Assessing internet and web services based webdom and virtual web-data-centric geographical study

At present, the traditional geographical study is somewhat shifted to virtual web-datacentric geographical study and it was started almost around last decade of the twentieth century concerning remotely sensed earth surface, digitisation, virtual data storing and their artificial intelligence based machine learning for spatio-temporal analysis, prediction and thematic mapping. Now in the age of webdom—a global digital kingdom of internet and web services, when internet services flooded everything relating to continuous up-gradation of computer-related science and technologies along with increasing number of internet users and GPS enabled smart phones, geographical data are generated by exaflood leading to bigdata. Many online data are now easily available to everyone from anywhere at any time. The objective is to assess the webdom and to understand the scope of contemporary virtual web-data-centric geographical study involving geographical bigdata, machine learning and WebGIS, when virtual world abundantly expands gradually during this period of webdom. Each data in bigdata contains geospatial attributes. Worldwide under the exponential growth and advancement of data science like other scientific disciplines geography is also predicting different phenomenon based on artificial intelligence and machine learning. The three main facets of virtual web-data-centric geographical study are geographical bigdata, geographical machine learning, and WebGIS. It is centrally concerned with digital data and web services. Here data are analysed through machine learning methods. Sometimes reliability of web-data is in question without field verification which is considered as the primary requisition of traditional geography.