GIS and remote sensing of forested environments
Faculty mentor/Supervisor:
Michael Wing
Email Address:
Department Affiliation:
Forest Engineering Resources & Management
Project Location:
Corvallis with remote locations being possible during Covid
Project Description:
The primary emphasis project will be on a NSF-funded project that is examining climate change impacts on southwestern white pine seedlings in Arizona. The AIS Lab has collected high resolution imagery using unmanned aircraft systems (UAS) from several Arizona locations over four years. The student would be involved in the on-going processing and analysis of these databases using GIS and remote sensing software, including generating Lidar-like point clouds of landscape features. This experience would include experience with a number of geospatial software packages and geoprocessing techniques. These skills should be very attractive to potential future employers.
Describe the type of work and tasks you anticipate the student will perform:
The student’s primary duty will be maintaining and analyzing large robust geospatial datasets. These datasets are primarily Lidar-like point clouds or high-resolution UAS-collected imagery but also include vector and raster layers. The student will process point clouds of the study area to extract seedling metrics including height and stand density. Most of the student work will involve using geospatial software to perform batch operations like clipping, creating terrain models, and extracting pixel values from Lidar and multispectral datasets. PhD student Matt Barker will be the primary mentor in using programming and geospatial analysis techniques to perform operations on the databases. The student will ideally work more independently once familiar with the processing techniques, and the work can be accomplished remotely by logging into one of the AIS Lab machines. Training and mentoring can also be accomplished remotely through Zoom.
Hourly rate of pay:
12
Detail your mentorship plan:
The primary mentors will be PhD student Matt Barker and will interactions will take place remotely. We will introduce the student to geospatial software packages they will use throughout their academic and professional career. The student will leave the project with practical knowledge of ArcGIS, FUSION, lidR, and other packages used for geospatial processing and analysis at the industry level. Through our project, the student will learn the critical role of geomatics in the forest management workflow. By contributing to several collaborative OSU/USFS/NSF research projects, the student will understand how scientists rely on scientific data to support management decisions. Gaining applied experience in GIS, remote sensing, and programming will make the student a desired employee and skilled resource for future hiring managers. The graduate student mentor for this project followed a professional trajectory in interdisciplinary geospatial science and will provide beneficial career and academic advice to the undergraduate student. The AIS lab will provide the student further resources and connections if interested in UAS operations and applied remote sensing research. The student will also experience a collaborative laboratory environment that functions through remote settings and the process that goes into conducting applied research. Mentored employment will allow a student interested in geospatial science to apply their coursework and surround themselves with OSU faculty and students engaged in helping them succeed.