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Jul 01 2021
TIDeS Project Seeks Curricular Materials Developers, Deadline July 1
Earth Analytics in Python Course
01 Nov 2019 | Teaching Materials | Contributor(s):
By Leah Wasser1, Jenny Palomino1, Chris Holdgraf2
1. Earth Lab - University of Colorado, Boulder 2. University of California, Berkeley
Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
Get Started With GIS in Open Source Python Workshop
15 Oct 2019 | Teaching Materials | Contributor(s):
By Leah Wasser1, Jenny Palomino1, Joe McGlinchy1
Earth Lab - University of Colorado, Boulder
There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in...
Introduction to Version Control and Git Workshop
By Leah Wasser, Max Joseph
Learn how to use version control with Git to work collaboratively and back up your work.
Writing Clean Code in R Workshop
By Max Joseph1, Leah Wasser
When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.
Introduction to Earth Data Science Textbook
By Jenny Palomino, Leah Wasser
Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior...
Earth Analytics in R Course
By Leah Wasser
Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
Earth Analytics Bootcamp Course
By Jenny Palomino1, Leah Wasser
The Earth Analytics Bootcamp is a three-week introductory-level course taught by instructors in Earth Lab and is a part of the Professional Certificate in Earth Data Analytics - Foundations at CU...
Jonathan Ian Garcia Dator
Measuring the Health of the Earth Using the Theory of Island Biography
25 Oct 2018 | Teaching Materials | Contributor(s):
By Jana Eggleston, Stephanie Renee Campau, Farshid Ahrestani, Holly D Gaff1
Old Dominion University
This module uses a variety of available datasets to explore methods of calculating biodiversity and measuring landscape as well as the relationship between those.
Map Your Hazards! – Assessing Hazards, Vulnerability and Risk
11 Jan 2018 | Teaching Materials | Contributor(s):
By Brittany Brand1, Pamela McMullin-Messier2, Melissa Schlegel3
1. Boise State University 2. Central Washington University 3. College of Western Idaho
The Map Your Hazards module provides students an interactive mechanism to engage in place-based exploration of natural hazards, social vulnerability, risk and the factors that shape their...
Natural Hazards and Risks: Hurricanes
By Lisa Gilbert1, Josh Galster2, Joan Ramage3
1. Williams College 2. Montclair State University 3. Lehigh University
Making the difficult decision to evacuate before a hurricane makes landfall can save lives and property. This two week module explores how hurricanes connect the ocean-atmosphere-terrestrial...
Interactions between Water, Earth’s Surface, and Human Activity
10 Jan 2018 | Teaching Materials | Contributor(s):
By Sue DeBari1, Kyle Gray2, Julie Monet3
1. Western Washington University 2. University of Northern Iowa 3. California State University - Chico
This two-week (~10-hour) module focuses on water and its importance to humans, both as a limited resource and in shaping Earth's surface.
Jul 17 2017
2017 Earth Educators' Rendezvous
Interactions Between Water, Earth's Surface, and Human Activity
out of 5 stars
24 Aug 2015 | | Contributor(s):: Sue Debari, Kyle Gray, Julie Monet
This resource has been updated - find the current version here: https://qubeshub.org/publications/288This module focuses on water and its importance to humans using Google Earth images of stream profiles in different climates, and with real river flooding data sets.