LAND SUITABILITY FOR RICE CROP FARMING IN KWARA STATE USING GIS-BASED MULTI-CRITERIA DECISION ANALYSIS Land suitability for rice cultivation

##plugins.themes.bootstrap3.article.main##

Ayo Babalola
Mohammed Idrees
Ruth Aniyikaiye
Hossein Ahmadu
Oyedapo Ipadeola

Апстракт

This study employs GIS-based multi-criteria decision approach to identify suitable areas for cultivating rice crop in Kwara State, Nigeria, using essential climatic, soil, terrain and environmental variables selected based on FAO framework for land evaluation. Weights indicating the relative importance of each variable was determined using Analytical Hierarchical Process (AHP). The criteria, their weights and constraints were integrated in GIS environment to produce suitability map, classified into five levels of suitability (Very highly suitable, highly suitable, moderately suitable, low suitable and not suitable) using weighted overlay operation. The result indicates that 9.7% (343803.75 ha) of the total land area is unsuitable for cultivating rice while 14.6% (516169.46 ha) is classified as low suitable area. The moderately suitable, highly suitable and very highly suitable classes occupy 30.8% (1091145.20 ha), 40.56% (1436504.55 ha) and 4.4% (154408.94 ha), respectively. Quantitative assessment of the work yields overall accuracy (area under the ROC curve) of 0.97 (97%). Based on the findings of this study, we recommend that the state land use planning agency review zoning mechanism, incorporates grassroot participatory land use planning policy and evaluate suitable land for other essential crops by incorporating GIS in order to sufficiently allocate lands for optimal utilization.

Downloads

Download data is not yet available.

##plugins.themes.bootstrap3.article.details##

Рубрика
Articles

Референци

Abach, R. O., & Ngigi, M. M. (2016). Land suitability study for rice growing in Kisumu county. International Journal of Geomatics and Geosciences, 7(1), 33–42.
Abah, R. C., & Petja, B. M. (2016). Crop Suitability Mapping for Rice, Cassava, and Yam in North Central Nigeria. Journal of Agricultural Science, 9(1), 96. https://doi.org/10.5539/jas.v9n1p96
Ahmed, G. B., Shariff, A. R. M., Idrees, M. O., Balasundram, S. K., & Bin Abdullah, A. F. (2017). Gis-based land suitability mapping for rubber cultivation in seremban, malaysia. International Journal of Applied Engineering Research, 12(20), 9420–9433.
Anees, M. M., Mann, D., Sharma, M., Banzhaf, E., & Joshi, P. K. (2020). Assessment of urban dynamics to understand spatiotemporal differentiation at various scales using remote sensing and geospatial tools. Remote Sensing, 12(8). https://doi.org/10.3390/RS12081306
Babatunde, R., Omoniwa, A., & Aliyu, J. (2019). Post-Harvest Losses along the Rice Value Chain in Kwara State, Nigeria: An Assessment of Magnitude and Determinants. Cercetari Agronomice in Moldova, 52(2), 141–150. https://doi.org/10.2478/cerce-2019-0014
Bagheri, M., Sulaiman, W. N. A., & Vaghefi, N. (2012). Land use suitability analysis using multi criteria decision analysis method for coastal management and planning: a case study of Malaysia. Journal of Environmental Science and Technology, 5(5), 364–372. https://doi.org/10.3923/jest.2012.364.372
Ceballos-Silva, A., & López-Blanco, J. (2003). Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and land use/cover mapping: A case study in Central Mexico. Agricultural Systems, 77(2), 117–136. https://doi.org/10.1016/S0308-521X(02)00103-8
Daniel, O. A. (2011). Determining Rice Productivity Level for Sustainable Agricultural Development in. Journal of Sustainable Development in Africa, 13(5), 125–135.
Falola, A., Animashaun, J. O., & Olorunfemi, O. D. (2014). Determinants of Commercial Production of Rice in Rice-Producing Areas of Kwara State , Nigeria. Albanian Journal of Agricultural Science, 13(2), 59–65.
Hao, N. H., Van, P. Van, & Ha, K. M. (2019). Applying AHP method and GIS to evaluate land suitability for paddy rice crop in Quang Xuong district, Thanh Hoa province. Can Tho University Journal of Science, Vol.11(3)(3), 1. https://doi.org/10.22144/ctu.jen.2019.032
Jeevalakshmi, D., Reddy, S. N., & Manikiam, B. (2016). Land cover classification based on NDVI using LANDSAT8 time series: A case study Tirupati region. International Conference on Communication and Signal Processing, ICCSP 2016, 560056, 1332–1335. https://doi.org/10.1109/ICCSP.2016.7754369
Kaaya, A. K., Winowiecki, L., Slater, B. K., Sciences, G., & Resources, N. (2019). Multi-criteria Land Evaluation for Rice Production using GIS and Analytic Hierarchy Process in Kilombero Valley, Tanzania. 18(2), 88–98.
Khattak, P., & Shabbir, R. (2012). Temporal Analysis of Wheat Yield and Climatic Trends in Pakistan. Elixir Agriculture, 52(10), 11598–11603. https://doi.org/10.5829/idosi.wasj.2013.24.10.1714
Kihoro, J., Bosco, N. J., & Murage, H. (2013). Suitability analysis for rice growing sites using a multicriteria evaluation and GIS approach in great Mwea region, Kenya. SpringerPlus, 2(1), 1–9. https://doi.org/10.1186/2193-1801-2-265
Kumar, R., & Patel, G. R. (2020). Assessment of Agro-Land Suitability for Rice (Oryza sativa L.) in Bhal Area of Gujarat Using GIS and Remote Sensing. International Journal of Current Microbiology and Applied Sciences, 9(4), 1207–1214. https://doi.org/10.20546/ijcmas.2020.904.143
Maddahi, Z., Jalalian, A., Zarkesh, M. M. K., & Honarjo, N. (2017). Land suitability analysis for rice cultivation using a GIS-based fuzzy multi-criteria decision making approach: Central part of amol district, Iran. Soil and Water Research, 12(1), 29–38. https://doi.org/10.17221/1/2016-SWR
McCauley, A., Jones, C., & Jacobsen, J. (2009). Soil pH and Organic Matter. Nutrient Management Module No. 8, 8, 1–12.
Merem, E. C., Twumasi, Y., Wesley, J., Isokpehi, P., Shenge, M., Fageir, S., Crisler, M., Romorno, C., Hines, A., Hirse, G., Ochai, S., Leggett, S., & Nwagboso, E. (2017). Analyzing Rice Production Issues in the Niger State Area of Nigeria’s Middle Belt. Food and Public Health, 7(1), 7–22. https://doi.org/10.5923/j.fph.20170701.02
Mukti, A., Prasetyo, L. B., & Rushayati, S. B. (2016). Mapping of Fire Vulnerability in Alas Purwo National Park. Procedia Environmental Sciences, 33, 290–304. https://doi.org/10.1016/j.proenv.2016.03.080
NPC. (2006). Nigeria Population Census - 2006. Nigeria Data Portal. https://nigeria.opendataforafrica.org/ifpbxbd/state-population-2006
Olaleye, A. O., Akinbola, G. E., Marake, V. M., Molete, S. F., & Mapheshoane, B. (2008). Soil in suitability evaluation for irrigated lowland rice culture in southwestern nigeria: Management implications for sustainability. Communications in Soil Science and Plant Analysis, 39(19–20), 2920–2938. https://doi.org/10.1080/00103620802432824
Oriola, E., & Olabode, A. (2014). Geodatabase for Sustainable Rice Production in Kwara State. International Journal of Advanced Biological Research, 4(1), 36–47.
Ouri, A. E., Golshan, M., Janizadeh, S., Cerdà, A., & Melesse, A. M. (2020). Soil Erosion Susceptibility Mapping in Kozetopraghi. Land, 1–18. https://doi.org/doi:10.3390/land9100368
Park, S., Im, J., Jang, E., Rhee, J., & Basin, P. R. (2019). Fuzzy AHP Integrated with GIS Analyses for Drought Risk Assessment : A Case Study from Upper. Agricultural and Forest Meteorology, 216, 157–169. http://dx.doi.org/10.1016/j.agrformet.2015.10.011
Saaty, T. L. (2004). Decision making — the Analytic Hierarchy and Network Processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1–35. https://doi.org/10.1007/s11518-006-0151-5
Sadiq, M. S., Singh, I. ., & Yakubu, G. . (2017). Global Warming Potentials of Lowland Paddy Rice Production in Kwara State of Nigeria : Lessons for Sustainable Agriculture. International Journal of Research in Agriculture and Forestry, 4(9), 20–32.
Samanta, S., Pal, B., & Pal, D. K. (2011). Land Suitability Analysis for Rice Cultivation Based on Multi-Criteria Decision Approach through GIS. International Journal of Science & Emerging Technologies, 1, 12–20.
Shabani, S., Reza, H., & Blaschke, T. (2020). Forest stand susceptibility mapping during harvesting using logistic regression and boosted regression tree machine learning models. Global Ecology and Conservation, 22, e00974. https://doi.org/10.1016/j.gecco.2020.e00974
Sinha, D. D., Singh, A. N., & Singh, U. S. (2014). Site suitability analysis for dissemination of salt-tolerant rice varieties in Southern Bangladesh. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 40(8), 961–966. https://doi.org/10.5194/isprsarchives-XL-8-961-2014
Suhairi, T. A. S. T. M., Jahanshiri, E., & Nizar, N. M. M. (2018). Multicriteria land suitability assessment for growing underutilised crop, bambara groundnut in Peninsular Malaysia. IOP Conference Series: Earth and Environmental Science, 169(1). https://doi.org/10.1088/1755-1315/169/1/012044
Taherdoost, H. (2018). Decision Making Using the Analytic Hierarchy Process ( AHP ); A Step by Step Approach. International Journal of Economics and Management System, February.
Tien, D., Le, H. Van, & Hoang, N. (2018). Ecological Informatics GIS-based spatial prediction of tropical forest fi re danger using a new hybrid machine learning method. Ecological Informatics, 48(April), 104–116. https://doi.org/10.1016/j.ecoinf.2018.08.008
Ujoh, F., Igbawua, T., & Ogidi Paul, M. (2019). Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data. Geo-Spatial Information Science, 22(4), 332–344. https://doi.org/10.1080/10095020.2019.1637075
Victor, O. K., & Samson, A. O. (2019). An Application of GIS-Based Multi-Criteria Decision Making Approach for Land Evaluation and Suitability Mapping for Rice Cultivation in Oye-Ekiti, Nigeria. Journal of Agriculture and Environmental Sciences, 8(1), 0–9. https://doi.org/10.15640/jaes.v8n1a3