Advanced Remote Sensing and Geospatial Analysis

This course builds on the introductory remote sensing class, FNRM 3262/5262. It provides a detailed treatment of advanced remote sensing and geospatial theory and methods including Object-Based Image Analysis (OBIA), lidar processing and derivatives, advanced classification algorithms (including Random Forest, Neural Networks, Support Vector Machines), biophysics of remote sensing, measurements and sensors, data transforms, data fusion, multi-temporal analysis, and empirical modeling. In-class and independent lab activities will be used to apply the course topics to real-world problems. Prior coursework in Geographic Information Systems, remote sensing, and statistics is necessary.

Prerequisites

  • FNRM 3262 (undergraduate students)
  • FNRM 5462 (graduate students)
Course ID
FNRM 3462
FNRM 5462
Credits
3
Semester Offered
Spring
Course Frequency
every year