A Remote Sensing (RS) and Geographic Information System (GIS) Approach to Estimating Electric Power Consumption: A Case of Sokoto Metropolis, Sokoto State, Nigeria

Journal Title: International Journal of Management, IT and Engineering - Year 2012, Vol 2, Issue 9

Abstract

Electricity consumption forecast for any city in Nigeria is an inexact estimate, as electricity workers are not aware of the size and rate of city expansion. This study therefore forecast electricity consumption of residential land use for Sokoto metropolis for 2020 using RS and GIS. 1986 and 2005 land use maps, 1986 Landsat TM and 2005 ETM+, 2003 Quickbird image, electricity consumption and building area coverage data from snowball-sampled 49 residential homes were combined within ArcGIS and Idrisi Andes environments. Each electric meter was observed for 30 minutes, then consumption and GPS location of each building were recorded, after which building areas were digitized from the Quickbird image. Area coverage was correlated with consumption. Also, the landsat data were classified into wetland, built up, baresurface and green area at 91% and 87% accuracies, producing. The land cover of 2020 was projected with Marcov Chain Analysis. The built up was extracted from each land cover map and was masked by non-residential land uses within the built up. Growth rate of non-residential land uses within the built up was estimated. Results showed a high positive correlation of 0.63 between building size and electricity consumption which is statistically significant at 99% confidence level. Residential land use expanded by 122% between 1986 and 2005 at an annual rate of 1.9 Km2. Non-residential land uses within the built up expanded by 50.4% at 0.33Km2 annual rate. Between 2005 and 2020, residential land use would have expanded by 31% and nonresidential land uses within the built up by 27%. The 2020 electricity consumption for residential land use was estimated as 3,412,000Kwh. With the current scenario signaling jeopardy for the realization of vision 2020, more funding of the sector by the government and adoption of improved method of management such as the application of RS and GIS by the Power Holding Company of Nigeria (PHCN) are recommended.

Authors and Affiliations

Nathaniel Bayode ENIOLORUNDA, Ibrahim Mustapha DANKANI and Nuradeen YUSUF

Keywords

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  • EP ID EP18556
  • DOI -
  • Views 245
  • Downloads 9

How To Cite

Nathaniel Bayode ENIOLORUNDA, Ibrahim Mustapha DANKANI and Nuradeen YUSUF (2012). A Remote Sensing (RS) and Geographic Information System (GIS) Approach to Estimating Electric Power Consumption: A Case of Sokoto Metropolis, Sokoto State, Nigeria. International Journal of Management, IT and Engineering, 2(9), -. https://europub.co.uk/articles/-A-18556