URBAN COVER TYPE ANALYSIS

Satellite imagery from sources such as Landsat Enhanced Thematic Mapper (ETM+) is typically Classified through unsupervised and supervised classification techniques. While these techniques can be highly accurate, they are also time consuming and expensive for large areas. Other classification techniques have been proven effective for large areas. Using regression-tree analysis with a variety of imagery to classify large areas produces highly accurate results in a relatively short time and is inexpensive. For this project, we used regression-tree analysis to classify images.

Status This project is complete.

Final Project Report (10.8 MB)
Remote Sensing Tip (4 MB)
Project Poster  (2MB)
Final PowerPoint Presentation (4.2MB)