The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
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Similar to the SSA interpolation maps, every depth was
processed to yield a 3D map for other soil properties. The
overall information was used to provide a new view to
describe the soils within the area in question. As
demonstrated previously, an extra layer can be obtained
from the POS activity by adding the GPS measurements to
the kriging interpolation to generate DTM information.
Including the topography information along with a
quantitative description of the soil surface (using the IS
technology) as well as the soil profile (using the POS
approach) may be further used to classify the soil pedons to
an agreed-upon soil order. This stage will enable the
projection of all digital information on a classic soil map
that will consist of the hierarchy of soil orders. This stage,
however, requires more study and all layers will need to be
programmed to match the USD A (or similar) definition
system of the soil orders. This activity requires digitizing
the USD A user guide manual in such a way that the
spectral-spatial layers (IS, POS, and GPS based) will be
able to be defined by the proper (and accurate) pedogentic
root tree approach. Although this stage still lies ahead, the
present approach suggests that we are very close to
achieving that end. In other words, a first step toward
fully automating the soil mapping mission has been
completed. Utilizing the optical method is very simple and
does not require professional soil surveying skills. Since it is
a purely technical, scientifically oriented method, it can be
used to collect many samples quickly and use by other
applications such as precision farming and environmental
watching.
Surface Specific Area - Depth View
Figure 4: A cube (layer stack) description of the SSA property
throughout the soil areas studied
3. SUMMARY AND CONCLUSIONS
Combining optically based sensors that operate from both air
and ground domains can provide important information about
the soil entity. The new POS approach enables the soil profile to
be conveniently evaluated for a soil mapping mission. Instead of
opening trenches, which involves subjectively describing the
profile in the field and sending soil samples to the laboratory,
the POS approach with NIRS analysis enables in situ soil profile
recognition rapidly and effectively. The POS results provide
new insight into the soil properties on a spatial basis and may be
used in the future to automatically define the soil pedon in the
field. Further study is thus required to correlate the spectral data
information to the exact soil classification system that is
commonly used.
ACKNOWLEDGMENT
This work was supported by the Ministry of Agriculture, Government
of Israel, Soil Division grant 1/95-1/97.
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Banin, A., and A. Amiel. 1970. A correlation study of the
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Ben-Dor, E., and A. Banin. 1995. Near infrared analysis as a rapid
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USDA. 1999. Soil Taxonomy, Agriculture Handbook no. 436,
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Conservation Service. Washington. D.C.