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Quantifying The Drivers and Impacts of Natural Disturbance Events 鈥� The 2013 Colorado Floods
Quantifying The Drivers and Impacts of Natural Disturbance Events 鈥� The 2013 Colorado Floods The 2013 Colorado Front Range Flood Why was the Flooding so Destructive? The St. Vrain River in Boulder County, CO after (left) and before (right) the 2013 鈥� - 3427
Visualize Elevation Changes Caused by the 2013 Colorado Floods using NEON LiDAR Data in R
Visualize Elevation Changes Caused by the 2013 Colorado Floods using NEON LiDAR Data in R This tutorial explains how to visualize digital elevation models derived from LiDAR data in R. The tutorial is part of the Data Activities that can be used with the 鈥� - 3428
Data Activity: Visualize Stream Discharge Data in R to Better Understand the 2013 Colorado Floods
Data Activity: Visualize Stream Discharge Data in R to Better Understand the 2013 Colorado Floods Several factors contributed to the extreme flooding that occurred in Boulder, Colorado in 2013. In this data activity, we explore and visualize the data for 鈥� - 3430
Introduction to Hierarchical Data Format (HDF5) - Using HDFView and R
Introduction to Hierarchical Data Format (HDF5) - Using HDFView and R 鈥� Introduction to Hierarchical Data Format (HDF5) - Using HDFView and 鈥� - 3431
Introduction to Hyperspectral Remote Sensing Data in R
Introduction to Hyperspectral Remote Sensing Data in R 鈥� Introduction to Hyperspectral Remote Sensing Data in R 鈥� - 3432
Introduction to Light Detection and Ranging (LiDAR) in R
Introduction to Light Detection and Ranging (LiDAR) in R 鈥� Introduction to Light Detection and Ranging (LiDAR) in R 鈥� - 3433
Document Your Code with Jupyter Notebooks
Document Your Code with Jupyter Notebooks 鈥� Document Your Code with Jupyter Notebooks 鈥� - 3436
Introduction to Working with Raster Data in R
Introduction to Working with Raster Data in R 鈥� Introduction to Working with Raster Data in R 鈥� - 3438
Introduction to Working With Time Series Data in Text Formats in R
Introduction to Working With Time Series Data in Text Formats in R 鈥� Introduction to Working With Time Series Data in Text Formats in 鈥� - 3439
Document Your Code with R Markdown
Document Your Code with R Markdown 鈥� Document Your Code with R Markdown 鈥� - 3441
Git 07: Updating Your Repo by Setting Up a Remote
Git 07: Updating Your Repo by Setting Up a Remote This tutorial covers how to set up a Central Repo as a remote to your local repo in order to update your local fork with updates. You want to do this every time before starting new edits in your local 鈥� - 3442
Quantifying The Drivers and Impacts of Natural Disturbance Events 鈥� The 2013 Colorado Floods
Teaching Module Quantifying The Drivers and Impacts of Natural Disturbance Events 鈥� The 2013 Colorado Floods Authors: Leah A. Wasser, Megan A. Jones Languages: R This lesson demonstrates ways that society and scientists identify and use data to understand 鈥� - 3443
Assignment: Version Control with GitHub
Assignment: Version Control with GitHub DUE: 21 June 2018 During the NEON Data Institute, you will share the code that you create daily with everyone on the NEONScience/DI-NEON-participants repo. Through this week鈥檚 tutorials, you have learned the basic 鈥� - 3444
Data Management using NEON Small Mammal Data
Teaching Module Data Management using NEON Small Mammal Data Authors: Jim McNeil, Megan A. Jones Teaching Module Overview Undergraduate STEM students are graduating into professions that require them to manage and work with data at many points of a data 鈥� - 3445
Data Management using National Ecological Observatory Network鈥檚 (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis
Data Management using National Ecological Observatory Network鈥檚 (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis 鈥� Data Management using National Ecological Observatory Network鈥檚 (NEON) Small Mammal Data with Accompanying 鈥� - 3446
Using NEON Data and Educational Materials in Your Classroom | LDC 2017
Using NEON Data and Educational Materials in Your Classroom | LDC 2017 鈥� Using NEON Data and Educational Materials in Your Classroom | LDC 鈥� - 3447
NEON Data Education Fellows Faculty Mentoring Network
NEON Data Education Fellows Faculty Mentoring Network Applications are no longer being accepted. This unique networking and professional development opportunity聽is geared towards faculty interested in implementing or adapting existing NEON teaching 鈥� - 3448
CO-Labs tour of NEON
CO-Labs tour of NEON Sign up to join Dan Powers of CO-Labs on a tour of the NEON program! Tour Details: The tour will include presentations on the project as well as glimpses of our calibration/validation labs, flux tower and more. We will end the tour 鈥� - 3449
Work with NEON OS & IS Data - Plant Phenology & Temperature
Work with NEON OS & IS Data - Plant Phenology & Temperature 鈥� Work with NEON OS & IS Data - Plant Phenology & Temperature 鈥� - 3450
Before and After the Hurricanes: NEON Data for Harvey, Irma and Maria
Before and After the Hurricanes: NEON Data for Harvey, Irma and Maria The hurricane season of 2017 has been one for the record books with three major hurricanes making landfall on U.S. states and territories within a four-week period. Hurricanes Harvey, 鈥�