Abstract

Unplanned and uncontrolled industrialization leads to environmental pollution, which ends up impacting human life and destroying the economy. Especially in the era of global warming, coastal regions worldwide are the most vulnerable and hold significant ecological importance for human habitation. In 1998, the establishment of the Mongla Export Processing Zone (MEPZ) in the coastal town of Mongla Thana, which is already famous for its seaport, led the area to the challenges of salinity intrusion and the shrinking of agricultural land and its fertility. Unplanned industrialization in the area causes vegetation loss, severe droughts, and other environmental challenges, threatening local biodiversity and agricultural sustainability. In this paper, the effects of unplanned industrialization inside the Mongla EPZ on the area land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and urban heat island (UHI) spanning from 2007 to 2023 have been investigated. Along with that, a machine-learning-based artificial neural network (ANN) model was employed to forecast the situation in 2027 and 2031. Our industrial settlement analysis reveals that a substantial rise in industrial building was seen in 2015 in the EPZ area, whereas the EPZ area was almost settlement-free before 2011. With this increase in 2015, above 2% of the total municipal area faced drought, which will become over 30% by 2023. The NDVI values are decreasing year-wise, which reveals that the area is becoming less vegetation-rich. Also, the increasing industrial activities in the EPZ led to an LST increment. Our CA-ANN algorithm-based future prediction shows that about 30% of the whole municipality will face LST 27 °C by 2031. Along with that, the area's UHI value, over 2 °C higher than the rural surrounding area, will reach 6.5% by 2031. Our findings indicate that the municipal area will face a devastating future, including vegetation loss, a high probability of severe drought, and ultimately, environmental degradation. This study will help raising awareness and decision-making process to mitigate the environmental risks and supporting sustainable development.

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