On completion of the course the student should be able to: - Account for aims and methods for data collection via remote sensing with the aim of addressing change and damage detection in forest ecosystems. - explain the physical bases of remote sensing of vegetation in general and forests in particular. - explain and apply the stages in processing of remote sensing data, collect and prepare data, pre-processing, classification, estimation and discover changes and estimation of reliability for different remote data sources. - execute a change detection analysis using high performance computation (e.g. google earth engine).
Extent:
Vecka 1: Förstudievecka (på distans)
vecka 2: Remningstorp (på plats Sön-sön)
Vecka 3: Eget arbete/hemuppgift (på distans)
Prerequisites
To be eligible, students need to be a registered PhD student in the field
of ecology, conservation biology, forest management, remote sensing or
related field. Some experience in computation and scripting in R is
advised but not mandatory.