Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China
AbstractThe loss of lake area significantly influences the climate change in a region, and this loss represents a serious and unavoidable challenge to maintaining ecological sustainability under the circumstances of lakes that are being filled. Therefore, mapping and forecasting changes in the lake is critical for protecting the environment and mitigating ecological problems in the urban district. We created an accessible map displaying area changes for 82 lakes in the Wuhan city using remote sensing data in conjunction with visual interpretation by combining field data with Landsat 2/5/7/8 Thematic Mapper (TM) time-series images for the period 1987–2013. In addition, we applied a quadratic exponential smoothing model to forecast lake area changes in Wuhan city. The map provides, for the first time, estimates of lake development in Wuhan using data required for local-scale studies. The model predicted a lake area reduction of 18.494 km2 in 2015. The average error reached 0.23 with a correlation coefficient of 0.98, indicating that the model is reliable. The paper provided a numerical analysis and forecasting method to provide a better understanding of lake area changes. The modeling and mapping results can help assess aquatic habitat suitability and property planning for Wuhan lakes. View Full-Text
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Duan, G.; Niu, R. Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China. Sustainability 2018, 10, 149.
Duan G, Niu R. Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China. Sustainability. 2018; 10(1):149.Chicago/Turabian Style
Duan, Gonghao; Niu, Ruiqing. 2018. "Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China." Sustainability 10, no. 1: 149.
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