Cellular Automata Modelling: Predictions of Urban Sprawl and Impact to Microclimate in the Salatiga City

Abstract

Economic growth in the urban area of Salatiga is currently under pressure due to infrastructure expansion that is driving urban sprawl, which has the potential to cause long-term environmental degradation. The research methodology combines remote sensing with GIS, the random forest classification method, cellular automata, ground surface temperature, and statistical correlation tests, using Landsat time-series imagery as the data source. The results of this study indicate that during the 2012–2026 period, the area of built-up land increased by 497.98 hectares, accompanied by the loss of 764.79 hectares of vegetation cover. This resulted in an increase of approximately 250.07 hectares in the area experiencing extreme high temperatures (>35°C). Projections for 2042 indicate that built-up land will increase to 2,623.54 hectares, which has the potential to pose a threat of environmental degradation. This study concludes that there is a very strong positive correlation (r = +0.85) between the increase in built-up land and the expansion of the extreme temperature zone, as well as a negative correlation (r = -0.90) caused by the reduction in vegetation cover. This study is expected to support the achievement of Sustainable Development Goals (SDGs) 11 and 13.