====== O04: Current Applications of Remote Sensing =======




===== Lecture =====

Please follow this link to find today's lecture:

[[https://www.youtube.com/watch?v=lwdcda8lbbg&list=PL1MbwuMcC4yWw0UhPyJE-oJCfXLIYrBYM&index=2]]


===== Reading Task =====

  * [[https://www.nature.com/articles/s41467-022-29838-9| Machine learning-based global maps of ecological variables and the challenge of assessing them]]
  * [[https://www.sciencedirect.com/science/article/pii/S0303243421003202?via%3Dihub | Countrywide mapping of shrub forest using multi-sensor data and bias correction techniques]]



===== Bonus R Practice =====

To go into more details of the modelling process, you will find a [[https://drive.google.com/file/d/1q-6NkoT3XUb4ANcHDPeUZI-QABFnbOj8/view?usp=sharing|Bonus R Task here]]. Namely the Rscript ''TASK-BONUS-random-forest.R'' with the associated files ''landsat_fogo_ndvi.tif'' and ''modelling_data.csv''. Try to train and validate a random forest model and predict landcover for the entire island of fogo. If you struggle with this task, do not worry. This will also be part of the Module next week, where we can give more guidance and tutorials in person.