Wetland Mapping Using SAR Data from the Sentinel-1A and TanDEM-X Missions: A Comparative Study in the Biebrza Floodplain (Poland)
- Mapping wetland with only the C-band S1A, based on the multi-temporal series of SAR images with coarser geometric resolution and fixed polarizations (VV-VH).
- Mapping wetland with experimental fully polarimetric quad-pol X-band TSX/TDX data with higher geometric resolution.
- Compare the wetland mapping using the dual polarization TSX/TDX subsets; that is, HH-HV, HH-VV, and VV-VH. These subsets represent the standard products that could be acquired by an operational X-band SAR sensor outside of special observation campaigns.
- Compare wetland mapping using S1A and TSX/TDX data based on the same polarization (VV-VH) and covering the same observation period—enhancing the differences in geometric resolution and its effect on classification accuracy.
- Study the suitability of the Shannon Entropy as a polarimetric descriptor of wetland land cover, starting from dual-pol and quad-pol data.
- Assess the contribution of interferometric coherence as an additional layer for land cover classification over wetland.
2. Materials and Methods
2.1. Description of the Study Area and the Available Ground Truth
2.2. Sentinel-1A and TSX/TDX Datasets
2.3. Image Pre-Processing
2.4. Multi-Temporal Image Classification
3. Results and Discussion
- Mapping wetlands with the C-band S1A alone, based on the multi-temporal series of SAR images with VV/VH polarization. The results achieved with the time series of S1A SN were quite poor. The OAA for all classes equaled 65% and the KIA was 0.58. These values were not satisfactory. For this reason, the S1A dataset was not recommended for herbaceous wetland mapping in the Biebrza valley. There was a second disadvantageous feature of the S1A dataset; its geometric resolution was too coarse to detect not only the small areas of vegetation associations adjacent to oxbows and floodplain lakes, but also the small permanent water bodies.
- Mapping wetlands with the experimental fully-polarimetric quad-pol X-band TSX/TDX data. The results achieved (polarizations VV/VH/HV/HH) are the best amongst all the SN time series. The OAA was 79%, with a high coefficient of agreement, KIA, of 0.75. The results achieved using the fully polarimetric data and the Yamaguchi four-component decomposition (YAM4) were less useful than expected because the OAA was 43% and the KIA was 0.39. For this area and for the majority of classes over time, the dominant scattering mechanism was volume scattering, which decreased the OAA. The advantage of this decomposition was in revealing partially flooded herbaceous vegetation by the double bounce effect for particular TSX/TDX acquisitions. The results achieved using SE decomposition were better than those using the YAM4 dataset: the OAA was 55% and the KIA was 0.48. This could have been caused by the intensity component contribution outside of the polarimetric behavior.
- Comparing wetland mapping using the dual polarization TSX/TDX subsets; that is, HH-HV, HH-VV and VV-VH. For the dual-pol TSX/TDX products, the OAA and KIA were smaller than those from the four polarizations dataset: OAA = 76% and KIA = 0.71 for HH/HV; OAA = 74% and KIA = 0.69 for HH/VV; and OAA = 68% and KIA = 0.63 for VV/VH. However, there was a relatively small difference between the results achieved by quad-pol and the best dual-pol (HH/HV). Thus, this configuration can be recommended for wetland mapping purposes.
- Comparing wetland mapping using S1A and TSX/TDX, considering the same polarization (VV-VH) and covering the same observation period. The TSX/TDX dataset showed better performance. The difference of the OAA for the S1A and TSX/TDX datasets was about 3%. It seemed that the coarser geometric resolution had a negative influence on the results achieved by the S1A dataset.
- Studying the suitability of the Shannon Entropy as polarimetric descriptor of wetland land cover. The results achieved with the SE time series were quite poor, with the OAA ranging from 47% to 58%, and KIA ranging from 0.41 and 0.52. As a consequence, this dataset is not recommended for the mapping of the herbaceous wetland at all. The OAA values are lower for the pairs of bands containing cross-pol components (VH or HV). According to Reference , these components are strongly affected by the noise equivalent sigma zero over wetlands areas, thus affecting the SE parameter.
- Assessing the contribution of the interferometric coherence as an additional layer for land cover classification. The interferometric coherence estimated for the acquisitions of S1A, with a 12-day interval, and TSX/TDX, with an 11-day interval, turned out to be useless as land cover discriminators over this wetland. On the other hand, the coherence calculated for the TSX/TDX interferometric pairs acquired simultaneously (at the same time from two sensors) causes an increase of the OAA comparing to the SN time series. The OAA increased 7% for the HH-HV and HH-VV, 15% for the VV-VH, and 4% for the VV-VH-HV-HH datasets. The interferometric coherence is considered an important asset of quad-pol TSX/TDX acquisitions.
- Open water mapping (flood) at the scale of the Middle and Lower Basins of the Biebrza River based on the dual-pol sigma nought time series of Sentinel-1 for assessing annual hydrological conditions influencing biodiversity.
- Submerged vegetation mapping both from the Sentinel-1 and the TerraSAR-X Strip Map for: (i) assessing annual hydrological conditions, and (ii) mapping the presence of water in the periods of grass mowing on the parcels used temporarily by farmers for hay production.
- Checking the common reed mowing during winter as agreed between BbNP and the farmers using the TerraSAR-X HH/HV dual-pol. This action is ecologically important for the improvement of the life conditions of wading birds.
Conflicts of Interest
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|No.||Class||Number of Parcels||Number of Pixels TSX/TDX||Number of Pixels Sentinel-1A||Area (ha)|
|Frequency||9.65 GHz||5.405 GHz|
|Wavelength||X (3 cm)||C (5.6 cm)|
|Imaging Mode||Stripmap||Interferometric Wide|
|Ground resolution, rg by az||1.2 m × 6.6 m||3.1 m × 21.7 m|
|Pixel spacing, rg by az||0.9 m × 2.2 m||2.3 m × 13.8 m|
|Polarization||Quad (HH, HV, VH, VV)||Dual (VV, VH)|
|Incidence angle at the centre of the Area of Interest||36°||38.9°|
|Revisit time||11 days||12 days|
|Covered area||15 km × 30 km||250 km × 170 km|
|SN||Sigma Nought images|
|SN + Coh||Sigma Nought and coherence images|
|SE||Shannon Entropy images|
|YAM4||Yamaguchi four-component decomposition results (quad-pol data only)|
|No.||Class||Number of Parcels||Number of Pixels TSX/TDX||Number of Pixels Sentinel-1A||Area (ha)|
|1||permanent water bodies||10||36,299||2502||22.69|
|2||temporarily flooded grasslands||12||8771||576||5.48|
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Mleczko, M.; Mróz, M. Wetland Mapping Using SAR Data from the Sentinel-1A and TanDEM-X Missions: A Comparative Study in the Biebrza Floodplain (Poland). Remote Sens. 2018, 10, 78. https://doi.org/10.3390/rs10010078
Mleczko M, Mróz M. Wetland Mapping Using SAR Data from the Sentinel-1A and TanDEM-X Missions: A Comparative Study in the Biebrza Floodplain (Poland). Remote Sensing. 2018; 10(1):78. https://doi.org/10.3390/rs10010078Chicago/Turabian Style
Mleczko, Magdalena, and Marek Mróz. 2018. "Wetland Mapping Using SAR Data from the Sentinel-1A and TanDEM-X Missions: A Comparative Study in the Biebrza Floodplain (Poland)" Remote Sensing 10, no. 1: 78. https://doi.org/10.3390/rs10010078