Full text: Proceedings, XXth congress (Part 3)

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
  
that the orbitally georeferenced images are too much in the east 
and usually in the south. It should be noted that these results are 
the comparison to the reference, i.e., to the georeferenced ETM- 
image using ground control points from the map. 
Table 2. The comparison of the location of the images 
georeferenced using orbital information to the reference image 
georeferenced using ground control points 
  
  
  
  
  
  
  
  
  
Error in east | Error in | Planimetric 
direction north error 
direction 
MSS 1975 -915.0 -2.0 915.0 
MSS 1983 -978.0 205.0 999.3 
TM 1990 -1019.0 126.0 1026.8 
ETM 1999 -414.0 1070.0 1147.3 
. SRTM- -268.0 233.0 355.1 
DEM 
ASTER- -410.0 851.0 944.6 
DEM I 
ASTER- -898.0 481.0 1018.7 
DEM 2 
  
  
  
  
  
  
It is very likely that the positional accuracy of images 
georeferenced using orbital information is higher than using 
ground control points due to a small scale map used in the 
ground control point collection. The master image was 
georeferenced using 14 ground control points measured from 
the 1: 500 000 scale maps (TPC G-4C, TPC G-4D, UK 1998) 
and first degree polynomial transformation. The georeferencing 
errors are very high due to the small scale map, the average 
root-mean-square-error being 19.7 pixels. 
3.4 Interpretation methods 
Image interpretation methods were image clustering of the 
Landsat-images to determine the general land cover, change 
detection using the Landsat-images and image enhancement of 
the QuickBird image to aid visual interpretation. 
3.4.1 Clustering Landsat images: A general overview of land 
cover was acquired using clustering analysis. In clustering 
analysis, or unsupervised classification, the image pixels have 
been divided into categories or clusters according to their 
spectral similarities. The principle is that the spectrally similar 
pixels belong to the same cluster and different pixels to different 
clusters. When the clusters have been formed, they are 
interpreted by comparing them to satellite image, reference 
images like aerial images or maps, or ground survey data. The 
Landsat MSS-, TM- and ETM-images were clustered into 30 
clusters using k-means algorithm. (Richards, 1993). The clusters 
were interpreted by comparing them to satellite image and 
determining the most likely land cover. 
3.4.0 Change detection using Landsat images: Change 
detection was performed between the Landsat images in order 
to determine the places of land cover changes. Change images 
were formed by computing the differences of red and near- 
infrared channels (ETM-channel — other image channel) and 
clustering these two differences to 30 clusters using k-means 
algorithm and the clusters were interpreted to categories no- 
change and change. Also the type of change was interpreted if 
possible. 
Change images were computed using red channels (channel 5 in 
MSS, 3 in TM and ETM) and near-infrared channels (channel 6 
in MSS, 4 in TM and ETM). The purpose of using red channel 
900 
was to find changes concerning bare ground and mineral soil, 
especially sand. The purpose of using near-infrared channel was 
to find changes related to vegetation cover. The used pixel size 
was 60 meters when comparing the MSS- and ETM-images and 
30 meters when comparing the TM-and ETM-images. Ratio 
images CH7/CH1 were also computed from TM- and ETM- 
images and their difference image computed. It was hoped that 
this channel ratio would be sensitive to sandy soils (see also, 
Hofmann, K. — Geerken, R., 1998). It should be noted that the 
seasons of images were different, so some changes are due to 
the seasonal difference of vegetation. Also, some detected 
changes can be due to the misregistration between images. 
3.4.3 Image enhancement of the QuickBird image: Gradient 
images were computed from the previously referred QuickBird- 
image in order to enhance linear features like roads and paths, 
or other signs about the human activity like houses or ruins. 
Gradient images were computed using a Sobel gradient 
(Gonzales and Wintz) with 3x3 filtering window for channels 1, 
2 and 3. 
4. THE CONSTANTLY 
CHANGING DESERT BORDER 
At Jebel Bishri environment largely dictates the possibilities to 
carry out certain subsistence strategies, and this has also 
affected the formation of particular types of archaeological 
remains in the area which has been desert-steppe throughout the 
Holocene, i.e., the past ten thousand years. 
The specific archaeological remains left by different groups of 
people are usually determined as tool-kits, assemblages or 
technocomplexes (see definitions in Clarke, 1978). The desert- 
steppe environment offers sites that have a good surface 
distribution and are often visible for thousands of years on the 
surface. However, the Mediterranean and semi-arid regions are 
especially vulnerable to erosion. The limestone and sandstone 
slopes of Jebel Bishri are easily eroded by winds, sand storms 
and different run-off mechanisms caused by rains. It is known 
that generally erosion causes decreasing artefact diversity from 
slopes towards valleys (Evans - O Connor, 1999), but this is a 
theoretical approach which does not take into account the 
possible density of occupation and accumulation of 
occupational layers at the sites beneath slopes. 
The increasing desertification on the mountain is especially 
detectable in the Landsat satellite data comparing the 
movements of sands during the last thirty years. There was a 
drastic increase of the sand cover from the year 1986 to 1993. 
The peak of the sand movements was reached in 1993 (see 
Meissner - Ripke, 1995). Some minor increase was still 
detectable in the central area of Jebel Bishri and to the north 
from the Landsat-7 ETM image analysis marking the difference 
between the years 1993 and 1999. Monitoring these changes 
allows us to understand the environmental changes, which have 
affected the constrains to different livelihoods in the region. 
The influence of a state in the livelihood of the nomads has been 
detectable in our ethnoarchaeological study of the sedentarizing 
nomads in the village of Shanhas in the western piedmont area 
of Jebel Bishri. The CORONA satellite photographs also 
provide evidence that agricultural initiations were carried out by 
ploughing the ground also on the mountain in the 1960s. 
Ploughing and agriculture have, however, been found to cause 
catastrophic effects to the grazing grounds and the traditional 
livelihood of the nomads. Well water does not suffice in the 
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