Wetland Surface Temperature (WST) maps are an increasingly important parameter to understand the extensive range of existing processes in wetlands. The Wetlands placed in neighborhoods of agricultural and industrial lands are exposed to more chemical pollutants and pesticides that can lead to spatial and temporal variations of their surface temperature. Therefore, more studies are required for temperature modeling and the management and conservation of these variations in their ecosystem. Landsat 8 time series data of Sulduz region, Western Azerbaijan province, Iran were used in this study. The WST was derived using a mono-window algorithm after implementation of atmospheric correction. The NDVI (Normalized Differential Vegetation Index) threshold method was also employed to determine the surface emissivity (ελ). Our findings show that the WST experienced extensive spatial and temporal variations. It reached its maximum value in June and also experienced the highest mean in the same month. In this research, August (12.08.2013) had a lowest spatial standard deviation regarding surface temperature and June (28.06.2013) had the highest one. Wetlands' watersides adjacent to industrial zones have a higher surface temperature than the middle lands of these places. The map obtained from the WST variance over time can be exploited to reveal thermal stable and unstable zones. The outcome demonstrates that land use, land cover effectively contribute to wetland ecosystem health. The results are useful in the water management, preventive efforts against drying of wetland and evapotranspiration modeling. The approach employed in this research indicates that remote sensing is a valuable, low-cost and stable tool for thermal monitoring of wetlands health.
To cite this article (Atıf): Eisavi, V., Maleknezhad, Y., Niknezhad, S.A., 2016. Spatial and temporal modeling of wetland surface temperature using Landsat-8 imageries in Sulduz, Iran. Journal of the Faculty of Forestry Istanbul University 66(1): 46-58. DOI: 10.17099/jffiu.26733