Combination of Simple Additive Weighting (SAW) and Hierarchical Analysis Process (HAP) Methods for the Determination of Construction Suitability Zones in the Eastern Part of the Jijel Region (North East Algeria)

  • Karim RemoumEmail author
  • Azzedine Bouzenoune
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


The objective of this study was to propose concepts allowing the establishment of an interactive system of decision support adapted to the conduct of territorial processes relative to the challenges of the different phases of decision making. To support effectively the problem of Territorial Planning which consists in the search for a surface satisfying at best some criteria among a set of variants, Geographical Information Systems (GIS) and existing geotechnical data were analyzed and aggregated using MultiCriteria Decision Support (AMCD), namely the Simple Additive Weighting method (SAW) and the Analytic Hierarchy Process method (AHP). The combination of the two methods allowed us to make a concordance map to select the best suitable sites.


Geographic information system (GIS) Simple additive weighting (SAW) Hierarchical analysis process (AHP) Multi-criteria decision analysis (AMCD) ArcGis 

1 Introduction

The growing population and industrial development of the Jijel region is a challenge for the local authorities. They have to resort to new techniques for spatial planning. Indeed, it is important that all the parameters involved in the planning of this region are taken into account for effective sustainable implications. It seems appropriate to use a multidisciplinary approach which makes it possible to propose a decision support tool for the identification of areas suitable for the construction and implementation of works of great, vital importance.

The Geographic Information System (GIS) and the Multicriteria Assessment (EMC) are particularly useful for identifying sites suitable for this type of development. The integration of GIS and multicriteria analysis methods is a privileged and essential way to render GIS genuine decision support systems [1, 2]. This approach has already been applied by several authors for the choice of a given site [3, 4].

The objective of this study was to develop a model for the selection of areas suitable for construction, particularly vital works from a geographic information system (GIS) and multi-criteria assessment in order to guide decision-makers in reviving this sector for spatial planning for sustainable development.

The study area is characterized by a large depression located in the eastern part of Jijel, bordered to the south, east and west by a group of mountains whose absolute altitude is from 300 to 1000 m. The overall area of this basin is approximately 244 km2.

2 Materials and Methods

The materials consist of data and software. The applied approach in this study requires a compilation of cartographic data (topographic map at the 1:25,000 scale, geological map at the 1:50,000 scale) and alphanumerical data relating to geotechnical surveys. The collection of these data enabled the establishment of a Space Reference database. ArcGIS 10.2.2 software was used for data processing.

The data used in this study can be grouped into three main data sources such as basic topographic maps, a lithological map and geotechnical studies data. From these three data sources, six factors were chosen for the achievement of the different layers in ArcGIS. These are soil, slope, flood susceptibility, swelling potential, liquefaction potential, and depth of groundwater. Many steps have been completed in the GIS to obtain the final layers required in this study. In GIS, each criterion was classified into classes, and each class received a relevance rating based on experts and previous literature in this area.

After having prepared all the criteria within ArcGIS, and in order to obtain suitable sites for construction in the eastern part of Jijel, both methods were adopted to calculate the weights of the criteria and the production of the final map of construction suitability index using the “Map Algebra” spatial extension tool in the GIS.

3 Results

In the SAW method, the final map of suitability for construction was divided, using the method of equal intervals in five classes: very low, low, medium, high and very high; these different classes covered areas occupying 40.06 km2 (16.17%), 23.66 km2 (9.55%), 27.71 km2 (11.18%), 64.76 km2 (26.46 km2) and 91.56 km2 (36.96%), respectively. Similarly, the final map of suitability for construction established by AHP was divided into five classes, very low, low, medium, high and very high, covering areas of 40.06 km2 (16.17%), 8.21 km2 (3.31%), 38.22 km2 (15.43%), 15.51 km2 (6.26%) and 145.75 km2 (58.83%), respectively.

In order to combine the maps obtained from the two methods (SAW and AHP), each map was classified into five categories. The five categories were numbered as follows: very low (1), low (2), medium (3), high (4), and very high (5). The final maps were seized into the GIS for eventual processing by the spatial analysis tool “Map Algebra”. The results of this process included the number of pixels for each class and the number of raster category combinations for SAW and AHP, as well as the percentages of correspondents for each category, are shown in Table 1.
Table 1

The results of combining two maps resulting from (SAW) and (AHP) methods

Raster value


Raster category (AHP)

Raster category (SAW)

Corresponding pixels ratios




3 (M)

3 (M)

9, 19




5 (VH)

5 (VH)

36, 96




1 (VL)

1 (VL)

16, 17




5 (VH)

4 (H)

21, 87




2 (L)

2 (L)

3, 31




3 (M)

2 (L)

6, 24




4 (H)

3 (M)

1, 99




4 (H)

4 (H)

4, 27


VL Very low, L Low, M Moderate, H High, VH Very high

4 Discussion

The combined number of categories for SAW and AHP [(1, 1), (2, 2), (3, 3), (4, 4) and (5, 5)] was considered to be the number of the corresponding pixels resulting from the two methods. The different combinations of categories [(5, 4), (3, 2), (4, 3)] were not considered as concordant.

The percentage of raster values for the corresponding and non-corresponding categories is shown in Fig. 1. The final comparison map resulting from the combination of the two maps using the two methods was reclassified, then the categories with the same number of corresponding raster were merged to produce the category of concordant and non corresponding areas (Fig. 2). The percentage of corresponding pixels in the comparison map is 70% (in green), while the percentage of non corresponding pixels is 30% (yellow).
Fig. 1

The percentages of raster values of the classes of the comparison map

Fig. 2

Comparison map of concordant and non-concordant areas between AHP and SAW methods and its percentages

5 Conclusion

GIS combined with multi-criteria analysis provide land management opportunities that integrate all the parameters related to sustainable management. These techniques were applied to the eastern part of the Jijel region for the modeling of spaces suitable for the construction and implementation of vital works. The aptitude maps obtained by the SAW and AHP method were intended to guide development actors. They highlighted five categories: very low, low, medium, high and very high. The final map resulting from the combination of the two suitability maps for building reveals two categories: concordance areas with a percentage of pixels of 70% and a non-concordance area that represents 30% of the pixels. The concordance zone between the two maps helps guide decision-makers in choosing suitable sites for vital consideration works.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Laboratory of Geological EngineeringUniversity Mohammed Seddik Ben Yahia of JijelJijelAlgeria

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