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Open Educational Resources in Sustainable Technologies

Geocomputation

Renewable Energy

Energy Systems

  • energy-sparks - An open source application that is designed to help schools improve their energy efficiency.
  • Building DC Energy Systems - Hosts an Open Educational Resource (OER) for Building DC Energy Systems.
  • Systems' Engineering for Energy Efficiency - A Python course on Systems engineering for energy efficiency in German within the Master of Electrical Engineering and Master of Renewable Energy at the Cologne University of Applied Sciences.
  • ESM-lectures - Lecture slides for KIT Energy System Modelling course.
  • Power Systems Optimization - How to implement and apply linear and mixed integer linear programs to solve such problems using Julia/JuMP, and the practical application of such techniques in energy systems engineering.
  • Data Science for Energy System Modelling - Find practical introductions to many Python packages that are useful for dealing with energy data and building energy system modells.

Consumption of Energy and Resources

  • openlca-python-tutorial - Explains the usage of the openLCA API from Python.
  • GreenCity - Teach people in a playful and challenging way to have an eco-friendly lifestyle.
  • Advanced Urban Analytics - This course series takes a computational social science approach to working with urban data.

Climate and Earth Science

  • ClimateModeling_courseware - A collection of interactive lecture notes and assignments in Jupyter notebook format.
  • Earth and Environmental Data Science Book - An Introduction to Earth and Environmental Data Science.
  • Free Earth Data Science Courses & Textbooks - A site dedicated to tutorials, course and other learning materials and resources developed by the Earth Lab team.
  • Climate Change Impact Assessment - A practical walk-through.
  • MIT-PraCTES - Materials for MIT workshop "Practical Computing Tutorials for Earth Scientists".
  • ICAR - A simplified atmospheric model designed primarily for climate downscaling, atmospheric sensitivity tests, and hopefully educational uses.
  • GEOG0133 - Open Terrestrial Carbon modelling and monitoring lecture.
  • The Climate Laboratory - A hands-on approach to climate physics and climate modeling.
  • Climate Risks Academy 2021 - Contains solutions for the advanced assignment of the Modelling Lab of the Climate Risks Academy 2021.
  • PyEarthScience - Python modules, scripts and iPython notebooks, in particular for Earth System data processing and visualization used in climate science.
  • EDS220_Fall2021 - Provide an introduction to various environmental data sets, which should give you a good sense of the range of tools out there for manipulating and processing environmental data.
  • Climate Change Impact Assessment: A practical walk-through - Throughout the course of this book, you will learn how to acquire observed historical climate data from Environment and Climate Change Canada, and perform basic analyses of a climate index and meteorological variables.
  • LP DAAC E-Learning - Frequently updated presentations, webinars, tutorials, and video tips on accessing, managing, and processing LP DAAC data using a variety of software, web applications, custom tools, and scripts.
  • Copernicus Training - Data tutorials for the Copernicus Climate Change and Atmosphere Monitoring Services.
  • The Environmental Data Science book - A living, open and community-driven online resource to showcase and support the publication of data, research and open-source tools for collaborative, reproducible and transparent Environmental Data Science.
  • Earthdata Cloud Cookbook - This Cookbook is learning-oriented to support scientific researchers using NASA Earthdata from Distributed Active Archive Centers as they migrate their workflows to the cloud.
  • Project Pythia - A community learning resource for Python-based computing in the geosciences.
  • MOOC Machine Learning in Weather & Climate - Explore the application of Machine Learning across the main stages of numerical weather and climate prediction.
  • HPC4WC - High Performance Computing for Weather and Climate Course.
  • ARSET Fundamentals of Machine Learning for Earth Science - This training will provide attendees an overview of machine learning in regards to Earth Science, and how to apply these algorithms and techniques to remote sensing data in a meaningful way.

Earth Observation

  • Radiant MLHub Tutorials - Tutorials to access Radiant MLHub Training Datasets.
  • Fundamentals of Remote Sensing - Participants will have a basic understanding of NASA satellites, sensors, data, tools, portals and applications to environmental monitoring and management.
  • Open Source Geoprocessing Tutorial - Tutorial of fundamental remote sensing and GIS methodologies using open source software in python.
  • EO College - This course is part of a series of online learning materials that will give you insights on the potential of remote sensing technologies for applications over land surfaces.

Earth Systems

Atmosphere

Cryosphere

Biosphere

  • mebioda - This repository contains materials for the MSc course Methods in Biodiversity Analysis.
  • NEON Data Skills - Provides tutorials and resources for working with scientific data, including that collected by the National Ecological Observatory Network.
  • python-ecology-lesson - Data Analysis and Visualization in Python for Ecologists.
  • R-ecology-lesson - Data Analysis and Visualization in R for Ecologists.
  • ECOSTRESS Tutorial - The ECOSTRESS mission is tasked with measuring the temperature of plants to better understand how much water plants need and how they respond to stress.
  • Tutorial for Working with NASA VIIRS Surface Reflectance Data - Converting VNP09GA files into quality-filtered vegetation indices and examining the trend in vegetation greenness during July 2018 to observe drought in Europe.
  • MapBiomas 101 - Google Earth Engine Tutorials to produce annual land use and land cover maps from Brazil.
  • Gedi Tutorials - Tutorials on producing high resolution laser ranging observations based on data of the Global Ecosystem Dynamics Investigation.

Hydrosphere

  • MarineEcosystemsJuliaCon2021.jl - Modeling Marine Ecosystems At Multiple Scales Using Julia.
  • CoastWatch Satellite Course - The goal of the course is to familiarize university researchers and students with different types of ocean satellite data, different tools, and teach participants how to use satellite data in their own research using their choice of software (R, python, ArcGIS).
  • The Argo Online School - Teach the basic foundations to use and understand Argo an international program that collects information from inside the ocean using a fleet of floats that drift with the ocean currents.
  • Analytical Groundwater Modeling - Analytical Groundwater Modeling: Theory and Applications Using Python.

Natural Resources

Sustainable Development Goals

Integrated Assessment Modelling and Climate Econometrics