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Application of GIS in Land Evaluation and Development of Suitability Map for Capsicum Production in Nairobi Peri-Urban Counties

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Application of GIS in Land Evaluation and Development of Suitability Map for Capsicum Production in Nairobi Peri-Urban Counties OPEN ACCESS Freely available online Journal of Remote Sensing & GIS Review Article Application of GIS in Land Evaluation and Development of Suitability Map for Capsicum Production in Nairobi Peri-Urban Counties 1 1* 1 2 3 4 5 6 Michelle AO , Gitari HI , Danga B , Raza MA , Kisaka OM , Elbeltagi A , Singh RJ , Soratto RP 1Department of Agricultural Science and Technology, Kenyatta University, Nairobi, Kenya; 2Department of Agronomy, Sichuan Agricultural University, Sichuan, China; 3Department of Agroforestry and Rural Development, University of Kabianga, Kenya; 4Agricultural Engineering Department, Mansoura University, Mansoura 35516, Egypt; 5Department of Agricultural Science, ICAR- Indian Institute of Soil and Water Conservation, Dehradun, India; 6Department of Crop Science, São Paulo State University (UNESP), Botucatu, São Paulo, Brazil ABSTRACT This study was carried out to determine the areas which are best suited for capsicum (Capsicum annuum L.) production in the peri-urban counties of Nairobi, Kenya. The study used a multi-criteria evaluation approach by applying the Analytic Hierarchy Process (AHP). Soil (pH, drainage, texture, and electrical conductivity), climate (temperature and rainfall), and topography (slope and elevation) were the main criteria selected from literature for the study. The AHP was used to determine the relevance of a criterion based on its cumulative weights as per the Saaty’s table. The cumulative weights were used to construct output maps using Quantum Geographic Information Software (QGIS) software. Crop suitability map was produced through overlaying of the different thematic maps and suitability levels were based on Food and Agriculture Organization (FAO) land suitability classification. The results showed that about 50% of land in Kiambu County, 8% in Kajiado County and 12% in Machakos County is suitable for capsicum production. The remaining areas were reported unsuitable for the production of the crop due to the presence of some limitations such as soil texture, soil pH, drainage and climate. The findings of this study will be useful to decision making and planning and for further studies. Keywords: Capsicum annuum; Land suitability analysis; AHP, GIS, Multi-criteria evaluation. INTRODUCTION Optimizing capsicum production is possible through sustainable farming, which entails cultivation of a crop in a conducive Soils fertility as determined by nutrient distribution is considered and favorable environment [2]. To practice this; crops need to to be one of the most important factors affecting productivity of be planted where they are most suited to grow. capsicum grows crops such as capsicum (capsicum annuum L.). capsicum is among best in hot/warm regions such as Eastern and Coastal Kenya the first plants to be domesticated and is normally referred as chili with altitudes of up-to 2000 m above the sea level with rainfall pepper plant due to its spicy or pungency nature [1]. In Kenya, of between 600–1250 mm per annum. The crop can grow well capsicum is a good source of income where it is both exported as in different soils; however, it prefers well-drained soils with an well as consumed locally. It is very rich in nutrients and vitamin, effective rooting depth of 400–700 mm, a soil pH of 5.5–6.8 and and can be consumed raw as a salad or cooked. Being a high-value adequate supply of nutrients [4,5]. capsicum grown in loamy to crop, its production has been decreasing over the last years. For sandy loamy soils with a soil electrical conductivity of <1000 µS instance, according to FAOSTAT, its production has been on the cm-1 produces better yields [5]. Annual temperature requirement decline in Kenya since 2014 [2]. Specifically, in 2014, 2015, 2016 for optimal seed and fruit development of capsicum ranges from and 2017 the country’s capsicum production was 2219, 2805, 2481 25°C to 30°C and 18°C to 20°C during the day and night and 2197 tons, respectively. This becomes a major concern that respectively [1]. Determining where capsicum is suited requires ought to be addressed given that majority of citizens depend on a detailed evaluation of land; such studies help match crop it [3]. requirements with land qualities [6]. According to Kato, selecting Correspondence to: Gitari HI, Department of Agricultural Science and Technology, Kenyatta University, Nairobi, Kenya; E-mail: [email protected]. ke Received: June 11, 2021; Accepted: June 25, 2021; Published: July 2, 2021 Citation: Michelle AO, Gitari HI, Danga B, Raza MA, Kisaka OM, Elbeltagi A, et al. (2021) Application of GIS in Land Evaluation and Development of Suitability Map for Capsicum Production in Nairobi Peri-Urban Counties J Remote Sens GIS 10. 290. Copyright: © 2021 Michelle AO, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. J Remote Sens GIS, Vol. 10 Iss. 6 No: 290 1 Gitari HI, et al. OPEN ACCESS Freely available online suitable crops using computers have been done before with soil, km²; it lies between latitude 1.12°S and 1.08°S, longitude of climate, geological, and geomorphological conditions being used between 36.52°E and 37.33°E, and an altitude of between 1800 as determining factors [7]. and 2100 m above the sea level. It falls in the upper midlands agro-ecological zone characterized as having medium potential for Geographic Information System (GIS) has been adopted by agricultural production [18]. It receives an average annual rainfall different sectors in national development but little has been done of 962 mm and an average temperature of 18.8°C. June and July to support decisions for development in agriculture. Petja et al [8]. are the coldest months while January–March and September– recommended the use of these technologies to improve quality of October are the hottest months. Acrisols, Alisols, Lixisols, and life. Previously, GIS has been applied under different scenarios. Luvisols are the dominant soils in Kiambu County; characterized For instance, [2] Ashraf assessed the suitability of growing wheat by increased clay content in the sub soil, low water storage (Triticum aestivum L.) using multi-criteria evaluation (MCE) capacity and with poor structure [9]. and GIS. It provided information that helped farmers select their cropping patterns. Stickler et al. (2007) produced maps that determined the production capabilities for soybean (Glycine max (L.) Merr.), sugarcane (Saccharum spp.), and oil palm (Elaeis guineensis Jacq.) [9]. Crop nutritional and ecological requirements were identified and the data was used to develop spatially explicit variables, which were used to determine suitable regions where the crops could be grown [1]. It has conducted crop suitability study for mapping of rice (Oryza sativa L.), cassava (Manihot esculenta (L.) Crantz), and yam (Dioscorea spp.) in Nigeria. In Philippines, [3] produced nutrient distribution and crop suitability maps for growth of rice, maize (Zea mays L.), coconut (Cocos nucifera L.), mango (Mangifera indica L.), bananas (Musa ssp.), and potatoes (Solanum tuberosum L.). In Kenya, Mugo et al. (2016) used GIS to identify suitable land for green gram (Vigna radiata L.) production in Kitui. They found out that all lands in Kitui are suited for green gram production. Kuria et al. (2011) used GIS technology to assess if rice could be Figure 1: A map showing the counties where study was carried grown in Tana Delta; suitability map was prepared to identify the out: Kiambu, Kajiado, and Machakos. various areas of suitability [10]. The study by Kihoro et al. (2013) Kajiado County borders Nairobi to the South with a total area investigated the suitability of growing rice in Mwea region using of 21,292.7 km²; it lies between latitude 2.01°S and 2.15°S, a MCE and GIS [11]. The result showed that 75% of the total longitude 36.02°E and 37.64°E, with altitudes of between 500 land already under production of rice was highly suitable, and and 2500 m above the sea level. The climate in Kajiado County only 25% was ranked as being moderately suitable. In Nyandarua is characterized by steppe with an average annual rainfall of 500 County, Kamau et al. (2015) determined potato suitability mm and an average temperature of 18.9°C. Rainfall is mostly analysis using GIS and remote sensing. The results revealed that received in the month of April, with August being the driest 38% of the agricultural land was best suited for growing potato month. It falls in the lowland’s midlands agro-ecological Zone with 51% and 11% being moderately and marginally suitable, [10]. Ferralsols, Vertisols, Cambisols, Leptosols and Acrisols are respectively. the main soils that dominate Kajiado County; characterized by uneven clay distribution with high sodium content [9]. Nonetheless, little has been done in determining the suitability of growing capsicum in Kenya. To fill this gap, the current study On the other hand, Machakos County borders Nairobi to the evaluated land in Kiambu, Kajiado and Machakos counties for West with a total area of 5,953 km²; it lies between latitude its suitability for capsicum production [12]. In an effort to apply 1.35°S and 1.44°S, longitude of between 36.94°E and 37.80°E, GIS technology, the study aimed at assessing the suitability of and an altitude of between 1000 to 2100 m above sea level. It growing capsicum based on critical factors considered to be falls in the upper highlands agro-ecological zone hence classified affecting its growth. This was achieved by determining soil as semi-arid [10]. It records an average annual rainfall of 830 mm properties, climatic and topographic characters, and utilizing GIS and an average temperature of 19.0°C. The County is dominated tools in the production of output maps (soil fertility map and by low fertile and easily erodible soils such as Alfisols, Ultisols, crop suitability maps).
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