Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series
Abstract
:1. Introduction
1.1. SAR for Time Series Mapping
1.2. Interferometric Coherence Used in Classification
1.3. Variable Selection in Classification
1.4. Objectives
2. Study Area
3. Data and Methods
3.1. Choice of SAR Sensors
3.2. Training Data
3.3. Sentinel-1 Processing
3.4. RADARSAT-2 Processing
3.5. Random Forest Classification Scenarios and the Shapley Value
3.6. Assessing Variable Importance and the Contribution of Groups of Variables
4. Results
4.1. Assessment of Overall, User’s, and Producer’s Accuracy
4.2. Comparing Variable Importance (MDA), Contributions, and Interactions (Shapley Value)
5. Discussion
5.1. Issues with Collecting Time Series Data
5.2. Comparison of Variable Importance (MDA) and Contribution (Shapley)
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Sensor | Date | Sensor Information | Sensor | Date | Sensor Information |
---|---|---|---|---|---|
S1 | 06-April | Track 33 | RS2 | 21-July | FQ1W ASC |
S1 | 18-April | Track 33 | RS2 | 14-August | FQ1W ASC |
S1 | 30-April | Track 33 | RS2 | 07-September | FQ1W ASC |
S1 | 12-May | Track 33 | RS2 | 01-October | FQ1W ASC |
S1 | 05-June | Track 33 | RS2 | 25-October | FQ1W ASC |
S1 | 23-June | Track 33 | RS2 | 20-June | FQ5W ASC |
S1 | 29-June | Track 33 | RS2 | 14-July | FQ5W ASC |
S1 | 11-July | Track 33 | RS2 | 07-August | FQ5W ASC |
S1 | 23-July | Track 33 | RS2 | 31-August | FQ5W ASC |
S1 | 04-August | Track 33 | RS2 | 24-September | FQ5W ASC |
S1 | 16-August | Track 33 | RS2 | 18-October | FQ5W ASC |
S1 | 28-August | Track 33 | RS2 | 20-June | FQ1W DESC |
S1 | 09-September | Track 33 | RS2 | 14-July | FQ1W DESC |
S1 | 21-September | Track 33 | RS2 | 07-August | FQ1W DESC |
S1 | 03-October | Track 33 | RS2 | 31-August | FQ1W DESC |
S1 | 15-October | Track 33 | RS2 | 24-September | FQ1W DESC |
RS2 | 18-October | FQ1W DESC |
Objective 1 | |||||
Scenario ID | Groups | Shapley Value | Overall Accuracy | Objective Addressed | Sensor |
1 | RS2 (all) | 0.4 | 81.2 | 1 | S1 & RS2 |
S1 (All) | 0.41 | ||||
2 | RS2 amp + RS2 coh | 0.39 | 80.9 | 1 | S1 & RS2 |
S1 amp + S1 coh | 0.41 | ||||
Objective 1a | |||||
Scenario ID | Groups | Shapley Value | Overall Accuracy | Objective Addressed | Sensors |
3 | RS2 Summer (all) quad | 0.41 | 78.7 | 1a | RS2 |
RS2 Fall (all) quad | 0.38 | ||||
4 | RS2 Summer amp quad | 0.43 | 78.1 | 1a | RS2 |
RS2 Fall amp quad | 0.35 | ||||
5 | RS2 Summer diff quad | 0.28 | 71.9 | 1a | RS2 |
RS2 Fall diff quad | 0.44 | ||||
6 | RS2 Summer decomp | 0.34 | 73.6 | 1a | RS2 |
RS2 Fall decomp | 0.4 | ||||
7 | S1 Spring coh | 0.25 | 80.6 | 1a | S1 |
S1 Summer coh | 0.27 | ||||
S1 Fall coh | 0.28 | ||||
8 | S1 Spring amp | 0.23 | 68.1 | 1a | S1 |
S1 Summer amp | 0.26 | ||||
S1 Fall amp | 0.19 | ||||
9 | S1 Spring diff | 0.12 | 45.3 | 1a | S1 |
S1 Summer diff | 0.18 | ||||
S1 Fall diff | 0.15 | ||||
10 | S1 Spring (all) | 0.25 | 80.7 | 1a | S1 |
S1 Summer (all) | 0.28 | ||||
S1Fall (all) | 0.27 | ||||
11 | S1 VV (all) | 0.41 | 79.6 | 1a | S1 |
S1 VH (all) | 0.39 | ||||
Objective 2 | |||||
Scenario ID | Groups | Shapley Value | Overall Accuracy | Objective Addressed | Sensors |
12 | RS2 quad coh | 0.17 | 78.8 | 2 | RS2 |
RS2 quad amp | 0.22 | ||||
RS2 quad diff | 0.2 | ||||
RS2 quad decomp | 0.2 | ||||
13 | S1 coh | 0.37 | 80.9 | 2 | S1 |
S1 amp | 0.28 | ||||
S1 diff | 0.16 | ||||
Objective 2a | |||||
Scenario ID | Groups | Shapley Value | Overall Accuracy | Objective Addressed | Sensors |
14 | RS2 quad pol amp | 0.43 | 76.3 | 1 & 2a | RS2 & S1 |
S1 dual pol amp | 0.34 | ||||
15 | RS2 quad amp + diff | 0.46 | 78 | 1 & 2a | RS2 & S1 |
S1 dual amp + diff | 0.35 | ||||
16 | RS2 quad coherence | 0.32 | 80.9 | 2a | RS2 & S1 |
S1 dual pol coh | 0.49 | ||||
17 | RS2 dual pol coh | 0.28 | 78.2 | 2a | RS2 & S1 |
S1 dual pol coh | 0.5 | ||||
18 | RS2 FQ1ASC quad coh | 0.18 | 59.7 | 2a | RS2 |
RS2 FQ1DESC quad coh | 0.2 | ||||
RS2 FQ5DESC quad coh | 0.22 | ||||
19 | RS2 dual HHHV coh | 0.23 | 72.5 | 2a | RS2 |
RS2 dual HHHV amp | 0.28 | ||||
RS2 dual HHHV diff | 0.22 | ||||
20 | RS2 dual VVHV coh | 0.21 | 75 | 2a | RS2 |
RS2 dual VVHV amp | 0.29 | ||||
RS2 dual VVHV diff | 0.25 | ||||
21 | RS2 HH coh | 0.22 | 76 | 2a | RS2 |
RS2 HH amp | 0.25 | ||||
RS2 HH diff | 0.29 | ||||
22 | RS2 HV coh | 0.2 | 67.8 | 2a | RS2 |
RS2 HV amp | 0.29 | ||||
RS2 HV diff | 0.2 | ||||
23 | RS2 VV coh | 0.29 | 72.4 | 2a | RS2 |
RS2 VV amp | 0.25 | ||||
RS2 VV diff | 0.19 | ||||
24 | RS2 coh HH | 0.21 | 59.9 | 2a | RS2 |
RS2 coh HV | 0.18 | ||||
RS2 coh VV | 0.21 | ||||
25 | RS2 amp HH | 0.21 | 68.4 | 2a | RS2 |
RS2 amp HV | 0.27 | ||||
RS2 amp VV | 0.21 | ||||
26 | RS2 diff HH | 0.31 | 69.9 | 2a | RS2 |
RS2 diff HV | 0.21 | ||||
RS2 diff VV | 0.18 | ||||
27 | S1 VV coh | 0.47 | 79 | 2a | S1 |
S1 VV amp | 0.2 | ||||
S1 VV diff | 0.12 | ||||
28 | S1 VH coh | 0.4 | 80.4 | 2a | S1 |
S1 VH amp | 0.26 | ||||
S1 VH diff | 0.14 | ||||
29 | S1 VV coh | 0.42 | 78.6 | 2a | S1 |
S1 VH coh | 0.37 | ||||
30 | S1 VV amp | 0.3 | 68.8 | 2a | S1 |
S1 VH amp | 0.39 |
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Millard, K.; Kirby, P.; Nandlall, S.; Behnamian, A.; Banks, S.; Pacini, F. Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series. Remote Sens. 2020, 12, 2465. https://doi.org/10.3390/rs12152465
Millard K, Kirby P, Nandlall S, Behnamian A, Banks S, Pacini F. Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series. Remote Sensing. 2020; 12(15):2465. https://doi.org/10.3390/rs12152465
Chicago/Turabian StyleMillard, Koreen, Patrick Kirby, Sacha Nandlall, Amir Behnamian, Sarah Banks, and Fabrizio Pacini. 2020. "Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series" Remote Sensing 12, no. 15: 2465. https://doi.org/10.3390/rs12152465