Intelligent visual analytic techniques for flood area mapping application

Data Science and Visual Analytics techniques are hand and glove of exploring the insights of many complex application models. In this regard, the role of BigData analytics using voluminous unstructured database records of many applications is already proved beyond the doubts. In the case of geospatial big data domain as on date few use cases of vector based analytic models are evolving with the support of SpatialHadoop environment and currently becoming a field of research attraction mainly to support real time geospatial models. In line to this, this paper mainly brings out the details of developing a geospatial flood area mapping model without the use of SpatialHadoop as the model mainly works on regional scale raster file formats. The proposed model mainly takes the advantages of interactive visual analytics techniques both to visualize the intermediate process results as well as in refining the parameters of the model and finally enhancing the accuracy of the end results.