RESUMO
Mangroves provide essential ecosystem services including coastal protection by acting as coastal greenbelts; however, human-driven anthropogenic activities altered their existence and ecosystem functions worldwide. In this study, the successive degradation of the second largest mangrove forest, Chakaria Sundarbans situated at the northern Bay of Bengal part of Bangladesh was assessed using remote sensing approaches. A total of five multi-temporal Landsat satellite imageries were collected and used to observe the land use land cover (LULC) changes over the time periods for the years 1972, 1990, 2000, 2010, and 2020. Further, the supervised classification technique with the help of support vector machine (SVM) algorithm in ArcGIS 10.8 was used to process images. Our results revealed a drastic change of Chakaria Sundarbans mangrove forest, that the images of 1972 were comprised of mudflat, waterbody, and mangroves, while the images of 1990, 2000, 2010, and 2020 were classified as waterbody, mangrove, saltpan, and shrimp farm. Most importantly, mangrove forest was the largest covering area a total of 64.2% in 1972, but gradually decreased to 12.7%, 6.4%, 1.9%, and 4.6% for the years 1990, 2000, 2010, and 2020, respectively. Interestingly, the rate of mangrove forest area degradation was similar to the net increase of saltpan and shrimp farms. The kappa coefficients of classified images were 0.83, 0.87, 0.80, 0.87, and 0.91 with the overall accuracy of 88.9%, 90%, 85%, 90%, and 93.3% for the years 1972, 1990, 2000, 2010, and 2020, respectively. By analyzing normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and transformed difference vegetation index (TDVI), our results validated that green vegetated area was decreased alarmingly with time in this study area. This destruction was mainly related to active human-driven anthropogenic activities, particularly creating embankments for fish farms or salt productions, and cutting for collection of wood as well. Together all, our results provide clear evidence of active anthropogenic stress on coastal ecosystem health by altering mangrove forest to saltpan and shrimp farm saying goodbye to the second largest mangrove forest in one of the coastal areas of the Bay of Bengal, Bangladesh.
Assuntos
Ecossistema , Áreas Alagadas , Humanos , Bangladesh , Meio Ambiente , SoloRESUMO
Rapid urbanization with an increasing rate of urban built-up area is decreasing urban green space resulting in changing urban microclimate conditions showing increasing land surface temperature. A better understanding of these effects is important to formulate effective strategies in addressing the impact of increasing built-up area. Land surface temperature patterns in an urbanized city in Bangladesh (Mymensingh district) were investigated using Landsat satellite sensor data from 1988 to 2016. A total of nineteen Landsat satellite images were used to retrieve land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI). The radiative transfer equation (RTE) model was applied to derive LST for the years 1988, 1992, 1999, 2004, 2008, 2012, and 2016. Further, the Landsat-derived LST results were compared with MODIS Terra satellite outputs (MOD11A1) for the validation of our study results. Our results showed NDVI higher in 2008 and lower in 2004, LST maximum in 1988 and minimum in 2008, and NDBI higher in 2004 and lower in 2012. Seasonally, summer was characterized by higher LST and winter by lower LST, while NDVI was higher in autumn and lower in winter, however, NDBI was higher in winter and lower in autumn. Spatially, a relatively higher LST and NDBI was observed in the southwest, followed by central, and northern regions, whereas the trend was opposite for NDVI. Using Pearson's correlation, results showed a strong significant negative correlation between LST and NDVI and a positive significant correlation between LST and NDBI. Further, simple linear regression analysis revealed that LST decreased with increasing NDVI most quickly in 2012, followed by the years 2016, 2008, 1992, 1988, 1999, and 2004. On the other hand, LST increased with increasing NDBI most quickly in 1999, followed by the years 2016, 1988, 1992, 2012, 2004, and 2008. Thus, long-term observation suggested that urbanization had driven a decrease in green space while simultaneously increasing the land surface temperature within an urbanized area. This study has concluded that the protection of urban green spaces is needed as an effective step toward addressing adverse effects of regional climate change and desertification.
