EOS 753 - Observing the Earth and its Environment

 

index.html   syllabus.html  

eos753S09-Lecture01.ppt   eos753S09-Lecture02.ppt   eos753S09-Lecture03a.ppt   eos753S09-Lecture03b.ppt   eos753S09-Lecture04.ppt   eos753S09-Lecture05.ppt   eos753S09-Lecture07.ppt   eos753S09-Lecture08-09.ppt  

mapproj.pdf  

R scripts

 



Description

EOS 753
Observing the Earth and its environment

Spring 2009 Semester
(January - May 2009)

Every Thursdays from 19:20 to 22:00
Research 1- Room 302

Guido Cervone
gcervone@gmu.edu

Abstract

This course will provide the requisite materials to understand and apply techniques of remote sensing to study the Earth and its environment.  The course is targeted to graduate students in Earth Science, Geoinformatics, Geospatial Intelligence, Computer Science, Engineering, and related fields.  No prior knowledge of remote sensing is required nor expected.  Basic computer skills, including the ability to analyze data, generate maps and plots will be discussed and demonstrated.

Every day numerous satellites from different countries acquire and transmit multispectral high resolution data of the Earth and its environment. Such data are used for a variety of operational and research applications, such as weather forecasting, national security, natural hazards, navigation, land use and land cover, surface temperature, climate change, urban planning and many others. Massive amounts of data are received, processed, stored and distributed by several centers around the world, giving an unprecedented access to global high resolution information.  Such information can give new insights to study the complementary nature of different parameters of the Earth’s environment.

Using remote sensing data requires understanding measurements and limitations of satellites and their sensors, and studying the algorithms used to generate products and analyze them. In fact, raw satellite data do not usually provide information ready to be used, and they must be processed using specific algorithms to calibrate the measurements, generate meaningful physical products, and geolocate the generated products onto the irregular surface of the Earth.

The first part of the course discusses remote sensing methodologies, products availability and characteristics, data types and formats, and basic programming to analyze data, generate maps and plots. The methodologies survey includes a systematic study of how each part of the electromagnetic spectrum is used to gather data about the Earth.  The limitations imposed by satellite engineering and sensor limitations on data gathering are discussed. Data reduction and analysis techniques specific to remote sensing applications are covered.

The second part of the course discusses remote sensing applications for specific tasks including natural hazards, global change, seasonal and inter-annual studies.  Current research issues will be illustrated, including examples pertaining to the atmosphere, land masses, and oceans, and concluding with a survey of some problems that are at the current frontiers of remote sensing. Programs will be provided in R (www.r-project.org) to automatically download, analyze and map different data sources.

The format of the course is a 110 minutes of lecture, followed by a 60 minutes in class discussion. The class discussions are based on assigned readings related to the topic of lecture.  Each student is expected to read the assigned readings before each class, and be able to provide a critical analysis of the work, and engage in an in depth discussion.

 


Instructor

Guido Cervone

Assistant Professor
Department of Geography and Geoinformation Science (GGS)
and
Center for Earth Observing and Space Research (CEOSR)

Contacts
Office: Research 1, room 327
Telephone: 703.993.1799
email: gcervone@gmu.edu
MSN: gcervone@gmu.edu
gtalk: gcervone
Yahoo: gcerv1
AIM: gcerv1


Grading

 

Class Discussions and Summaries 20%
Each week students are assigned one or more readings for the next class. Students are expected to read and critically evaluate the material, and actively participate to the in class discussion. Additionally, students are expected to summarize in one or two paragraphs each of the readings assigned, emphasizing the strengths and weaknesses of the described approaches and methods.

Midterm Project 20 %
The goal of the midterm is to have the students research on a topic of their interest, which will later be investigated for their final project. The midterm will consists of an in class presentation and a short report (~5 pages). Acceptable topics will be discussed in class, and must be agreed with the instructor. The midterm can be related to the student's own research, or the work of others. Students are encouraged to choose a topic of interest for their M. S. or Ph.D. dissertation.

Final Project 40 %
The final project is the biggest contributor to the student's grade. The goal of the project is to give an opportunity to the students to work on topics of their interest. As for the midterm, the final project consists of two parts, an oral presentation and a written report (~15 pages). The topic of the final project should be a continuation of the midterm. While in the midterm the students will be graded on the formulation of a problem and their research on previous and related work, in the final students will be graded on how the problem was investigated and on the results obtained.

Final Exam 20 %
An in class final exam will be given on the topics discussed in class. The exam may cover material from the textbook, lectures assigned readings and in class discussion.

Policy on Absence
Students are expected to actively participate in the lecture and class discussion. When a student misses a lecture, he is invited to let the instructor know in advance. The student is still responsible for reading the weekly assignements, and turn in their summary on time.

 


Class Material

 

Textbook

Elachi, Charles. Introduction to the Physics and Techniques of Remote Sensing. Wiley Series in Remote Sensing, John Wiley & Sons, New York, (1987).

You can find the textbook for a cheeper price here

Additional readings will be assigned throughout the class.

Equipment

Students must be able to run R (www.r-project.org) to complete the assignments.  R is an open source scripting language with tailored for strong statistics analysis.  It is available for most platforms, including Linux and OS X.  Students who do not have access to their own computers, can use the COS computer platforms for completing their assignments and for the final project.

The main website for the CEOSR's HRPT antenna receiving station is http://terra.cos.gmu.edu/antenna


Schedule
January 22
Description, goals, introduction to remote sensing, our Earth
January 29

The EM spectrum and atmospheric opacity, how satellites sense data. Intro to R

February 05
Generic conical orbits, Kepler's laws, orbital mechanics, satellite orbits. Statistics using R.
February 12
Map projections, sensor calibration and data georectification.
February 19
The world in the IR -- IR remote sensing and its application for vegetation and land cover
February 26
Data mining / Data processing
March 05
Midterm presentation - Report due
March 12
No Class - Spring Break (March 9 - 15)
March 19
Remote sensing products I
March 26
Remote sensing products II
April 2
Remote sensing products III
April 9
Remote sensing products IV
April 16
GIS - Data formats - Spatial Databases - Review and Topic lecture.
April 23
Hyperspectral remote sensing- Guest Speaker
April 30
Final presentation - Final report due
May 7
Final Exam Due



Last Modified: Tuesday, 05-May-2009 12:59:31 EDT