Advanced Remote Sensing
This project-oriented course focuses on advanced classification procedures incorporating digital elevation data, fuzzy and object-oriented classification, and new millennium data sources including ASTER, RADAR, MODIS, LiDAR and high-resolution scenes. Repeat imagery is used to assess local and global changes in land cover, oceanic, atmospheric and/or cryospheric environments.
In this course, students will use industry-standard software such as PCI Catalyst, ArcGIS Pro, QGIS, R and Python to complete advanced analysis of remotely sensed images.
Schedule
| Date | Topic |
| Jan-07 | Introduction |
| Jan-10 | Landsat 8, 9; sentinel |
| Jan-11 | Intro to PCI Catalyst, Sentinel |
| Jan-14 | Landsat-like sensors |
| Jan-17 | Principal Component Analysis /hyper |
| Jan-18 | Principal Component Analysis / Tassel cap |
| Jan-21 | High-Resolution sensors |
| Jan-24 | DEMs |
| Jan-25 | DEMs/Topographic co-registration |
| Jan-28 | High Res Presentations – class |
| Jan-31 | Low/med res: MODIS |
| Feb-01 | LiDAR |
| Feb-04 | Planetary Remote Sensing |
| Feb-07 | MODIS – Presentations – class |
| Feb-08 | RPAS Data |
| Feb-11 | SAR- amplitude |
| Feb-14 | INSAR |
| Feb-15 | SAR |
| Feb-18 | Midterm 1 |
| Feb-21 | Family Day |
| Feb-22 | Reading Break |
| Feb-25 | Reading Break |
| Feb-28 | OOC-segmentation |
| Mar-01 | OOC – segmentation |
| Mar-04 | Machine Learning |
| Mar-07 | Cube / RPAS data |
| Mar-08 | Machine Learning |
| Mar-11 | Large Datasets / Area |
| Mar-14 | Time series |
| Mar-15 | Google Earth Engine / Planetary Engine (Alex) |
| Mar-18 | Applications: environmental monitoring |
| Mar-21 | Applications: emergency management |
| Mar-22 | Project |
| Mar-25 | Course review / summary |
| Mar-28 | Lecture exam2 |
| Mar-29 | Project |
| Apr-01 | RPAS demo |
| Apr-04 | Class project demos |
| Apr-05 | Project (20%) |