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Artificial Intelligence for Very High Resolution Earth Observation: Environment Monitoring

Datcu, Mihai (2019) Artificial Intelligence for Very High Resolution Earth Observation: Environment Monitoring. [Other]

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Abstract

The Earth is facing unprecedented climatic, geomorphologic, environmental and anthropogenic changes, which require global scale observation and monitoring. Thus a multitude of new orbital and suborbital Earth Observation (EO) sensors and mission are in operation or will be soon launched. The interest is in a global understanding involving observation of large extended areas, and long periods of time, with a broad variety of EO sensors. The collected EO data volumes are thus increasing immensely with a rate of many Terabytes of data a day. With the current EO technologies these figure will be soon amplified, the horizons are beyond Zettabytes of data. The challenge is the exploration of these data and the timely delivery of focused information and knowledge in a simple understandable format. Therefore, search engines, and Data Mining are new fields of study that have arisen to seek solutions to automating the extraction of information from EO observations and other related sources that can lead to Knowledge Discovery and the creation of an actionable intelligence. Knowledge Discovery is among the most interesting research trends, however, the real challenge is to combine Artificial Intelligence with the power and potential of human intelligence, this being a primary objective in the field of Human Machine Communication (HMC). The goal is to go beyond the today methods of information retrieval and develop new concepts and methods to support end users of EO data to interactively analyze the information content, extract relevant parameters, associate various sources of information, learn and/or apply knowledge and to visualize the pertinent information without getting overwhelmed. In this context, the synergy of HMC and information retrieval becomes an interdiscipliinary approach in automating EO data analysis.

Item URL in elib:https://elib.dlr.de/130905/
Document Type:Other
Additional Information:This was a tutorial by Prof. Datcu in the frame of Blaise Pascal International Chair
Title:Artificial Intelligence for Very High Resolution Earth Observation: Environment Monitoring
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Date:April 2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Earth Observation Data, Artificial Intelligence, Very High Resolution Imagery
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Karmakar, Chandrabali
Deposited On:21 Nov 2019 13:42
Last Modified:04 Dec 2019 15:29

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