Digital Image Processing for Remote Sensing
Course information
This class is a general introduction to Digital Image Processing, with special focus on remote sensing applications using Google Earth Engine (GEE). It was taught at UNAM (Universidad Nacional Autónoma de México) in 2024, as part of the Licenciatura en Geografía Aplicada in the Escuela Nacional de Ciencias de la Tierra (ENCIT).
Note: students enrolled in this course had no prior programming knowledge.
Instructor
Sébastien Valade (UNAM)
Part 1: fundamentals of Digital Image Processing
Introduction
- Introduction (slides)
Lecture 01
Lecture 02
- Lecture: Digital Image Basics (slides) (slides extra)
- Tutorial: Numpy (notebook)
- Exercises: notebook, images
- Exercises (solved): notebook
Lecture 03
Lecture 04
- Lecture: Morphology and Segmention (slides)
- Exercises: notebook, images
- Exercises (solved): notebook
Part 2: remote sensing applications with Google Earth Engine (GEE)
Lecture 05
Lecture 06
Lecture 07
Lecture 08
Lecture 09
Lecture 10
- Lecture: GEE Mosaicking and Compositing (slides)
Extra
- PlanetScope in GEE (slides by Dulce Ruiz)
- GOES16 in GEE (notebook1, notebook2 by Santiago Piñón Juárez)
Recommended Literature
- Chuvieco, E. (2010). Teledetección ambiental
- Gonzalez R.C. & Woods, R.E. (2018). Digital Image Processing (4th Ed.)
- Lillesand, T., Kiefer, R. W., & Chipman, J. (2014). Remote sensing and image interpretation.
- Cardille J. A., et al. (2024). Cloud-Based Remote Sensing with Google Earth Engine
- Canty M. J. (2019). Image Analysis, Classification and Change Detection in Remote Sensing. CRC Press. 4th Edition