Agriculture Reference
In-Depth Information
gather soil spectral information and publish it in the form of a soil spectral atlas. Their soil
spectral library very soon became a classic tool that soil scientists came to rely on. Later,
when laboratory and portable field spectrometers were introduced into the market (around
1993), more scientists realized the potential of soil spectroscopy, and consequently more
spectral libraries were assembled and new quantitative, chemometric applications, such as
NIRA, were developed and implemented for various soil materials. A summary of soil
reflectance theory and its applications can be found in various publications (Irons et al. 1989;
Ben-Dor et al. 1999; Ben-Dor 2002). A study by Brown et al. (2006) showed that NIRA can
work successfully under a generic global view rather than relying on a specific soil
population. An extensive study with over 1,100 soil samples, using several data-mining
algorithms to model and interpret diffuse reflectance spectra of soils and predict a number
of soil attributes was recently performed by Rossel & Behrens (2010).
1.4 Imaging spectroscopy and remote sensing
Imaging spectroscopy (IS), or hyperspectral remote sensing, is an advanced tool that
generates data of high spectral resolution, with the aim of providing near-laboratory-quality
reflectance (or emittance) for each single picture element (pixel) from a far distance (Vane et
al. 1984). This information enables the identification of objects based on the spectral
absorption features of chromophores and has been found very useful in many terrestrial and
marine applications (Clark & Roush 1984; Dekker et al. 2001). IS brings a new dimension to
the field of remote sensing by expanding the envelope of point spectrometry to the spatial
domain. It provides a tangible perspective by adding spatial detail to spectral information,
thereby enhancing the thematic application of spectral recognition algorithms. This
capability exists for both far and close distances, such as data acquired by satellites or by
microscopic sensors, respectively. Whereas the former is used for mapping the earth from
space, the latter is used for mapping micro targets, such as microorganisms and cell bodies,
to account for their biochemical processes in a spatial domain (Soenksen et al. 1996;
Levenson & Farkas 1997). It is interesting to note, however, that although soil scientists have
recognized the potential of reflectance spectroscopy and in fact termed it a novel
technology, in many ways, the use of IS for soil applications remains undeveloped and is
seldom reported. Though the IS approach is a cost-effective method, its adoption is limited
because the data is difficult to process, only a few sensors are operated worldwide, and it
has not yet been recognized by many end users. Hence, the journey from point spectroscopy
to a cognitive (imaging) spectral view of soils has not yet been completed, although there is
no doubt that it may open up new frontiers in the field of soil science. Thus far, only
exclusive and select groups around the world have been able to use IS for soil applications.
Nevertheless, over the past 10 years, these groups have demonstrated remarkable
achievements and have documented its significant capability. For further information refer
to the chapter on “Optical remote sensing techniques for soil contamination monitoring and
vulnerability assessment“ in this topic.
1.5 Acquiring reflectance information from soil
To acquire reflectance information from the VNIR-SWIR region, several sensors, methods,
protocols and platforms are used. Basically, the VNIR-SWIR sensors consist of an apparatus
(with filters, grating, prisms, interferometer, etc.) that splits the measured radiation into
individual wavelengths (or regions), several detectors (mostly CCDs) which are sensitive to
