Observation of surface water is a functional requirement for studying ecological and
hydrological processes. Recent advances in satellite‐based optical remote sensors have …

Downscaling has an important role to play in remote sensing. It allows prediction at a finer
spatial resolution than that of the input imagery, based on either (i) assumptions or prior …

Straightforward classification using kernelized SVMs requires evaluating the kernel for a test
vector and each of the support vectors. For a class of kernels we show that one can do this …

Blind hyperspectral unmixing (HU), as a crucial technique for hyperspectral data
exploitation, aims to decompose mixed pixels into a collection of constituent materials …

Hyperspectral unmixing, the process of estimating a common set of spectral bases and their
corresponding composite percentages at each pixel, is an important task for hyperspectral …

When we talk about forests, we talk about 30% of our planet's land surface 6 area. In 2000
there was an estimated 3 870× 10 ha of forest worldwide, of which 1 5% is in forest …

This paper reviews progress in hyperspectral remote sensing (HRS) in China, focusing on
the past three decades. China has made great achievements since starting in this promising …

Recent advances in robotics and machine vision enable automated measurement of
vibration for civil engineering structures. Various types of robotic platforms such as drones …

Occurrence of mixed pixels in remote sensing images is a major problem particularly at
coarse spatial resolutions. Therefore, sub-pixel classification is often preferred, where a …

The properties of geographical phenomena vary with changes in the scale of measurement.
The information observed at one scale often cannot be directly used as information at …