Use of Landsat Imagery Time-Series and Random Forests Classifier to Reconstruct Eelgrass Bed Distribution Maps in Eeyou Istchee
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Image Selection and Acquisition
2.3. Ground-Truth and Validation Data
2.4. Bathymetric Data
2.5. Input Features
2.6. Model Training Data
2.7. Random Forests Image Classification
2.8. Postprocessing
2.9. Accuracy Assessment
2.10. Comparison to Aerial Photos
3. Results
3.1. Spectral Separability between Classes
3.2. Image Classification
3.3. Validation of the Image Classification
3.4. Temporal Evolution of the Eelgrass Extent
4. Discussion
4.1. An Assessment of the Classified Images
4.2. Eelgrass Spatial and Temporal Dynamics
4.3. Sources of Water Turbidity
4.4. Issues in Eelgrass Mapping
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Sensor | Image Acquisition Date | Image Path/Row |
---|---|---|
Landsat-5 MSI | 24 July 1988 | 020020/020022 |
020020/020023 | ||
17 July 1991 | 020020/020022 | |
020020/020023 | ||
16 September 1996 | 020020/020022 | |
020020/020023 | ||
Landsat-8 OLI | 16 September 2019 | 020020/020022 |
020020/020023 |
Band Name | Landsat-5 TM | Landsat-8 OLI |
---|---|---|
Coastal | 430–450 | |
Blue | 450–520 | 450–510 |
Green | 520–600 | 530–590 |
Red | 630–690 | 640–670 |
NIR | 760–900 | 850–880 |
SWIR1 | 1550–1750 | 1570–1650 |
SWIR2 | 2080–2350 | 2110–2290 |
Variable | Layer Name | Formula (1) | Reference |
---|---|---|---|
DVI | Difference Vegetation Index | NIR − R | [109] |
GDVI | Green Difference Vegetation Index | NIR − G | [110,111] |
GNDVI | Green Normalised Difference Vegetation Index | (NIR − G) /(NIR + G) | [112] |
GRVI | Green Ratio Vegetation Index | NIR/G | [110] |
NDAVI | Normalised Difference Aquatic Vegetation Index | (NIR − B) /(NIR + B) | [113] |
NDVI | Normalised Difference Vegetation Index | (NIR − R) /(NIR + R) | [114] |
NG | Normalised Green Vegetation Index | G/(NIR + R + G) | [110] |
NNIR | Normalised Near-Infrared Vegetation Index | NIR /(NIR + R + G) | [110] |
NR | Normalised Red Vegetation Index | R/(NIR + R + G) | [110] |
RVI | Red Ratio Vegetation Index | NIR/R | [115] |
WAVI | Water-Adjusted Vegetation Index | 1.5 (NIR − B) /(NIR + B + 0.5) | [113] |
Coastal/Green | Bathymetric Ratio (Coastal/Green) | Ln(C)/Ln(G) | [106] |
Coastal/Red | Bathymetric Ratio (Coastal/Red) | Ln(C)/Ln(R) | [106] |
Blue/Green | Bathymetric Ratio (Blue/Green) | Ln(B)/Ln(G) | [106] |
Blue/Red | Bathymetric Ratio (Blue/Red) | Ln(B)/Ln(R) | [106] |
RD-1 | Relative Depth 1 | Water < 5 m deep | This paper |
RD-2 | Relative Depth 2 | Water < 2 m deep | This paper |
Class | 1988 | 1991 | 1996 | 2019 |
---|---|---|---|---|
Eelgrass | 4604 | 3028 | 4012 | 3225 |
Low Turbidity | 9234 | 38,501 | 14,568 | 7795 |
High Turbidity | 1962 | 417 | 3744 | 2474 |
Seafloor | 2721 | 1034 | 1726 | 905 |
Deep Water | 119,800 | 56,024 | 79,992 | 106,253 |
Total | 138,321 | 99,004 | 104,042 | 120,652 |
Site Number | Longitude (West) | Latitude (North) |
---|---|---|
HQ-07 | 79°27′51″ | 54°17′40″ |
HQ-08 | 79°25′23″ | 54°17′17″ |
HQ-09 | 79°27′50″ | 54°14′17″ |
HQ-10 | 79°07′00″ | 54°08′59″ |
HQ-11 | 78°59′09″ | 53°34′27″ |
HQ-12 | 79°06′34″ | 53°30′34″ |
HQ-13 | 79°04′35″ | 53°27′04″ |
Year | Average | Class | Eelgrass | Low Turbid | High Turbid | Seafloor |
---|---|---|---|---|---|---|
1988 | 1.950 | Low Turbid | 1.936 | |||
High Turbid | 1.901 | 1.923 | ||||
Seafloor | 1.974 | 1.981 | 1.968 | |||
Deep Water | 1.980 | 1.906 | 1.931 | 1.998 | ||
1991 | 1.983 | Class | Eelgrass | Low Turbid | High Turbid | Seafloor |
Low Turbid | 2.000 | |||||
High Turbid | 1.966 | 1.999 | ||||
Seafloor | 2.000 | 2.000 | 2.000 | |||
Deep Water | 1.987 | 1.904 | 1.979 | 2.000 | ||
1996 | 1.996 | Class | Eelgrass | Low Turbid | High Turbid | Seafloor |
Low Turbid | 2.000 | |||||
High Turbid | 1.997 | 2.000 | ||||
Seafloor | 1.994 | 2.000 | 1.996 | |||
Deep Water | 1.999 | 1.992 | 1.986 | 2.000 | ||
2019 | 1.997 | Class | Eelgrass | Low Turbid | High Turbid | Seafloor |
Low Turbid | 2.000 | |||||
High Turbid | 1.999 | 2.000 | ||||
Seafloor | 2.000 | 2.000 | 1.999 | |||
Deep Water | 1.999 | 1.984 | 1.985 | 2.000 | ||
Average | 1.982 | Class | Eelgrass | Low Turbid | High Turbid | Seafloor |
Low Turbid | 1.999 | |||||
High Turbid | 1.999 | 1.999 | ||||
Seafloor | 1.999 | 1.999 | 1.991 | |||
Deep Water | 1.999 | 1.946 | 1.970 | 1.999 |
1988 | Eelgrass | Low Turbidity | High Turbidity | Seafloor | Deep Water | Total | UA * (%) |
Eelgrass | 4142 | 40 | 15 | 35 | 354 | 4586 | 90.32 |
Low Turbidity | 68 | 9041 | 10 | 24 | 81 | 9224 | 98.02 |
High Turbidity | 14 | 8 | 1859 | 1 | 69 | 1951 | 95.28 |
Seafloor | 36 | 15 | 3 | 2620 | 4 | 2678 | 97.83 |
Deep Water | 239 | 25 | 26 | 2 | 119,499 | 119,791 | 99.76 |
Total | 4499 | 9129 | 1913 | 2682 | 120,007 | 138,230 | |
PA * (%) | 92.06 | 99.04 | 97.18 | 97.69 | 99.58 | Overall Accuracy (%) = 99.23 | |
1991 | Eelgrass | Low Turbidity | High Turbidity | Seafloor | Deep Water | Total | UA (%) |
Eelgrass | 2881 | 15 | 10 | 19 | 103 | 3028 | 95.15 |
Low Turbidity | 27 | 37,016 | 3 | 23 | 1431 | 38,500 | 96.15 |
High Turbidity | 14 | 5 | 361 | 2 | 35 | 417 | 86.57 |
Seafloor | 15 | 45 | 0 | 974 | 0 | 1034 | 94.20 |
Deep Water | 26 | 1335 | 10 | 0 | 54,651 | 56,022 | 97.55 |
Total | 2963 | 38,416 | 384 | 1018 | 56,220 | 99,001 | |
PA (%) | 97.23 | 96.36 | 94.01 | 95.68 | 97.21 | Overall Accuracy (%) = 96.85 | |
1996 | Eelgrass | Low Turbidity | High Turbidity | Seafloor | Deep Water | Total | UA (%) |
Eelgrass | 3367 | 0 | 136 | 58 | 450 | 4011 | 83.94 |
Low Turbidity | 0 | 12,240 | 0 | 0 | 2323 | 14,563 | 84.05 |
High Turbidity | 146 | 5 | 3385 | 45 | 160 | 3741 | 90.48 |
Seafloor | 71 | 0 | 31 | 1624 | 0 | 1726 | 94.09 |
Deep Water | 187 | 2031 | 65 | 0 | 77,617 | 79,900 | 97.14 |
Total | 3771 | 14,276 | 3617 | 1727 | 80,550 | 103,941 | |
PA (%) | 89.29 | 85.74 | 93.59 | 94.04 | 96.36 | Overall Accuracy (%) = 94.51 | |
2019 | Eelgrass | Low Turbidity | High Turbidity | Seafloor | Deep Water | Total | UA (%) |
Eelgrass | 12,906 | 0 | 0 | 1 | 25 | 12,932 | 99.80 |
Low Turbidity | 0 | 31,055 | 1 | 0 | 178 | 31,234 | 99.43 |
High Turbidity | 1 | 1 | 9674 | 0 | 300 | 9976 | 96.97 |
Seafloor | 0 | 0 | 0 | 3618 | 0 | 3618 | 100.00 |
Deep Water | 4 | 175 | 3 | 0 | 414,701 | 414,883 | 99.96 |
Total | 12,911 | 31,231 | 9678 | 3619 | 415,200 | 472,643 | |
PA (%) | 99.95 | 99.44 | 99.96 | 99.97 | 99.88 | Overall Accuracy (%) = 99.85 |
Layer | 1988 | 1991 | 1996 | 2019 |
---|---|---|---|---|
Coastal | n.d. | n.d. | n.d. | 3 |
Blue | 11 | 2 | 18 | 6 |
Green | 3 | 1 | 4 | 4 |
Red | 8 | 10 | 6 | 13 |
NIR | 5 | 4 | 5 | 14 |
SWIR-1 | 18 | 18 | 21 | 2 |
SWIR-2 | 4 | 21 | 22 | 25 |
Turbidity | 7 | 9 | 10 | 1 |
Bathy-BG | 10 | 8 | 9 | 7 |
Bathy-CG | n.d. | n.d. | n.d. | 9 |
Bathy-BR | 12 | 5 | 7 | 19 |
Bathy-CR | n.d. | n.d. | n.d. | 17 |
DVI | 13 | 12 | 8 | 15 |
GDVI | 9 | 3 | 3 | 5 |
GNDVI | 20 | 16 | 13 | 23 |
GRVI | 21 | 15 | 16 | 21 |
NDAVI | 15 | 14 | 11 | 11 |
NDVI | 19 | 20 | 15 | 20 |
NG | 16 | 7 | 14 | 12 |
NNIR | 22 | 17 | 19 | 18 |
NR | 14 | 13 | 20 | 16 |
RVI | 17 | 19 | 12 | 24 |
WAVI | 6 | 11 | 17 | 10 |
RD-1 | 2 | 6 | 1 | 8 |
RD-2 | 1 | 22 | 2 | 22 |
Ground-Truth | |||||
---|---|---|---|---|---|
1988 | Class | Eelgrass present | Eelgrass absent | Total | UA * (%) |
Classified | Eelgrass Present | 42 | 11 | 53 | 79.3 |
Eelgrass Absent | 8 | 62 | 70 | 88.6 | |
Total | 50 | 73 | 123 | ||
PA * (%) | 84.0 | 84.9 | Overall Accuracy (%) = 84.6 | ||
Ground-Truth | |||||
1991 | Class | Eelgrass Present | Eelgrass Absent | Total | UA * (%) |
Classified | Eelgrass Present | 75 | 16 | 91 | 82.4 |
Eelgrass Absent | 25 | 84 | 109 | 77.1 | |
Total | 100 | 100 | 200 | ||
PA * (%) | 75.0 | 84.0 | Overall Accuracy (%) = 79.5 | ||
Ground-Truth | |||||
1996 | Class | Eelgrass Present | Eelgrass Absent | Total | UA* (%) |
Classified | Eelgrass Present | 66 | 12 | 78 | 84.6 |
Eelgrass Absent | 24 | 78 | 102 | 76.5 | |
Total | 90 | 90 | 180 | ||
PA * (%) | 73.3 | 86.7 | Overall Accuracy (%) = 80.0 | ||
Ground-Truth | |||||
2019 | Class | Eelgrass Present | Eelgrass Absent | Total | UA * (%) |
Classified | Eelgrass Present | 69 | 13 | 82 | 84.2 |
Eelgrass Absent | 10 | 16 | 26 | 61.5 | |
Total | 79 | 29 | 108 | ||
PA * (%) | 87.3 | 55.2 | Overall Accuracy (%) = 78.7 |
Year | North | South | Total | Source |
---|---|---|---|---|
1986 | 79.61 | n.d. * | 93.02 | [43] |
1988 | 82.39 | 86.89 | 169.28 | This paper |
1991 | 64.56 | 56.34 | 120.90 | [45] |
1991 | 50.47 | 59.35 | 109.82 | This paper |
1995 | 81.19 | 74.97 | 156.16 | [40] |
1996 | 60.00 | 45.51 | 105.51 | This paper |
2019 | 66.37 | 59.31 | 125.68 | This paper |
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Clyne, K.; LaRocque, A.; Leblon, B.; Costa, M. Use of Landsat Imagery Time-Series and Random Forests Classifier to Reconstruct Eelgrass Bed Distribution Maps in Eeyou Istchee. Remote Sens. 2024, 16, 2717. https://doi.org/10.3390/rs16152717
Clyne K, LaRocque A, Leblon B, Costa M. Use of Landsat Imagery Time-Series and Random Forests Classifier to Reconstruct Eelgrass Bed Distribution Maps in Eeyou Istchee. Remote Sensing. 2024; 16(15):2717. https://doi.org/10.3390/rs16152717
Chicago/Turabian StyleClyne, Kevin, Armand LaRocque, Brigitte Leblon, and Maycira Costa. 2024. "Use of Landsat Imagery Time-Series and Random Forests Classifier to Reconstruct Eelgrass Bed Distribution Maps in Eeyou Istchee" Remote Sensing 16, no. 15: 2717. https://doi.org/10.3390/rs16152717
APA StyleClyne, K., LaRocque, A., Leblon, B., & Costa, M. (2024). Use of Landsat Imagery Time-Series and Random Forests Classifier to Reconstruct Eelgrass Bed Distribution Maps in Eeyou Istchee. Remote Sensing, 16(15), 2717. https://doi.org/10.3390/rs16152717