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Evaluation of drought is essential and useful to eradicate climate change impact. Therefore, this study aims to explore the spatiotemporal drought intensity trend in seven climatic zones of Bangladesh during 1979-2019. Mann-Kendall trend test and Standardized Precipitation Evapotranspiration Index (SPEI) are employed to identify drought trend and status, whereas spatial visualization is checked through Inverse Distance Weighting Interpolation. The study's findings emphasize the decreasing rate of SPEI in all climatic zones except the south-eastern zone, which is > 0.0065, >0.007, >0.0128, and >-0.0001 for SPEI 09 12, 24, and 06, respectively. Furthermore, the northern region has the highest value in SPEI in some periods with the highest decrease rate in SPEI 06, SPEI 09, SPEI 12 demonstrates greater drought responsibilities. The Barisal (.>-3.75), Rangpur (>-3.65), Dinajpur ((>-3.00), Rajshahi (>-4.35), Bogra (>-4.50), Ishurdi (>-3.45), Faridpur (>-4.30) and Madaripur (>-2.10) found under extreme drought-prone climatic zone. Thus, the study recommends taking initiatives and management for water resources to adopt mitigation planning for drought-prone climatic zones.

Waterlogging hazard is a significant environmental issue closely linked to land use for sustainable urbanization. NDWI is widely and effectively used in identifying and visualizing surface water distribution based on satellite imagery. Landsat 7 ETM+ and Landsat 8 OLI TIRS images of pre and post-monsoon (2002, 2019) have been used. The main objective of this study is to detect the seasonal variation of waterlogging in Rangpur City Corporation (RPCC) in 2002 and 2019. In the present study, we used an integrated procedure by using ArcGIS raster analysis. For pre and post-monsoon, almost 93% accuracy was obtained from image analysis. Results show that in 2002 during the pre and post-monsoon period, waterlogged areas were about 159.58 km2 and 32.32 km2, respectively, wherein in 2019, the changes in waterlogged areas are reversed than 2002. In 2019, during pre-monsoon, waterlogged area areas were 122.79 km2, and during post-monsoon, it increased to 127.05 km2. The research also depicts that the trend of the waterlogging situation largely depends on seasonal rainfall and a flawed drainage system. Keywords : Seasonal variation; Waterlogging; Remote sensing; GIS; Rangpur City Corporation   Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Urbanization is closely associated with land use land cover (LULC) changes that correspond to land surface temperature (LST) variation and urban heat island (UHI) intensity. Major districts of Bangladesh have a large population base and commonly lack the resources to manage fast urbanization effects, so any rise in urban temperature influences the population both directly and indirectly. However, little is known about the impact of rapid urbanization on UHI intensity variations during the winter dry period in the major districts of Bangladesh. To this end, we aim to quantify spatiotemporal associations of UHI intensity during the winter period between 2000 and 2019 using remote-sensing and geo-spatial tools. Landsat-8 and Landsat-5 imageries of these major districts during the dry winter period from 2000 to 2020 were used for this purpose, with overall precision varying from 81% to 93%. The results of LULC classification and LST estimation showed the existence of multiple UHIs in all major districts, which showed upward trends, except for the Rajshahi and Rangpur districts. A substantial increase in urban expansion was observed in Barisal > 32%, Mymensingh > 18%, Dhaka > 17%, Chattogram > 14%, and Rangpur > 13%, while a significant decrease in built-up areas was noticed in Sylhet < −1.45% and Rajshahi < −3.72%. We found that large districts have greater UHIs than small districts. High UHI intensities were observed in Mymensingh > 10 °C, Chattogram > 9 °C, and Barisal > 8 °C compared to other districts due to dense population and unplanned urbanization. We identified higher LST (hotspots) zones in all districts to be increased with the urban expansion and bare land. The suburbanized strategy should prioritize the restraint of the high intensity of UHIs. A heterogeneous increase in UHI intensity over all seven districts was found, which might have potential implications for regional climate change. Our study findings will enable policymakers to reduce UHI and the climate change effect in the concerned districts.

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