Quantifying sustainable urbanization by predictive modeling for better agricultural management: A case study in the South Asiatic Region - Kashif Ali; Jawad Ali Shah; Saif Ullah; Syed Turab Raza (Heliyon)
Global population growth and uncontrolled are creating threats to agricultural land. To address urbanization, proactive planning is required. Land use and land cover (LULC) classification maps for 2002–2022 were analyzed using remote sensing (RS) and geographic information systems (GIS) in Sahiwal, Punjab, Pakistan. Idrisi's Cellular Automata (CA)–Markov model was used to predict future scenarios. The results showed that urbanization was rapidly accelerated in large LULC changes that were unpredictable. In particular, the urbanized area increased by 234.7 km2 (91 %) from 22.83 km2 in 2002 to 257.53 km2 in 2022, with a reduction of 656.05 km2 (52 %), from 1252.52 km2 in 2002 to 596.47 km2 in 2022, of agriculture land. About 17.05 km2 of land was lost to urbanization; however, a large portion of CA 251.75 km2 was absorbed due to careless urban growth. The CA-Markov projection revealed that from 2022 to 2042, agriculture will experience the largest net change, losing about −226.09 km2 of land. However, the projected results showed that the urban class will be expanded up to 450.23 km2 and will gain approximately 192.7 km2 in 2042. The overall findings show that it is possible to manage outcomes quantitatively and control haphazard and unplanned urban sprawl by putting forward a comprehensive master plan.