Satellite time series with high spatial resolution is critical for monitoring land surface
dynamics in heterogeneous landscapes. Although remote sensing technologies have …

Spatio-temporal fusion (STF) aims at fusing (temporally dense) coarse resolution images
and (temporally sparse) fine resolution images to generate image series with adequate …

Studies of land surface dynamics in heterogeneous landscapes often require remote
sensing data with high acquisition frequency and high spatial resolution. However, no single …

Longer time high-resolution, high-frequency, consistent, and more detailed land cover data
are urgently needed in order to achieve sustainable development goals on food security …

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 …

Remote sensing optical sensors onboard operational satellites cannot have high spectral,
spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can …

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 …

Due to sensor design limitations and the influence of weather factors, it is currently
challenging to obtain remote sensing images with high temporal, spatial, and spectral …

Simultaneously capturing spatial and temporal dynamics is always a challenge for the
remote sensing community. Spatiotemporal fusion has gained wide interest in various …

Spatio-temporal image fusion methods have become a popular means to produce remotely
sensed data sets that have both fine spatial and temporal resolution. Accurate prediction of …