The training material introduces students from agriculture-related study programmes to the basics of remote sensing and Earth Observation. This course is in Spanish language.

This course is an introduction to the European Union's Earth Observation Programme and focuses on the Copernicus Atmosphere Monitoring Service.

This course is an introduction to the European Union's Earth Observation Programme and focuses on the Copernicus Climate Change Service.

This presentation gives a basic overview on the use of Earth observation data from Synthetic Aperture Radar (SAR) systems for flood mapping. It was prepared using modified EO College resources.

This is a lesson on Earth observation data that can be combined with administrative, social and economic data at multiple scales for in-depth analyses.

This is a lesson on monitoring the urban heat islands. This beginner’s lesson introduces the student to GIS and vector/raster data.

In this course students will get an introduction to the main ideas and tools to acquire reproducible research practices. Special emphasis is given to literate programming and how to create reproducible notebooks.

The programming course introduces the student the basics of the Leaflet library to create simple web-based maps. It provides examples to handle base maps and vector data with Leaflet.js. This course is in Spanish language.

This course contains the basic elements of Earth observation from space, dealing with the basic physical principles, technologies and methodologies used.

The text provide introductory concepts on detecting changes using EO data. Considerations about quantitative vs qualitative assessment as well as methods and processing steps are also provided.

This is a training material on Introduction to Remote Sensing containing basic definitions, satellite data sources and brief description of Copernicus services with particular focus on the Copernicus Land Monitoring Service.

This is a training material on Sentinel-2 data and vegetation indices. It is divided into two modules: 1) Introduction to spectral indices and 2) Application of vegetation spectral indices.

This module gives an overview of the non-technical aspects related to Spatial Data Infrastructures (SDI). In an SDI several technical and non-technical components work together. This module is targeting process owners and managers.

Spatial data are widely used in public and private organisations. However, the data are often difficult to find, access, use and combine. Spatial data infrastructures (SDI) are a solution to this lack of accessibility and interoperability.

This is an introductory course to GIS including basic information on: Geographic Information Systems, raster and vector models, coordinate systems, attribute and spatial queries, simple analysis using geoprocessing tools and data visualization.

Decision Trees (DT) is a non-parametric classifier that gained popularity in different domains because its structure is explicit and easily interpretable.

Random Forests (RF) is one of the most popular machine learning classifiers due to its capability to obtain good classification results with a relatively reduced number of training samples and user-defined parameters.

This course introduces preprocessing operations, sometimes referred to as image restoration and correction, used to correct radiometric and geometric data distortions specific to sensors used in EO.

Quantifying the quality of satellite, aero and drone data products by decomposing the inherent uncertainty components is a very challenging task. This course provides an overview of EO data validation procedures and frameworks.

This is an introductory course about The Copernicus Land Monitoring Service (CLMS) and its components and the data they provide.

This is a lesson on monitoring the urban heat islands. This beginner's lesson introduces the student to remote sensing.

This slideset is a tutorial for a basic analysis of urban heat islands. Within the tutorial SNAP, QGIS and eCognition are used.

A a brief introductory presentation to the Erasmus+ EO4GEO project. EO4GEO is an Erasmus+ Sector Skills Alliance gathering 26 partners from 13 EU countries. This presentation is available in English, Italian, Spanish and German.

This training material provides an overview of 'Terrascope'. With this material, you can familiarize yourself with Terrascope and learn how to access to the data and process it.

This slide set provides overview of how researchers or students could utilize Terrascope Jupyter notebooks and API such as openEO to develop remote sensing algorithms and applications.

This introductory course in remote sensing and (satellite) image analysis covers the basic analysis workflow. It requires a lecture or any other introductory class in the theoretical fundamentals of remote sensing.