ENEE 759D: Data Structures and Algorithms for Remote Sensing Data Processing
Remotely sensed data is the primary source of information to study the earth's environment at regional and global scales. Raw satellite data have to be processed and integrated into a database system to produce multitemporal data sets that can be used for various environmental studies. The main goal of the course is to introduce basic algorithms and related data structures for processing remtotely sensed imagery with a particular emphasis on spatial data structures.
ENEE 446 and some programming experience with C.
Basic understanding of computer architecture and programming in high level programming language such as C. The student is also expected to have had at least some preliminary exposure to elementary data structures and algorithms.
1. Hanan Samet, The Design and Analysis of Spatial Data Structures, Addison-Wesley, Reading, Mass., 1990.
Grading Method:Midterm 45%
Oct. 22, 1998