How Big Data Can Help to Monitor the Environment and to Mitigate Risks due to Climate Change

A review

verfasst von

J. P. Montillet, G. Kermarrec, E. Forootan, M. Haberreiter, X. He, W. Finsterle, R. Fernandes, C. K. Shum

Abstract

Climate change triggers a wide range of hydrometeorological, glaciological, and geophysical processes that span across vast spatiotemporal scales. With the advances in technology and analytics, a multitude of remote sensing (RS), geodetic, and in situ instruments have been developed to effectively monitor and help comprehend Earth’s system, including its climate variability and the recent anomalies associated with global warming. A huge volume of data is generated by recording these observations, resulting in the need for novel methods to handle and interpret such big datasets. Managing this enormous amount of data extends beyond current computer storage considerations; it also encompasses the complexities of processing, modeling, and analyzing. Big datasets present unique characteristics that set them apart from smaller datasets, thereby posing challenges to traditional approaches. Moreover, computational time plays a crucial role, especially in the context of geohazard warning and response systems, which necessitate low latency requirements.

Organisationseinheit(en)

Institut für Meteorologie und Klimatologie

Externe Organisation(en)

Aalborg University
Jiangxi University of Science and Technology
University of Beira Interior
The Ohio State University
Physikalisch-Meteorologisches Observatorium World Radiation Center (PMOD/WRC)

Typ

Rezension in Fachzeitschrift

Journal

IEEE Geoscience and Remote Sensing Magazine

Band

12

Seiten

67-89

Anzahl der Seiten

23

ISSN

2473-2397

Publikationsdatum

06.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Informatik (insg.), Instrumentierung, Erdkunde und Planetologie (insg.), Elektrotechnik und Elektronik

Ziele für nachhaltige Entwicklung

SDG 13 – Klimaschutzmaßnahmen

Elektronische Version(en)

https://doi.org/10.1109/MGRS.2024.3379108 (Zugang: Geschlossen)