Assessment of Spatio-Temporal Empirical Forecasting Performance of Future Shoreline Positions
نویسندگان
چکیده
Coasts and coastlines in many parts of the world are highly dynamic nature, where large changes shoreline position can occur due to natural anthropogenic influences. The prediction future positions is great importance better planning management coastal areas. With an aim assess different methods prediction, this study investigates performance predictions by quantifying how varies depending on time depths input historical data horizons predicted shorelines. Multi-temporal Landsat imagery, from 1988 2021, was used quantify rates movement for period. Predictions using simple extrapolation end point rate (EPR), linear regression (LRR), weighted (WLR), Kalman filter method were predict positions. Root mean square error (RMSE) accuracies. For depth, our results revealed that higher number shorelines calculating predicting change predictive yielded. horizon, accuracies substantially immediate years (138 m/year) compared more distant (152 m/year). Our also demonstrated forecast varied temporally spatially period region. Though area located Bangladesh, has potential forecasting applications other deltas vulnerable globally.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14246364