NASA Internship - Remote Sensing
Title: Exploring land cover dynamics with high resolution data and high end computing Type: Internship Session: Summer 2019 Center: Goddard Space Flight Center Building: 33 Room: G415 Description: NASA currently hosts over six Petabytes of very high-resolution (VHR) data (< 5 m spatial resolution) in high end computing environments. Complicated data formats and the sheer volume of data have limited the exploitation of these datasets. Recent work has been done to develop an automated search/discovery and pre-processing tool to generate analysis ready (ortho-rectified, top of atmosphere corrected, geotiff format) data from the VHR data with an Application Program Interface (API). We propose to have a student exercise this API tool to generate data for several regions, evaluate the results and generate land cover dynamics (including land cover change, and canopy height/cover dynamics) using machine learning approaches in a high-end computing environment. The student will use the API and other tools developed by the PI as well as open source software (Python, R, gdal) in the Advanced Data Analytics Platform (a super computing environment hosted at NASA GSFC) to process imagery and develop information about ecosystem dynamics. The results of this work will provide direct feedback to improve the API tools developed by the PI and will afford the student the opportunity to gain experience with both VHR data and high end computing. Computer/Software Skills: Operational knowledge of linux operating systems and course work in ecology, remote sensing, image processing and image interpretation. Programming experience with R, Python and gdal and/or experience with manipulating large datasets on large computational clusters. Technical Skills: Basic remote sensing theory is required coupled with programming to manipulate and write algorithms to process large datasets. Academic Level(s): College Junior;College Senior;Master's;Doctorate Major(s): Computer and Information Sciences - Computer Programming; Computer and Information Sciences - Computer Science; Computer and Information Sciences - Data Processing; Computer and Information Sciences - Information Science/Studies; Multi-disciplinary - Biological and Physical Sciences; Multi-disciplinary - Mathematics and Computer Science; Multi-disciplinary - Natural Sciences; Physical Science - Geological and Earth Science/Geosciences; Social Science - Geography and CartographyMission directorate(s) directly benefiting from the tasks involved in this internship: Science Mission
