Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

In remote sensing (RS), use of single optical sensors is frequently inadequate for practical
Earth observation applications (eg, agricultural, forest, ecology monitoring) due to trade-offs …

Spatiotemporal fusion (STF) techniques play important roles in Earth observation analysis
as they enable the generation of images with high spatial and temporal resolution. However …

Spatio-temporal fusion is a technique used to produce images with both fine spatial and
temporal resolution. Generally, the principle of existing spatio-temporal fusion methods can …

Abstract The Terra/Aqua MODerate resolution Imaging Spectroradiometer (MODIS) data
have been used widely for global monitoring of the Earth's surface due to their daily fine …

Significant progress has been made in spatiotemporal fusion for remote sensing images;
however, most models require inputs to be free of clouds and without missing data …

The unmixing-based spatiotemporal fusion model is one of the effective ways to solve
limitations in temporal and spatial resolution tradeoffs in a single satellite sensor. By using …

Spatiotemporal satellite image fusion (STIF) has been widely applied in land surface
monitoring to generate high spatial and high temporal reflectance images from satellite …

Numerous spatiotemporal fusion models have been developed to fuse dense time-series
data with a high spatial resolution for monitoring land surface dynamics. Nonetheless …

One of the obstacles in monitoring agricultural crops is the difficulty in understanding and
mapping rapid changes of these crops. With the purpose of addressing this issue, this study …