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 …

We propose a novel spatiotemporal fusion method based on deep convolutional neural
networks (CNNs) under the application background of massive remote sensing data. In the …

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

In the imaging process of optical remote sensing platforms, clouds are an inevitable barrier
to the effective observation of sensors. To recover the original information covered by the …

Spatiotemporal image fusion is a potential way to resolve the constraint between the spatial
and temporal resolutions of satellite images and has been developed rapidly in recent …

Remote sensing provides us with an approach for the rapid identification and monitoring of
spatiotemporal changes in the urban ecological environment at different scales. This study …

Probing the long-term spatiotemporal patterns of wetland vegetation changes and their
response to climate change and human activities is critical to make informed decisions …

Urbanization not only directly alters the regional ecosystem net primary productivity (NPP)
through land-cover replacement, but it is also accompanied by huge indirect impacts due to …

Urban ecological environment is the basis of citizens' survival and development. A rapid and
objective urban ecological environment assessment (UEEA) plays an important role in the …