CYCVIVAug 19, 2021

Challenges and Solutions for Utilizing Earth Observations in the "Big Data" era

arXiv:2108.08886v19 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental overview addressing data management issues for researchers and practitioners in geoscience and EO fields.

The paper reviews the challenges and current state-of-the-art in Earth Observation (EO) data preservation and manipulation in the Big Data era, focusing on modern approaches for compressing, clustering, and modeling EO data for analysis and visualization.

The ever-growing need of data preservation and their systematic analysis contributing to sustainable development of the society spurred in the past decade,numerous Big Data projects and initiatives are focusing on the Earth Observation (EO). The number of Big Data EO applications has grown extremely worldwide almost simultaneously with other scientific and technological areas of the human knowledge due to the revolutionary technological progress in the space and information technology sciences. The substantial contribution to this development are the space programs of the renowned space agencies, such as NASA, ESA,Roskosmos, JAXA, DLR, INPE, ISRO, CNES etc. A snap-shot of the current Big Data sets from available satellite missions covering the Bulgarian territory is also presented. This short overview of the geoscience Big Data collection with a focus on EO will emphasize to the multiple Vs of EO in order to provide a snapshot on the current state-of-the-art in EO data preservation and manipulation. Main modern approaches for compressing, clustering and modelling EO in the geoinformation science for Big Data analysis, interpretation and visualization for a variety of applications are outlined. Special attention is paid to the contemporary EO data modelling and visualization systems.

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