Remote Sensing of Shallow Coastal Benthic Substrates: In situ Spectra and Mapping of Eelgrass (Zostera marina) in the Gulf Islands National Park Reserve of Canada
Abstract
:1. Introduction
- 1.
- Can submerged eelgrass be spectrally distinguished from other submerged substrates? If so, what spectral variables (bands and/or band slopes/ratios) offer the most accurate separation among substrates with the least redundancy?
- 2.
- How effective are these spectral variables for detecting eelgrass in a hyperspectral airborne image?
- 3.
- What is the wavelength-dependent depth limit of eelgrass spectral detection in situ and in the image?
2. Methods
2.1. Study Area
Average | Range | |
---|---|---|
Temperature | 11.5 °C | 11.3–12.2 °C |
Salinity | 29 ppt | 28.9–29.4 ppt |
aCDOM(440) | 0.24 m−1 | 0.18–0.33 m−1 |
TSM | 4.03 g m−3 | 2.25–6.08 g m−3 |
TOC | 47.60% | 32.7–65.3% |
Chl-a | 2.44 mg m−3 | 1.28–7.23 mg m−3 |
2.2. Data Acquisition
Field photo | Common name | Latin name | Abbr. | Above-water spectra (n) |
---|---|---|---|---|
| Eelgrass | Zostera marina | sE dE | 21 shallow 4 deep |
| Green algae: Sea Lettuce | Ulva fenestrata | sAg | 6 shallow 0 deep |
| Green algae: Filamentous | Enteromorpha spp. | sAg | 2 shallow 0 deep |
| Sand | - | sS dS | 6 shallow 3 deep |
| Deep water (>30 m) | - | dW | 7 |
2.3. Data Reduction and Variable Selection
Identifying Major Spectral Variables
Wavelengths | Slope(s) Ratio(r) | Description | Reference |
---|---|---|---|
480, 490 | s,r | Chl blue absorption | This study |
500, 530 | s,r | Green peak: Ascending edge to 530 nm shoulder | This study |
536, 566 | s,r | Greek peak: Ascending edge shoulder to max | This study |
500, 566 | r | Max blue absorption: Max green reflectance | This study |
566, 600 | s,r | Green peak: Descending edge | This study |
620, 640 | s,r | Chl-b & water red absorption: Descending slope | This study |
630, 640 | s,r | Detect diatom epiphytes | This study |
650, 660 | s,r | Chl red absorption: Descending edge | This study |
566, 670 | r | Chl max green reflectance: Max red absorption | [63] (672:550) |
566, 694 | r | Green peak: Sand NIR peak | This study |
566, 710 | r | Green peak: Vegetation NIR peak | [64] |
570, 710 | r | Green peak: Vegetation NIR peak | This study |
670, 700 | s,r | Red edge: Correlated with chlorophyll-a | [65] |
668, 710 | r | Red edge | [66] (RVI) |
690, 710 | r | NIR peak position | [64] |
Variable Selection: M-Statistic and Discriminant Analysis
2.4. Case Study: Classification of Hyperspectral Airborne Image
- Image 1:
- Full spectral resolution above-water image
- Image 1R:
- Reduced variable above-water image (Set 2 from previous)
- Image 2:
- Full spectral resolution water-corrected image
- Image 2R:
- Reduced variable water-corrected image (Set 2 from previous)
Substrate Classes | Substrate Abbr. | Ground-truth Survey Sites | AISA Training/Validation Sites (~20%/80%) |
---|---|---|---|
Shallow Eelgrass | (sE) | 265 | 51/214 |
Deep Eelgrass | (dE) | 19 | 4/15 |
Green Algae | (sAg) | 129* | 24/105 |
Shallow Sand | (sS) | 49 | 10/39 |
Deep Sand | (dS) | 32 | 6/26 |
Brown Algae | (sAb) | 7 | 2/5 |
Exposed Sea Asparagus | (eAsp) | 6 | 2/4 |
3. Results
3.1. Spectral Characteristics of the Benthic Substrates
3.2. Water Correction
3.3. Spectral Variable Selection
Indices
Band | sS | sAg | dE | dS | dW |
---|---|---|---|---|---|
s500-530 | 5.73 | 1.63 | 1.90 | 0.49 | 1.76 |
R'566 | 0.56 | 1.40 | 2.51 | 0.68 | 2.80 |
R'580 | 2.10 | 1.64 | 0.33 | 3.21 | 1.05 |
R'602 | 5.70 | 0.64 | 0.56 | 2.46 | 0.25 |
Band | sS | sAg | sE | dS | dW |
---|---|---|---|---|---|
s500-530 | 11.45 | 2.91 | 1.90 | 4.55 | 0.09 |
R'566 | 1.62 | 0.56 | 2.51 | 1.47 | 1.10 |
R'580 | 3.86 | 2.93 | 0.33 | 6.60 | 2.10 |
R'602 | 8.93 | 1.19 | 0.56 | 4.22 | 0.26 |
Band | sS | sAg |
---|---|---|
566:600 | 0.78 | 1.23 |
3.4. Case Study: Classification of a Hyperspectral Airborne Image
4. Discussion
Can Submerged Eelgrass be spectrally Distinguished from other Submerged Substrates? If so, What Spectral Variables (Bands and/or Band Slopes/Ratios) Offer the Most Accurate Separation among Substrates with the Least Redundancy?
How Effective are these Spectral Variables for Detecting Eelgrass in a Hyperspectral Airborne Image?
What is the Wavelength-Dependent Depth Limit of Eelgrass Detection in situ and in the Image?
5. Conclusions
Acknowledgements
References and Notes
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O’Neill, J.D.; Costa, M.; Sharma, T. Remote Sensing of Shallow Coastal Benthic Substrates: In situ Spectra and Mapping of Eelgrass (Zostera marina) in the Gulf Islands National Park Reserve of Canada. Remote Sens. 2011, 3, 975-1005. https://doi.org/10.3390/rs3050975
O’Neill JD, Costa M, Sharma T. Remote Sensing of Shallow Coastal Benthic Substrates: In situ Spectra and Mapping of Eelgrass (Zostera marina) in the Gulf Islands National Park Reserve of Canada. Remote Sensing. 2011; 3(5):975-1005. https://doi.org/10.3390/rs3050975
Chicago/Turabian StyleO’Neill, Jennifer D., Maycira Costa, and Tara Sharma. 2011. "Remote Sensing of Shallow Coastal Benthic Substrates: In situ Spectra and Mapping of Eelgrass (Zostera marina) in the Gulf Islands National Park Reserve of Canada" Remote Sensing 3, no. 5: 975-1005. https://doi.org/10.3390/rs3050975