Advances in remote sensing technologies helped us to improve the monitoring of the wetlands; however, mapping the water under vegetation is still a challenge for delineating water extent. To solve this issue, here we employed different polarisation of SAR and interferometric coherence of sentinel-1 data in combination with optical sentinel-2 data to better delineate water extent in the wetlands by detecting the water below the vegetation. After preprocessing the images, we used the K-means clustering algorithm provided in the cloud computing platform of Google Earth Engine, to detect the double-bounce of the radar signal coming from flooded vegetation. We also took advantage of the high-resolution national land cover of Sweden as an ancillary layer to extract only the relevant satellite backscattering information in our study area. In the end, we compared our results with hydroclimatic and field data gathered from the study area. Our workflow revealed that using multi-layers of optical, radar and interferometric coherence improves the detection of hidden water below the vegetation and enhances the correlation of total detected water with discharge data. The proposed method can be used to study wetlands’ water availability changes and is an input to the policy-making programs for increasing wetlands’ resistance to the impacts of human activity and climate change.
- Wetlands' shape files
- 10m high-resolution national land cover of Sweden
- Interferometric coherence layers (processed by ENVI SARscape)