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Demand-driven data services for humanitarian aid

Schneibel, Anne and Gähler, Monika (2020) Demand-driven data services for humanitarian aid. Fachtagung Katastrophenvorsorge, Online.

Full text not available from this repository.

Abstract

In a crisis event, humanitarian aid organisations often do not have the latest spatial information at the required scale, which they would urgently need for many decision-making assessments. In the project "Demand-driven Data Services for Humanitarian Aid" (Data4Human), remote sensing data and other data sources are to be analysed in order to identify they possible use in the humanitarian context. The topics were jointly defined by aid organisations and DLR scientists and include current technical aspects such as artificial intelligence, the use of web-based data sources or the creation of dynamic interfaces for data exchange. The areas of application range from disaster control and food security to the violation of human rights, and are adapted to the needs of specific users.

Item URL in elib:https://elib.dlr.de/137670/
Document Type:Conference or Workshop Item (Other)
Title:Demand-driven data services for humanitarian aid
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schneibel, AnneAnne.Schneibel (at) dlr.dehttps://orcid.org/0000-0003-4329-1023
Gähler, MonikaMonika.Gaehler (at) dlr.dehttps://orcid.org/0000-0001-7421-3488
Date:19 November 2020
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Humanitarian Aid, Geodata, Remote Sensing, Artificial Intelligence, Web Harvesting
Event Title:Fachtagung Katastrophenvorsorge
Event Location:Online
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoproducts and systems, services
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Schneibel, Anne
Deposited On:19 Nov 2020 11:59
Last Modified:25 Feb 2021 10:54

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