Summary of Field Data Collection Ordway- Swisher Biological Station (OSBS) Sept. 30, Oct. 1, 2 and 3; 2016

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1 Summary of Field Data Collection Ordway- Swisher Biological Station (OSBS) Sept. 30, Oct. 1, 2 and 3; 2016 Professor Paul Gader, Computer and Information Sciences and Engineering Engineering School of Sustainable Infrastructure and Environment University of Florida Susan Meerdink and Erin Wetherley Geography UC Santa Barbara OSBS is a University of Florida Research Station that serves as a core NEON site. Previous NEON AOPs were conducted at OSBS in 2010 and in A NEON AOP was also conducted at OSBS Sept. 23 Oct. 26, This report describes spectral and RGB image data acquired on the ground over a 4- day period during the 2016 NEON AOP. Fri. Sep. 23 Sat. Sept. 24 Sun. Sept. 25 Mon. Sept. 26 Botanist IDs Field Spectra NEON Flight over OSBS Field Spectra Understory Distributions Field Spectra Understory Distributions Understory Distributions The collection was organized by Paul Gader. He was assisted by two Ph.D. students from Professor Dar Roberts lab at UC Santa Barbara. They had recently collected time series field spectrometer data from coastal grasslands in Santa Barbara for Dr. Gader and developed an efficient protocol. The team was also assisted by Dr. W. Mark Whitten, a research biologist at the Florida Museum of Natural History and Yuxi Gao, a Forestry student advised by UF Professor Stephanie Bohlmann. Dr. Whitten identified vegetation to the species level and Yuxi Gao provided general assistance. The intent was to gather data for studying the health of Sandhill Forests, the predominant ecosystem at OSBS. This ecosystem depends on frequent fires but most Sandhill Forests throughout the southeast have experienced fire suppression. The distribution of vegetation in the understory is a good indicator of health. A Sandhill Forest that has experienced frequent burns will have an understory that mainly consists of wiregrass (Aristida stricta), small Turkey Oaks (Quercus laevis), exposed sandy soil, leaf litter from Oak and Pine. The Sandhill Forest ecosystem experienced a 98 percent decline in acreage throughout its range. It is considered critically endangered. From 1936 to 1995, Florida experienced a 90 percent decline in longleaf pinelands due to conversion to pine plantations, development, and agriculture [1]. The Longleaf Pine (Pinus palustris) in such a forest are relatively sparse so quite a bit of understory is exposed and not directly below the needles of the trees. However, multiple reflections from the needles in the trees, and perhaps the bark itself, can influence the signature of the understory.

2 Data were therefore collected from vegetation and non- vegetation materials typical of a healthy understory. The experiment that would use these data involves designing and assessing algorithms for estimating the percentage of these materials in a Sandhill Pine Forest. Most of the materials in the understory are smaller than a pixel so these algorithms will require spectral unmixing. Two types of data were collected: (1) Field Spectra & RGB Images and (2) Framed RGB Images. They are described below. (1) Field Spectra & RGB Images were collected over 14 types of materials. The materials are named in Table 1 and spectra are depicted in Fig Some photos are shown in Fig. 4 and 5. Eight types of photosynthetic vegetation (PV) were sampled. Some wiregrass spectra were collected far from tall trees to obtain spectra with no chance of multiple reflections from trees. Table 1. Materials used for Field Collections Common Name Scientific Name Wiregrass Aristida stricta Wiregrass No Pine Reflection Aristida stricta Dog Fennel Eupatorium capillifolium Gopher Apple Licania michauxii Turkey Oak Quercus laevis Goats Rue Tephrosia virginiana Long Leaf Pine Pinus palustris Persimmon Dispyros virginiana Road Brown Sand White Sand Sand and Litter Litter An Canon SX50 HS camera and the pistol- grip optics of the ASD Field- Spec 4 spectrometer were simultaneously mounted on a tripod which was configured so that the camera and spectrometer optics were extended in front of the tripod and were oriented to collect data looking straight down. Camera Spectrometer Optics Figure 1. Depiction of Field Spectra Collection Setup Each location that spectra were acquired was assigned a unique code. At each location that spectra were collected, two images and 5 spectra were collected. One image was acquired with the

3 handwritten code visible and one without the handwritten code. More specifically, the following protocol was followed: 1. The tripod was positioned over the material of interest. 2. The tripod was manipulated to ensure that the spectrometer and camera were level, as measured by small levels. 3. Five spectra were acquired. 4. The paper with the handwritten code was inserted into the field of view. 5. An RGB image was acquired. 6. The handwritten code was removed from the field of view. 7. An RGB image was acquired. 8. The distance from the spectrometer optic to the ground was measured. 9. The distance from the spectrometer optic to the top of the vegetation as measured. Some example spectra are shown below: Figure 1. Field Spectra of non- vegetation. From left to right, top to bottom: Road, Brown Sand, Sand Mixed with Leaf Litter, Leaf Litter, and Sand.

4 Figure 2. Field Spectra of Vegetation, except wiregrass. From left to right, top to bottom: Long Leaf Pine, Dog Fennel, Gopher Apple, Turkey Oak, Goats Rue, Persimmon. Note that there is one anomalous spectrum labeled Licania michauxi, which is probably sand. Figure 3. Wiregrass field spectr compared to longleaf pine spectra. Pictures of typical examples of the vegetation investigated in these experiments follow.

5 Wiregrass (Aristida stricta) Turkey Oak (Quercus laevis) Gopher Apple (Licania michauxii) Long Leaf Pine (Pinus palustris) Persimmon (Dispyros virginiana) Goats Rue (Tephrosia virginiana) Framed RGB Images: Distributions of Understory Materials. The purpose of estimating the distributions of understory materials was to serve as test data for evaluating the percentage of understory materials in a region of a sandhill forest. RGB images of understory were collected over approximately 176m 2 divided into two 4.2m x 21m plots. The plots were divided into 4 rows x 20 columns = 80 locations to be imaged. Each rows is referred to as a transect. Each area that was imaged contained a square wooden, white frame that with internal size of approximately 1.05m x 1.05m. At each location, the percentage area of each understory type inside the frame was estimated by consensus between Gader, Meerdink, and Wetherley. Some examples of are shown below.

6 Examples of the transects are shown below. References. [1] "Guide to the Natural Communities of Florida", Florida Natural Areas Inventory, Florida Department of Environmental Protection (FDEP), Division of State Lands, State of Florida.