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Open Educational Resources in Sustainable Technologies

Geocomputation and Geospatial

Renewable Energy

  • To Catch The Sun - Inspiring stories of communities coming together to harness their own solar energy, and how you can do it too.
  • geothermics - Educational repository with Jupyter Notebooks all around the topic of geothermal energy.
  • Photovoltaics Education Website - A detailed deep dive to get started with photovolatic technology.
  • Predicting the Wind: Data Science in Wind Resource Assessment - Contains material for a hands-on tutorial and additional content about data science in wind resource assessment.
  • PVSC48-Python-Tutorial - Computing tutorial with focus on PV computing packages, Python, data wrangling with Pandas, and data viz.
  • Electrify - A web / mobile Tycoon-style game teaching about electricity production and consumption.
  • Fundamentals of Solar Cells and Photovoltaic Systems Engineering - Learn modeling solar radiation, calculating IV curves for varying irradiance and temperature, modeling electricity generation from PV installations, optimizing PV module orientation and inclination, and conducting time series analysis of solar generation.
  • pv-tutorials - Links to tutorial material for various open-source software packages for PV modeling and analysis.

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.
  • oemof Workshop on Modeling Heat Pumps - Learn how to use and apply oemof libraries in the context of modeling heat pumps in energy system analysis.

Consumption of Energy and Resources

Green Software

  • Sustainable Software Engineering - A course that covers techniques for measuring and improving environmental, social, and individual sustainability at every stage of the software lifecycle.

Climate and Earth Science

  • Xarray Tutorial - An open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun.
  • 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.
  • Applied Environmental Statistics - Applied Environmental Statistics course of the Boston University.
  • ClimateMatch Academy - A wide-reaching, inclusive and approachable program aimed to introduce computational methods for climate science.
  • climate-emulator-tutorial - A tutorial for getting started with machine learning for climate modeling.
  • Utilizing Open Science Techniques for Exploring Greenhouse Gas Data - An Interactive Workshop on the U.S. Greenhouse Gas Center and VEDA Tools for use in Earth Science Research
  • PyPRECIS - A learning tool to faciliate processing of regional climate model output.
  • CSDMS Ivy - Course material on scientific software development for researchers in earth and planetary surface processes.
  • Sketchbook Earth - A project aiming to illustrate the production of Climate Intelligence Reports, traditionally done with the ECMWF’s in-house developed tools.
  • CMIP6 Cookbook - This Project Pythia Cookbook covers examples of analysis of Google Cloud CMIP6 data using Pangeo tools.
  • PO.DAAC Tutorials - Make NASA’s ocean, climate, and surface water data universally accessible and meaningful.

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.
  • LPDAAC-Data-Resource - This repository is a place to find data user resources that demonstrate how to use NASA Land Processes Distributed Active Archive Center (LP DAAC) tools, services, and data.
  • E-TRAINEE - Course on Time Series Analysis in Remote Sensing for Understanding Human-Environment Interactions
  • GALUP - Build local capacity in the region of Ghana regarding remote sensing and GIS, and transfer the land use planning framework for continued planning.
  • OCO2-OCO3 - For public accessibility and data visualization, a beginner-level tutorial is available for users interested in exploring the OCO2 and OCO3 data.
  • Using NASA Satellite Data for Real-Time Environmental Monitoring - Using NASA's ECOSTRESS Satellite Data for Real-Time Environmental Monitoring.
  • Landsat ML Cookbook - Covers the essential materials for working with Landsat data in the context of machine learning workflows.
  • SERVIR Applied Deep Learning Book - Use satellite data and geospatial technology to address critical challenges in weather & climate resilience, agriculture and food security, ecosystem and carbon management, water security, disasters, as well as air quality and health
  • HYR-SENSE - Hyperspectral and Thermal Remote Sensing for Environmental Justice" program. Participants will gain hands-on experience with hyperspectral and thermal imaging remote sensing technology and its applications for environmental justice issues.

Earth Systems

Atmosphere

Cryosphere

Biosphere

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.
  • Intro to Physical Oceanography - Course materials for Introduction to Physical Oceanography.
  • Coastal Dynamics Open Codebook - Discusses the interrelation between physical wave, flow, and sediment transport phenomena and the resulting morphodynamics of a wide variety of coastal systems.
  • ECCO Hackweek 2024 Website - Explore NASA’s ECCO Ocean State Estimate, using Python, Julia, and cloud-based resources to work on oceanographic and climate data projects.

Natural Resources

Sustainable Development Goals

Integrated Assessment Modelling and Climate Econometrics