<abstract xmlns="http://www.w3.org/1999/xhtml">

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.
</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.

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

Department of Geomatics, Faculty of Environmental Design

Reports on Geodesy and Geoinformatics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

For several decades, Nigerian cities have been experiencing a decline in their biodiversity resulting from rapid land use land cover (LULC) changes....

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

Article Category: Original Article

Online veröffentlicht: 31. Dez. 2020

Seitenbereich: 29 - 38

Eingereicht: 26. Feb. 2020

Akzeptiert: 09. Nov. 2020

DOI: https://doi.org/10.2478/rgg-2020-0009

Schlüsselwörter
LULC, change detection, Landsat, Cellular Automata Markov (CAM) model, Nigeria

© 2020 Yahaya A. Aliyu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

Article Category: Original Article

Online veröffentlicht: 31. Dez. 2020

Seitenbereich: 29 - 38

Eingereicht: 26. Feb. 2020

Akzeptiert: 09. Nov. 2020

DOI: https://doi.org/10.2478/rgg-2020-0009

SchlüsselwörterLULC, change detection, Landsat, Cellular Automata Markov (CAM) model, Nigeria

© 2020 Yahaya A. Aliyu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
LULC, change detection, Landsat, Cellular Automata Markov (CAM) model, Nigeria