Publication

During the last decade, urban growth has been increased rapidly in Gopalganj district of Bangladesh. Therefore, this study seeks to observe fluctuations in land use and land cover (LULC) in Gopalganj with its effects over the past two decades. Built-up areas have increased by 21.17% over the last two decades. Urban vegetation has declined in parallel with the increase in vacant land in the district from 2000 to 2010. However, in the next ten years, it has occupied about 72.76 square km of bare-land. By using Artificial Neural Network (ANN) with integrated cellular automation (CA) simulation, the model predicted that urban areas would grow by 10.88% in the central and north-western regions of the district by 2050. Urban vegetation will decrease by 4.09%, with a significant reduction in bare land and water bodies. The accuracy of the predicted LULC is 89.48% based on validation result. This prediction may help municipal and administrative authorities, urban planners to achieve a planned and sustainable future city of Gopalganj.

Environment is anything that immediately surrounds an object and influences it directly. The objective of this study is to examine the current state of softscape and Hardscape features, as well as their 10-year evolution. This study collects primary data from a field survey and uses Landsat 7 and 8 raster data as secondary source for various analyses. This project uses image classification, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built Index (NDBI), Normalized Difference Water Index (NDWI), Land Surface Temperature (LST), and other remote sensing tools to analyze the current scenario of softscape and hardscape features in the candidate environment. This analysis concludes that, since 2009, vegetation covering has decreased by 33.28 percent during a period of ten years. Then, the vegetation's health value (NDVI) is enhanced by 0.11 in 2014, and then again in 2019. Although there is a strong association between NDBI and LST for imbalances between the area's softscape and hardscape characteristics, LST has decreased as NDBI has increased. In addition, the pollution effects in nearby rivers are diminishing as a result of the decline in industrial activity in that region.

Khulna is Bangladesh's third-largest city. 32% drive. 5.9% of inhabitants bike. Transit demand depends on need, purpose, and ability. Safe and affordable bicycles appeal to students. Khulna's weak public transit and dismal socioeconomic conditions encourage cycling. This study evaluates northern Khulna students' bicycle use and travel habits. This study examines socioeconomic characteristics with biking. Five wards were researched in Khulna's north (6,7,9,10,14). Randomly polled 100 students. Collect time, distance, origin-destination, trip generation, and social/economic aspects. Middle- and lower-middle-income students use bikes for cheap transportation. Average rush-hour speed is 16.30 km/h. Wards 6 and 10 have the most journeys and destinations. 77% of bike trips are to school or practice. Some respondents bike to the market, for fun, etc. Monthly bike maintenance is 115 BDT. Accidents are more likely for 13–15-year-olds traveling 19.61 kmph with 4/5 cyclist crash. The student enjoys walking and rickshaws. They use alternative transportation in bad weather and if their bike breaks. Mahindra and vehicle. Regression model: distance reduces trip generation. Income and transportation aid. Bicyclists have parking, safety, and infrastructural issues. This research rarely mentions bike infrastructure. This research can improve Khulna's transportation policies.

SWM is an integral part of an eco-neighborhood. Khulna City, Bangladesh produces 600 tons of solid garbage each day, and collects 400 tons (KCC). 200 tons of trash pollute Khulna. Recycling is 7.2%. This research assesses the existing SWM system in Nirala, a proposed Khulna residential development. Nirala's 67.31 acres have 3000 residents. Using LCI, Nirala and Copenhagen's eco-neighborhood Christianshavn's SWM systems are compared. 10,140 people live in Christianshavn's 848 acres. Copenhagen aims to increase its garbage recycling rate to 70% by 2024. Copenhagen sends 2% of its domestic garbage to landfills, while Khulna sends almost 65%. Nirala's SWM score is 2.25 times lower than Christianshavn's. Low community participation is the cause of Nirala's poor SWM, according to TOPSIS. The report concludes with a few plausible proposals, such as permanent jobs for master role SWM staff of KCC, recycling biodegradable trash as compost, and appropriate implementation of privatization program per city master plan, which may inspire stakeholders to improve the current system.