A spatio-temporal prediction model theory based on deep learning to evaluate the ecological changes of the largest reservoir in North China from 1985 to 2021.
Yao, Jiaqi, Mo, Fan, Zhai, Haoran, Sun, Shiyi, Feger, Karl-Heinz, Zhang, Lulu, Tang, Xinming, Li, Guoyuan and Zhu, Hong, (2022). A spatio-temporal prediction model theory based on deep learning to evaluate the ecological changes of the largest reservoir in North China from 1985 to 2021.. Ecological Indicators, 145 109618-n/a
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Article
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Sub-type Journal article Author Yao, Jiaqi
Mo, Fan
Zhai, Haoran
Sun, Shiyi
Feger, Karl-Heinz
Zhang, Lulu
Tang, Xinming
Li, Guoyuan
Zhu, HongTitle A spatio-temporal prediction model theory based on deep learning to evaluate the ecological changes of the largest reservoir in North China from 1985 to 2021. Appearing in Ecological Indicators Volume 145 Publication Date 2022 Place of Publication Amsterdam, Netherlands Publisher Elsevier Start page 109618 End page n/a Language eng Abstract Miyun Reservoir, located in the Miyun District, Beijing, China, is the largest comprehensive water conservancy project and is an important ecological protection area in the North China region. Changes within the basin are the driving factors affecting the ecosystem in the watershed; therefore, it is important to analyze the changes in the ecological environment of Miyun Reservoir. For the analysis of a long time series of image data remotely sensed by satellite, the outliers caused by atmospheric, lighting, and sensor measurement errors are significant, and it is difficult for traditional algorithms to effectively recover the true image value. To address this, this paper proposes a theoretical model for predicting spatio-temporal variation based on deep learning to identify and correct invalid and anomalous values in extended time series data. This study corrected and analyzed the results of Remote Sensing based Ecological Index inversion of Landsat data of the Miyun Reservoir watershed from 1985 to 2021. The findings and conclusions of this study are important for the analysis of long time series image data from satellite remote sensing and for improving regional ecological evaluation and sustainable development planning. Keyword Miyun reservoir
E3d-LSTM
Deep learning
Mann-Kendall test
Ecological environment
RSEICopyright Holder The Authors Copyright Year 2022 Copyright type Creative commons ISSN 1470-160X DOI https://doi.org/10.1016/j.ecolind.2022.109618 -
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