Assessment of LULC change dynamics and its relationship with LST and spectral indices in a rural area of Bengaluru district, Karnataka India

Abstract

In recent decades, rural areas in the surroundings of metropolitan cities have undergone substantial development in India. This has resulted in changes in land use and land cover (LULC) patterns having a significant impact on hydrological processes and climate change. Therefore, comprehending such modifications is critical for the decision-making process, and the development of a sustainable environment. The current study focused on comprehending the spatio-temporal dynamics of LULC changes and their repercussions on variations in Land Surface Temperature (LST) profiles over a two-decade period in the Dodballapur Taluk, Bengaluru Rural District of Karnataka State in India. The study also investigates the relationship between LULC changes, Land Surface Temperature (LST), and spectral indicators such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI). Landsat 7 ETM + satellite images acquired in the years, 2001, 2010, and 2019 were used in the study. The Supervised Maximum Likelihood Classifier (MLC) technique was adopted to classify images and assess spatio-temporal LULC changes and analyse transformations of several LULC classes viz. barren land (BL), built-up land (BUL), crop land (CL), pasture (P), uncultivated land (UCL), shrub land (SL), and water bodies (WB). The accuracy assessment ensured the veracity of the image classification. The results showed that a) built-up, crop, and shrub land have been increased by 75.54%, 38.18%, and 52.57% respectively, b) barren, pasture, and uncultivated land have been increased by 22.94%, 4.89%, and 50.62% respectively; and c) the area covered with surface water bodies has been significantly reduced by 635.58%. The analysis of LST changes revealed a 2.09 °C increase in mean LST with a variance of 2.75 °C, showing considerable fluctuations in cold and hot weather conditions. The regression study of scatterplots for LST-NDVI revealed triangular space (R2 = −0.234), LST-NDBI revealed right-angled triangle space (R2 = 0.567), and LST-NDWI also exhibited right-angled triangular space (R2 = −0.533). Intriguingly, the relationship between NDVI and NDBI exhibited a crescent shaped scatterplot with R2 value of −0.448. The findings of the study can assist policymakers and decision-makers in developing and implementing policies for sustainable rural development and water resource management.