Kelp forests are highly productive three-dimensional marine ecosystems that provide valuable ecosystem services globally. Along the coast of British Columbia, Macrocystis pyrifera and Nereocystis luetkeana are two key species that form surface-canopies that are vulnerable to both biotic and abiotic drivers; making it imperative to monitor and understand whether these ecosystems are changing in the face of climate change. The monitoring of kelp forests is commonly enhanced by use of remote sensing, which allows researchers to survey large portions of the coast where it would otherwise be difficult to collect data, and to use archived imagery for comparisons of historic and contemporary kelp forest trends. Generally, the remote sensing of kelp surface-canopy relies on differences in the high near-infrared (NIR; 700-1000 nm) signal of kelp and the low NIR signal of water. However, kelp surface-canopy reflectance signals can be affected by submergence under water, caused by oceanographic features like tides and currents, or simply due to differences in the morphology and buoyancy of kelp canopy structures. This submersion may cause uncertainties when estimating the surface-canopy area of kelp beds in remote sensing imagery. This research aims to understand the effects of submersion on the remote sensing of kelp surface-canopy. To address our goal, (i) Nereocystis canopy structures (bulb and blade) were submerged while collecting above-water hyperspectral measurements. The hyperspectral data into the bandwidths of high-resolution multispectral aerial and space-borne sensors and vegetation indices were calculated to understand the kelp detection limits when using shorter red-edge wavelengths (RE; 690-750 nm) instead of the longer NIR wavelengths. The results showed that submerged kelp can be detected deeper in the water column using shorter RE wavelengths compared to the more commonly used NIR wavelengths. Further, (ii) in situ hyperspectral data were also collected for the different surface-canopy structures and compared with UAV imagery, which showed that the buoyancy of the kelp canopy structures at the surface affected the relative magnitude of reflectance in both the RE and NIR and supported the findings of the submersion experiment. The total surface-canopy area derived from classification with both RE and NIR vegetation indices were compared in the UAV imagery, and the RE index detected roughly 18% more kelp than the NIR index, with no differences seen between Macrocystis and Nereocystis, or between high and low tide in beds larger than 150m2. Finally, (iii) to understand how submersion by tides and currents affect the ability to estimate surface-canopy area for both Macrocystis and Nereocystis, surface-canopy area was derived from multispectral unoccupied aerial vehicle (UAV) imagery and compared with in situ tide and current data, which showed that surface-canopy area had a strong negative linear relationship with tidal height at all sites regardless of species. Macrocystis occupied sites where currents were low (<10cm/s) and did not affect the surface-canopy. Therefore, the extent of all Macrocystis beds decreased at a similar rate over their tidal range (22.7 + 2.8%/m). Nereocystis beds occupied a wider range of current speeds (0.0 - 19.0 cm/s), and at sites with high current speeds (> 10 cm/s) increasing current and tidal height decreased surface-canopy area simultaneously, resulting in both a higher and more variable rate of decrease (30.5 + 9.1%/m) with increasing tidal height than Macrocystis. Together, this thesis addressed critical questions related to the effects of kelp submersion on the remote sensing of surface-canopy forming kelps, and we provide recommendation for remote sensors who wish to minimize errors when using remote sensing to map kelp forests. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/14087 |
| Date | 05 August 2022 |
| Creators | Timmer, Brian |
| Contributors | Costa, Maycira, Juanes, Francis |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | Available to the World Wide Web |
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