Educational Resource Hub
This crowd-sourced database of educational resources is meant to encompass any tools relevant to people working in the climate and health space. This might include submissions by the content authors themselves, or simply recommendations from community members for resources they have found helpful. This collection includes only links directing users to existing resources - it is not meant to house or archive content.
Keep in mind, this is a crowd-sourced database. CAFE does not verify the quality nor endorse the use of any materials included in this database. Make sure to follow the terms of use and attribution requirements specific to each resource. If you have created or used sources that would be relevant to the community of practice, please add it to the database by entering it in the submission form below.
This workshop introduces participants to the modern approach to working with large datasets in QGIS. Modern data formats - such as Cloud-Optimized GeoTIFFs (COG), Cloud-Optimized Point Clouds (COPC), and FlatGeoBuf (FGB) allow datasets to be streamed from cloud storage without having to download entire files. Spatial Temporal Asset Catalog (STAC) provides a standardized way to query cloud-hosted datasets. Combined with QGIS, these technologies allow users to visualize and analyze large datasets which was not possible before.
Dynamic World is a landcover product developed by Google and World Resources Institute (WRI). It is a unique dataset that is designed to make it easy for users to develop locally-relevant landcover classification easily. Contrary to other landcover products which try to classify the pixels into a single class – the Dynamic World (DW) model gives you the the probability of the pixel belonging to each of the 9 different landcover classes. The full dataset contains the DW class probabilities for every Sentinel-2 scene since 2015 having <35% cloud-cover. It is also updated continuously with detections from new Sentinel-2 scenes as soon as they are available. This makes DW ideal for change detection and monitoring applications.
QGIS allows you to define custom Actions on map layers. Actions can launch commands or run python code when the user clicks on a feature from the layer. This workshop will cover QGIS Actions in detail along with use cases on how you can harness its power to automate GIS workflows. We will focus on Python Actions and go through various examples of implementing new functionality and automating tasks with just a few lines of PyQGIS code.
This workshop requires prior knowledge of Python and familiarity with PyQGIS API.
This 5-hour hands-on workshop is designed to help participants learn the basics of the Google Earth Engine platform. This beginner-friendly class covers a range of topics to help participants get comfortable with the Code Editor environment and the Google Earth Engine API to implement remote sensing workflows. During the workshop, you will learn how to load, filter, analyze, and export datasets from the Earth Engine Data Catalog. The workshop also covers Map/Reduce programming concepts so you can scale your analysis to large regions and work with time-series data.
This is an advanced-level course that is suited for participants who are familiar with the Google Earth Engine API and want to learn advanced data processing techniques and understand the inner-workings in Earth Engine.
This workshop focuses on techniques for automation of GIS workflows and covers the Processing Toolbox in detail.
GIS and Remote Sensing plays a critical role in the management of water resources. Many practitioners in this field are constrained by the availability of tools and computing resources to use these techniques effectively. Recent advances in cloud computing technology have given rise to platforms such as Google Earth Engine, which provide free access to a large pool of computational resources and datasets. The course is designed for researchers in the water sector, academicians, water managers, and stakeholders with basic knowledge of Remote Sensing. It will enable them to leverage this platform for water resource management applications.
Crowd-Sourced Climate Change and Health Educational Resources Collection Submission Form
Do you have a resource you’d like to share with the community in this educational resource collection? Please fill out the submission form below.
Your entry will be checked to ensure the content is appropriate, but will not be assessed for accuracy or completeness, and no other quality checks will be done.
If you have a dataset you’d like to share with the community, think about posting it to the CAFE collection on Dataverse!
Please fill out the form to add a resource you think might be helpful for the climate change and health community of practice.
The type of resources that should be shared here are one of the following:
- Book or reference text (e.g. textbook or guidebook on best practices or other essential knowledge)
- Code repository (e.g. a GitHub code bank of an existing analysis)
- Online code tutorial or vignette (e.g. a walkthrough of specific code or methods with examples and explanations)
- Online course (e.g. a series of learning objectives with content and assessment)
- Video or recorded webinar (e.g. educational resources presented in video format)
