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Remote sensing satellite images with a high spatial and temporal resolution play a crucial role in Earth science applications. However, due to technology and cost constraints, it is difficult for a single satellite to achieve both a high spatial resolution and high temporal resolution. The spatiotemporal fusion method is a cost-effective solution for generating a dense temporal data resolution with a high spatial resolution. In recent years, spatiotemporal image fusion based on deep learningdoi:10.3390/rs14030461 fatcat:5s36qvzxireibmufythw5ysazm