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Showing papers by "Pavan Kumar published in 2016"


Journal ArticleDOI
TL;DR: In this paper, the authors used remote sensing images to predict the precise carbon content associated with organic matter in the soil using NDVI and related equations, to prepare digital soil organic carbon map.

52 citations


Journal ArticleDOI
TL;DR: In this paper, a methodology was suggested to generate drought maps by combining rainfall and rainy days, for all the 12-year period of 2001-2012, during the major rainfall period, i.e., southwest monsoon (June-September) over India at 10 km × 10 km pixel for meteorological drought analysis.
Abstract: Drought is a natural climatic phenomenon occurring due to deficiency of precipitation. It is precursor of famine and is difficult to monitor due to its slow progression. The present study employs understanding drought and analyzing its various parameters such as rainfall. One of the main aspects of drought planning and mitigation includes hazard assessment, which describes the physical nature of drought and plays an important role in the relationship between vulnerability and risk. The study uses CPC rainfall time series of 12 years, 2001–2012, during the major rainfall period, i.e., southwest monsoon (June–September) over India at 10 km × 10 km pixel for the meteorological drought analysis. Drought occurrence patterns in the country in the 12-year time series period were analyzed using mean, inter-annual variability (coefficient of variation CV) and drought frequency of rainfall and rainy days. The analysis has highlighted the areas with lower mean rainfall and higher CV and higher drought frequency. Meteorological drought map based on rainfall and rainy day deviations was prepared separately, for all the 12 years, based on IMD criteria of rainfall deviations. Spatial agreement analysis between rainfall-based drought map and rainy days-based drought map was performed using kappa index. It is interesting to note that the agreement between the two maps was <50 % in all the 12 years. The result indicates that a combination of rainfall and rainy days brings additional information on drought intensity. Therefore, in this study, a methodology was suggested to generate drought maps by combining rainfall and rainy days.

17 citations