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.
Climate change threatens individual and community health, as well as healthcare delivery, with rising morbidity and mortality from extreme heat and disease, and risks to infrastructure from extreme events. EcoAdapt, with the Natural Resources Defense Council, assessed climate adaptation planning for public health in 16 U.S. states. Objectives included assessing public health officials’ understanding, documenting activities, creating case studies, and sharing resources on CAKE. States were categorized by presence of statewide and/or public health climate plans. Most state health department efforts focused on capacity building, environmental monitoring, vulnerability assessments, public outreach, and collaboration. Eighteen case studies illustrate how practitioners are integrating climate change into public health.
This resource introduces the field of spatio-temporal statistics within the context of the modern "big data" era, emphasizing the growing need to analyze data that varies across space and time. While traditional work in this area was highly technical, the book aims to offer a more accessible introduction through practical examples and R Labs at the end of each chapter. It is geared toward readers with a foundational understanding of statistics, particularly those familiar with probability, inference, and matrix algebra. Overall, the book fills a gap by making spatio-temporal data analysis more approachable for students and applied researchers.
This book describes how Earth's climate is changing, how it has been changing in the recent geological past and how it may change in the future. It covers the physical sciences that build the foundations of our current understanding of global climate change such as radiation, Earth's energy balance, the greenhouse effect and the carbon cycle. Both natural and human causes for climate change are discussed. Impacts of climate change on natural and human systems are summarized. Ethical and economical aspects of human-caused climate change and solutions are presented.
Now as we know the basics of Python programming we are ready to apply those skills to different GIS related tasks. During the next seven weeks this course will teach how to deal with spatial data and analyze it using “pure” Python.
This resource includes open-source slide decks from UMN Climate Change and Health Curriculum. This slide deck contains good introductory material regarding specific climate change issues and their impacts on the physical, social, and mental health of the general population and specific demographics.
The Geo-Python course teaches you the basic concepts of programming and scientific data analysis using the Python programming language in a format that is easy to learn and understand (no previous programming experience required). Each lesson is a tutorial with specific topic(s) where the aim is to gain skills and understanding how to solve common data-related tasks using Python. Geo-Python is jointly organized by the Master’s Program in Geography and the Bachelor’s Program in Geoscience at the University of Helsinki.
Introducing the geemap Python package for interactive mapping with Google Earth Engine and ipyleaflet. More information about the geemap package can be found at https://geemap.org
This book introduces and explains the concepts underlying spatial data: points, lines, polygons, rasters, coverages, geometry attributes, data cubes, reference systems, as well as higher-level concepts including how attributes relate to geometries and how this affects analysis. The relationship of attributes to geometries is known as support, and changing support also changes the characteristics of attributes. Some data generation processes are continuous in space, and may be observed everywhere. Others are discrete, observed in tesselated containers. In modern spatial data analysis, tesellated methods are often used for all data, extending across the legacy partition into point process, geostatistical and lattice models. It is support (and the understanding of support) that underlies the importance of spatial representation. The book aims at data scientists who want to get a grip on using spatial data in their analysis. To exemplify how to do things, it uses R. In future editions we hope to extend this with examples using Python and Julia.
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)
