R for Remote Sensing

Turn multispectral, hyperspectral and lidar observations into analysis-ready datasets with R. Using forest and ecological examples, participants assess metadata and data quality, correct geometric and radiometric errors, reduce noise, and derive spectral indices and structural features. Exercises connect temporal change analysis and classification with scale, accuracy and uncertainty, producing reproducible workflows for spatial research.

2026-11-10–2026-11-13, 12:00–16:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €420. Participants need basic competence and confidence in R and RStudio; prior remote-sensing experience is optional.