Land use and land cover (LULC) changes induced by human or natural processes drive biogeochemistry of the Earth influencing the climate at global as well as regional scales. Drastic changes in the land cover with the decline in vegetation and water bodies due to anthropogenic activities enhances the heat emission from land surface and atmospheric temperatures Increased land surface temperature (LST) is mainly due to increase in concentrated human activities, paved land cover or barren lands. Due to complexity of landscapes the sampling was difficult to derive LST and environmental response relationships. Temporal data acquired through space borne remote sensors has bridged the gap of temporal data for the entire earth surface. The current study explores the relation between surface biophysical parameters to sub-pixel thermal variations. The thermal infrared bands of remote sensing data help to retrieve LST, which are supplemented by ground based measurements. Analysis of LST with LULC indicates a negative correlation between vegetation indices and LST. The general trend in the ambient temperature of Uttara Kannada over the 31 year period was established. It clarifies that there was a fundamental drift of temperature rise in recent years, especially during the last decade.

Water pollution is a major threat to the existence of living beings. The restoration measures can be taken by assessing the extent of pollution in water bodies using various water quality indices. National Sanitation Federation Water Quality Index (NSFWQI) is the most widely used index. Usually NSFWQI is determined by collecting and analyzing water samples from various locations and it is a tedious and expensive process. Trophic status is usually ascertained from satellite imagery of Landsat TM. Here attempt has been made to quickly assess the pollution status in a vast area (Akkulam-Veli Lake, Kerala, India) directly from the satellite imagery (IRS P6-LISSIII) using NSFWQI. It is also attempted to calculate the pH, dissolved oxygen (DO), biochemical oxygen demand (BOD) and fecal coliforms (FC) in the Lake system.Regression equations for the prediction of NSFWQI, pH, DO, BOD and FC from radiance values from green, red, NIR and SWIR bands of satellite imagery were developed. The study reveals that the simple regression equation formed by the ratio of radiance in the green and the red bands, which yields a strong correlation coefficient for the prediction of NSFWQI. For the prediction of DO, the best equation is the simple regression equation formed by the ratio of radiance in green and red bands with a strong correlation. For BOD, multiple regression equation was formed by the radiance in the red and SWIR bands with a strong correlation. The best equation for predicting pH is the regression equation with the ratio of green and red bands with a strong correlation. But for fecal coliform, multiple regression equation is the best equation formed by the ratio of radiance in the green and SWIR bands with a low correlation coefficient. The performance of this model can be improved by using a large set of data.The spatial variation of these utmost important water quality characteristics is derived from imagery using remote sensing techniques. It is also found out whether the water quality is conforming to the standards or not for envisaging control measures. IRS P6-LISSIII imagery can give a quick assessment of the pollution status of the Lake system using water quality index (NSFWQI). Control measures can accordingly be adopted on priority basis. Satellite imagery can be used for the quick assessment of urban pollution status of water bodies all over the world.

Achyranthes aspera (Prickly chaff) seeds contain spines which often cause irritation on the hands of those who collect them. The main objective of this investigation was to evaluate its irritant potential on animal 's

India is the fast developing country with the population of 120 crores. The prevalence of diabetes is 17 to 23%. Both urban and rural diabetic population is increasing because of deficiency in detection of prediabetic conditions. Training in diabetic management for doctors, nurses and health workers is not up to the mark. Until we fulfil all these things to concerned persons and diabetic awareness to the community it will become very difficult to prevent patients going from pre diabetic to frank Diabetes. Treating DM it is an art.