Role of Machine Intelligence and Big Data in Remote Sensing
Suriya Murugan, Anandakumar Haldorai · Advances in data mining and database management book series · 2019
Technological advances in computing, data storage, networks, and sensors have dramatically increased our ability to access, store, and process huge amounts of data. “Big data” as a term has been the biggest trends of the last few years, leading to an elevation in research, as well as industry and government applications. The problem with current big data analysis faces any one of the following challenges: heterogeneity and incompleteness, scale, timeliness, privacy, and human collaboration. It's an undeniable fact that “data” forms the basis for geospatial industry. With technological advances in the collection, distribution, management, and access of data, there is an exponential increase in the amount of geospatial information. Computational intelligence techniques such as machine learning optimization and advanced data analytics can help make faster decisions. This chapter analyses how geospatial data is driving software and services market as a “big data challenge” and how biologically inspired techniques are effective in analyzing remote sensing data.