11-15 September 2023
To foster international participation, this course will be held online
The course is facing ecological remote sensing problems mainly related to planetary changes. The course is dedicated to scholars having no experience with R. We will start in R from scratch and
code remotely sensed analysis with a step-by-step procedure.
At the end of the course, attendees will have the ability to code their analysis workflows as well as report the output in LaTeX. The final part of the course is dedicated to the basics of LaTeX
scripting considering both articles and presentations.
- Opening and managing a GitHub account to store your code
- Basic coding in R: from scratch until remote sensing data analysis
- Basic intro to LaTeX for coding texts and output reporting
Daily schedule: 15:00 - 18:00 (Berlin time)
** Session 1 – Introduction (Monday)
- The roots of ecological remote sensing
- Reference systems: introduction to the main coordinate systems
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** Session 2 – Remote sensing data exploration (Tuesday)
- Setting up, importing and visualizing remote sensing data in R (with Landsat data)
[R package: raster]
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** Session 3 – Remote sensing data exploration 2 (Wednesday)
- Vegetation indices: the case of Amazon forest
[R packages: raster, RStoolbox]
- Multitemporal analysis of remote sensing data: the case of Greenland ice melt (with Copernicus data)
[R package: raster, ggplot2, viridis]
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** Session 4 – Remote sensing data analysis (Thuersday)
- Image classification: introduction to unsupervised image classification
[R package: RStoolbox]
- Multivariate analysis: PCA
[R package: RStoolbox]
- Spatial variability and image diversity (with Sentinel data): the case of the Similaun Glacier
[R packages: raster, rasterdiv]
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** Session 5 – Reporting 1 (Friday)
- knitr: reports in R
[R package: knitr]
- LaTeX basics: articles in LaTeX
- LaTeX basics: beamer presentations in LaTeX
Cancellation Policy:
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.