Using Geographically Weighted Regression to estimate the spatial patterns of fuelwood utilization in Nigeria
Research output: Contribution to journal › Article › peer-review
While the use of fuelwood for cooking among households in the various states of Nigeria supersedes any other cooking fuel type, the consumption pattern is spatially heterogeneous in the country. This paper uses Nigerian socio-economic data and fossil fuel distribution data obtained from the National Population Commission and the Nigerian Petroleum Corporation respectively to identify the diverse spatial pattern of fuelwood utilization in Nigeria, using Geographically Weighted Regression (GWR) model (local regression). The results of the local regression model coefficients highlights the relationships of fuelwood usage with its impact factors, as well as the spatial variations in the use of fuelwood amongst the 36 states of Nigeria (and Abuja the capital city). The analysis of these results, supported by the existing literature, leads to the conclusion that the northern part of the country uses more fuelwood than the south, which is closely related to the region’s socio-economic activities. This method reveals the local aspects of the relationships which may be concealed when qualitative analysis or global regression (which assumes that one model fits all) are used.
|Journal||American Journal of Geographic Information System|
|Publication status||Published - Jul 2014|
- Using Geographically Weighted
Final published version, 964 KB, PDF document
Licence: CC BY