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

In this paper, we discuss spatiotemporal data fusion methods in remote sensing. These
methods fuse temporally sparse fine-resolution images with temporally dense coarse …

Abstract Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new
sources of data to effectively characterize vegetation metrics at very high spatial resolution …

This paper provides an overview of the recent developments in remote sensing technology
and machine learning algorithms for estimating important biophysical and biochemical …

Remote Sensing Image Fusion: A Practical Guide gives an introduction to remote sensing
image fusion providing an overview on the sensors and applications. It describes data …

Acquiring useful data from agricultural areas has always been somewhat of a challenge, as
these are often expansive, remote, and vulnerable to weather events. Despite these …

Spatio-temporal image fusion aims to increase the frequency and resolution of multispectral
satellite sensor images in a cost-effective manner. However, practical constraints on input …

Because of low temporal resolution and cloud influence, many remote-sensing applications
lack high spatial resolution remote-sensing data. To address this problem, this study …

Owing to low temporal resolution and cloud interference, there is a shortage of high spatial
resolution remote sensing data. To address this problem, this study introduces a modified …

To better understand the progression of cotton root rot within the season, time series
monitoring is required. In this study, an improved spatial and temporal data fusion approach …