A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh

Synergistic effects of carbon and heat under disturbance of human activities: Evidence from a resource-based city of China

For resource-based cities, the rapid development of industrialization and urbanization has led to significant carbon emissions (CEs), accelerated the rise of urban land surface temperatures (LSTs) and hindered sustainable urban development. This study constructed a model to measure the carbon-heat relationship to clarify the complex relationship between LSTs and CEs in resource-based cities. The results show that:1) High-temperature areas are primarily concentrated around the urban center and large industrial zones, with average LSTs reaching a peak of 35.7 °C in 2015, indicating severe temperature polarization; 2) CEs exhibited an overall upward trend with a diffusion effect, particularly pronounced in the urban center and industrial zones. Areas with extremely significant, strong significant, and generally significant growth in CEs accounted for 4.64%, 3.81%, and 81.35%, respectively, showing a concentrated increase in the urban center; 3) A positive correlation between CEs and LSTs of the city was identified, and the distribution of urban heat island and the high value area of CEs are concentrated and similar; 4) The synergistic effects between LSTs and CEs varied between urban center, suburban and peripheral areas, due to human activities. Areas with a high positive correlation between CEs and LSTs are concentrated in urban centers and peripheral areas, while for urban suburbs, the correlation is weak or even absent. To mitigate the negative effects of carbon-heat accumulation, urban centers should avoid high population concentrations, and the carbon sink potential of green spaces near industrial zones and peripheral areas should be fully utilized. These insights provide actionable strategies for sustainability of resource-based cities, particularly in the governance of urban thermal environments and the mitigation of CEs.

Geo-spatial based cyclone shelter suitability assessment using analytical hierarchy process (AHP) in the coastal region of Bangladesh

The coastal district of Bangladesh is susceptible to cyclones, which cause significant damage to infrastructure, economy, and social structures every year. The importance of protecting lives and property in these vulnerable areas is a top priority, especially in times of cyclones and storm surges. Therefore, the identification of potentially suitable shelter locations is essential for disaster risk resilience planning and implementation in the coastal regions. In this context, our research focuses on Barguna, which has witnessed severe damage from previous cyclones over the last several decades. We aim to identify and map feasible cyclone shelter suitability by utilizing GIS, AHP, Hotspot Analysis, and Remote Sensing techniques. The use of advanced techniques enables a comprehensive assessment of multiple variables that influence shelter suitability, ensuring the selection of the most strategically significant locations. The goal is to enhance disaster preparedness and resilience in Barguna District, reducing the risk and vulnerability of its coastal communities to cyclones. Seven variables associated with cyclone hazards, such as elevation, slope, distance from roads and rivers, population density, land use, and cover, and proximity to healthcare facilities, are considered to identify the safest and most suitable cyclone shelter areas. The assessment of the appropriateness of shelter locations for the study area was facilitated by the collection of 181 GPS locations regarding existing cyclone shelters. The findings reveal that approximately 15.53 % (1956 ha) of the total land area is considered less suitable, 67.31 % (84763 ha) moderately suitable, 16.70 % (21024 ha) suitable, and 0.29 % (362 ha) highly suitable for optimal cyclone shelter establishment in the study area. This study has a major limitation due to the use of Landsat imagery, which may not always provide fully accurate image classification. To validate our methods, we collected existing cyclone shelter data and performed a pixel-based accuracy assessment, achieving high accuracy and confirming the reliability of our approach. This research addresses a critical gap in cyclone shelter planning, offering valuable insights for residents and decision-makers to mitigate cyclone risks not only in the Barguna district but also in similar coastal regions of Bangladesh. The framework developed in this study can aid non-government organizations and the government in determining the most appropriate locations to construct cyclone shelters to build a safer, more resilient future for the region, capable of withstanding the relentless threats posed by cyclones every year.

Identifying Urban Heat Effect through Satellite Image Analysis: Focusing on Narayanganj Upazila, Bangladesh

The rapid growth of population and land use cover change are closely connected. Narayanganj Sadar Upazila is the first Growing City in Bangladesh. Land use and land cover change are very first. Global warming, increased greenhouse gas emissions, and other environmental issues have become critical issues to address in recent times. Because of the Unplanned Expansion of urban areas, the LULC pattern is changing, and this kind of adverse (LST increasing, Heat Island Growth) impact is increasing. In this area, the amount of vegetation is decreasing day by day. The objectives of this study are to identify land use land cover (LULC) dynamics for the year 2001 to 2021, identify Urban Heat Islands from the value of land surface temperature (LST) and identify hotspots based on normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI) and land surface temperature (LST) doing weighted overlay among them.  To determine the land cover pattern, and change at Narayanganj Upazila in the years 2001, 2011, and 2021, the land cover type was divided into four categories (build-up, vegetation, water bodies, and barren soil) in geographic information system (GIS) and Earth Resources Data Analysis System (ERDAS) Imagine 2014. The overall accuracy of LULC in 2001, 2011, and 2021 was 90.08, 91.34, and 92.02, respectively. And the value of the kappa coefficient for the years 2001, 2011, and 2021 was 0.91, 0.89, and 0.90, respectively. This study demonstrates an increase of 14.22% in built-up area and destruction of 15.5% of vegetation, 3.26% of barren soil, and 1.05% of the waterbody in the previous 21 years in Narayanganj Upazila. This study will help the administration, agricultural directorates, Pourashava office, and city corporation authority to take necessary measures to mitigate the adverse impacts of land cover change. They can make new rules and regulations on the construction of buildings, restrictions on filling water bodies and measures to conserve vegetation.