Kelly is interested in protected land conservation, climate change, and historical ecology. Global climate change and associated increases in the frequency and severity of disturbance events (e.g. flood, fire and disease) will play a defining role in the future of California’s landscapes. Historical data can help inform ranges of variability, thresholds, and triggers that influence the outcome of today’s landscapes. Such research is critical to helping land managers maintain resilient landscapes and better prepare for the future. My research proposes to use historical vegetation maps and field data from the Wieslander Vegetation Type Mapping project in concert with modern resurveys and remotely sensed classified vegetation maps.
Jenny is interested in GIS technologies, land use and land cover change analysis, and spatial planning of multi-use landscapes. Jenny is co-advised withMatthew Potts. I spend much of my time writing scripts to geoprocess spatial data in Python and R as well as administering PostgreSQL databases (with and without PostGIS). My dissertation focuses on understanding how landscapes within National Park Service (NPS) units in the Pacific West Region are influenced by surrounding areas. There are many spatial datasets critical to understanding these dynamics, including access (e.g., roads and trails entering park units), adjacent landownership and land use (e.g., public/private, size), adjacent population dynamics and social-economic characteristics, and biogeographic characteristics of the parks.
Christine comes to us from the Cal Academy, and has research and management experience in East Africa. She is interested in using an integrated approach to human-wildlife conflict analysis, including spatial analyses, behavioral ecology, and stakeholder input, to determine best practices for community-based human-wildlife conflict mitigation in wildlife dispersal areas in East Africa. Christine is also part of the first cohort of students in the new NSF-funded project on campus Data Science for the 21st Century: Environment and Society (DS421).
Stefania Di Tommaso
Stefania has a Master’s degree in Telecommunications Engineering (Politecnico di Bari), where she worked on change detection techniques using SAR data. She also has a Post Master degreecourse in satellite remote sensing technologies. She was working with us on the wetland carbon capture project, and she has worked on the SNAMP project, and she is now working on the carbon project.
Proxima DasMohapatra is joining us for the spring semester to work on our IGIS Dark Data project with Kelly, Sean and Shane. She is a graduate student at the School of Information. Prior to joining grad school, she worked as a technology analyst in India. At the I School, she is interested in data analytics and the various domains in which data is heavily used on a daily basis to garner insights and foster growth. Outside of school, she likes to paint, play table tennis and read up about Greek and Roman gods. She is really excited to be a part of the team this semester, and looking forward to working with each one in the team!
Ovidiu Csillik is a fully funded second year PhD student at the Doctoral College, GIScience of the University of Salzburg, Austria. His PhD research topic is related to Efficient image segmentation techniques for remote sensing data. His educational background includes a Bachelor’s degree in Geography and a Master’s degree in Geographic Information Systems (GIS), both acquired at Department of Geography, West University of Timisoara, Romania. During his Master degree and afterwards, Ovidiu developed good research skills in the field of Object-based image analysis (OBIA), in which he had done his Master thesis (automated comparison of two object-based classified models) and he is a co-author of an article published in ISPRS Journal of Photogrammetry and Remote Sensing. Besides OBIA, Ovidiu also developed skills in GIS, programming, statistics and geomorphometry, publishing an article in Geomorphology. He had also been involved in teaching, research projects and business. The most recent research is related to improving the speed of image segmentation and satellite image time-series analysis for crop mapping using object-based image analysis.