Abstract
As wetlands are one of the world’s most important ecosystems, their vulnerability necessitates the constant monitoring and mapping of their changes. Satellite-based remote sensing has become an essential data source for mapping and monitoring wetlands. As wetlands are dynamic ecosystems, their classification depends on many different parameters. However, considering their complex structure; wetlands tend to be challenging land cover for classification, which sometimes requires the use of multi-sensor remote sensing techniques. The objectives of this study were: (i) to investigate the monthly dynamics of several wetland classes using multi-sensor parameters; (ii) to find correlations between the investigated parameters. Thus, we extracted the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from Landsat 8, and extracted dual polarization backscatter values (VH-VV) from the Sentinel-1 satellite at a monthly period over a year. The results showed strong correlation between the LST and the NDVI values of 0.94, and strong correlation between the microwave (VH) and both thermal and optical parameters with a 0.81 correlation coefficient, while there was weak or no correlation between the VV and the other investigated parameters. We strongly recommend that future studies clarify the Sentinel-1 backscatter values in wetland areas, by taking multiple field measurements close to the image acquisition time.
Highlights
As one of the world’s most productive natural ecosystems, wetlands are of significant importance in hydrological and ecological processes
As Synthetic Aperture Radar (SAR) sensors can often penetrate through herbaceous vegetation (C-band), the stronger backscatter signal is expected from wetter surfaces the one from a drier surface [37], the wetter surfaces are easier to identify through remote sensing techniques [3], which makes the detection of open water bodies without vegetation relatively simple as weak or no signal returns to the antenna
The objective of this research was to investigate the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) values obtained from Landsat 8 satellite, and VV and VH backscatter values obtained from the Sentinel-1 satellite, over a wetland area on a monthly basis and to investigate the correlation between these values
Summary
As one of the world’s most productive natural ecosystems, wetlands are of significant importance in hydrological and ecological processes. Wetlands have many definitions in the literature, they can be defined as areas filled or soaked with water for at least part of the year. Wetlands are vital for storing carbon to help ameliorate the side effects of anthropogenic greenhouse gases on the atmospheric temperature [3]. Their importance is high, both natural and human-induced forces threaten wetlands [4]. According to The United Nations World Water Development Report, around two-thirds of wetlands have been lost or degraded since the beginning of the 20th century [5], from which has emerged the need for their continuous mapping and monitoring
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