RESEARCH ARTICLE

Application of Multi-Criteria Decision-Making in LandEvaluation of Agricultural Land Use

Seyed Ali Jozi & Farkhondeh Ebadzadeh

Received: 20 December 2012 /Accepted: 12 August 2013# Indian Society of Remote Sensing 2013

Abstract The present study was carried out to evaluate agri-cultural capability of a watershed located in Khuzestan; aprovince in southern Iran. It is aimed to examine the applica-bility ofMulti Criteria Decision-Making (MCDM)methods insite selection process. Accordingly, the ecological resources ofthe watershed were initially identified. To specify the criteriarequired for agricultural land evaluation, Delphi method wasapplied. After selecting the criteria, they were weighted usingAnalytical Hierarchy Process (AHP)Method.Weighted Over-lay (WO) Method was also used to overlay the map layers inthe GIS environment. Afterwards, sensitivity analysis wasperformed using Weights Sensitivity Analysis (WSA) methodto show the impressibility rate of the results against a certainchanges in the inputs. The results revealed that out of6591.2 ha of the total watershed area, 50.8 % has unsuitablepotentiality while 27.32 % has a poor suitability for irrigatedagriculture. It was also determined that only 6.96 % of thewhole study area has a suitable potential for this purpose.Besides, the findings indicated that 23.38 % of the totalwatershed area is unsuitable for rain-fed farming. the resultsalso showed that 31.78 % and 19.12 % of the entire study areahas moderate and high potentials for rain-fed agriculture,respectively. In a general overview, this study could presenthow MCDM is effective in handling land capability studies.

Keywords Ecological land evaluation .Multi CriteriaDecisionMakingMethod (MCDM) . Delphi method .

Agricultural land use . Khuzestanwatershed . Iran

Introduction

Nowadays, it is highly recommended to implement develop-ment plans just in accordance with the potential of resourcesand environmental carrying capacity in order to achieve sus-tainable development (Witlox 2005; Arán Carrión et al. 2008;Yallop and Clutterbuck 2009; Kheirkhah Zarkesh et al. 2010).The efficient use of natural resources requires deep under-standing of land capabilities before any decision for furtherdevelopment. Land capability evaluation is of great impor-tance so that if a piece of land does not have appropriatepotential for a specific use (even if there are all economic-social infrastructures available for that kind of land use), itsimplementation will not only improve the environmental sit-uation, but also cause degradation of the land. Ecologicalcapability determines various types of land uses and alsoeconomic potentials play a complementary role for ecologicalfunctions. Accordingly, these two factors specify the type ofthe land uses in a watershed. Different kinds of ecologicalresources are identified and evaluated to determine the eco-logical capabilities of a land. Geographic Information Systems(GIS) is commonly assumed to be a useful tool for spatialplanning whereas it has many capabilities in collecting, stor-ing, editing, analyzing and modeling data (van Haaren andFthenakis 2011; Pedrero et al. 2011; Gorsevski et al. 2012).Nowadays, it is common to use mathematical models such asfuzzy methods, analytical hierarchy process, etc. to evaluateland capabilities (Chang et al. 2008; Ekmekçioğlu et al. 2010;Schaerf et al. 2011). Zhang et al. (2004) developed a systemfor quantitative evaluation of soil productivity in an area of81,600 ha in china by integrating fuzzy logic and Delphi

S. A. JoziDepartment of Environment, Faculty of Technical and Engineering,Islamic Azad University, North Tehran Branch, Tehran, Irane-mail: sajozi@yahoo.com

F. Ebadzadeh (*)Department of Environment, Islamic Azad University, Science andResearch Branch-Khuzestan, Khuzestan, Irane-mail: ebadzadeh64@yahoo.com

J Indian Soc Remote SensDOI 10.1007/s12524-013-0318-8

method. Considering both land and surface water potentials,Eldho et al. (2009) developed a fuzzy rule-based inferencesystem in GIS environment to assess the land suitabilitypertaining to the specified crop. They used weighted linearaggregation method and Yager’s aggregation method to esti-mate the aggregated effect of the attributes in each group andto compare the results. Kheirkhah Zarkesh et al. (2010) ex-amined the applicability of the Spatial Analytical HierarchyProcess (SAHP) model in land use planning. There have beenseveral methods for multi criteria land capability analysis ofwhich Weighted Linear Combination (WLC) is one of themost commonly used one. Presently, this method is widelyused by environmental scientists due to its ease of implemen-tation in GIS as well as involving viewpoints of analyst teamin determining the importance of criteria. In this regard, thepresent study was done with the purpose of evaluating agri-cultural capabilities (irrigated and rain-fed) in Deli BaghmalekWatershed. Examination of applicability of multi-criteriadecision-making (MCDM) approach in agricultural site selec-tion studies was another issue of the research ahead. On otherwords, the research will show how effectiveMCDMwould bein handling land capability analysis.

Method and Materials

Study Area

Deli Baghmalek Watershed is located in the eastern KhuzestanProvince, in an area of about 6591.2 ha. It has three variousecosystems of mountain, foothills and plains. The area is situatedwithin the latitudes 31° 27′ 42″–31°42′ 09″N and longitudes 49°42′ 19″–49° 53′12″ E (Fig. 1). This watershed is restricted toSeleh be Sar mountains from North, Baghamalek County fromthe east, to Pirkary mountains from the west and Sardeli Moun-tain from the south. The highest and lowest altitudes in thewatershed are 1,320 m and 580 m, respectively. The annualaverage rainfall in the region reaches 609.2 mm and the annualaverage temperature is 20.64 °C (IRIMO 2008). There is aseasonal river within the study area. Due to the status of theslopes in the watershed, the floods of the highlands flow into theriver. The alluvium is not that much thick in this plain. Theriverbeds or stream beds are only places for the settlement ofalluvial deposits in the watershed. The plain surface is constitutedof poorly cemented Bakhtiari conglomerate so it has a little waterdischarge. The alluvium consists of clay, sand, gravel, silt andresiduals from the destruction of conglomerates. The groundwa-ter aquifers are local and confined so there is a small chance toreach the water up to several meters below the surface. There are77 different species of mammals, birds, reptiles and amphibiansincluding 19 species of mammals, 42 species of birds, 13 speciesof reptiles and 3 species of amphibians in this area. Field cropsand rangeland areas are two main land cover types in the plain

and marginal areas, respectively. The dominant plant speciesbelong to the families Compositae, Plantaginaceae andGramineae. In Deli BaghmalekWatershed, there is no woodlandunless small, scattered communities of forest trees includingQuercus persica , Amygdalus scoparia , Pistacia atlantica ,Pistacia khinjuk and Ziziphus spina Christi (MPOKP 2008).Land capability evaluation would be an important tool to pre-serve erosion-prone areas and to develop sustainable farming inthe watershed.

Methodology

In the first step of the agricultural land capability evaluation,the required basic data of the ecological resources was initiallycollected by field studies, literature reviewing and drillingtrenches. The collected database includes the meteorologicaldata consisting of temperature, precipitation, relative humidity,wind speed, annual regime of sunshine hours, hydrologicalstatistics, soil characteristics (such as texture, structure, depth,etc.), geological characteristics. After identification of renew-able and non-renewable resources, the maps of slope, aspectand elevation were produced using Digital Elevation Model(DEM) derived from topographic maps of the study area.Afterwards, the maps of all basic resources were generated inArc GIS9.3 Software with the same scale and coordinatesystem (UTM, WGS 89). The process of land capability eval-uation of Deli Baghmalek Watershed is presented in Fig. 2.

In this research the most important criteria affecting onagricultural land use (rain-fed and irrigated) was determinedusing Delphi method. Delphi is a questionnaire-based methodcarried out in partnership with people who have expertise inthe given subject. These people are known as Delphi panelists.Contrary to what is common in the quantitative surveys, thepanelists are not selected based on probability sampling be-cause Delphi technique is a group decision-making mecha-nism which needs qualified specialists who have deep knowl-edge of the subject. In this study, the number of the Delphipanelists was calculated using Cochran’s formula (Eq. 1).Accordingly, a total of 30 specialists who were expert inwatershed management, land use planning, agronomy, plantbreeding, irrigation and drainage, pedology, and other relatedfields were determined as the Delphi panel members.

n ¼ Nt2pq½ �t2pqþ N−1ð Þd2� � ð1Þ

Where:

n sample sizeN Population sizeT confidence levelP expected proportion (a fraction of one)d Precision (a fraction of one)

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Fig. 1 The situation of the study area in Iran

Choosing the most suitable criteria related to agricultural site selection

Presenting assessment model for agriculture using weighted linear combination method

Identifying and gathering site selection criteria for agricultural land use

Identification of criteria relevant to agriculture

Prioritizing and weighing criteria

Sensitivity analysis

Proposals

Consultation with the team members

Literature reviews

Land capability evaluation using MCDM Method

Importing data into GIS Software and preparing criterion maps

Application of Analytical Hierarchy Process Method

Standardization of criterion maps using Fuzzy Method

Application of GIS Software

Application of Delphi method through questionnaires

Application of Arc GIS 3.2 and preparation of base maps

Fig. 2 Agricultural land capability evaluation process in the Deli Baghmalek Watershed

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After introducing the panelists, a Delphi questionnaire con-taining a total of 36 parameters for rain-fed agriculture and 29parameters for irrigated agriculture was initially prepared. It isworth noting that the parameters were adopted from FAO, theconstraints of the study area and the literature reviews. Togather votes in favor and against of the criteria listed, thepanelists were polled at the first round of the Delphi, thedistributed questionnaires were then analyzed using the soft-ware Excel. Accordingly, criteria earned more than half of thevotes in favor were accepted to precede the second round of theDelphi. This process continued until reaching consensus in thethird round. Accordingly, 17 criteria out of 36 parameters forrain-fed agriculture and 23 out of 29 parameters for irrigatedagriculture were introduced as the affective criteria for landcapability evaluation of Deli BaghmalekWatershed. It is worth

noting that the importance of the criteria were determined ineach round using Likret Scale. Developed by Likert in 1932, Itis a five point scale used to measure attitudes by asking peopleto respond to a series of statements about a topic, in terms ofthe extent to which they agree with them. The Likert-type scaleassumes that the strength/intensity of experience is linear fromstrongly agreed to strongly disagreed (Likret 1932).

Undoubtedly, climatic conditions are considered of greatimportance criteria affecting on different kinds of land uses.Nearly, any kind of land uses is affected by climatic characte-ristics such as rainfall, temperature and relative humidity. Inaddition to the climatic factors, some other criteria such aswatershed degradation status, risk of flooding, wetland areasand various soil characteristics such as salinity, pH, organicmatter, etc. were also chosen as the most effective factors by the

Fig. 3 Hierarchal structure of irrigated agriculture land capability evaluation in Deli Baghmalek Watershed

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Delphi experts. After determining the most important criteria, itwas time to simplify the problem (identification of placessuitable for agricultural land use) into the hierarchal structure.Figures 3 and 4 illustrate the hierarchal structure of the decisiontrees used to run MCDM analysis for the present study.

In land capability evaluation studies, it is necessary todetermine the relative importance of criteria. This can be doneby the pairwise comparison method. In this research, each ofthe criteria maps was prepared in Arc GIS9.3 software as athematic map in raster format. Then, theywere weighted usingeigenvector method. Accordingly, the criteria were pairwiselycompared with each other based on the preference scale. Thesoftware Expert choice was used to facilitate the weightingprocess. Table 1 gives an example of pairwised matrix appliedin this research. As the table shows, the highest importancewas allocated to the all the matrices in the questionnaire were

scored by the experts in a pairwise manner. The scores wereentered in the left upper triangular of the matrices. Since, eachcriterion compared with itself, would have an equal prefer-ence, so the main diameter of the matrices was filled bynumber 1. Table 3 shows the pairwise comparison of thecriteria used in irrigated agricultural land capability analysisin the physical environment. In physical environment, thehighest importance was allocated to the climatic sub-criteriaby the Delphi panelists. This was due to the determining roleof the climatic components on the irrigated farming. Watershortage, long term aridity and low level of humidity in thestudy area make the climatic conditions as a limiting factor forexpansion of irrigated fields in the study area. The second andthird priorities were respectively assigned to the soil charac-teristics and physiographic criteria. Soil characteristics such asfertility, depth, texture, etc. are of great importance for estab-lishment of irrigated agriculture in the study area so they weretaken into the consideration as the second top priority criteriain the decision tree. Fortunately, the physiographic condition

Fig. 4 Rain-fed agriculture land capability map in Deli Baghmalek Watershed

Table 1 Preferencevalues for pairwise com-parisons (Saaty 1980)

Descriptions Scale

Equally preferred 1

Equally to moderately 2

Moderately preferred 3

Moderately to strongly 4

Strongly preferred 5

Strongly to very strongly 6

Very strongly preferred 7

Very strongly to extremely 8

Extremely preferred 9

Table 2 Pairwise comparison of irrigated agriculture criteria in physicalenvironment

Criterion Climate Soil Physiographic Total weight

Climatic 1 2 6 0.6

Soil characteristics 2.1 1 3 0.3

Physiographic 1.6 1.3 1 0.1

C.I.=0.0254 C.R.=0.0205

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of the watershed creates no considerable limitation for farmingso that they were at least importance. Less than 0.1 consistencyratios indicated the accuracy of the judgments. The WeightedOverlaymethodwas used to overlay themap layers. The valuesin the various criteria maps such as slope (%), elevation (m),rainfall (mm), etc. are expressed in different units of measure-ment and pixel sizes. Therefore, in order to compare andintegrate the criteria maps with each other, all the values needto be standardized and transformed to the same unit of mea-surement (Saaty 1988, 1990). This is called standardization ormaking dimensionless. In present study, the standardization ofcriteria maps was done based on fuzzy logic within the range of0–1 (Zaredar et al. 2010). In this range, the higher valuesrepresent higher suitability and vice versa. This was donethrough re-classification of the raster maps. By reclassification

process, each of the raster maps is converted into the nominal-ordinal raster. Accordingly, all the dimensionless raster layerswould have same extent and pixel size After fuzzification of thecriteria maps, the final rain-fed and irrigated agricultural landcapability maps were prepared through overlaying the maplayers using Weighted Linear Combination (WLC) (Madrucciet al. 2008; Moeinaddini et al. 2010; Zhang and Zhou 2011;Zaredar and Rezakhani 2011).

S ¼X

wi xi ∏cj

Where;

S suitabilityWi the weight of the factor i

Table 3 The weights obtainedfrom pair-wise comparison of thecriteria

Criterion Weight Criterion Weight

Soil depth (Cm) 0.128 Average annual temperature 0.391

Soil structure 0.085 Average annual rainfall 0.177

Pebble percent 0.047 Relative humidity 0.143

Current land use 0.750 Annual evaporation 0.123

Distance from water sources (rivers, springs etc.) 0.600 Slope 0.489

Distance from the villages 0.200 Aspect 0.098

Distance from access roads 0.200 Soil texture 0.233

C.I.=0.057 C.R.=0.046

Fig. 5 The irrigated agriculture land capability map of Deli Baghmalek Watershed

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xi dimensionless value of the factor icj constraint mapΠ multiply mark

Ultimately, sensitivity analysis was done using WeightsSensitivity Analysis (WSA) method to determine the stabilitylevel of the obtained results. The sensitivity analysis is amethod to indirectly incorporate uncertainty in the decision-making process. Sensitivity analysis is a procedure to deter-mine the impacts of changes in inputs (geographical data anddecision-makers’ priorities) on the outputs (the rankings of thealternatives). If the changes do not have meaningful andsignificant effects on the outputs, it can be concluded thatthe ranking is stable enough. In sensitivity analysis, thosemethods are taken into the consideration by which the errorsin a set of input data can influence on the error rate of the finaloutputs (the criterion outcomes). In other words, it is done toface no statistically significant differences between the select-ed variables in case of respiting the study for several times.The Weights Sensitivity Analysis (WSA) method was used inthis research to perform sensitivity analysis and make sure ofthe model viability. This method was selected because theweights of criteria and attitudes are of great importance com-ponents of such analyses. It is worth noting that the analysis

was performed in the environment of GIS software. In theabove procedure, using the weights interference (“a±0.05”),any change in the value of the option will change the rankings.

Results and Discussion

As it has already been mentioned, the criteria were weightedusing AHP Method (Table 2 shows an instance of the calcu-lated weights). The Weighted Linear Combination (WLC)Method was then applied to overly the standardized maplayers in the environment of GIS software (Table 3).

Ecological land capability evaluation was examined in anarea of 6591.2 ha which the detailed results are presented inthe followings:

The watershed capability for irrigated agriculture

From total area of the watershed, 3347.9 ha equal to 58.31 %belongs to the classes 4 and 5 (unsuitable) and 1800.9 ha thatamount to 27.32 % is categorized in the poor potential class.Meanwhile, 947.03 ha equivalent to 14.37 % have a moderatepotential for irrigated farming. It was found that 458.5 ha

Fig. 6 Hierarchal structure of rain-fed agriculture land capability evaluation in Deli Baghmalek Watershed

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(equal to 6.96%) has a high potential for irrigated farming. Asthe results suggest, the best places for irrigated agriculture aresituated in Deli Valley and its periphery lands wherein thereare seasonal rivers and watercourses. Due to the fact that theland slope overlooks the valley Deli, the fertile soil upstreamthe watershed is transported by floods to the valley and createdthe best places for irrigated farming. In this part of the water-shed, there are a number of springs which partly offset thewater shortage of the irrigated farming. More than 95 % of thewhole farmlands are currently allocated to rain-fed agriculturefor reasons such as water deficit and steep lands in the easternand western strips. The southern and eastern parts of thewatershed have a poor potential for the mentioned land use.From the geological point of view, the watershed belongs toBakhtiari and Lahbary geological formations with slopesranging between 20 % and 30 %. The steep slope causes thetop-soil being washed. Accordingly, the eastern part of thewatershed is not suitable for irrigated agriculture (Fig. 5).

The watershed capability for rain-fed agriculture

Out of the watershed total area (6591.2 ha), 1344.6 ha (equalto 20.4 %) are assigned to the classes 4 and 5 (unsuitable).Around 1845.54 ha (tantamount to 28 %) has a poor potentialwhile 2109.19 ha equivalent to 32 % has a moderate potentialfor rain-fed agriculture. It was determined that 1291.87 ha(equal to 19.6 %) has a suitable potential for rain-fed farming.It is worth mentioning that the best places for rain-fed farmingare situated in Deli Valley and its marginal lands. Due toreasons such as the existence of more than 9 villages withinthe valley, access roads, water resources, suitable and deepsoils and relatively gentle slopes, the lands are prone to rain-fed agriculture. It should be noted that these lands havealready been plowed in the past decades and now, are underrain-fed cultivation. As Fig. 4 illustrates, the rain-fed farm-lands in the watershed are just the same as places introducedsuitable by MCDM method. Although the northern parts ofthe watershed have “quite suitable” and “suitable” potentials

for rangeland, they have been destroyed and allocated to therain-fed farming. Finally, the sensitivity analysis was done toassess changes in the inputs how will affect the final resultsobtained (Fig. 6). As can be seen in Fig. 5, the obtained resultsindicate 71.6 % and 94.41 % validity levels for irrigated andrain-fed farming, respectively. In other words, in 94.41 % ofthe iterations, similar results were obtained for rain-fed agri-culture by changing the weights while 71.6 % of all iterationswere resulted in the same outcomes for irrigated agriculture(Fig. 7).

Conclusions

The current study focuses on agricultural land capability eval-uation of a watershed named Deli Baghmalek which is locatedin a province in southern Iran. After creating the database, theland capability maps for rain-fed and irrigated agriculture inthe study area were prepared. As a commonly used method,the advantages and disadvantages of multi-criteria decision-making was examined through the present case study. Inmulti-criteria decision-making method, it is possible to over-lay any number of layers which will result in more accurateresults. The main advantage of this method is that it caninterfere the importance of the factors in final decision byweighing them. So far lots of studies have been done toexamine the applicability of MCDM in site selection process.Zucca et al. (2008) conducted a research to examine theapplication of spatial multi-criteria analysis in site selectionof a local park situated in Bergamo Province, Italy. Theyfinally concluded that the method is effective to solve com-plex decisional problems in land-use planning. Pedrero et al.(2011) showed that how effective MCDM is in site selectionof aquifer recharge with reclaimed water. In 2008, NyomanRadiarta and his colleagues presented a GIS-based multi-criteria evaluation models to identify suitable sites for Japa-nese scallop (Mizuhopecten yessoensis) aquaculture in FunkaBay, Japan. All the mentioned studies present the results the

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100

Irrigated Agriculture Rain-fed Agriculture

Validity Percent

Validity Percent

Fig. 7 Validity of rain-fed andirrigated agriculture landcapability maps

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same as the research ahead. In 2011, Zaredar and KheikhahZarkesh despite confirmation of usefulness of MCDM inbeing fast, easy and low expenses, concluded that the methodhas some inefficiencies such as sensitivity to the decision-makers’ idea. The result is partly inconsistent with theachievements of the current study.

Due to the low-efficiency of the rain-fed agriculture in thewatershed, it is proposed to be allocated suitable lands to thiskind of land use. Besides, it is suggested that by combinationof two methods MCE and FAO, a new method under the titleof FAO-MCE is provided to determine the suitability of thewatershed for diff erent farming crops.

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