# Assessment of Carbon Flux and Soil Moisture in Wetlands Applying Sentinel-1 Data
## 2 Materials and Methods
### Methods  
The positions of the measurement plots, has been determined by GPS and were further used for preparing the measurement points layer which was needed for extracting satellite data. Sentinel-1 IW and TSX ScanSAR microwave images have been processed using ESA Sentinel-1 Toolbox (S1 TBX, developed for ESA by Array Systems Computing--Toronto, ON, Canada, in partnership with DLR--National Aeronautics and Space Research Centre, Germany, Brockmann Consult--Hamburg, Germany, and OceanDataLab--Locmaria Plouzane, France) in SNAP (Sentinel Application Platform, and is a common architecture for all Sentinel Toolboxes being jointly developed by Brockmann Consult and Array Systems Computing) to derive a backscatter coefficient (\(\sigma^{\circ}\)) (dB). The processing included: speckle filtering applying Gamma-MAP filter \(7\times 7\), radiometric calibration and data conversion to backscattering coefficient. Then, scenes were geometrically registered to local projection PUWG1992 and S1 \(\sigma^{\circ}\) values which corresponded to measurement points were extracted (5 \(\times\) 5 pixels--within this area three in-situ measurements have been carried out to calculate mean value) using ERDAS software (Hexagon Geospatial/Intergraph(r), Norcross, GA, USA). Landsat 8 OLI images have been processed using ERDAS software. Then, the scene acquired in UTM map projection and WGS84 ellipsoid was geometrically registered to local projection PUWG1992. Atmospheric Correction of TOA reflectance (Top of Atmosphere) was not applied. It was not necessary for the classification process, which uses only one cloud-free image, as the training data and the data to be classified are in the same relative scale. [41]. The wetland vegetation habitats have been classified using combined one Landsat 8 OLI image and three TerraSAR-X ScanSAR VV images, all registered in the year 2013. These images have been chosen for classification, because of their high spatial resolution and the period of the growing season (before the first cut). Moreover, X-wave is dedicated to vegetation studies. Also, there was no possibility to acquire adequate optical and Sentinel-1 images for the study period. Landsat 8 OLI spectral bands have been resampled to pixel size of TSX images i.e., 18 m. The pixel-based supervised maximum likelihood classification method was applied using the ERDAS software. This type of classification has been used due to availability of adequate ground truth data collected in 2013 during field campaigns. The representative, homogeneous ground reference data were used for training and testing purposes. There were no changes in wetland vegetation type and cover from 2013 to 2015. The collected time series of CO2 flux concentration were validated in terms of temporal linearity. Fluxes with a correlation coefficient of the slope R\({}^{2}\) > 0.95 were accepted for further analysis. The CO2 flux rate (NEE and RESP) was then calculated using the following equation described by [PERSON] and [PERSON] in [42]:  
\[\mathrm{E}\ =\ \mathrm{\rho}\cdot\frac{\mathrm{V}}{\mathrm{A}}\cdot\frac{ \mathrm{\Delta C}}{\mathrm{\Delta t}}\cdot\frac{273}{\mathrm{T}\ +\ 273} \tag{1}\]  
where: E--CO2 flux rate (mg m\({}^{-2}\cdot\)h\({}^{-1}\)); V--chamber volume (0.056 m\({}^{3}\)); A--collar area (m\({}^{2}\)); \(\frac{\mathrm{\Delta C}}{\mathrm{\Delta t}}\)--average rate of CO2 concentration change with time; T--air temperature in chamber (\({}^{\circ}\)C). NEE and RESP values were then predicted to umol CO2 m\({}^{-2}\cdot\)s\({}^{-1}\) assuming that 1 umol CO2 weights 44 \(\upmu\)g.  
In-situ measured soil-vegetation parameters and satellite microwave data were analysed for wetland vegetation habitats. Simple and multiple regression analyses were used to create the best models--first to examine the relationship between soil moisture and the backscattering coefficient of Sentinel-1, as well as the relationship between LAI and \(\sigma^{\circ}\) of S1. Data were checked for normal distribution and significance prior to all analysis.