Remote sensing using various spectrometers and imagers has several key advantages. First, the sensors can be spaceborne, airborne, vehicle-mounted, or even hand-held so that the area of coverage is significantly larger than in situ sensors. Notable spectral sensors include MODIS, AVIRIS, and LIBS. Consequently, large area remote sensing, such as soil monitoring, drought monitoring, rock sample analysis in Mars, and standoff chemical agent detection, is achievable. Second, spectral sensors contain rich information about the materials of interest. For example, AVIRIS contains more than 200 spectral bands. On the other hand, these advantages also bring unique challenges in spectral processing. Firstly, spectral sensors are sensitive to atmospheric conditions, viewing angles, and time of day. In addition, the spatial resolution and temporal resolution can be very coarse in some imagers. Finally, the computational load is also significant for data processing.

The aim of this special issue is to present recent advances in remote sensing using spectral sensors.

Potential topics include, but are not limited to:

• New multispectral/hyperspectral imagers with high spatial resolution
• New multispectral/hyperspectral imagers with extended spectral ranges such as the ultraviolet range
• Novel and high performance (robust to environmental conditions, high accuracy, low false alarms, fast) algorithms for processing the spectral data
• Fusion of multiple imagers to improve temporal, spatial, and spectral resolution
• Advanced feature extraction and target identification algorithms for spectral sensors
• Remote spectral sensors such as laser induced breakdown spectroscopy (LIBS) and Raman spectroscopy and corresponding processing algorithms
• Applications of remote spectral sensing