Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and
spectral resolutions. In this paper, we propose an integrated framework for the spatio …

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 …

Current satellite remote-sensing systems compromise between spatial resolution and
spectral and/or temporal resolution, which potentially limits the use of remotely sensed data …

The optical remote sensing images not only have to make a fundamental tradeoff between
the spatial and spectral resolutions, but also are inevitable to be polluted by the clouds; …

It is a challenging task to integrate the spatial, temporal, and spectral information of
multisource remote sensing images, especially in the case of heterogeneous images. To this …

Timely data quality assessment has been shown to be crucial for the development of IoT-
based applications. Different IoT applications' varying data quality requirements pose a …

Improving the spatial resolution of hyperspectral (HS) images is of great significance for the
subsequent applications. As the multispectral (MS) image can provide abundant …

Studies of land surface dynamics in heterogeneous landscapes often require satellite
images with a high resolution, both in time and space. However, the design of satellite …

In this letter, a general Bayesian data fusion (BDF) approach is proposed and applied to the
spatial enhancement of ASTER thermal images. This method fuses information coming from …

In this paper we evaluate k-nearest neighbor (KNN), linear and quadratic discriminant
analysis (LDA and QDA, respectively) for embedded, online feature fusion which poses …