Analysis of Sensor Imaging and Field-Validation for Monitoring, Evaluation and Control Future Flood Prone Areas along River Niger and Benue Confluence Ecology, Lokoja, Nigeria
Abstract
The study area often suffered from flood for the last two year resulting to ecological damages including farmlands, infrastructures, property damage, loss of life and degradation of land-cover. Flood prone areas assessment is conducted using sensor data from space-borne optical sensors with cross-validation by ground-truthing the study area along the two major rivers that converge at Lokoja, otherwise called river-confluence. Maximum likelihood classification (MLC) and ISO-clustering unsupervised classification method of Arcmap-10.1 using NigeriaSat-1 data is applied to the regimes of up-stream and down-stream of River Niger and River Benue respectively. Based on ground truthing of the study areas, classification of inundated areas closely connected with actual flood prone area was developed. The results of the classifications of flood prone areas were displayed on satellite imagery, of which the percentage differences of change detected from variations of 16 class of land-use (LU) and land-cover (LC) using optical sensor shows that wetland flood plain comprising of runoffs-routes and lowland areas recorded the highest of 14.42% using MLC and 16.02% using ISO-DATA. In the final analysis, the classification accuracy conducted shows that the ecology of flood prone areas can be adequately classified using MLC (54.89%) and ISO-clustering unsupervised classification (45.11%). In the same vein, the result of regression function shows high correlation coefficient of 0.6242 (62%) and high strength in their relationship of which the potential flood runoff-route did correlate with the state of the location of the study area. It is anticipated that remote-sensing data integrated from optical sensors could be used to supplement up-stream, down-stream and runoffs-route to monitor, evaluate and detect floods prone areas. It is therefore significant that government and relevant agencies adopts these findings to help in the monitoring, evaluating and control of future ecological disasters.
Keywords:Analysis, lokoja,river niger, river benue, confluence, monitor, evaluate, control, ecology, flood, spatial, temporal
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ISSN (Paper)2224-3216 ISSN (Online)2225-0948
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