Field work using spatial data can be a very overwhelming process to start figuring out without guidance from people with experience. As an undergraduate student, I have been very fortunate to be part of forest biogeography and forestry field work in multiple places studying several aspects of forests. In these experiences I have helped create multiple kinds of spatial data using different methods of data collection and equipment. In this blog post I will talk more about the field work experiences that I have had and what it has been like to go from the field to creating data to making spatial data to be studied. I will also share the resources that the Donald W. Hamer Center for Maps and Geospatial Information has, and how they can enable library patrons to do field work of their own and create spatial data.
My first field work experience was working with Dr. Alan Taylor, a professor in the geography department, in which we studied forest fire effects in Lassen Volcanic National Park in Northern California. The research we were conducting was a continuation of fire effects studies that the professor has been sampling annually for decades in this area. The professor joined us for the first 10 days of the field work and then the rest of the sampling was done by one graduate student and the undergraduates’ students including myself. We conducted this research for 7 weeks over the summer of 2022 and sampled 3 kinds of plots both inside the park and in a nearby experimental forest. This field work required us to camp for the entire 7 weeks and to do two 3-to-4-day backpacking trips into the back country of the park in remote areas. This experience was extremely important to my college experience and has helped shape my path as a geographer and environmental researcher.
Dr. Taylor (in the red) teaching us how to preform plot surveys.
The methods of sampling that we did for the research were random plot sampling. We did this sampling using environmental conditions for the two plots we placed within the park boundary. The other plots we sampled are two one-hectare areas within the experimental forest that were subdivided into grids. In these plots each tree was identified and sampled for several characteristics. To find the plots within the national park, we used handheld GPS units that directed us to the latitude and longitude of the plot centers for the plots within the national park. The accuracy of the GPS units could only get us within 10 feet of the plot center, so we used photography and plot data taken in previous years to align ourselves with the exact plot center. For the experimental forest plots, we only needed to use the handheld GPS to locate the corner of the plots. Once we found the corner of the plots, we used the wooden stakes placed there in the past to help mark out the spacing of the grid of the plot to ensure that we repeated the sampling the same way that it had been done in the past.
A view of Mount Lassen from a charred forest during work.
To make this data spatial and able to be used in a GIS environment we took the data collected in the field back to the lab here and Penn State and entered the locations of each plot and the associated data on the forest that was collected with them. For the randomly placed plots we only had to plug in the coordinates of the plot centers and then include the observations like number and size of trees, burn severity, percentage of shrub, grass and forb cover in addition to some other data.
My second fieldwork experience was with a new lab in the forestry department under the supervision of Dr. Tong Qiu. The work I conducted for this project was to help build and place seed traps to study how environmental conditions affected the reproduction of trees and how many seeds they produce and how they disperse those seeds. This research was conducted on Penn State property in the Stone Valley Forest area near Shavers Creek Environmental Center. During this same summer, I studied to earn my FAA part 107 drone license to begin learning how to use drones to create local spatial data. Overall, I spent 2-3 weeks creating the seed traps and surveying the points where I placed them in the stone valley forest. Then I spent the rest of the summer studying for the drone exam and spending one day per week doing a resurvey of multiple characteristics of each tree within the plots. The characteristics included diameter at breast height (DBH), canopy status, number of seeds on each tree etc.
Installing seed traps with fellow student coworker Evan Hackett from the Forestry Department.
To create the seed trap study areas, we used 4 1-acre plots that had already been tagged and had each species of tree identified. These plots also had spatial data that had all the information about each tree and their locations. In these 4 plots I built and randomly distributed 10 traps that capture the seeds of the various trees within the plots. After all the seed traps were placed, I returned to each of them with a survey grade GPS that I borrowed from the Donald W. Hamer Center for Maps and Geospatial Information. Using this GPS and the ESRI app Field Maps I created high accuracy spatial data for the exact location of each of the traps. Using the exact location of the trees and seed traps, we can study the phenology of these trees in the future. This project is still ongoing and will require multiple years to capture the seeds multiple times to then collect and study them.
I also made use of the ESRI field maps app when resurveying the trees from the 4 plots that we were using to ensure I had the right trees. Using the approximate location, the species and associated information, I ensured that I was sampling the same tree with new information showing the growth and development of each tree. I did not finish my sample of these trees because I was working alone and there are 1,400 to be sampled. This project is ongoing, but my involvement has diminished because I am busy with classes and new projects.
Bad Elf Flex Survey GPS used to create spatial data in Field Maps app.
Finally, I am working on a new project that involves field work for my final semester of college. This work is with Dr. Patrick Drohan, a soil science professor in the college of Ecosystem Science and Management. In this project I will go into the field to create spatial data for agricultural nutrient runoff modeling. I will be creating this spatial data by flying a drone with high resolution cameras and multispectral cameras. From the images created with the drone I will use a computer software called Agisoft Metashape to assemble the images into one GIS imagery data layer. Then I will create a terrain model using this data layer by utilizing a technique called photogrammetry. After I create the data other researchers will take over the modeling of nutrient runoff. The end goal of the project is to understand how effective riparian buffers are at mitigating agricultural nutrient runoff.
Fin learning to fly a new drone at the PSU student farm.
These are some of the ways I contributed to the creation of spatial data from research conducted in the field. This is the kind of work I enjoy most because I can work outdoors while still utilizing technical and scientific knowledge. Some things I want to highlight again for anyone who might want to create their own spatial data are:
- ESRI ArcGIS Field Maps. This app integrates very well with other ESRI software’s and makes field-based data collection very easy. Everyone at Penn State has access to these softwares.
- The mapping resources available to be loaned from the Donald W. Hamer Center for Maps and Geospatial Information. The Bad elf Flex GPS unit was essential for me to create high accuracy spatial data and it integrates very easily with the Field Maps app.
- Field based research is hard. It takes lots of time to plan and prepare to ensure you are using your time effectively. Other experiences researchers are the best resources for figuring out how to get started on your own spatial data collection.
To read more about the GPS resources that the Donald W. Hamer Center for Maps and Geospatial Information has available to borrow read here.
To learn more in detail about the process of creating spatial data using the Field Maps app see this blog post.
Fin is a fourth-year student at Penn State majoring in Geography and minoring in Soil Science. Fin has had multiple lab research positions where he has contributed to creating spatial data for forest biogeography and forestry research. Fin’s other interests include using drones to collect geospatial data, competing with the PSU soil Judging team and spending time outdoors. Fin has been working at the Donald W. Hamer Center for Maps and Geospatial Information since February 2022.
