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Flood is one of the most devastating climatic disasters around the world. The physical and infrastructural damage of floods is uncontrollable and challenging to recover. Though the mismanagement of the water system is one cause of flood, some countries face a seasonal natural flood, which is impossible to avoid. The history of flood affection in these countries are long, and people don't have any other choice but to adapt to this circumstance every year. The continuous flood event has several climatic impacts that are not broadly documented and remain in the shadows of severe infrastructural damage. This research aims to identify the effect of monsoon floods on vegetation and land surface temperature (LST). The study area is the northeast part of Bangladesh, a highly flood-prone area. The research incorporates Google Earth Engine (GEE) to manage the satellite image data related to this research which are Sentinel-1 SAR imagery and Landsat-8 imagery. Six years of data from 2015 to 2020 have been taken to continuously monitor the flooded area, vegetation, and LST dynamics. Primary results indicate a yearly increase and decrease of the flooded area with 57.3% highest increase rate in 2019. A continuous increase of Enhanced Vegetation Index (EVI) value and decrease of LST has a changing pattern similarity with flooded area fluctuation over the year. Also, the flooded areas have around 50% less mean EVI value than the non-flooded areas, eventually rising average LST in flooded areas. 10,024 grids of 1 km × 1 km have been used to extensively analyze the relationship of flood and EVI through correlation and linear regression. The final result reveals a clear negative correlation value (less than 0.56 for all the years) of EVI with flooded areas, having the highest R-squared value of 0.4325 in 2017.

Flood is one of the most devastating climatic disasters around the world. The physical and infrastructural damage of floods is uncontrollable and challenging to recover. Though the mismanagement of the water system is one cause of flood, some countries face a seasonal natural flood, which is impossible to avoid. The history of flood affection in these countries are long, and people don't have any other choice but to adapt to this circumstance every year. The continuous flood event has several climatic impacts that are not broadly documented and remain in the shadows of severe infrastructural damage. This research aims to identify the effect of monsoon floods on vegetation and land surface temperature (LST). The study area is the northeast part of Bangladesh, a highly flood-prone area. The research incorporates Google Earth Engine (GEE) to manage the satellite image data related to this research which are Sentinel-1 SAR imagery and Landsat-8 imagery. Six years of data from 2015 to 2020 have been taken to continuously monitor the flooded area, vegetation, and LST dynamics. Primary results indicate a yearly increase and decrease of the flooded area with 57.3% highest increase rate in 2019. A continuous increase of Enhanced Vegetation Index (EVI) value and decrease of LST has a changing pattern similarity with flooded area fluctuation over the year. Also, the flooded areas have around 50% less mean EVI value than the non-flooded areas, eventually rising average LST in flooded areas. 10,024 grids of 1 km × 1 km have been used to extensively analyze the relationship of flood and EVI through correlation and linear regression. The final result reveals a clear negative correlation value (less than 0.56 for all the years) of EVI with flooded areas, having the highest R-squared value of 0.4325 in 2017.

This book encourages Children on 3R’s (Reduce, Reuse and Recycle)

There is a resurgent interest in the study of ‘urban commons’ in critical geography scholarship as a way to reimagine cities beyond the pervasive neoliberal framing. Inspired by this body of work, this paper explores the processes through which marginalised groups, despite their many socio-economic limitations, negotiate and transform their sparse urban resources into ‘commons’ to survive in cities. We use qualitative interviews and participant observations to examine two case studies of informal settlements in Dhaka and Khulna city in Bangladesh. The ‘commons identikit’ is used to analyse how informal settlers negotiate survival by enacting particular social relationships among themselves and beyond, ensuring access, use, and exchange of materials and ideas, as well as distributing care, benefits, and responsibility of their commons. By bringing a commons perspective to the pre-existing and emerging local tactics, we highlight the logics and relationality that help these communities make efforts of collective survival and aspire to a better future. We argue that there are significant practical benefits to recognising the self-organising logics of the precariously positioned communities in the city. Furthermore, commoning the city constitutes a major extension of the theorisation of urban informal settlements and the city as urban commons.

Purpose The purpose of this paper is to find out the causes of increasing population in the real estate area. The demographic in information of the respondents and the level of satisfaction was also carried out for this study. Design/methodology/approach The authors use both primary and secondary data. Total 329 respondents were surveyed at the real estate area after completing sample size determination. Secondary data was collected from journals, real estate offices and papers. After that, using regression and correlation analysis, the data was analyzed and finalized. Findings This study identified migration as the most critical variable. The study determined ten hypotheses and only accepted two. By that, this study finds out the causes of the increasing demand of plots and flats in real estate. Originality/value This study will work as a baseline study for the real estate sector in Bangladesh. Most of the research on Bangladesh’s real estate is done mainly on real estate market assessment and consumer satisfaction. Nevertheless, this study will find out the causes of the increasing population in real estate.