic view, afforded from above, was
a primary motive for releasing the investments necessary to access space beyond the Earth
system. Access to space meant release from limitations imposed by the mismatch between
the human scales of experience and the geographic scope of the Earth system. In fact,
remote sensing has coevolved tightly 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, and is now providing us with a front row seat from
which to observe the spectacle of the human superorganism in action.
Military and strategic interests, have, of course, been tantamount in the pursuit of space,
including the development of remote sensing technology. However these drivers are
substantially weaker today. 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
whole world system, in all its dynamics and complexity, will be replicated continuously 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. Importantly, 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.
This semester the course is organized around the general topic of global change. In this
context, your lab projects will focus on one of the following subtopics:
Land and Sea Ice in the Arctic
Tropical Deforestation
Urbanization in Asia
Protected Areas and People in Africa
Fire and Drought in the Western United States
Drought/Productivity/Fire Assessment for the US Southeast
YOUR PROFESSOR
I began my career in the UNC Geography Department as an assistant professor in 1995, and
received tenure in 2001. Prior to that, I received a Ph.D. in Geography from Boston
University (1995), bachelors and masters degrees in Geography from UC Santa Barbara
(1988, 1990), and an associate degree in Music from Santa Barbara City College (1986). My
research areas include landscape ecology, biogeography, macroecology, and ecosystem
ecology, to which I apply a variety of tools, including satellite remote sensing, in situ and
other biophysical data, and quantitative spatial modeling. In reality, I find it increasingly
problematic to pin disciplinary labels on what professional scholars actually do, and I
subscribe to a world-system, or whole system perspective that seeks unification in our
approach to the World System.
I grew up in coastal California, at about the same latitude as Chapel Hill, and I return their
when I can for family, research, and peace of mind. I lived in Boston for four years, and love
the urban environment almost as much as the landscapes of my youth. While in high school
I surfed and pretended to be a rock star, leading inevitably, to a series of jobs related to
recycling, hauling debris, painting, sanding, and spinning pizzas. I went back to school and
enjoyed learning enough to stick with it as a career.
My current research effort is dedicated to three main projects, and several others that are
under incubation or sitting on a respirator. I study habitat connectivity for rare and
endangered species at Ft. Bragg, NC in collaboration with colleagues from Virginia Tech,
NC-State, and Duke Universities (DoD). With Bob Peet in Biology at UNC I study patterns
of plant species richness in NC, SC, and VA (NASA). I am beginning on a project with Mike
Emch (Geography) to study the social and biogeographical determinants of evolution on the
H5N1 avian influenza virus. I am about to submit a proposal to NASA with Ross
Meentemeyer (UNC-Charlotte) and Christina Tague (UCSB) on the impact of sudden oak
death on stream nutrient dynamics in Big Sur, CA. I have additional interests in the
California Channel Islands and possibly emerging work in the Galapagos.
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% See schedule of assigned and due dates.
Project: 20%
Quizzes: 15%
Midterm Exam: 20%
Final Exam: 20% (cumulative)
Participation and Engagement: 5%
See schedule below for important dates.
CLASS SCHEDULE
WEEK
TOPICS
MAIN THEMES
1 8/21 – 8/23
Jensen RSE Ch2
Lillesand & Keifer Ch1
Introduction & Background
Technology
Data
Applications
MODIS
Pigeons to Payloads
Lab 1
2 8/28, 8/30
Image Data
3 9/4, 9/7
Lillesand Ch. 1 and
appendix 1
Bits/Bytes/Binary/
Resolutions
Spatial (IFOV)
Temporal
Spectral
Directional
Radiometric
Basics of Electromagnetic
Radiation (EMR) &
Matter:
Definitions & Units; EM
Spectrum & Major Spectral
Regions; Radiation Laws;
NOTES
4 9/11, 9/13
Sensors
Jensen RSE Ch. 7
Types and Specs of Orbits;
Robinson Ch. 2 p26-51 Orbital Design & Geometry;
Sensor design & components
Space Junk
Quiz 1
5 9/18, 9/20
Orbits:
Jensen DIP Ch. 2 to
p141
6 9/25, 9/26
Radiative Transfer (RT):
Jensen DIP Ch. 4
Atmospheric RT; Canopy RT;
Water RT; Terrain Effects;
BRDF
7 10/2 – 10/4
8 10/9, 10/11
Image Statistics
Summary Statistics; Σ, μ, PDFs
Quiz 2, Lab 3
Exam I (through Week 7)
Fates of EMR
Lab 1 due
Lab 2
Catch up and Review
Lab 3 due
Projects Day
Lab 4
9 10/17, Break!
Jensen DIP Ch. 5, 7, 8
Scene-to-Sensor-to-Image:
Image Properties;
Structures & Formats;
Assumptions/Limitations
Display & Enhancement:
Contrast Enhancement;
Geometric Enhancement
10 10/23, 10/25
Jensen DIP Ch. 9, 13
Classification:
Information Domains;
Parametric/Nonparametric;
Perpixel/Segmentation; Tassled
Cap;
Supervised Classification:
MDM, PPiped, BML; Accuracy
Assessment
Unsupervised Classification:
Chain Method; ISODATA
Other Data Types:
LiDAR, RADAR, Thermal
Quiz 3
Lab 4 due
Lab 5
Vegetation Indices:
Tassled Cap; DVI, RVI, PVI,
NDVI, SAVI, Ts/NDVI
Advanced Products:
LAI, fPAR, Pnet, NPP, Ocean,
Atmosphere, Geophysics
Quiz 5
Wrap Up
Projects Day
11 10/30, 11/1
12 11/6 – 11/8
Jensen RSE Ch. 9, 10
13 11/13, 11/15
14 11/20, Break!
Jensen RSE Ch. 11, 12
15 11/27, 11/29
Quiz 4
Lab 5 Due
Project Presentations
Evals
16 12/4 = last class
Final: 12/11 @ 4:00
Project Presentations
Final Exam (cumulative)
Please consult the course websites at:
http://blackboard.unc.edu
http://www.unc.edu/courses/2006fall/geog/477/001/www/
An excellent resource for Remote Sensing in the News
http://earthobservatory.nasa.gov/.