Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada
Abstract
:1. Introduction
2. Data and Methods
2.1. Study Area
2.2. Data
2.3. Hydroperiod
2.4. Wetland Inventory
2.5. Accuracy Assessment
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Class | Forms | Water Permanence Types 1 |
---|---|---|
Marsh | Graminoid | Temporary [II] |
Seasonal [III] | ||
Semi-permanent [IV] | ||
Swamp | Wooded, coniferous | |
Wooded, mixedwood | ||
Wooded, deciduous | ||
Shrubby | Temporary [II] 2 | |
Seasonal [III] 2 | ||
Shallow Open Water | Subersed and/or floating aquatic vegetation | Seasonal [III] |
Semi-permanent [IV] | ||
Permanent [V] | ||
Intermittent [VI] | ||
Bare | Seasonal [III] | |
Semi-permanent [IV] | ||
Permanent [V] | ||
1 Roman numerals for wetland permanence types relate to wetland classes as outlined in [9]. | ||
2 Swamp water permanence types are only applicable to shrubby swamps given a current a lack of available information on wooded swamp types. |
Hydroperiod Value (%) | Vegetation Height (m) | Wetland Classification |
---|---|---|
85–100 | Not applied | Open water |
51–84 | <2 | Semi-permanent marsh |
51–84 | >2 | Semi-permanent swamp |
20–50 | <2 | Seasonal marsh |
20–50 | >2 | Seasonal swamp |
1–19 | <2 | Temporary marsh |
1–19 | >2 | Temporary swamp |
0–1 | Not applied | Upland |
Hydroperiod-Based Wetland Inventory | ||||||
---|---|---|---|---|---|---|
Validation Dataset | Marsh | Open Water | Swamp | Upland | Total | Producer Accuracy |
Marsh | 2260.33 | 0.04 | 0.58 | 878 | 3138.95 | 0.72 |
Shallow Open water | 616.24 | 66.67 | 1.19 | 42.31 | 726.41 | 0.09 |
Swamp | 0.1 | 0.1 | ||||
Upland | 903.62 | 0.09 | 45,225.74 | 46,129.45 | 0.98 | |
Total | 3780.19 | 66.71 | 1.86 | 46,146.15 | ||
User Accuracy | 0.6 | 1 | 0.98 | OA = 95% |
Hydroperiod-Based Wetland Inventory | ||||
---|---|---|---|---|
Validation Dataset | Wetland | Upland | Total | Producer Accuracy |
Wetland | 2945.05 | 920.41 | 3865.46 | 0.76 |
Upland | 903.71 | 45,225.74 | 46,129.45 | 0.98 |
Total | 3848.76 | 46,146.15 | ||
User Accuracy | 0.77 | 0.98 | OA = 96% |
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DeLancey, E.R.; Czekajlo, A.; Boychuk, L.; Gregory, F.; Amani, M.; Brisco, B.; Kariyeva, J.; Hird, J.N. Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada. Remote Sens. 2022, 14, 3401. https://doi.org/10.3390/rs14143401
DeLancey ER, Czekajlo A, Boychuk L, Gregory F, Amani M, Brisco B, Kariyeva J, Hird JN. Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada. Remote Sensing. 2022; 14(14):3401. https://doi.org/10.3390/rs14143401
Chicago/Turabian StyleDeLancey, Evan R., Agatha Czekajlo, Lyle Boychuk, Fiona Gregory, Meisam Amani, Brian Brisco, Jahan Kariyeva, and Jennifer N. Hird. 2022. "Creating a Detailed Wetland Inventory with Sentinel-2 Time-Series Data and Google Earth Engine in the Prairie Pothole Region of Canada" Remote Sensing 14, no. 14: 3401. https://doi.org/10.3390/rs14143401