IIARD International Institute of Academic Research and Development

IIARD INTERNATIONAL JOURNAL OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT (IJGEM )

E-ISSN 2504-8821
P-ISSN 2695-1878
VOL. 10 NO. 9 2024
DOI: 10.56201/ijgem.v10.no9.2024.pg126.145

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Spatial Pattern of Landuse/Landcover and Flood Management Strategies by Vulnerable Communities in Kogi State, Nigeria

Innocent E. BELLO, Isaac A. AGBANWU, Ismaila K. ISHAYA, Sunday Y. KPALO

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Abstract

Flood is among the most recurring and devastating natural hazards causing colossal loss of lives and severe economic damages throughout the world. Kogi State in Nigeria, because of its confluence nature, experiences perennial flooding which this study seeks to examine. The objectives of this study includes to: identify and map landuse/land cover dynamics as they accelerate flooding, identify and examine the effects of flood risk on vulnerable communities, and examine the flood management practices in Kogi State. LandSat satellite images obtained from USGS Global Land Cover Facility website of different epochs (2000, 2005, 2010, 2015, 2020 and 2024) were used to model the variations in the spatial pattern of landues/landcover (LULC) changes. ENVI Remote Sensing Software was used to carry out digital image processing of the images and then classify the images into Crop, Settlement, Water and Island. ASTER elevation image data (DEM) of 30m Resolution was used to create terrain model of Kogi State to show regions of low lands that easily get flooded. The ArcGIS 10.5 was used to create the map layouts. The vulnerable communities to flood were geo-tagged using the Garmin 72+ handheld GPS. Using simple random sampling technique, a total of 418 copies of questionnaire sampled across the three senatorial zones of Kogi State: Kogi East - 197 (44.94%), Kogi West - 112 (27.89%), and Kogi Central - 109 (27.16%)) were analyzed using descriptive statistics, including graph and tables. 418 copies of questionnaires administered to residents were used to examine the impact of flooding on vulnerable communities at risk of flooding. The study reveals that the 2020 and 2024 images had scan and cloud cover errors; hence, they were excluded from further analyses. LULC change was considered to be partly responsible for flood in the vulnerable communities as most crop lands had been converted to settlements. The identified major vulnerable communitie

keywords:

Flood Management, Vulnerable Communities, Landuse/Landcover, Remote Sensing/GIS

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