Monitoring and forecasting spatio-temporal LULC for Akure rainforest habitat in Nigeria

Abstract

For several decades, Nigerian cities have been experiencing a decline in their biodiversity resulting from rapid land use land cover (LULC) changes. Anticipating short/long-term consequences, this study hypothesised the effects of LULC variables in Akure, a developing tropical rainforest city in south-west Nigeria. A differentiated trend of urban LULC was determined over a period covering 1999–2019. The study showed the net change for bare land, built-up area, cultivated land, forest cover and grassland over the two decades to be −292.68 km2, +325.79 km2, +88.65 km2, +8.62 km2 and −131.38 km2, respectively. With a projected population increase of about 46.85%, the study identified that the built-up land cover increased from 1.98% to 48.61%. The change detection analysis revealed an upsurge in built area class. The expansion indicated a significant inverse correlation with the bare land class (50.97% to 8.66%) and grassland class (36.33% to 17.94%) over the study period. The study observed that the land consumption rate (in hectares) steadily increased by 0.00505, 0.00362 and 0.0687, in the year 1999, 2009 and 2019, respectively. This rate of increase is higher than studies conducted in more populated cities. The Cellular Automata (CA) Markovian analysis predicted a 37.92% growth of the study area will be the built-up area in the next two decades (2039). The 20-year prediction for Akure built-up area is within range when compared to CA Markov prediction for other cities across the globe. The findings of this study will guide future planning for rational LULC evaluation.

Spatio-Temporal Evaluation of Urban Growth of Zuru Metropolis, Nigeria

“…The LAC between 2008-2018 was also higher than between 1988-1998. The overall LAC between 1988-2018 was 0.0444, which was higher than the LAC (0.127) for a period of 1999-2019 for Akure, Ekiti state of Nigeria.as reported by Aliyu et al (2020).…”

“…It requires land area of the city (built-up) in hectares and the corresponding population size, for the respective years of interest (Aliyu et al, 2020). The estimated built-up area was obtained from the classified maps (Figure 4).…”

“…This result signified an expansion in urban space of the study area. The built-up area class is the most important predictor of urban area expansion (Aliyu et al, 2020). Vegetation and rocky surface classes recorded losses in area change (see Figure 5a -5d) because they were converted and modified into built-up area.…”

“…In recent years, remotely sensed (RS) technology has been used in the monitoring of LULC, with encouraging results. The RS technology has evolved into an essential tool for stakeholders to use in evaluating and anticipating LULC as it occurs throughout time (Aliyu et al, 2020). Previous studies have used remotely sensed datasets to assess land cover over time in various developing countries across the world (Rimal et al, 2020).…”

“…Previous studies have used remotely sensed datasets to assess land cover over time in various developing countries across the world (Rimal et al, 2020). Some of the studies addressed: analysis of LULC changes (Mmom and Fred-Nwagu, 2013;Bello et al, 2014;Mishra et al, 2014); analysis of LC changes (Bakr et al, 2010;Abiodun et al, 2011;Fichera et al, 2012); change detection of urban sprawl (Oyinloye, 2010;Tamilenthi and Baskaran, 2011;Viana et al, 2019); monitoring and forecasting of spatiotemporal LULC using CA Markov (Yikalo, 2009;Sundara Kumar et al, 2015;Aliyu et al, 2020).…”