Tanmay Mondal <br/><br/>
Understanding the impact of urbanisation on wetlands using random forest machine learning algorithm in Google Earth Engine: a case of East Kolkata Wetlands, India 

 - P 608-617 
<br/><br/> Land cover maps help in understanding the spatial and<br/>temporal dynamics of a particular area in a given time.<br/>The present study was done in the Kolkata Metropolitan Area (KMA) and East Kolkata Wetland (EKW) in<br/>India using the machine learning (ML) algorithm of<br/>random forest classification and prediction in Google<br/>Earth Engine. The ML algorithm was used to classify<br/>the land use land cover (LULC) maps of KMA and<br/>EKW for 2002, 2013 and 2023. The ML prediction<br/>model further used these LULC maps to predict the future land cover map for the year 2033, both for KMA<br/>and EKW. A correlation analysis was done between<br/>the built-up of KMA and the built-up of EKW to assess<br/>the impact of the urban expansion of KMA on the wetlands of EKW. The present study explored the impact<br/>of the increase in built-up area on the wetland and it<br/>was seen that the built-up of EKW was increasing due<br/>to the increase in the urban expansion of KMA. As a<br/>result, the wetland is experiencing a decrease in biodiversity and quality of water and soil.  
<br/><br/><label>Subjects--Facted Index Terms: </label><br/>Change detection<br/>random forest<br/> Google Earth Engine<br/>machine learning<br/>prediction