Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Analysis of Satellite Images to Assess AIAPs Distribution
2.2.1. Landsat Data
2.2.2. Image Processing
2.2.3. Accuracy Assessment
2.3. Long-Term Trend Analysis of Climate Variables
3. Results
3.1. Accuracy Assessment and Land Use
3.2. Long-Term Trend Analysis of Climate Variables
4. Discussion
5. Limitations and Challenges of the Study
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Date of Acquisition | Mission | WRS Path/Row | Landsat Sensor | Band Descriptions | Spatial Resolution (meters) |
---|---|---|---|---|---|
25-01-1992 | Landsat 4-5 | 141/54 | TM | Bands 1~7 | 30 |
08-03-1996 | Landsat 4-5 | 141/54 | TM | Bands 1~7 | 30 |
23-01-2000 | Landsat 7 | 141/54 | ETM+ | Bands 1~8 | 30 |
31-01-2003 | Landsat 7 | 141/54 | ETM+ | Bands 1~8 | 30 |
07-03-2007 | Landsat 4-5 | 141/54 | TM | Bands 1~7 | 30 |
27-02-2010 | Landsat 4-5 | 141/54 | TM | Bands 1~7 | 30 |
21-03-2013 | Landsat 8 | 142/54 | OLI, TIRS | Bands 1~9/10~11 | 30 |
27-01-2016 | Landsat 8 | 141/54 | OLI, TIRS | Bands 1~9/10~11 | 30 |
13-01-2017 | Landsat 8 | 141/54 | OLI, TIRS | Bands 1~9/10~11 | 30 |
03-01-2019 | Landsat 8 | 141/54 | OLI, TIRS | Bands 1~9/10~11 | 30 |
Land Use Type | Description |
---|---|
Non-aquatic plants | Areas covered by non-aquatic plants (i.e., dense forests, sparse forests, agricultural plants, plantations) inside tank cascade system |
AIAPs | Aquatic plants covering the water surface in the tank system |
Open areas | Sedimented areas/barren lands, paddy cultivations and built up areas (i.e., footpaths) |
Water | Deep and shallow water in tanks and streams, which includes both pure and sedimented water |
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 26 | 0 | 0 | 0 | 26 | 95.8% | 100% |
AIAPs | 1 | 29 | 0 | 0 | 30 | 100.0% | 96% |
Open areas | 0 | 0 | 31 | 0 | 31 | 100.0% | 100% |
Water | 0 | 0 | 0 | 30 | 30 | 100.0% | 100% |
Total | 27 | 29 | 31 | 30 | 117 | - | - |
Overall Accuracy = 99.04%; Kappa Coefficient = 0.9872 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 26 | 0 | 0 | 0 | 26 | 96.0% | 100% |
AIAPs | 0 | 27 | 0 | 4 | 31 | 79.4% | 87% |
Open areas | 1 | 0 | 28 | 0 | 29 | 77.8% | 96% |
Water | 0 | 7 | 8 | 62 | 77 | 93.9% | 81% |
Total | 27 | 34 | 36 | 66 | 163 | - | - |
Overall Accuracy = 87.68%; Kappa Coefficient = 0.8248 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 34 | 0 | 2 | 0 | 36 | 87.50% | 94.79% |
AIAP | 0 | 27 | 2 | 4 | 33 | 100.00% | 81.82% |
Open areas | 5 | 0 | 27 | 0 | 32 | 77.14% | 84.38% |
Water | 0 | 0 | 4 | 39 | 43 | 90.70% | 90.70% |
Total | 39 | 27 | 35 | 43 | 144 | - | - |
Overall Accuracy = 88.28%; Kappa Coefficient = 0.8429 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 34 | 0 | 5 | 0 | 39 | 94.1% | 87% |
AIAPs | 0 | 36 | 0 | 0 | 36 | 100.0% | 100% |
Open areas | 0 | 0 | 33 | 4 | 37 | 86.8% | 89% |
Water | 2 | 0 | 0 | 59 | 61 | 93.7% | 97% |
Total | 36 | 36 | 38 | 63 | 173 | - | - |
Overall Accuracy = 93.57%; Kappa Coefficient = 0.9125 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 59 | 0 | 1 | 0 | 60 | 92.0% | 98% |
AIAPs | 0 | 48 | 0 | 0 | 48 | 85.7% | 100% |
Open areas | 4 | 0 | 32 | 0 | 36 | 97.0% | 89% |
Water | 1 | 8 | 0 | 53 | 62 | 100.0% | 85% |
Total | 64 | 56 | 33 | 53 | 206 | - | - |
Overall Accuracy = 93.15%; Kappa Coefficient = 0.9075 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 30 | 4 | 2 | 0 | 36 | 100.0% | 83% |
AIAPs | 0 | 41 | 0 | 0 | 41 | 80.4% | 100% |
Open areas | 0 | 2 | 39 | 0 | 41 | 95.1% | 95% |
Water | 0 | 4 | 0 | 33 | 37 | 100.0% | 89% |
Total | 30 | 51 | 41 | 33 | 155 | - | - |
Overall Accuracy = 92.26%; Kappa Coefficient = 0.8964 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 29 | 0 | 0 | 0 | 29 | 86.7% | 100% |
AIAPs | 1 | 62 | 0 | 0 | 63 | 92.4% | 98% |
Open areas | 3 | 5 | 44 | 0 | 52 | 100% | 84% |
Water | 0 | 0 | 0 | 85 | 85 | 100% | 100% |
Total | 33 | 67 | 44 | 85 | 229 | - | - |
Overall Accuracy = 95.86%; Kappa Coefficient = 0.9425 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 81 | 4 | 1 | 0 | 86 | 95.5% | 94% |
AIAPs | 3 | 50 | 7 | 0 | 60 | 83.3% | 84% |
Open areas | 0 | 0 | 64 | 0 | 64 | 82.1% | 100% |
Water | 1 | 6 | 6 | 57 | 70 | 100.0% | 81% |
Total | 85 | 60 | 78 | 57 | 280 | - | - |
Overall Accuracy = 90.05%; Kappa Coefficient = 0.8666 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 27 | 0 | 0 | 0 | 27 | 95.0% | 100% |
AIAPs | 0 | 32 | 0 | 0 | 32 | 86.5% | 100% |
Open areas | 1 | 0 | 21 | 0 | 22 | 100.0% | 94% |
Water | 0 | 5 | 0 | 39 | 44 | 100.0% | 89% |
Total | 28 | 37 | 21 | 39 | 125 | - | - |
Overall Accuracy = 94.88%; Kappa Coefficient = 0.9305 | |||||||
| |||||||
Ground Truth (Pixels) | |||||||
Class | Non-Aquatic Plants | AIAPs | Open Areas | Water | Total | Producer’s Accuracy | User’s Accuracy |
Non-aquatic plants | 68 | 0 | 0 | 0 | 68 | 94.5% | 100% |
AIAPs | 1 | 32 | 7 | 0 | 40 | 100.0% | 79% |
Open areas | 3 | 0 | 24 | 0 | 27 | 77.4% | 90% |
Water | 0 | 0 | 0 | 52 | 52 | 100.0% | 100% |
Total | 72 | 32 | 31 | 52 | 187 | - | - |
Overall Accuracy = 94.16%; Kappa Coefficient = 0.9191 |
Land Use Class | Area km2 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
1992 | 1996 | 2000 | 2003 | 2007 | 2010 | 2013 | 2016 | 2017 | 2019 | |
Non-aquatic plants | 1.060 | 2.388 | 1.277 | 2.522 | 2.995 | 1.379 | 3.387 | 3.279 | 2.477 | 5.575 |
AIAPs | 2.762 | 2.023 | 2.339 | 2.561 | 2.887 | 3.429 | 3.687 | 3.258 | 3.670 | 3.551 |
Open areas | 5.340 | 6.303 | 4.812 | 8.100 | 7.351 | 10.323 | 4.190 | 4.967 | 8.571 | 4.751 |
Water | 17.190 | 15.639 | 17.925 | 13.170 | 13.119 | 11.223 | 15.089 | 14.850 | 11.635 | 12.476 |
Total | 26.353 | 26.353 | 26.353 | 26.353 | 26.352 | 26.353 | 26.353 | 26.354 | 26.353 | 26.353 |
Period | Change in AIAPs Area (km2) | Rate of Change (% change per year) |
---|---|---|
1992–1996 | −0.74 | −0.18 |
1996–2000 | 0.32 | 0.08 |
2000–2003 | 0.22 | 0.07 |
2003–2007 | 0.33 | 0.08 |
2007–2010 | 0.54 | 0.18 |
2010–2013 | 0.26 | 0.09 |
2013–2016 | −0.43 | −0.14 |
2016–2017 | 0.41 | 0.41 |
2017–2019 | −0.12 | −0.06 |
1992–2019 (overall) | 0.79 (28.6% increase) | 0.03 |
Series/Test | Kendall’s Tau | p-Value | Sen’s Slope |
---|---|---|---|
Annual Average Temperature | 0.253 | 0.050 | 0.012 |
Total Annual Rainfall | 0.246 | 0.056 | 14.725 |
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Kariyawasam, C.S.; Kumar, L.; Kogo, B.K.; Ratnayake, S.S. Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka. Climate 2021, 9, 31. https://doi.org/10.3390/cli9020031
Kariyawasam CS, Kumar L, Kogo BK, Ratnayake SS. Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka. Climate. 2021; 9(2):31. https://doi.org/10.3390/cli9020031
Chicago/Turabian StyleKariyawasam, Champika S., Lalit Kumar, Benjamin Kipkemboi Kogo, and Sujith S. Ratnayake. 2021. "Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka" Climate 9, no. 2: 31. https://doi.org/10.3390/cli9020031
APA StyleKariyawasam, C. S., Kumar, L., Kogo, B. K., & Ratnayake, S. S. (2021). Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka. Climate, 9(2), 31. https://doi.org/10.3390/cli9020031