Modelling vegetationloss and greenhouse gas emissions in Kaduna, Nigeria

Abstract

Tropical forests and other vegetated landscapes like grasslands and wooded savannahs play a major role in the global carbon sequestration process and their conservation and protection offers immense potential for reducing greenhouse gas emissions and global warming. This study aims to model the rate of vegetation loss as a result of diverse anthropogenic processes like urbanization, agriculture and infrastructural development in the fast growing city of Kaduna in northwest Nigeria . Land use change analysis between 1990 and 2009 is conducted and a transition potential map is produced based o n the established pattern of change and the land use change driver variables determined for the study area. This is achieved by a hybrid technique that integrates cellular automata, Markov chain analysis and artificial neural networks. The model is then us ed to predict land use change scenarios between 2001 and 2009 . Model validation is achieved by way of computing the ROC statistic using the simulated and actual land use maps of 2009 . Having obtained satisfactory outcomes, the model is then used to predict the urbanization scenario between 2009 and 2040 . Interventi ons are then proposed to reduce sprawl and loss of vegetated land based on certain constraints placed on the land use change processes and the sim ulation is then run again to 2040 to produce an alternative scenario of land use change to serve as a basis for the implementation of the REDD project. The REDD model utilizes a methodology for calculating and evaluating net anthropogenic greenhouse gas (GHG) emission reductions due to the implementation of a REDD project. This methodology is based on the World Bank’s BioCarbon Fund Project (BioCF) methodology for estimating reductions of GHG emissions for mosaic deforestation. Reductions in GHG emissions are calculated by subtracting the estimated carbon that would be saved through a REDD project intervention, along with the estimated carbon loss through leakage from the estimated carbon loss without the implementation of a REDD project intervention. The difference is known as additionality, and implies the net GHG emissions that are reduced owing to the implementation of the REDD project. The results obtained show significant reduction in GHG emissions based on the proposed planned interventions to reduce tropical land consumption and vegetation loss in Kaduna.