TY - JOUR
T1 - Land use and land cover change detection and prediction based on CA-Markov chain in the savannah ecological zone of Ghana
AU - Aniah, Philip
AU - Bawakyillenuo, Simon
AU - Codjoe, Samuel Nii Ardey
AU - Dzanku, Fred Mawunyo
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2023/1
Y1 - 2023/1
N2 - Environmental problems have accompanied the accelerated land use and land cover change (LULCC), yet few local level studies make an attempt to assess the dynamics of LULCC. This work employed GIS and remote sensing to quantify the past and predict future dynamics of LULCC based on the synergy Cellular Automata (CA) - Markov Chain Model (MCM). The results revealed that agricultural land in the Bongo district witnessed the greatest expansion from 10.03% to 27.17% of total area from 1990 to 2019, while wooded savannah area witnessed the greatest decline from a share of 42.26% to 15.51% of total area from 1990 to 2019. In the Kassena-Nankana West (KNW) district, shrub and tree savannah and agricultural land expanded from 32.91% to 54.2% and 9.44% to 18.16% of the total area, respectively, at the expense of wooded savannah area (-32.9% of total area) between 1990 and 2019. Future predictions based on prevailing socio-economic development demonstrate that the observed trend would continue till the 2050 period. In the Bongo district, the settlement area will witness the highest proportion of net increase in total area (5.63 km2) at the expense of wooded savannah (-11.26 km2) between 2019 and 2050. Conversely, in the KNW district, the shrub and tree savannah area will experience the highest proportion of net gain in total area (156.02 km2) at the expense of wooded savannah area (-111.49 km2) between 2019 and 2050. This result is an indication that the synergy CA-MCM have effectively captured the spatiotemporal trend in LULCC in this study.
AB - Environmental problems have accompanied the accelerated land use and land cover change (LULCC), yet few local level studies make an attempt to assess the dynamics of LULCC. This work employed GIS and remote sensing to quantify the past and predict future dynamics of LULCC based on the synergy Cellular Automata (CA) - Markov Chain Model (MCM). The results revealed that agricultural land in the Bongo district witnessed the greatest expansion from 10.03% to 27.17% of total area from 1990 to 2019, while wooded savannah area witnessed the greatest decline from a share of 42.26% to 15.51% of total area from 1990 to 2019. In the Kassena-Nankana West (KNW) district, shrub and tree savannah and agricultural land expanded from 32.91% to 54.2% and 9.44% to 18.16% of the total area, respectively, at the expense of wooded savannah area (-32.9% of total area) between 1990 and 2019. Future predictions based on prevailing socio-economic development demonstrate that the observed trend would continue till the 2050 period. In the Bongo district, the settlement area will witness the highest proportion of net increase in total area (5.63 km2) at the expense of wooded savannah (-11.26 km2) between 2019 and 2050. Conversely, in the KNW district, the shrub and tree savannah area will experience the highest proportion of net gain in total area (156.02 km2) at the expense of wooded savannah area (-111.49 km2) between 2019 and 2050. This result is an indication that the synergy CA-MCM have effectively captured the spatiotemporal trend in LULCC in this study.
KW - CA-Markov model
KW - Dynamics
KW - Ghana
KW - LULCC
KW - Remote sensing
KW - Savannah zone
UR - http://www.scopus.com/inward/record.url?scp=85144077569&partnerID=8YFLogxK
U2 - 10.1016/j.envc.2022.100664
DO - 10.1016/j.envc.2022.100664
M3 - Article
AN - SCOPUS:85144077569
SN - 2667-0100
VL - 10
JO - Environmental Challenges
JF - Environmental Challenges
M1 - 100664
ER -