Land surface temperature (LST) is a key factor in numerous areas such as climate change, land use/land cover in the urban areas, and heat balance and is also a significant participant in the creation of climate models. Landsat data has given numerous possibilities to understand the land processes by means of remote sensing. The present study has been performed to identify the LST of the study region using Landsat 8 OLI/TIRS satellite images for two time periods in order to compare the data. The study also attempted to identify and predict the role and importance of NDVI, NDBI, and the slope of the region on LST. The study concludes that the maximum and minimum temperatures of 40.44 C and 20.78 C were recorded during the November month whereas the maximum and minimum LST for month March has increased to 42.44 C and 24.57 C respectively. The result indicates that LST is inversely proportional to NDVI (−6.369) and slope (−0.077) whereas LST is directly proportional to NDBI (+14.74). Multiple linear regression model has been applied to calculate the extents of NDVI, NDBI, and slope on the LST. It concludes that the increase in vegetation and slope would result in slight decrease in temperature whereas the increase in built-up will result in a huge increase in temperature.
Identifying the land use/land cover pattern and its changes plays a considerable role in assessing the impact of man's activity towards natural ecosystem. This study focuses on the agrarian land use change over the study region of Pudukkottai district which is situated in the semi-arid region of Tamil Nadu, India. Agriculture is one of the significant sources of income for the economy of the country and most of the people engaged in agriculture and its related activity in the study area. It needs deep monitoring of the changes in the agricultural land use at time to time to prevent mismanagement and poverty among the people of the Pudukkottai district. The present research observes the land use change of agriculture for two periods i.e. 2005-2010 and 2010-2015 using Landsat images from USGS. To execute the land use characteristics, the study adopted four indicators they are net total area of change, annual area of change, annual rate of change and dynamic degree. The study concludes that maximum changes happened during 2010-2015 and minimum changes happened during 2005-2015. Maximum of agricultural land has changed into wasteland followed by built-up land and wetland.
The quality of drinking water sources in the Adyar river sub-basin of northern Tamil Nadu is assessed in this study. This research uses a combined water quality index (WQI) and pollution index (PI) to assess and characterise groundwater quality. Water samples will be collected from nine locations in the study area for the assessment. The water quality index was calculated based on Total Dissolved Substances (TDS), Nitrogen oxides (NOx), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Chloride (Cl), Sulphate (SO4), Bicarbonate (HCO3), Fluoride (F), Power of Hydrogen (pH) and Electrical Conductivity (EC). These twelve parameters were analysed and characterised according to standard methods and the Indian standard, which were then used in calculating the water quality index. Groundwater quality and pollution status of the Adyar river basin were assessed using the Groundwater quality index and comprehensive pollution index for the years 1990, 2005, and 2020. A result reveals that the groundwater quality has decreased from 1990 to 2020. Around seven parameters exceeded the permissible limits in 1990, nine parameters exceeded the permissible limits in 2005, and around eight parameters exceeded the allowable limits in 2020. The pollution status of the groundwater has considerably reduced from 1990 to 2020. Eastern parts of the study area were highly polluted and had low groundwater quality.
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