Coastal areas of Bangladesh have been considered to be vulnerable regions of the country for severe damage occurrence due to cyclones over the years, while coastal vegetation plays a vital role in mitigating climatic disasters. This study presents an analysis of cyclonic track and vegetation cover change detection based on satellite imagery of the selected coastal areas of Bangladesh (especially the southern part), namely—‘Bhola’ and ‘Barguna’ districts. This study aims to use Landsat satellite imagery, remote sensing, and GIS techniques to analyze vegetation change from the year 2000 to 2024 and determine major cyclonic tracks across the study area. The principal methodology employed in this study is the Normalized Difference Vegetation Index (NDVI) differencing and accuracy assessment of reclassified images that validate the detection of vegetation change over time. To find out the vegetation index, waterbody, and non-vegetation space, NDVI employs multi-spectral remote sensing techniques with a combination of satellite imagery bands. NDVI is one of the most frequently employed indices for vegetation analysis with the help of GIS and remote sensing. The process involves mosaicking Landsat images from different years, calculating the NDVI value, and using a user-identified approach to create a classified map from the NDVI map to assess area and change detection. The findings reveal a significant increase in vegetation cover in the Barguna and Bhola districts from 2000 to 2024. In 2024, Barguna district had the highest vegetation coverage 75.51%, the non-vegetated area coverage was 21.45%, and the water body coverage area was 3.04%. The non-vegetated area had the highest coverage of 48.8%, as found in 2005 in the Barguna district. In the Bhola district, the maximum increase of 69% in vegetation area occurred in 2024, the non-vegetated area decreased with a coverage of 10%, and the water body area almost had no change. The highest coverage of non-vegetated areas was found at 45.8% in 2000 in the Bhola district. The overall findings indicate that vegetation area gradually increased in Bhola over the years. To determine the overall accuracy of the reclassified NDVI maps, accuracy assessment, and Kappa coefficients were determined through the confusion matrix of ArcMap. Overall classification accuracy value was 90–94% with corresponding Kappa statistics being 80–88%, which is sufficient to prove the study analysis was almost accurate and perfect. This study also comprehensively analyzes the previous trajectories of major tropical cyclones that reached the study area between 2000 and 2024. The methodology involved mapping cyclone tracks using Arc GIS, which enabled cyclone paths to be visualized. The path analysis of cyclones revealed that Sidr, Mahasen, Komen, Raonu, Sitrang, and Midhli significantly affected the study area. Although the cyclones Amphan and Bulbul did not directly pass over the area, they still had a major impact on it. This study is expected to demonstrate the necessity to find out the cause of such reduction in vegetation cover and to look for new strategies for coastal vegetation survival.