Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

A satellite image time series (SITS) contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natura...

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Bibliographic Details
Main Authors: Yun-Long Kong, Qingqing Huang, Chengyi Wang, Jingbo Chen, Jiansheng Chen, Dongxu He
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Remote Sensing
Subjects:
long short-term memory
LSTM
recurrent neural network
RNN
online disturbance detection
satellite image time series
SITS
Online Access:http://www.mdpi.com/2072-4292/10/3/452

Internet

http://www.mdpi.com/2072-4292/10/3/452

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