Remote Sensing Big Data: Challenges, Opportunities, Management and Application

Abstract

Abstract:  Each single day many earth monitoring spaceborne and aerial sensors from various countries are collecting a huge quantity of remotely sensed data. This large amount of data is regarded as remote sensing (RS) big data or big RS data. Due to these massive amounts of data the world has entered in the age of big (RS) data. Big RS data have different physical, spatial and temporal features such as multisource, multiscale, high dimensional, dynamic state, isomer, and nonlinear properties. Moreover, RS big data are becoming as an economic resource and a modern key asset in several applications. The RS big data are using for various applications in resources as well as environment (both natural and built) for local and global observation, for example in agriculture, natural disaster monitoring, worldwide climate change, and urban planning. However, this paper aims to find the big RS data as well as data-intensive problems, counting RS big data challenges, analysis, methods, techniques, processing, managing, and effective utilization of big RS data. Furthermore, it seeks the methods and applications of RS big data. In the current study, the challenges and opportunities of RS big data applications were analyzed specifically. In order to explain the big RS data aspects, a case study discussing the application of RS big data was demonstrated. In this test case, RS big data were used to identify flood zones in Wadi Al Rimah in Kingdom of Saudi Arabia applying a big archive of RS data. In this study RS big data were applied to exhibit the substantial challenges along opportunities carried by the application of RS big data.