Colleagues - The deadline for the 2018 Data Institute on Remote Sensing with Reproducible Methods is fast approaching: March 20, 2018
Are you interested in working with remote sensing data to address science questions? Do you work in Python, yet haven’t worked with tools including GitHub or Jupyter Notebooks? If so, applying for the 2018 NEON Data Institute on Remote Sensing with Reproducible Workflows in Python! The Institute will take place July 9-14, 2017 at NEON Headquarters in Boulder, CO. More information about the event and the application process is on the NEON website: http://bit.ly/NEON-DI18app-ecolog This Data Institute is designed to teach skills and foundational knowledge for graduate students and early career scientists working with heterogeneous spatio-temporal data to address ecological questions. 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. The cost of the course is $650 which includes all instruction and lunches during the course. A limited number of tuition scholarships are available for graduate students and post-doctoral researchers. Applications are due March 20, 2018. Thank you, Megan -- Megan A. Jones, PhD Staff Scientist & Science Educator National Ecological Observatory Network (NEON) 720.921.2618 [email protected]<mailto:[email protected]> For tutorials and resources on working with ecological data, visit http://www.neonscience.org/resources/data-tutorials.
