The Egyptian Journal of Remote Sensing and Space Sciences (2015) 18, 181–193

HO ST E D BYNational Authority for Remote Sensing and Space Sciences

The Egyptian Journal of Remote Sensing and Space

Sciences

www.elsevier.com/locate/ejrswww.sciencedirect.com

RESEARCH PAPER

Identification of suitable sites for organic farming

using AHP & GIS

* Corresponding author. Tel.: +91 7351206000.

E-mail address: iirs.deeps@gmail.com (S. Deep).

Peer review under responsibility of National Authority for Remote

Sensing and Space Sciences.

http://dx.doi.org/10.1016/j.ejrs.2015.06.0051110-9823 � 2015 Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Ashutosh Kumar Mishra, Shikhar Deep *, Abhishek Choudhary

School of Environment & Natural Resources, Doon University, Dehradun 248001, India

Received 9 November 2014; revised 10 May 2015; accepted 22 June 2015

Available online 14 July 2015

KEYWORDS

Organic farming;

AHP;

GIS;

Rural tourism;

Site suitability

Abstract Uttarakhand is covered with 64.76% of its area under Himalayan forest providing the

exquisite biodiversity and differences in climate with a miscellany of flora and fauna. Therefore cre-

ates great scope for the development of organic farming in rural areas to boost the rural economies.

But organic farming is not very much evolved in this state due to lack of adequate transportation

services and other socioeconomic reasons. Remote sensing and GIS can play an important role in

the identification of the suitable zones for the development of organic farming in more facile man-

ner. In this paper a methodology is proposed to identify the suitable zones in the state for the devel-

opment of the organic farming using Analytical Hierarchy Process (AHP) and Geospatial

techniques to boost rural economies and promote rural tourism to make self-sustainable villages.

This study represents the efficacy of AHP and weighted overlay model for the site suitability anal-

ysis of organic farming in the study area.� 2015 Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This

is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/

4.0/).

1. Introduction

Uttarakhand is a state known for its biodiversity and climate

all over the world and having great potential for the develop-ment of rural tourism. Management of rural tourism isnecessary for the conservation and protection of natural trea-

sures with economic improvement of the local villagers.Uttarakhand has been facing challenges of different natural

disasters in recent years and due to unemployment, peoplefrom hilly areas are migrating towards the plains.

Environmental impacts due to land cover disturbance andtourism are also main problems in mountain regions (Booriet al., 2015). Organic farming can play an important role for

socio economic development and to make villages self-sustainable. Degradation of environmental quality and foodsafety concerns due to excess use of fertilizers promoted theorganic farming in recent decades (Lapple and Cullinan, 2012).

Organic farming has a great scope in the Uttarakhandbecause of its climatic and environmental conditions.Avoidance of the external inputs such as synthetic fertilizers

and pesticides makes its environmentally friendly. Organicfarming also lowers the nitrogen losses from soil and enhances

182 A.K. Mishra et al.

soil carbon sequestration (Leifeld, 2012). To get maximumproduction suitable land, local environmental and geologicalconditions are prime necessity. Identification of suitable sites

for organic farming or agriculture requires consideration ofdifferent climatic, topological environment and geophysicallimitations (Kamkar et al., 2014). Therefore accurate and

recent land use/land cover (LULC) and other geophysicaldata should be considered for assessing environmentalconcerns (Deep and Saklani, 2014). Geospatial tools can be

used for the identification of the suitable lands for the organicfarming on different criteria like soil quality, geology,drainage, topography of the place. This technique can alsohelp to identify and prioritize the potential sites for the organic

farming.Analytical Hierarchical Process (AHP) is used as a decision

making tool for the identification of suitable organic farming

sites. AHP was developed by Saaty (1980), for setting-up ahierarchical model based on criteria and alternatives for repre-senting the complex problems (Roig-Tierno et al., 2013). As a

multicriteria decision-making method, the AHP has beenapplied for solving a wide variety of problems that involve

Figure 1 The stud

complex criteria across different levels, where the interactionamong criteria is common (Feizizadeh et al., 2014; Tiwariet al., 1999).

Weighted overlay along with the AHP gives very promisingresult for the site suitability analysis of organic farming. It canbe used to multi-level hierarchical structure on different

criteria and constrains (Triantaphyllou and Mann, 1995;Boroushaki and Malczewski, 2008). The method has steps todetermine the relative importance of weights on each criteria,

before determining the final score (Bunruamkaew andMurayam, 2011). AHP is one of the promising methods usedfor the agricultural land suitability analysis based on individ-ual criterions through quantitative analysis (Chen et al.,

2010a; Akinci et al., 2013). Pair wise comparison method isused to estimate the overall weight of individual criteria or ele-ment. Integration of AHP and GIS helps in decision support

system by creation of suitability maps.GIS is used as a decision maker tool for the site suitability

analysis and for developmental activities (Khahro et al., 2014).

Land use suitability mapping and its analysis is one of the mostuseful applications of the GIS (Javadian et al., 2011).

y area (zone 1).

Identification of suitable sites for organic farming 183

Integration of GIS with multi criteria evaluation methodsreveals its extreme applicability in site suitability analysis.GIS technology is used to formulate different criteria maps

which are used in AHP to construct the site suitability modelfor organic farming (Xu et al., 2012).

Almost 78% of state population depending on agriculture

possesses a great scope of organic farming. The implementa-tion of organic farming in the state will not only boost therural economy but also promote the rural tourism and diversi-

fication of farmers and thus prevent the migration of peoplefrom hilly region. The cost of the productivity, net profit andthe total labor cost are key factors in adaptation of new tech-nologies like organic farming (Thapa and Rattanasuteerakul,

2011). So selection of appropriate land which is having themaximum productivity, maximum net profit on lesser inputis expected. Since very less area is available for organic farming

in the study area mainly because of natural resources and highelevation variation. Thus is a strong reason for the applicabil-ity of this study. The objective of this study is to find the suit-

Figure 2 Schematic represent

able areas for the organic farming using AHP and GIS in thestudy area.

2. Study area

The study area was chosen on the basis of UttarakhandTourism Development Master Plan 2007–2022. According to

this master plan Uttarakhand is divided into 7 zones. Zone1was taken as the study area shown in Fig. 1. The area liesbetween Latitude 30�110 26.04800N, Longitude 78�01047.61500E and the elevation of study area lies between the ele-vations of 133 to 2877 m. From the northeast, zone 1 is sepa-rated by Aglar River and by road connecting to Kalsi, and

from east by Kempty Falls, Mussoorie, Dhanaulti andChamba and in the west and south by the state boundariesof Himachal Pradesh and Uttar Pradesh respectively

(Uttarakhand Tourism Development Master Plan 2007–2022,2008). Study area is also important for the pilgrimage

ation of the methodology.

Figure 3 Site suitability model for organic farming.

Table 1 Sub-criteria for organic farming.

Criteria Sub criteria

1 = highest importance 2 = significant importance 3 = average importance 4 = slight importance 5 = lowest importance

Roads <5 km 5–10 km 11–20 km 21–40 km >40

Drainage <5 km 5–10 km 11–20 km 21–40 km >40

Slope 0–5� 5–10� 14–24� 24–34� 34–74�Soil Younger alluvium Bhabar soil Older alluvium Red and yellow soil Sub-mountainous soil

Geology Alluvium Neo-proterozoic Mid-miocene Pleistocene Pliocene

Table 2 AHP matrix.

Criteria Road Drainage Soil Slope Geology LULC

Road 1.00 0.25 0.25 0.17 0.50 0.17

Drainage 4.00 1.00 6.00 0.33 3.00 0.25

Soil 4.00 0.17 1.00 0.25 3.00 0.25

Slope 6.00 3.00 4.00 1.00 4.00 1.00

Geology 2.00 0.33 0.33 0.25 1.00 0.25

LULC 6.00 4.00 4.00 1.00 4.00 1.00

Weight 0.04 0.19 0.09 0.30 0.06 0.33

Scale: 1 – Equal importance, 3 – Moderate importance, 5 – Strong importance, 7 – Very strong importance, 9 – Extreme importance, 2,4,6 and 8

are intermediate values (Garcıa et al., 2014).

184 A.K. Mishra et al.

Table 3 Random inconsistency indices (RI) for N= 10.

N 1 2 3 4 5 6 7 8 9 10

RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.46 1.49

Identification of suitable sites for organic farming 185

and for the existing tourism sites like Dehradun, Mussoorie,Dhanaulti, Chamba, Rishikesh, Haridwar and Rajaji

National park.

3. Softwares and data used

Boundary map was generated using boundaries formUttarakhand tourism master plan 2007–2022, Vol. I. Thesoftwares used for this study were: Quantum GIS 2.2.0 used

Figure 4 Road networ

for digitization, ERDAS Imagine 2012 for rectification andArcGIS 10 for generation of criteria map and suitability model.

4. Methodology

In this study multi criteria site suitability analysis was done toidentify appropriate locations for organic farming based on a

group of criteria and constraints. Based on their importanceand significance in the organic farming six different criteriaand constrains were chosen. The selection of different criteria

was based on maximum limitation method that affects the pro-duct yield of organic farming which includes soil type, geology,slope, drainage, and availability of roads (Duc, 2006). Weights

for the each criterion were calculated using AHP and after thatweighted overlay was done to generate the suitability map.

k of the study area.

Figure 5 Drainage network of the study area.

186 A.K. Mishra et al.

The schematic representation of the methodology is shown inFig. 2.

4.1. Generation of criteria maps using GIS

Roads and drainage system maps were generated using

toposheets of Survey of India and open street map data.Soil and geology maps were generated using GeologicalSurvey of India map and NATMO geological map. Slope and

aspect were derived using ASTER data of 30 m resolution.LULC was generated using Landsat 8 of 15 m spatialresolution.

4.2. Standardization

All the criteria are in different units so to perform weightedoverlay they need to be in same units and hence needed tobe standardized. Standardization makes the measurementunits uniform, and the scores lose their dimension along with

their measurement unit (Effat and Hassan, 2013).All the vector layers shown in Fig. 3 were converted to ras-

ter further which were reclassified for the input to the weighted

overlay which finally gave the suitability map. Reclassify toolin Spatial Analyst of ArcGIS standardizes the values of all cri-teria for comparison.

Figure 6 Digital elevation map of the study area.

Identification of suitable sites for organic farming 187

The organic farming requires good soil and geology typewith having availability of drainage system for irrigation,roads are also important for the easy transportation of the

raw products. While Uttarakhand is a hilly state, slope and ele-vation also come under the decision making process whilechoosing suitable land for organic farming. For suitable site

selection all these criteria were taken into account during anal-ysis. All criteria were reclassified in five different classes. Thesub criteria were categorized on the scale of 1–5, 1 having

the highest importance and 5 having the lowest importanceshown in Table 1.

4.3. Determination of weights using AHP

AHP is used for a group of criteria, sub-criteria to set up thehierarchical structure by selecting the weightage of individualcriterion in whole decision making process. The weights reflect

the relative importance of each criterion and hence to beselected carefully. AHP can be applied to make pairwise com-parisons between the criteria and thus reduces the complexity(Saaty, 1977). It derives the weights by comparing pairwise the

relative importance of criteria, taken two at a time. Through apairwise comparison matrix, the AHP calculates the weighting

Figure 7 Slope map of the study area.

188 A.K. Mishra et al.

for each criterion by taking the eigenvector correspondingto the largest eigenvalue of the matrix, and then normaliz-ing the sum of the components to unity (Feizizadeh et al.,

2014).Using the AHP discussed above the pairwise comparison

matrix was generated by using scale of 1–9 in which 1 having

equal importance and 9 having extreme importance of in

between two criteria shown in Table 2 (Malczewski, 1999;

Saaty, 1980). The matrix generally has the property of

reciprocity, expressed mathematically as:n(n�1)/2 comparison

is used for n numbers of elements in pairwise comparison

matrix (Akinci et al., 2013). Once the pairwise matrix is made,

Saaty’s method of eigenvectors/relative weights is calculated.

AHP identifies and takes into account the inconsistencies of

the decision-makers which is its one of the strength (Saaty,1990; Garcıa et al., 2014). AHP efficiency criteria are measuredby Consistency Relationship (CR) which is estimated accord-

ing to Eq. (1).

CR ¼ CI

RIð1Þ

Figure 8 Soil map of the study area.

Identification of suitable sites for organic farming 189

CR represents a measure of the error made by the decision-maker or an indicator of the degree of consistency or inconsis-tency (Chen et al., 2010b). It indicates the likelihood that the

matrix judgments were generated randomly (Saaty, 1977;Park et al., 2011). The CR depends on the Consistency Index(CI) and Random Index (RI).

CI ¼ kmax � n

n� 1ð2Þ

Eq. (2) represents the CI where kmax is the largestor principal eigenvalue of the matrix, and n is the order ofthe matrix. RI is the average of the resulting consistency

index depending on the order of the matrix given by Saaty(1977) shown in Table 3. If the CR < 0.10 then the pairwise

comparison matrix is acceptable and the weight values arevalid. In our case the CR was 0.097 which is under acceptablelimits.

4.4. Generating land suitability model for organic farming

Suitability model was generated using ArcGIS 10 modeler by

combining all criteria maps and overlaying weighs of individ-ual criteria.

5. Results and discussions

The transportation of the raw product requires a well con-nected network of roads. So the land nearest to the roads

Figure 9 Geology map of the study area.

190 A.K. Mishra et al.

was given more importance and the road map is shown inFig. 4. The drainage network is shown in Fig. 5. Digital eleva-tion map was generated to show the height variation of the

study area shown in Fig. 6. The slope is also an importantparameter in the present study area; the lands having the min-imum slope were taken as the most suitable and have been

given the highest importance shown in Fig. 7. The soil andgeology type of the area is equally important for the organicfarming. The younger alluvial soil was found to be the most

suitable for the organic farming because it has clay and goodcapacity to bound water (Akınci et al., 2013) shown inFig. 8. The alluvium is given as the highest importance forthe organic farming because it is most suitable for farming

as it contains clay soil and retains moisture within it shown

in Fig. 9. LULC map was used to determine the available suit-able land for organic farming shown in Fig. 10.

The final site suitability map generated after weighted over-

lay for organic farming was divided in four classes i.e. mostsuitable (1212.77 sq. km), more suitable (434.45 sq. km.), lesssuitable (63.89 sq. km.) and not suitable (2816.43 sq. km.).

The study area being rich in natural resources (ReserveForests & Water Bodies) and also has huge variation in the ele-vation shows very less area suitable for the purpose. AHP gives

the most suitable areas which are most adequate with respectto the parameters considered as shown in Fig. 11. The darkgreen patches represent the most suitable area for the organicfarming while dark red patches represent the unsuitable area

for the organic farming.

Figure 10 LULC Map of the study area.

Identification of suitable sites for organic farming 191

6. Conclusions

The analysis of this study was mainly focused on the identifi-cation of the highly suitable land for organic farming in the

study area. AHP matrix with integration of GIS is used forthe analysis in which six different criteria were considered.The AHP with combination of GIS was found very usefulfor the suitable site identification. The final result can be

adopted for the decision making process of the organic farm-ing in the study area, as it gives insight in finding the suitableareas. The results can be more refined by critically analyzing

the techniques used. The study includes the physical parame-ters only and need to incorporate the social and economic

parameters. Since in AHP, the pairwise comparison is basedon expert opinions which are subjective. Any wrong judgmenton the any criteria can be easily conveyed to the weight assign-

ment (Kritikos and Davies, 2011). This is the main drawbackof the AHP technique (Nefeslioglu et al., 2013) and henceweights need to be assigned carefully. For more accurate and

beneficial results the study needs to be focused on some specificspecies like medicinal plants, which have great economic valueand covers scope of development of rural tourism too. The use

Figure 11 Suitability map for the organic farming in the study area.

192 A.K. Mishra et al.

of high resolution satellite data will aid in analyzing more finerareas. The identified zones have to be verified on ground level

with other local parameters before the final implementation.The study can be adopted for rest of zones and also incorpo-rating other domains of ecotourism than organic farming,which can flourish in that area.

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