Multimodal data fusion (MMDF) is the process of combining disparate data streams (of
different dimensionality, resolution, type, etc.) to generate information in a form that is more …

Recently, hyperspectral image classification based on deep learning has achieved
considerable attention. Many convolutional neural network classification methods have …

A method and apparatus is disclosed for applying high resolution spectral imaging
(hyperspectral or multispectral) to property characterization, specifically rooftop classification …

This study presents a point cloud de-noising and calibration approach that takes advantage
of point redundancy in both space and time (4D). The purpose is to detect displacements …

The 2012 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC)
of the IEEE Geoscience and Remote Sensing Society (GRSS) aimed at investigating the …

The fusion of high-resolution multispectral image (HrMSI) and low-resolution hyperspectral
image (LrHSI) has been acknowledged as a promising method for generating a high …

The use of airborne hyperspectral sensors for urban analysis represents a significant
advance in remote sensing. The greatest challenges to effectively using urban hyperspectral …

Automated classification of hyperspectral images is a fast growing field with numerous
applications in the areas of security and surveillance, agriculture, urban management, and …

Ground-based lidars and ceilometers are widely used for dust and volcanic ash observation
around the world. This is particularly interesting in Iceland where high-altitude dust events …

Synergistic applications based on integrated hyperspectral and lidar data are receiving a
growing interest from the remote-sensing community. A prerequisite for the optimum sensor …