A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …

Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest
from a large remote sensing image archive, which has remained to be a hot topic over the …

In hyperspectral remote sensing image classification, multiple features, eg, spectral, texture,
and shape features, are employed to represent pixels from different perspectives. It has …

This paper deals with the problem of content-based image retrieval (CBIR) of very high
resolution (VHR) remote sensing (RS) images using the notion of a novel Siamese graph …

Earth observation is the field of science concerned with the problem of monitoring and
modeling the processes on the Earth surface and their interaction with the atmosphere. The …

Shape and spectra are both important features of high spatial resolution remotely sensed
(HSRRS) imagery, and they are concrete manifestation of textures on such imagery. This …

Searching for relevant knowledge across heterogeneous geospatial databases requires an
extensive knowledge of the semantic meaning of images, a keen eye for visual patterns, and …

With complex building composition and imaging condition, urban areas show versatile
characteristics in remote sensing optical images. It demonstrates that multiple features …

Remote sensing (RS) image retrieval is of great significant for geological information mining.
Over the past two decades, a large amount of research on this task has been carried out …

With the emergence of huge volumes of high-resolution remote sensing images produced
by all sorts of satellites and airborne sensors, processing and analysis of these images …