The global ocean is the largest ecosystem on our planet, the scientific understanding of
which is the first step towards the sustainable development of the perpetual ocean. With the …

Remote sensing (RS) spatiotemporal prediction aims to infer future trends from historical
spatiotemporal data, eg, videos and time-series images, which has a broad application …

Deep learning, a data-driven technology, has attracted widespread attention from various
disciplines due to the rapid advancements in the Internet of Things (IoT) big data, machine …

The accurate mesoscale eddy identification methods with deep learning framework depend
on either single eddy characteristic from altimeter missions or multi-step eddy examination …

Predicting the trajectory of ocean eddies can promote the understanding of the transport of
matter and energy in the ocean. However, accurately and rapidly predicting the trajectory of …

Due to dynamic changes and instability of oceanic eddies, continuous tracking and
sampling using mobile platforms is a challenging field. Aiming at the requirements of …

Sea surface temperature (SST) prediction has an important practical value in marine
disaster prevention and mitigation. Most current methods only use the temporal correlation …

Mesoscale Eddy (ME) is a widely recognized and significant oceanic phenomenon
characterized by extensive energy exchange. Accurate predictions of the future geospatial …

Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …

Predicting the mesoscale eddies in the ocean is crucial for advancing our understanding of
the ocean and climate systems. Establishing spatio-temporal correlation among input data is …