Suitability analysis for rice growing sites using a multicriteria evaluation and GIS approach in great Mwea region, Kenya
© Kihoro et al.; licensee Springer. 2013
Received: 20 February 2013
Accepted: 12 June 2013
Published: 17 June 2013
Land suitability analysis is a prerequisite to achieving optimum utilization of the available land resources. Lack of knowledge on best combination of factors that suit production of rice has contributed to the low production. The aim of this study was to develop a suitability map for rice crop based on physical and climatic factors of production using a Multi-Criteria Evaluation (MCE) & GIS approach. The study was carried out in Kirinyaga, Embu and Mberee counties in Kenya. Biophysical variables of soil, climate and topography were considered for suitability analysis. All data were stored in ArcGIS 9.3 environment and the factor maps were generated. For MCE, Pairwise Comparison Matrix was applied and the suitable areas for rice crop were generated and graduated. The current land cover map of the area was developed from a scanned survey map of the rice growing areas. According to the present land cover map, the rice cultivated area was 13,369 ha. Finally, we overlaid the land cover map with the suitability map to identify variances between the present and potential land use. The crop-land evaluation results of the present study showed that, 75% of total area currently being used was under highly suitable areas and 25% was under moderately suitable areas. The results showed that the potential area for rice growing is 86,364 ha and out of this only 12% is under rice cultivation. This research provided information at local level that could be used by farmers to select cropping patterns and suitability.
KeywordsRice production area Bio-physical Factors Climatic factors GIS Land use variance Land suitability analysis
Rice is rapidly becoming a major food in much of sub-Saharan Africa and is set to overtake maize, cassava, sorghum, and other cereals in the near future. The demand is driven as much by population growth as by urbanization. In addition, the high cost of fuel makes rice attractive as it can be prepared quickly and with less energy requirement (Mati and Nyamai 2009). Within Kenya, the demand for rice continues to grow as more Kenyans make changes in their eating habits, and as urban population increases. Rice is currently the third most important cereal crop after maize and wheat. Rice is gaining popularity among the rural folk as well and consumption has risen dramatically over the last three years to stand at 300,000 metric tons per annum. But the annual ranges between 40,000 and 80,000 t. The deficit is met through imports (Mati et al. 2011).
Optimizing rice production can be achieved through sustainable agriculture or farming. The concept of sustainable agriculture or farming involves producing quality products in an environmentally benign, socially acceptable and economically efficient way (Addeo et al. 2001), ensuring optimum utilization of the available natural resource for efficient agricultural production. In order to comply with these principles of sustainable agriculture, one has to grow the crops where they suit best and for which first and the foremost requirement is to carry out land suitability analysis (Nisar Ahamed et al. 2000). Suitability is a function of crop requirements and land characteristics (Mustafa et al. 2011). Matching the land characteristics with the crop requirements gives the suitability. So, ‘Suitability is a measure of how well the qualities of a land unit match the requirements of a particular form of land use’. (FAO 1976). Land suitability analysis has to be carried out in such a way that local needs and conditions are reflected well in the final decisions (Prakash 2003).
Multi-Criteria Evaluation (MCE) approaches and GIS is useful because various production variables can be evaluated and each weighted according to their relative importance on the optimal growth conditions for crops (Perveen et al. 2007). However, the overlay procedure possible in GIS does not enable one to take into account that the underlying variables are not equally important (Janssen and Rietveld 1990). One approach that can help overcome such limitations is MCE, which has received renewed attention within the context of GIS-based decision-making (Pereira and Duckstein 1993). The objective of using MCE models is to find solutions to decision-making problems characterized by multiple alternatives, which can be evaluated by means of decision criteria (Jankowski et al. 2001). In this study, we applied Analytical Hierarchy Process (AHP) in integrating MCE with GIS. The specific objectives of this research were to develop a suitability map for irrigated paddy rice crop (Oryza sativa) based on physical and climatic factors of production and to identify potential areas for expanding and optimizing rice production in a rice producing area of Kenya.
Materials and method
The research was carried out in Kirinyaga, Mbeere and Embu counties in Kenya. It is bounded by latitudes 37°13′E and 37°56′E and longitudes 0°10′S and 0°54′S. Annual average precipitation is 950 mm, with the long rains falling between March and May, while the short rainy period is between October and December. The three counties are within the central and Eastern administrative provinces of Kenya. The surface area covers approximately 428,339 hectares.
The area traverses three agro-climatic zones, with maximum moisture availability ratios ranging from 0.65 for zone III toward the highland slopes, to 0.50 for the vast area covered by zone IV, and to 0.4 for the semi-arid zone V (Sombroek et al. 1982). Moisture availability zones are based on the ratio of the measured average annual rainfall to the calculated average annual evaporation. The area is generally hot, with average temperatures ranging between 23 and 25°C, having about 10°C difference between the minimum temperatures in June/July and the maximum temperatures in October/March.
Parameters for suitability analysis
Expert opinion of crop specialist was critical in this phase. Literature review of various references, interviews with local agronomists and researchers at Mwea Irrigation and Agricultural Development Centre (MIAD) and desk search of available data helped in identifying the critical requirements for suitable rice growing areas. The factors identified were related to climate (humidity and temperature), soil (soil texture, soil pH, soil drainage) and topography (slope).
Assigning weight of factors and multi-criteria evaluation (MCE)
Suitability levels of the six parameters
Very low suitability
30 – 60%
15 – 25
S-somewhat excessively drained
Moderately low suitability
15 – 30%
25 - 40
19 - 18
4.0 – 5.0
V-very poorly drained
8 – 15%
40 - 50
34 - 35
7.8 – 8.4
Moderately high suitability
5 – 8%
50 - 65
21 - 20
5.1 – 5.5
M-moderately well drained
2 – 5%
65 - 80
31 - 33
7.4 – 7.8
P- poorly drained
Very high suitability
0 - 2%
22 - 30
5.6 – 7.3
Seven-point weighing scale for pair-wise comparison
very low suitability
moderately low suitability
moderately high suitability
very high suitability
Pair wise comparison matrix of criteria in AHP
CR = 0.08
∑ = 1
In the diagonal, elements are assigned the value of unity (i.e., when a factor is compared with itself). Since the matrix is symmetrical, only the lower triangular half actually needs to be filled in. The remaining cells are then simply the reciprocals of the lower triangular half (for example, because the rating of Temperature relative to Topography is 3, the rating of Topography relative to Temperature will be 1/3).
Where: λmax: The maximum eigen value
CI : Consistency Index
CR : Consistency Ratio
RI : Random Index
n: The numbers of criteria or sub-criteria in each pairwise comparison matrix
Once the composite layers and their weights were obtained, the MCE procedure within Arc GIS 9.3 was applied to produce the map of suitable areas. The suitability map for rice crop (Figure 3) was identified by weighted overlay using spatial analyst tools in ArcGIS 9.3.
Present land use under rice cultivation
For this research, in order to generate the present Land use under rice growing ground survey map of the scheme area and outgrowers main blocks was obtained from MIAD and JICA. The map was scanned and digitized using Arc GIS 9.3. In order to use these types of data in GIS it was necessary to align it with existing geographically referenced data, the map generated and georeferenced to Arc_1960_ UTM_Zone_36N of WGS 1984.
Overlay present land use/cover and the suitability map
The present land use/land cover map under rice cultivation and the suitability map for rice crop were overlaid to identify differences as well as similarities between the present land use and the potential land use. For rice crop, a cross table between the map of suitable areas and the land use/land cover map was obtained. In this way, we obtained useful information concerning the spatial distribution of different suitability levels. This phase allowed us to fine-tune our results, because the resultant layer provided the information about how the rice crop was distributed across the various land suitability zones.
Results and discussions
Suitability map for rice crop
According to a related study in the Tana delta, Kuria et al. (2011), found the number of hectares available to each suitability class in the Tana delta area to be distributed as follows: 67% is highly to moderately suitable, 14% is moderately suitable, and 10% is marginally suitable. About 9% of the study area classified as Eutric Fluvisol was found to be currently unsuitable for rice cultivation, due to some limitation factors such as partly sandy clay texture, saline, low water retention, and high hydraulic conductivity. Dengiz (2013) did a similar study in Çankırı-Kızılırmak district in the Central Anatolian region of Turkey and found that the land highly and moderately suitable for rice cropping covered an area of about 837.3 ha (55.5%). Of the study area, 34% was unsuitable for rice, and those areas corresponded to adverse soil physical and chemical properties.
Present land use under rice cultivation
Overlay present land use/cover
Total potential area for rice growing
Suitable area for rice growing
Area under rice growing
Potential area for rice growing
Proportion of current rice production areas within the identified suitable areas
The results of this investigation were adequate in terms of the evaluation criteria set used here because, in a particular project, only a limited number of land qualities need be selected for use in evaluation (FAO 1993). In this investigation, the evaluation criteria were selected taking into consideration the crop requirements regarding local conditions. In this MCE, the factors were selected based on agronomic knowledge of local experts and reviews of existing literature. Such an approach produced valuable information on the relative importance of the factors under evaluation and could be a useful precedent for future studies of rice and other crops. This investigation also provides general alternatives for local farmers in the area of agricultural land management of a particular crop.
Conclusions and recommendations
In this study, we applied spatial analysis techniques to identify suitable areas for rice crop. The results obtained from this study indicate that the use of GIS and application of Multi-Criteria Evaluation using AHP could provide a superior database and guide map for decision makers considering crop substitution in order to achieve better agricultural production. This approach has been used in some studies in other countries. However, in Kenya this approach is a new and original application in agriculture, because it has not been used to identify suitable areas for rice crop. The study clearly brought out the spatial distribution of rice crop derived from digitizing data in conjunction with evaluation of biophysical variables of soil and topographic information in GIS context is helpful in crop management options for intensification or diversification.
This investigation is a biophysical evaluation that provides information at a local level that could be used by farmers to select their cropping pattern. Additionally, the results of this study could be useful for other investigators who could use these results for diverse studies. For further study, we propose to select more number of factors like soil, climate, irrigation facilities and socio-economic factors which influence the sustainable use of the land.
Analytical Hierarchy Process
Geographic Information System
Multi Criteria Decision Analysis
Multi-criteria Decision Making
Pairwise Comparison Matrix
Shuttle Radar Topographic Mission
Universal Transverse Mercator.
The authors would like to show sincere gratitude to African Association of Remote Sensing of Environment (AARSE) for awarding me the travel fellowship to attend the recent 9th international conference where this research was presented during the conference. Lots of thanks to the sample farmers (interviewees) who willingly accepted the interview. We are also grateful for Mwea Irrigation and Agricultural Development Centre (MIAD) agronomist, National Irrigation Board (NIB) and Water User’s Association (WUA) who helps us arranged the interview and the provision of the data required for this study. Thanks a lot to Faith maina for the guidance and moral support during the paper writing. The last but not the least is the research financiers JKUAT-RPE/NCST.
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