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- W2899282893 abstract "A wetland is a land area that is saturated with water. Most of the wetlands exhibit seasonal variations because of soil characteristics, climate variables and orography of a site. This study applies the orthogonal least square (OLS) algorithm under the system identification methodology for the identification of a nonlinear dynamic model structure of the tropical wetlands, using a remotely sensed dataset. Despite the availability of data from the multiple tropical sites, a single dynamic-model structure is able to explain the underlying processes, governing the wetland extents of the tropics. The model is validated against a fresh data set, derived using the similar remote sensing technique. Overall, this study is a novel application of the systems identification for obtaining a single model structure of a category of wetlands, enabling some understanding about their dynamics. The model can also be employed for the assessment of future wetlands in the advent of climate change." @default.
- W2899282893 created "2018-11-09" @default.
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- W2899282893 date "2018-09-01" @default.
- W2899282893 modified "2023-10-14" @default.
- W2899282893 title "A Data-Driven Framework for Identifying Tropical Wetland Model" @default.
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- W2899282893 doi "https://doi.org/10.1109/control.2018.8516826" @default.
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