On April 20, 2010, an explosion aboard the Deepwater Horizon drilling rig in the Gulf of Mexico caused one of the worst oil spill disasters in U.S. history. Satellites tracked this oil spill for months. In fact, this is a disaster in which satellite observations (and remote sensing in general) played a primary and pivotal role in monitoring the spill and its consequences for the environment. Two NASA satellites were capturing images of the oil spill in the Gulf of Mexico (a short video that reveals a space-based view of the burning oil rig and, later, the resulting spread of the oil spill is available at here) and NASA deployed several of its airborne and satellite research sensors to collect an unprecedented amount of remotely sensed data over the Gulf of Mexico region. 

For more information about active and passive remote sensing devises used to monitor the ever-changing oilslick please visit here

Capstone Capstone  Capstone

A fundamental problem in analysing satellite remote sensing data is merging two or more data sets which provide complementary information. The objective of this capstone project is to build a multispectral data fusion module that implements several state of the art data fusion algorithms and tests their performance on a variety of multispectral images captured during the oil spill in the Gulf of Mexico. There are many open-source image processing and scientific computing libraries that will be used as building blocks, primarily Numpy and Scipy . The focus of this capstone is to combine, generalize, and utilize existing functions in creation of one comprehensive data fusion library. 

Course Objectives: In this project-based course, students are grouped into teams to work on projects of practical importance in satellite image processing. Through this project, students are expected to expose themselves to the forefront of research and development in satellite image processing and data fusion. 

By the end of the course, students will:

1. learn data fusion algorithms

2. build a data fusion module designed in Python

3. test the module on a variety of remote sensing data sets

Prerequisites: CSc21700, CSc22000, Math34600. Pre or Co-requisites: CSc30100

The capstone course will last two semesters, Spring 2011 and Fall 2011. There are internships available for students who are interested in working during the summer.

 

© 2010, NOAA-CREST CSDIRS, CCNY-Glasslab/Michael Grossberg/Irina Gladkova/Paul Alabi

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