Studying Biological Impacts of Environmental Change Using Repeat Photography: Introduction to PhenoCam Data Products and Software Tools

Learn to work with repeat-photography images to study landscape changes. This workshop is a joint effort between the PhenoCam network and the National Ecological Observatory Network (NEON) to share recently developed tools facilitating access to, and analysis of, camera imagery and higher-order data products available through PhenoCam. Learning activities include:

1. data discovery using the PhenoCam API;
2. image processing using the xROI Shiny interface;
3. modeling and data integration in R using the phenor package; and
4. accessing phenological data across networks through Shiny (R).

While this workshop focuses on phenological repeat photography data, repeat-photography analyses have many applications. All disciplines and use-cases are encouraged to attend.

Workshop Objectives

Participants of the workshop will learn how digital repeat photography (e.g., via the PhenoCam network) can advance environmental and ecological studies. By the end of the workshop, participants will understand how recent advancements and developments in image processing using open-source analysis tools can be used to study ecosystem changes in real-time. Predicted outcomes for those who attend this workshop will include the ability to:

1. access and download raw and processed data from the PhenoCam network;
2. extract time-series data from any stack of digital images, including, but not limited to, the images of the PhenoCam network;
3. quantitatively remove data obtained under bad weather conditions (e.g., fog or cloud conditions); and
4. analyze extracted time-series across scales and networks to address environmental questions.

Required Prior Knowledge: Although a significant portion of the material will be interactive using graphical interfaces, there will be live coding sessions in R. So all participants are expected to have a prior knowledge of at least one programming language, and have R, and preferably RStudio, installed on a laptop to participate in all the sections.

Registration Required: This workshop will be taught at the 2018 meeting of the American Geophysical Union (AGU) in Washington D.C. You must be a registered attendee of the conference and register for this workshop with your AGU registration to participate in this workshop. For more information, visit the AGU 2018 annual meeting website. This is AGU Scientific Workshop WS17.   

Workshop Schedule

Location: Lafayette Park/Farragut Square, Grand Hyatt Washington, Washington DC near Walter E. Washington Convention Center

Please double check the conference schedule as rooms can change!

Please note that the schedule listed below may change depending upon the pace of the workshop!

Workshop Instructors

• Bijan Seyednasrollah, Postdoctoral Fellow and PhenoCam Data Scientist at Harvard University/Northern Arizona University
• Katharyn Duffy, Postdoctoral research associate, Northern Arizona University
• Koen Hufkens, Postdoctoral research associate & COBECORE project lead, Ghent University
• Megan A. Jones; @meganahjones, Research Scientist, Science Education; NEON program, Battelle

Please get in touch with the instructors prior to the workshop with any questions.

Twitter?

Please tweet using the hashtags #NEONData & #PhenoCam and tweet @PhenoCam & @NEON_Sci.

Before the Workshop

To participant in this workshop, you will need a laptop and an updated version of R, version 3.4 or later.
It is essential that you update to the most current release of R before you come to the workshop as a number of packages require the updated versions of R. If you use a Mac, your operating system may need to be updated to install the latest R version. There will not be sufficient time at the start of the workshop to complete this install.

Setting Up R & RStudio

Windows R/RStudio Setup

• Download R for Windows here
• Run the .exe file that was just downloaded
• Go to the RStudio Download page
• Under Installers select RStudio X.XX.XXX - Windows Vista/7/8/10
• Double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Mac R/RStudio Setup

• Go to CRAN and click on Download R for (Mac) OS X
• Select the .pkg file for the version of OS X that you have and the file will download.
• Double click on the file that was downloaded and R will install
• Go to the RStudio Download page
• Under Installers select RStudio 0.98.1103 - Mac OS X XX.X (64-bit) to download it.
• Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Linux R/RStudio Setup

• R is available through most Linux package managers. You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R).
• To install RStudio, go to the RStudio Download page
• Under Installers select the version for your distribution.
• Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Install R Packages

We will require a number of packages to interact with imagery and data. You must run the following code *before you come to the workshop**, as some packages take quite a while to download and install. If any of the packages fail that’s fine! Email the instructors or just come a little early to the workshop and we will help you debug.

 install.packages('rgdal')
 utils::install.packages('devtools', repos = "http://cran.us.r-project.org" )
 install.packages('hazer')
 install.packages('jpeg')
 install.packages('lubridate')
 install.packages('hazer')
 install.packages('data.table')
 install.packages('phenocamapi')
   install.packages('phenocamr')
 install.packages('xROI')
 devtools::install_github('khufkens/phenor')
 install.packages('daymetr')
 install.packages('tidyverse')
 install.packages('shiny')
 install.packages('xaringan')
 install.packages('maps')
 install.packages('raster')
 install.packages('sp')

Update R Packages

In RStudio, you can go to Tools --> Check for package updates to update previously installed packages on your computer.

Or you can use update.packages() to update all packages that are installed in R automatically.

More on Packages in R