The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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the surface down to 100cm (limited by the fiber optic length). 
2.4 Way of operation 
Eighteen boreholes were dug according to the surface IS-based 
map along the area. For every depth, the soil properties were 
estimated using the NIRS models. Based on this information, 
we generated a surface soil property map for every depth layer 
for five soil properties (see below). In addition, the soil color 
was estimated using a digitally based calculation of the VIS 
region. Each drill hole was vertically described and classified 
according to a certain soil order. At several locations, the soil 
profile description of the drill hole (based on the POS method) 
was compared to the tradition soil profile description using 
open trenches. 
2.5 Using the spectral-based model NIRS to evaluate soil 
properties 
One hundred and sixty soil samples, taken from Israeli soils, 
were used to generate the spectral models based on the NIRS 
approach. For that purpose, we used the surface reflectance and 
its equivalent wet laboratory information. The soils were 
analyzed in the laboratory for six soil properties that are 
considered to be important for the soil survey mission and were 
determined in the laboratory: Soil Moisture (SM), Organic 
Matter (OM), Hygroscopic Moisture (HIG), Field Moisture 
(FM), Soil Carbonate Content (SCC), Specific Surface Area 
(SSA), and iron oxide content (Fed). The models were validated 
in several drilling points against the (true) chemical properties 
from the area. 
2.6 Spatial processing of the soil drill information 
Every depth for a given property’s layer, using all POS points, 
was interpolated by Kriging manipulation to provide a spatial 
layer view of the property in question. Five layers per property 
were generated at 20-cm intervals (to a depth of 100cm), all 
together, summing up to 25 layers. The layers were projected on 
a DTM map of the area that was generated by using the GPS 
measurements that were taken during the POS field 
measurements. 
2. RESULTS AND DISCUSSION 
Figure 1 presents the proposed paper concept, where a new 
spectral-based approach has replaced the traditional soil 
mapping approach that used open trenches and laboratory work. 
Figure 1: The concept of the optically based approach to map 
soil against the traditional way (Acknowledgement is given to 
Dr. J. Dematte for part of the illustration) 
In general, the airphoto is replaced by an imaging spectrometer 
view that provides not only a cognitive presentation of the area; 
it also enables accurate classification of the soil surface based 
on its spectral properties. This information is then used to select 
the proper location for the drilling holes. In these points, the 
POS approach is used and the entire soil profile is described 
qualitatively and quantitatively in situ. An equivalent activity, 
using the convention approach, is characterized by opening 
trenches and sending the soils to the laboratory, which is a time- 
and money-consuming process. Finally, soil maps (or profile 
descriptions) are generated and a comparison between the two 
methods is possible. Tables 1 and 2 present a detailed 
description of four soil profiles, as obtained from the POS 
approach, for four different soils selected to validate the 
approach. Table 1 presents the traditional soil profile 
descriptions obtained from trenches that were opened at nearby 
positions and Table 2 presents the optical (POS) profile 
descriptions 
Horizon 
Depth 
(cm) 
Description 
Rhodoxeralf 
A 
0-40 
Bare cover, small amount of dry weed, no carbonate 
content, dry soil, color 2.5 YR 4/8 red, sandy texture. 
Bt 
40-55 
Elovial horizon, accumulation of clay and iron oxides, 
no carbonates, color 2.5 YR 3/6 dark red. 
В 
55-80 
No carbonates, sandy soil, color 2.5 YR 4/6 red. 
C 
80-100 
Sandy soil, brighter color, higher humidity, color 5 YR 
4/6 yellowish red. 
Haploxeralf 
A 
0-20 
The surface is covered with wild vegetation, high 
carbonate content, clay loam texture, color 10 YR 6/4 
light brown. 
В 
20-70 
High carbonate content, decreased organic matter, 
sandy clay loam texture, a high concentration of 
carbonate pebbles in the horizon, color 10 YR 6/4 
light brown. 
c 
70-90 
Sandy soil texture, decreased carbonate content, color 
10 YR 8/8 reddish yellow. 
Haploaquept 
A 
0-15 
Very rich in organic matter, dark color, rich in 
carbonates, loam sandy texture, color 10 YR 4/1 dark 
gray. 
A3 
15-50 
Very rich in organic matter, high soil moisture, loam 
sandy texture, 
color 10 YR 4/1 dark gray. 
В 
50-80 
High water table and bad drainage in the soil increase 
the moisture; the horizon contains evidence of its 
original lake materials as shells. Drastic change in 
color; color 10 YR 7/1 light gray. 
C 
80-100 
Highly rich in carbonates, high moisture, contains free 
water, very bright color 10 YR 8/3 very pale brown, 
clay loam texture. 
Chromoxerert 
A 
0-65 
Rich in organic matter, high carbonate content, clay 
texture, color 10 YR 4/3 brown. 
AC 
65-100 
Rich in organic matter, high soil moisture, clay 
texture, color 10 YR 3/3 dark brown. 
Table 1: Traditional soil profile descriptions, as was done in the 
field in nearby trenches 
As seen, the two tables are in good agreement; however, when 
using the POS approach, the information is more detailed. 
Bearing in mind that the POS information was obtained 
objectively in situ, we can conclude that the optically based 
approach is a much more effective method for carrying out soil 
survey missions than the traditional method. Since the POS 
technology permits many measurements in the space domain, 
interpolation maps may be generated in the field to provide a 
spatial view if the soil entity is in question. In the current 
study, we used an unsupervised technique applied to the IS 
image, which resulted in 6 classes using the ISO Data classifier.