Hyperspectral sensors

Birk, R. J. McCord, T. B. (1994) Airborne hyperspectral sensor systems.IEEE Aerospace and Electronic Systems Magazine 9, 26-33. 

Subterranean. Numerous techniques are used in subterranean remote sensing. For example, the data from aerial hyperspectral sensors are compared against spectral signature libraries for detection of mineral ores. Electromagnetic induction coils are used to detect changes in conductivity caused by groundwater, buried objects, or chemical contaminants. Flandheld, aerial, or spacebome ground-... 

Hyperspectral sensors mounted in small airplanes, hehcopters, and satellites. 

Change detection Data fusion Hyperspectral images Hyperspectral sensors Image processing Material identification Remote sensing... 

A hyperspectral sensor is able to record a high number of spectral bands, corresponding to narrow contiguous wavelength intervals. This characteristic permits the discrimination of different materials based on their unique spectral characteristics, called spectral signature. In general, two materials can be distinguished by broad and narrow spectral reflectance features determined by... 

In urban environment, hyperspectral remote sensing can be extremely useful, in particular for the management of pre-/post-seismic events. In this optic, the ability of hyperspectral sensors to discriminate several materials can be extremely useful in the characterization of the building type, by identifying the material used for the construction. Another important use of hyperspectral imaging is the ability to produce accurate geological maps of the soil. 

CHRIS is a high-resolution hyperspectral sensor installed on board the PROBA satellite. Distinctive feature of CHRIS is its ability to observe the same area under five different angles of view in the VIS (visible)/NIR (near infra-red) bands. Another important feature of CHRIS is the ability to be reprogrammable in terms of the number of spectral bands and spectral resolution (up to 150 spectral bands with a spectral resolution of 1.25 nm). This characteristic allows the acquisition of 62 narrow and quasi-contiguous spectral bands with the spatial resolution of 34-40 m or only 18 spectral bands with an enhanced spatial resolution of 18 m. 

The analysis of hyperspectral images is not an easy task. Due to the complexity of a hyperspectral sensor, hyperspectral images can be affected by several problems in terms of data tmiformity. Any nonuniformity in the system generates degrading artifacts. Since pushbroom scanners mainly characterize hyperspectral sensors, in this entry we will focus on the main problems that afflict this kind of sensors. 

In this entry we provided a brief description of the different aspects of the use of hyperspectral data in urban environment. In the introduction we presented a brief overview of imaging spectrometry in urban areas. The discussion continued with a description of the characteristics of the hyperspectral sensors and the problems related to the processing of hyperspectral images. We illustrated then the different techniques for the assessment of building vulnerability through the use of hyperspectral data. 

Mass spectroscopy Remote hyperspectral imaging Acoustically optical tunable filters Multidirectional flow injection sensor technologies... 

The method presented here is based off previous research into the use of physics-based target signatures in a scheme where detection is performed in the native image radiance space. Healey Slater (1999) and Thai Healy (2002) first presented the method as a way to overcome deficiencies in atmospheric compensation of visible / near infrared / shortwave infrared (Vis / NIR / SWIR) hyperspectral imagery. In this case, variability in the at-sensor target signature manifestations is modeled through variability in properties... 

Methods for improving image quality and reducing data load of nir hyperspectral images. Sensors 2008, 8,3287-3298... 

In Heiden et al. (2012), the height information obtained from LiDAR data has been introduced into orthorectification in order to improve the geometric accuracy of urban objects in the higher-resolution hyperspectral image data. This permitted to eliminate the influence of the facades of the buildings in large field of view (FOV) of such sensors and to improve the accuracy of surface material mapping. 

---