Advanced Remote Sensing

GEOG 457/657 – Winter 2024

Location and hours

Tuesday 8:30-9:20 – Lecture (10-4072)
Tuesday 11:30-2:20 – Lab (GIS Lab 8-125)
Thursday 8:30-9:20 – Lecture (10-4072)

Overview

Remote Sensing is a longstanding tool that has seen massive expansion in recent years. With increases in computational power and the miniaturization of electronics, we’ve seen new and more powerful sensors in space, and we’ve seen costs go down. The applications are far ranging, e.g. scientific, military, and humanitarian. This course will cover advanced workflows and image processing techniques and aims to be a bridge between technology and research. Most of the labs involve coding in Google Earth Engine and R. By the end of the course students will have generated automatic timelapse animations in 3D, done advanced supervised machine learning, and analyzed time series imagery.

Undergraduate/graduate students

This is a split course. Requirements for this course will be higher for graduate students.

Office hours

Tuesday from 10:30-11:30 in the GIS Lab. Please stop by and say hello.

Grading

  • 10 Labs (40%)
  • Presentations (10%) Feb 6 & Mar 14
  • Midterm exam (15%) Thu, Feb 15
  • Final exam (15%) Tue, Mar 26
  • Final project (20%) Thu, Mar 28

Required accounts

Schedule

ReadingLectureLabReading
Tue, Jan 4Intro LectureHansen et al. 2013
Tue, Jan 9Optical – Fundamentals 1 Lab 1: Google Earth EngineGorelick et al. 2017
Thu, Jan 11Optical – Fundamentals 2  
Tue, Jan 16Radar – Fundamentals Lab 2: GEE SAR Flooding
Thu, Jan 18Radar – InSARHowell et al. 2021
Tue, Jan 23Lidar – FundamentalsLab 3: lidR and LidarBC
Thu, Jan 25Lidar – Applications Roussel et al. 2020
Tue, Jan 30Drones – FundamentalsLab 4: Drones
Thu, Feb 1Drones – ApplicationsKattenborn et al. 2019
Tue, Feb 6Class PresentationsLab 5: Other sensors 
Thu, Feb 8Class Presentations  
Tue, Feb 13Applications / ReviewLab 6: Building websites
Thu, Feb 15Mid Term (15%)
Tue, Feb 20BREAK  
Thu, Feb 22BREAK  
Tue, Feb 27Clustering and ClassificationLab 7: Random Forest in GEEMahdianpari et al. 2020
Thu, Feb 29Classification, ML
Tue, Mar 5Time Series AnalysisLab 8: Trends in indices
Thu, Mar 7Time Series Analysis and Big data  
Tue, Mar 12Terrain Analysis – FundamentalsLab 9: Whitebox
Thu, Mar 14Other Sensors – High res
Tue, Mar 19Pixel Tracking – FundamentalsLab 10: Image velocimetry
Thu, Mar 21Ground-based RS  
Tue, Mar 26Exam (15%)Project time
Thu, Mar 28Field Trip – Drones
Tue, Apr 2Project PresentationsLab 11: Timelapse camera
Thu, Apr 4Project Presentations  
Tue, Apr 9Careers in remote sensingNo lab

Important dates

  1. Tue, Feb 6&8 – Class presentations
  2. Tue, Feb 13 – Final assignment – Short proposal due
  3. Thu, Feb 15 – Mid Term
  4. Thu, Mar 5 – Final Assignment – Revised proposal due
  5. Tue, Mar 26 – Final exam
  6. Thu, Mar 28 – Field Trip – Drones
  7. Tue, Apr 2 – Final Assignment – Presentations
  8. Thu, Apr 4 – Final Assignment – Presentations
  9. Tue, Apr 9 – Final Assignment – Due