Projects
I have had the privilege to work on projects with NOAA, NASA, USFWS, and USGS in several interdisciplinary teams looking at data from Maryland, Maine, and Australia. Below are brief descriptions and findings of these projects; please click on the photos to read more.
Double-crested cormorant colony. Image taken with federal permission and by a licensed UAV pilot, Meredith Lewis.
Partners: U.S. Geological Survey, U.S. Fish and Wildlife, Maine Department of Inland Fish and Wildlife, UMaine School of Computing and Information Science, UMaine Software Agents & Artificial Intelligence Laboratory
An Interdisciplinary Approach to Building Data Literacy in Wildlife Survey Technologies
My MSc thesis contributes to a larger project based in increasing interdisciplinary research among graduate students and research professionals. As a case study, we are assessing the feasibility of using Unoccupied Aerial Vehicles (UAVs) to survey and monitor nesting colonial birds in Maine as well as avenues for artificial intelligence in enhancing interpretation. We are working with wildlife ecologists and computer scientists to develop protocols and technology for UAV-based imagery collection and interpretation.
Associated publications:
Turner, R. M., Loftin, C. S., Revello, A., Kline, L. R., Lewis, M. A., & Yasaei Sekeh, S. 2021. Context-dependent deep learning. Modeling and Using Context. CONTEXT-21 special issue. https://www.openscience.fr/Context-Dependent-Deep-Learning.
​
​
Understanding Vessel Presence in Australian Marine Parks
Between Jan and Aug 2019, I worked as a contractor for NOAA NEFSC in passive acoustics monitoring. In collaboration with Parks Australia, our team analyzed acoustic data for vessel presence across several deployments in Marine Protected Areas. We found that vessel operators tended to adhere to no-fishing policies, and suspected perpetrators entered protected areas at predictable times. The project informed Parks Australia's patrol habits moving forward, and the project is ongoing at NOAA NEFSC.
Passive acoustic monitoring schematic designed by NOAA.
Partners: NOAA NEFSC Passive Acoustics Research Group, Parks Australia
Associated publications:
​
Kline, L. R., DeAngelis, A. I., McBride, C., Rodgers, G. G., Rowell, T. J., Smith, J., Stanley, J., Read, A. D., & Van Parijs, S. M. 2020. Sleuthing with sound: Understanding vessel activity in marine protected areas using passive acoustic monitoring. Marine Policy. https://doi.org/10.1016/j.marpol.2020.104138.
Operational Analysis of Winter Cover Crop Environmental Performance throughout the State of Maryland
I served as the NASA DEVELOP project lead for the second component of this project, during which we developed a program based in Google Earth Engine for assessing cover crop performance in Maryland. We developed code that integrated work from a previous term so that our partners could interact with a graphical user interface to calculate NDVI and biomass of cover crop fields. This program is used to inform the USDA and Maryland Department of Agriculture of premature termination of important cover crops that prevent nutrient runoff into the Chesapeake Bay.
Partners: Maryland Department of Agriculture, U. S. Geological Survey, U.S. Department of Agriculture, U.S. Environmental Protection Agency, National Aeronautic and Space Administration
Associated publications:
​
Peredo, J., Wayman, C., Whong, B., Thieme, A., Kline, L. R., Yadav, S., Eder, B., Lenske, V., Portillo, D., McCartney, S., Fitz, J., Oddo, P., Keppler, J., Hively, D., Bolten, J., McCarty, G., & Lyon, A. 2020. Utilizing Landsat and Sentinel-2 to Remotely Monitor and Evaluate the Performance of Winter Cover Crops Throughout Maryland. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. Volume XLII-3/W11, 2020 PECORA 21/ISRSE 38 Joint Meeting, 6-1 October 2019, Baltimore, MD, USA. https://doi.org/10.5194/isprs-archives-XLII-3-W11-125-2020.