Hossain, Md.J.; Mahmud, Md.M.; Islam, S.T. Monitoring Spatiotemporal Changes of Urban Surface Water Based on Satellite Imagery and Google Earth Engine Platform in Dhaka City from 1990 to 2021. Bulletin of the National Research Centre 2023, 47, doi:10.1186/s42269-023-01127-5.
Hossain, Md.J.; Mahmud, Md.M.; Islam, S.T. Monitoring Spatiotemporal Changes of Urban Surface Water Based on Satellite Imagery and Google Earth Engine Platform in Dhaka City from 1990 to 2021. Bulletin of the National Research Centre 2023, 47, doi:10.1186/s42269-023-01127-5.
Hossain, Md.J.; Mahmud, Md.M.; Islam, S.T. Monitoring Spatiotemporal Changes of Urban Surface Water Based on Satellite Imagery and Google Earth Engine Platform in Dhaka City from 1990 to 2021. Bulletin of the National Research Centre 2023, 47, doi:10.1186/s42269-023-01127-5.
Hossain, Md.J.; Mahmud, Md.M.; Islam, S.T. Monitoring Spatiotemporal Changes of Urban Surface Water Based on Satellite Imagery and Google Earth Engine Platform in Dhaka City from 1990 to 2021. Bulletin of the National Research Centre 2023, 47, doi:10.1186/s42269-023-01127-5.
Abstract
This research focuses on monitoring the spatiotemporal changes of urban surface water in Dhaka City from 1990 to 2021, utilizing satellite imagery and the Google Earth Engine (GEE) platform. Surface water is essential for urban, environmental, and agricultural ecosystems, and its dynamics have significant implications for water resource planning and environmental management. The main objectives of this study are to assess the extent of urban surface water coverage over the last three decades and identify trends of water loss or gain in the study area. The study employs Landsat 5 TM and Landsat 8 OLI/TIRS imagery, integrating GEE with machine learning coding and WRI techniques to extract and analyze surface water data efficiently. Traditional remote sensing methods for dynamic monitoring are time-consuming and cumbersome, but GEE offers a user-friendly and accurate approach, providing easy access to satellite data and cloud-based processing. The results reveal a concerning trend in urban surface water coverage, indicating a significant reduction from 36.23 km² in 1990 to 5.83 km² in 2021, representing a loss of approximately 20 square kilometers or 45 percent of surface water over the last three decades. The decline is attributed to factors such as unplanned urban expansion, rapid real estate development, and increased industrial and economic activities in the study area. The developed algorithms utilizing GEE offer valuable insights into the maximum and minimum extent of surface water, enabling effective surface water planning and management. These findings contribute to sustainable water resource management and environmental preservation in Dhaka City.
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
