EFFECTS OF LAND USE ON FOOD SECURITY IN MALETE USING MACHINE LEARNING ALGORITHM AND GEOGRAPHIC INFORMATION SYSTEM (GIS)

Authors

  • Abimbola I. I. Department of Surveying and Geo-informatics, Institute of Environmental Studies, Kwara State Polytechnic, Ilorin, Kwara State- Nigeria
  • Tajudeen O. M. Department of Agricultural Technology, Institute of Applied Sciences, Kwara State Polytechnic, Ilorin, Kwara State- Nigeria

Keywords:

Land use, Food security, Machine learning algorithm, Geographic information system

Abstract

In Malete Kwara State, Nigeria rapid urbanization and population growth particularly following the establishment of the Kwara State University in 2009 have led to increased land use and modifications that threaten food security. However, the impact of these changes has not been systematically evaluated and the lack of comprehensive assessments using advanced technologies such as machine learning algorithms and Geographic Information Systems (GIS) limits our understanding of how LULC changes affect agricultural productivity and food availability. This research aims to detect the effects of land use on food security in Malete by employing machine learning algorithms to analyze the relationship between LULC changes and agricultural outcomes. The results show significant changes in land use of the community including growth in constructed areas, variations in grazing land, increased crop cultivation and changes in forest cover. Data reveals fluctuations in land coverage over the years with forests, cultivations, constructed areas and open range being the main categories studied. In terms of tree coverage, there was a noticeable shift over the studied period. In 2002, the area covered by trees was relatively small, with only 170.01 hectares. However, by 2012, there was a significant increase, indicating a positive trend in tree cover expansion with the area reaching 1596.19 hectares. Surprisingly, by 2022, the area decreased to 500.6 hectares, suggesting a potential reversal or change in land management practices. Similarly, the cultivation of crops showed fluctuating trends. In 2002, there were no crops recorded in the area under study. However, by 2012, a small area of 69.92 hectares was cultivated for crops indicating some level of agricultural activity. This area slightly increased to 92.89 hectares by 2022, suggesting a gradual but limited expansion of agricultural land use. The expansion of built-up areas was particularly notable over the studied period indicating significant urbanization or infrastructure development. In 2002, the area covered by built-up structures was 104.67 hectares. By 2012, this area more than tripled to 319.16 hectares, reflecting rapid urban expansion. Subsequently, in 2022, there was a further increase to 603.95 hectares, highlighting ongoing urban development and land transformation. Conversely, the open range area exhibited dynamic changes over time. In 2002, the largest land use category was open range, covering a substantial 3045.24 hectares. However, by 2012, there was a significant decrease in open range area to 1333.86 hectares, indicating potential land use conversion or management shifts. Interestingly, in 2022, there was a notable increase to 2121.69 hectares, suggesting some level of reversion or change in land use patterns. It was recommended that through collaborative partnerships and adaptive management practices, stakeholders can navigate the complex landscape of LULC dynamics and pave the way for a more sustainable and resilient future in Malete.

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Published

2026-04-16

How to Cite

Abimbola, I. I., & Tajudeen, O. M. (2026). EFFECTS OF LAND USE ON FOOD SECURITY IN MALETE USING MACHINE LEARNING ALGORITHM AND GEOGRAPHIC INFORMATION SYSTEM (GIS). International Journal of Novel Research in Science, Technology and Engineering, 9(1). Retrieved from https://www.publications.oasisinternationaljournal.org/index.php/ijnrste/article/view/95