# Monthly Analysis of Wetlands Dynamics Using Remote Sensing Data
## 1 Introduction
In this study, they also used the combination of SAR backscatter intensity from ENVISAT ASAR and ALOS PALSAR, and NDVI values obtained from Landsat-7, and a positive correlation between the NDVI and the HH SAR values have been observed. [PERSON] et al. [19] compared the capabilities of radar and optical remote sensing data for estimating wetland biomass, and they tried to find the best method for biomass estimation. The study does not confirm a high correlation between the NDVI and SAR values but rather implicates significant confusion of the NDVI values in the wetland biomass estimation as NDVI can only obtain canopy information. However, it should be mention that in this study only one SAR and one optical image has been used. Coarse spatial resolution long time series of NDVI data from National Oceanic Atmospheric Administration (NOAA) Advanced Very High-Resolution Radiometer (AVHRR) have been used for the assessment of the annual greenness cycle of vegetation and the hydrological behavior of the wetlands [20]. The monthly mean NDVI values showed minima occurring during the winter months and maxima during the early summer. One of the important parameter to understand the extensive range of existing processes in the wetland areas is the Land Surface Temperature (LST) [21], which can be described as one of the most important variables in physical processes of the Earth, and it is one of the unexplored parameters for studying wetland dynamics [22]. LST is closely related to the surface energy balance and the water status of the land cover, and it depends on the radiative energy that the land absorbs [23]. With the latest technological developments in remote sensing, many Earth observation satellites like Landsat, Sentinel-3, MODIS, ASTER, operate in the thermal infrared region offering thermal bands for retrieving thermal maps of the Earth's surface. Landsat-8 is the latest satellite from the Landsat legacy and offers 100-m thermal data. Retrieving LST using Landsat data has been the subject in many studies, resulting in several methods and algorithms [24; 25]. Although several studies have investigated the relation between SAR data and data from optical satellites [26], the relation between SAR values and LST values within a wetland have not been a subject of a detailed investigation. A spatial and temporal modeling of the wetland surface temperature has been done by [PERSON] et al. (2018), where they used time series from Landsat. Also, they employed correlation analysis to assess the relationship between the vegetation cover and the wetland surface temperature changes, where they found a high correlation of 0.8, and the results indicate that the wetland temperature is substantially affected by the air temperature. The goal of the presented study is to explore the potential correlation between several parameters from both optical and SAR data for better understanding of wetlands dynamics. For this purpose, eleven Landsat-8 and twelve Sentinel-1 images have been downloaded, pre-processed and used in the analyses. Since researchers have had difficulties using low and middle spatial resolution images for mapping wetlands because the majority of the pixels were a mixture of several land cover types, in this paper the average monthly values were used to analyze the monthly dynamics for each class determined in the study area. Thus, monthly LST and NDVI values have been retrieved from optical/thermal Landsat-8 data, while, the monthly SAR data values (dual polarization VV + VH), were retrieved from Sentinel-1 satellite images. The findings of this study will redound to the benefit of monitoring wetlands considering that the world's most productive natural ecosystems are threatened by both natural and human-induced changes. From a remote sensing point of view, this paper connects both thermal and visible with the microwave portion of the electromagnetic spectrum for the interest of wetland areas.