Agriculture Reference
In-Depth Information
the penetrating optical device information with the hyperspectral remote sensing data will
also enable extracting the spatial distribution of the contaminant in question in 3D view.
Data merging of soil reflectance information with GIS layers and other potential sensors that
can be used simultaneously is also a key vision for the future. Time-series spectral
measurements of large areas are also very important. Future IS from orbit will enable global
coverage of every point on the globe with very good signal-to-noise ratio, such as the
PRISMA (Labate et al. 2009) ,HyspIRI (Knox et al. 2010) and EnMAP (Stuffler et al. 2007)
programs. This will enable monitoring soil surface changes in short- and long-term
scenarios. Another future activity related to soil spectroscopy and soil contamination
assessment is the development of better computing systems in which better models to
derive highly accurate soil attributes will be achieved. To that end, the “all possibilities”
approach in which all statistical and data-manipulation techniques can be applied
automatically to a set of data is strongly required. Computing power and simple operation
algorithms are key factors to that end.
10. General conclusions and summary
Soil reflectance spectroscopy can assess soil properties rapidly and quantitatively in both
point and spatial domains. Direct and indirect soil properties, as well as soil contamination
characteristics, can be extracted efficiently at low cost
in situ
. To that end, the VNIR-SWIR
spectra must be preprocessed and modeled against reference data obtained by traditional
methods. While some soil contaminants are featureless in the VNIR-SWIR region, their
detection and quantification is possible, as they may be detected indirectly based on their
association with other detectable materials. Although a wide range of factors can affect soil
reflectance spectra in both laboratory and field domains thus strongly affecting the
consistency of the resulting measurements, recent developments and proper protocols are
allowing for more consistent and accurate results. While using NIRS to predict soil
contaminants can save time, some cases involve the trade-off of reduced accuracy. Thus, the
spectral assessment of soil samples cannot completely replace, but rather complements the
classical chemical analysis in these and other cases. The benefits of using NIRS can result in
the practicable processing of a large number of samples and savings in chemicals, lengthy
tedious processes and manpower. In terms of spatial analysis, an airborne or spaceborne
hyperspectral sensor can be useful for the screening of large areas and the reproduction of
the spatial distribution patterns of contaminated soil areas. Nevertheless, the field of
reflectance spectroscopy as a tool for monitoring contaminated soils still requires further
study toward increased accuracy and the development of practical real-life applications.
11. References
Ben-Dor, E., 2002. Quantitative remote sensing of soil properties.
Advances in Agronomy
, 75,
pp.173-243.
Ben-Dor, E. & Banin, A., 1995. Near-infrared analysis as a rapid method to simultaneously
evaluate several soil properties.
Soil Science Society of America Journal
, 59(2), pp.364-
372.
Ben-Dor, E. et al., 2009. Using Imaging Spectroscopy to study soil properties.
Remote Sensing
of Environment
, 113, p.S38-S55.
Ben-Dor, E., Heller, D. & Chudnovsky, A., 2008. A Novel Method of Classifying Soil Profiles
in the Field using Optical Means.
Soil Sci Soc Am J
, 72(4), pp.1113-1123.
