Remote Sensing with Reproducible Workflows in Python: Data Institute Application deadline

When: March 20, 2018
Location: 1685 38th St, Suite 100, Boulder, CO

Applications Now Open for NEON’s 2018 Data Institute: Remote Sensing with Reproducible Workflows in Python

This Data Institute provides a unique opportunity for participants to gain hands-on experience working with openly available NEON data using well-documented, reproducible methods using Python. Participants will also gain important applied knowledge about using heterogeneous remote sensing data sources to address spatio-temporal ecological research questions.

Important Dates

  • Applications are due by March 20, 2018
  • Payment due late April 2018
  • Online, pre-institute materials (1-5 hrs/week): June 1 to July 5, 2018
  • In-person institute in Boulder, CO: July 9-14, 2018

2018 Theme: Remote Sensing with Reproducible Workflows in Python

Through data intensive live-coding, short presentations, and small group work, we will cover:

  • Background theoretical concepts related to LiDAR and hyperspectral remote sensing
  • Fundamental concepts required to ingest, visualize, process, and analyze NEON hyperspectral and LiDAR data.
  • Best practices on reproducible research workflows: the importance of documentation, organization, version control, and automation.
  • Scientific spatio-temporal applications of remote sensing data using open-source tools, namely Python and Jupyter Notebooks.
  • Machine learning for prediction of biophysical variables such as above-ground biomass using NEON LiDAR and ground measurements.
  • Classification of hyperspectral data using deep-learning approaches.
  • Using remote sensing data products with in situ data to quantify uncertainty associated with remote sensing observations.

You can view the 2017 Data Institute for sample materials.  The primary additions to the 2018 Data Institute will include more details on biomass calculations and hyperspectral image classification.  

A deep dive into NEON’s Remote Sensing Data

During the course, participants will work with hyperspectral, lidar and RGB camera data collected by NEON’s Airborne Observation Platform (AOP). Students will have direct access to NEON’s science staff responsible for the collection, algorithm development and production of NEON AOP data. Workshop lessons will focus on how to efficiently utilize NEON AOP data for scientific applications and how common remote sensing processing methods will impact data quality. Additionally, participants will tour the NEON calibration facilities to gain a deeper understanding of the importance of calibration to reduce data uncertainty during collection and processing.

Who should apply

This Data Institute is geared towards graduate students and early career scientists who have some programming and remote sensing experience and want to develop critical skills and foundational knowledge for working with heterogeneous spatio-temporal data to address ecological questions. Qualified applicants are required to have some prior basic experience in the Python programming environment (or experience in another programming environment and willing to learn basic Python prior to Institute). All participants must bring their own laptop to participate in the hands-on data activities.

Location & Tuition

  • The Institute will take place at Battelle office/NEON headquarters in Boulder, CO from July 9-14, 2018.
  • The cost of the Institute is $650 and includes 6 days of instruction, lunches, and coffee/snacks. A limited number of tuition scholarships are available for graduate students and post-doctoral researchers. 
  • The application primarily consists of answering multiple choice questions pertaining to your background using different data and tools in addition to a short statement of why you want to participate in the Data Institute.
  • If you opt to apply for the scholarship, an additional short statement on why this course will further your career goals is required. 

The application is now closed. If you are interested in the Institute, but missed the application period, please contact us

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