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• W2896695937 abstract "Wetland areas are known as ‘the kidneys of the Earth’ because they provide important functions towards stabilizing the environment, long-term protection of water sources, effectively minimizing sediment loss, purifying surface water from industrial and agricultural pollutants, and enhancing aquifer recharge. The condition of water supply in wetlands directly affects the growth of wetland plants and local biodiversity. Therefore, drought monitoring is vital in wetlands. In this study, Vegetation Temperature Condition Index (VTCI) derived from normalized difference vegetation index (NDVI) and land surface temperature (LST) is used to observe the drought status of the wetland in the cross-border (China and North Korea) Tumen River Basin from 1991 to 2016. For this purpose, the Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) data for six periods were used for the analysis. Soil moisture maps acquired from the China Meteorological Administration Land Data Assimilation System Version 1.0 (CLDAS-V1.0) were then introduced for validating the reliability of the drought monitoring method. The results showed that most areas with a normal moisture level (decreased 25.8%) began experiencing slight drought (increased 29.7%). The coefficient of determination (R2) between VTCI and soil moisture showed values of 0.69, 0.32, and 0.2 for 0–5 cm, 0–10 cm, and 10–20 cm thicknesses, respectively. Although climate change probably contributes to the formation of drought by decreasing precipitation (50 mm decrease in Chinese section) and increasing temperature (0.5°C increase in North Korean section), human activities such as surges in daily water consumption appear as the main threats that leading to droughts in this wetland." @default.
• W2896695937 created "2018-10-26" @default.
• W2896695937 creator A5000684290 @default.
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• W2896695937 date "2018-10-16" @default.
• W2896695937 modified "2023-10-10" @default.
• W2896695937 title "Drought monitoring of the wetland in the Tumen River Basin between 1991 and 2016 using Landsat TM/ETM+" @default.
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• W2896695937 doi "https://doi.org/10.1080/01431161.2018.1524604" @default.
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