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Investigation of Non-natural Information from Remote Sensing Images: A Case Study Approach

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Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

The frequent changes in natural and non-natural information on the earth can be imaged using remote sensing (RS) techniques. Non-natural information changes are more frequent than natural changes on the planet; thus, they have a drastic impact on geographical information systems (GIS). Revolutions in satellite imaging technology have improved the interpretation of non-natural information (e.g., roads, buildings, bridges, dams) for GIS updates in a shorter period of time compared with ground surveying. The interpretation of road information is particularly vital for navigation. High-resolution RS images provide a good interpretation of road information; however, different interferences (e.g., building rooftops, parking lots, shadows from buildings, trees, vehicles) appear as noise, which reduces the efficiency of the extraction. In this chapter, different types of RS images are investigated, including panchromatic, aerial, multispectral, synthetic-aperture radar, and light detection and ranging.

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Akhtar, N., Choubey, N.S., Ragavendran, U. (2019). Investigation of Non-natural Information from Remote Sensing Images: A Case Study Approach. In: Anandakumar, H., Arulmurugan, R., Onn, C. (eds) Computational Intelligence and Sustainable Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-02674-5_12

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