Sensors, bands, and spectral signatures
60 min
Lecture on optical sensors, atmospheric effects, and class separability.
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Remote Sensing
Land Cover Mapping with Multispectral Imagery
Plan and deliver a land-cover classification course module using optical satellite imagery.
intermediate~18 hours
For faculty
Faculty can use this skillset to scaffold a remote-sensing unit that moves from sensor basics to supervised classification and accuracy assessment.
Competencies
Raster interpretation
Remote Sensing
Coordinate reference systems
Foundations
Spatial statistics
Analysis
Objectives
- Explain spectral reflectance differences among common land-cover classes.
- Design a classification workflow appropriate for regional monitoring.
- Evaluate map accuracy with an independent validation sample.
Outcomes
- Produce a land-cover map with documented methods and accuracy metrics.create
- Justify class definitions against stakeholder information needs.evaluate
- Interpret confusion matrices and recommend improvements.analyze
Theory sessions
Demo sessions
False-color and index workflows
45 min
Instructor demo of NDVI and composite interpretation in GIS software.
Exercise sessions
Signature exploration lab
90 min
Compare NDVI and false-color composites for urban, cropland, and forest sites.
Supervised classification project
180 min
Train a classifier, validate with hold-out samples, and write a methods note.
Assessment methods
Practical / lab test
Observed GIS or remote-sensing task under timed conditions.
Project / portfolio
Submitted maps, notebooks, or analysis portfolio.
Rubric-based assignment
Written or mapped deliverable scored with a rubric.