20 May
11 Jun


PhD course: Forest Change detection with remote sensing and high-performance cloud-computing, 5 ECTS

events | seminars, workshops |

The combination of time series of satellite imagery and high-performance cloud-computing capabilities to handle ‘big data’ provides an asset for timely detection of forest damages that can be complementary to traditional methods and help overcoming some of the limitations of national inventories.

The aim of the course is provide the students with theoretical and practical knowledge of working with data from remote sensing and field inventory and how to combine these in order to address issues connected to change and damage detection in forest ecosystems. The course will introduce the students to the techniques and platforms used in forest remote sensing, including imaging and laser scanning techniques and platforms like satellites, planes, drones and mobile devices. The students will learn different techniques for extracting forest information with a focus on change detection from these different data sources. Theory in basic understanding of how remotely sensed data will be transformed into forest information using statistical modelling will be given. Practical skills will be taught through computer exercises as well as hands-on experience of data collection in the field by using drones. Data processing steps like: spectral calibration; feature extraction; histogram matching, change detection and time series analysis will be explained and practiced.

Register for the reserve list of the course: The course is full. From today (2024-03-27) when you register to the course you are put in a reserve list.


Time: 2024-05-20 - 2024-06-11
City: Skara
Organiser: Department of forest resource management
Last signup date: 30 April 2024


Pre-workshop self-study, including reading course textbook, Remote sensing and image interpretation (Lillesand, kiefer & Chipman), scientific articles as well as view recorded video lectures to get a basic understanding of the topic. One week (40h).

Workshop at Remingstorp supertest site (26th of May to 2nd of June). Including lectures/seminars; computer exercises, data acquisition using drones; in-situ calibration and fieldtrip.

Preliminary schedule:


Morning - afternoon: Travel to Remingstorp/Skara

Evening: Get-together party


Morning - afternoon: Introduction exercises in remote sensing (Satellite images, Lidar, Photogrammetry)

Evening: Drone demo


Morning: Field visit: Spectral data acquisition

Afternoon: Lab: Spectral calibration

Evening: Reflection and discussion 


Morning: Field visit: 3D data acquisition

Afternoon: Lab: 3D remote sensing

Evening: Reflection and discussion 


Morning: Field visit: Multiple data set acquisition

Afternoon: Lab: Mixing different sensor data/Change detection

Evening: Reflection and discussion 


Morning: Introduction High performance computing (HPC)

Afternoon: Lab: Introduction High performance computing (HPC)

Evening: Reflection and discussion 


Morning: High performance computing (HPC)

Afternoon: Lab: HPC

Evening: Introduction to home assignment


Pack up and travel home

Post-Workshop self-study. Teacher-guided HPC exercises, where the student will conduct a change detection analysis as an individual project. Two weeks (80h)