Evaluation of spatiotemporal dynamics of land cover and land surface temperature using spectral indices and supervised classification: a case study of Jobai Beel Area, Bangladesh

Abstract

This study aims to evaluate the spatiotemporal change of land cover (LC) and surface temperature of the Jobai Beel area, an exclusive agriculture zone, situated in the far-flung area of northwest Bangladesh using satellite data. Multi-temporal Landsat series of data from 1989 to 2020 and geospatial techniques have been employed to evaluate the LC change and land surface temperature (LST) variation. Different spectral indices such as NDVI, MNDWI, NDBal have been used to retrieve individual LC. Corresponding LST has also been extracted using the thermal bands. Supervised Classification and the post-classification change detection technique were employed to determine the temporal changes and validate the individual LC. The results were employed to assess the LST variation associated with LC changes. The results reveal that the area had undergone a drastic and inconsistent heterogeneous LC transformation during the study period. Water and vegetation areas have expanded at a rate of 0.24km2/year and 0.45km2/year respectively, while bare lands have shrunk at a rate of 0.70km2/year. In general, Bare land exhibits a significant positive correlation, when Vegetation areas show a significant negative correlation with LST. However, the correlation between water areas and LST was found statistically insignificant. Agriculture in the form of vegetation has been found the most dominating land cover character throughout the study period, which has been regulating the LST variation across the area.