A multi-criteria analysis (MCA) approach to describe the effective utilization of geospatial techniques for disaster risk reduction at village level in Kopili River Basin (KRB) of Assam State, India is presented. The KRB is chronically flood affected due to seasonal monsoon and rise in water levels of Kopili River. Based on the MCA approach using flood hazard layer derived from the spatio-multi-temporal historic satellite data-sets (comprising of sensors from RISAT-1 SAR, Radarsat SAR and IRS AWiFS), socio-economic data (based on five census variables), infrastructure (road network) and land use vulnerabilities (cropped and uncropped areas), flood risk zones are derived. Our study elucidates that 24,837 ha of crop area spread across 95 villages in the KRB falls in high risk zone, about 39,209 ha distributed in 150 villages falls under moderate-high risk zones and remaining area spread over 162 villages is more or less unaffected. The proposed approach can be applied elsewhere in other river basins to estimate the flood risk so as to mitigate the disaster risk posed by the floods.
A collection of datasets is Big data so that it to be To process huge and complex datasets becomes difficult. so that using big data analytics the process of applying huge amount of datasets consists of many data types is the big data on-hand theoretical models and technique tools. The technology of mobile communication introduced low power ,low price and multi functional devices. A ground for data mining research is analysis of data pertaining to mobile communication is used. theses mining frequent patterns and clusters on data streams collaborative filtering and analysis of social network. The data analysis of mobile communication has been often used as a background application to motivate many technical problem in data mining research. This paper refers in mobile communication networking to find the fault nodes between source to destination transmission using data mining techniques and detect the faults using outliers. outlier detection can be used to find outliers in multivariate data in a simple ensemble way. Network analysis with R to build a network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.