CI87 CI91 CI94 P1* K1 P2* K2 P3* K3 
Township (Ha) (Ha) (Ha) 
AFLOU 1.47 2:33 3.47 6893.65 1543.56 3897.84 
AIN SIDI ALI 1.69 1.99 3.26 15372.61 13084.23 308.17 
BEIDHA 0.42 0.36 0.48 35295.06 10640.24 3664.00 
BRIDA 2.42 2.88 3.63 283.68 9312.28 490.72 
GUELTET SIDI SAÂD 0.44 0.37 0.64 50017.10 23533.99 3544.40 
HADJ MECHERI 1.57 1.25 1.76 0.00 22899.00 7788.20 
SEBGAG 5.03 2.51 3.96 445.35 12694.42 1165.06 
SIDI BOUZID 0.98 0.64 0.89 16836.21 6044.86 3689.67 
TOTAL 125143.66 99752.58 24548.06 
Mean 1.55 1.35 2.01 
  
P1: Grazing surface in good state.K1- 1.(Ki, i- 1,3: Weight assigned to the type of surface.) 
P2: Grazing surface in degraded state. K2- 0.6. 
P3: Grazing surface in very degraded state. K3- 0.4. CI: Charge Index. 
Table 1. Evaluation of the charge index and the grazing surfaces per township. 
B. Combination of the different layers 
The overlay of the land cover layer, where the different 
weighted grazing are represented with the pasture area 
distribution layer, inform us on the grazing status. This 
information is given by the computation of the charge index. 
IIL RESULTS AND DISCUSSION 
Firstly, the treatments done on this data base allowed us set up 
the following remarks: 
-the charge index computed in three different dates over the 
townships shows that the considerable increase of this index is 
in 91 and 94 (see Table 1). 
-this index is very superior to the normal threshold which is 0.25 
(Boukhobza, 1982) by hectare. In the case of an index greater 
than this threshold, the grazing degradation will occur. 
According to table 1, the charge index is very high in the four 
townships: AFLOU, AIN SIDI ALI, BRIDA and SEBGAG. 
This is due to the increase of the livestock number and the 
decrease of grazing areas. 
We noticed that the charge index of SEBGAG township is the 
greatest one and this will involve bad consequences on the 
grazing status. Nevertheless, the charge index of the remaining 
three township GUELTET SIDI SAAD, BEIDHA and SIDI 
BOUZID are small because of the presence of big grazing areas. 
Secondly, the combination of the information layers shows us 
the distribution of the main drillings and the pastoral wells on 
the whole study area (see Fig. 1). 
The townships BEIDHA and GUELTET SIDI SAAD are much 
better supplied by water than the others and this is due to the 
existence of a considerable number of pastoral wells and 
drillings. This advantage makes these townships more attractive 
in pastoralism. 
According to the pasture density map (see Fig. 1), we notice that 
the focalisation points are much concentrated in the south of the 
study region which is flat. This aspect allows good circulation of 
the herd. In addition, the densities vary between 2600 and 26000 
animals per year. 
Since the concentrated points are situated on the degraded 
regions, we conclude that this degradation is due to the big 
number of animals pasturing during the year. 
The map of synthesis in the Figure 1 combining the livestock 
density, land cover, administrative limits and hydraulic resource 
helps us with management in terms of finding areas of 
satisfactory grazing, water availability, existence of large and 
good grazing areas (abundance of food), and accessible land. 
Now, thanks to GIS tools and its functionalities the townships 
BEIDHA and GUELTET SIDI SAAD are the most suitable for 
the criteria mentioned above. 
IV. CONCLUSION 
This study gives the contribution of the GIS in the integration 
process of the physical and socio-economic data in the aim of 
producing maps and answers to complex interrogations in order 
to find out the causes of grazing degradation and to propose the 
best plan for the suitable grazing management. 
The spatial representation offered by GIS facilitates the 
expertise which identifies the most affected regions by the 
livestock concentration, shows the distribution of the necessary 
resources for the pastoralism and facilitates the research of new 
sites satisfying to the good criteria. 
The next steps aim to integrate temporal and spatial components 
for the space management in addition to the area potential 
valorisation. 
Finally, the functionalities of GIS represent an advantage for the 
space spatio-temporal organisation comprehension. 
748 Intemational Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998