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

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 …

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

Due to the limitation of technology and budget, it is often difficult for sensors of a single
remote sensing satellite to have both high-temporal and high-spatial (HTHS) resolution at …

Remote sensing provides rich sources of data for the monitoring of land surface dynamics.
However, single-sensor systems are constrained from providing spatially high-resolution …

Due to the trade-off of temporal resolution and spatial resolution, spatiotemporal image-
fusion uses existing high-spatial-low-temporal (HSLT) and high-temporal-low-spatial (HTLS) …

In the last few years the scientific community has realized that obtaining a better
understanding of interactions between natural systems and the man-made environment …

Remote sensing images obtained by a variety of sensors have been widely used in different
Earth observation tasks. However, owing to budget and sensor technology constraints, a …

Spatiotemporal fusion (STF) is considered a feasible and cost-effective way to deal with the
trade-off between the spatial and temporal resolution of satellite sensors, and to generate …

Due to technological limitations and budget constraints, spatiotemporal image fusion uses
the complementarity of high temporal–low spatial resolution (HTLS) and high spatial–low …