Information management and technology

This theme covers aspects related to hardware, software, networks, and media for the collection, storage, processing, transmission and presentation of information for disaster risk reduction (DRR), as well as related services. It also addresses information management to support knowledge sharing for DRR, such as data exchange standards and taxonomy.

Latest Information management and technology additions in the Knowledge Base

African children fetch water from a water source
While early warning systems are effective, to fully inform disaster-risk-reduction interventions they require effective coordination and early action protocols that function across multiple levels of governance, from local to national levels.
Anticipation Hub
The regional scientific and principal organisation, the Pacific Community (SPC), is spearheading a new project, called Digital Earth Pacific, to capture extensive satellite information about climate change and natural disasters in the region.
Inter Press Service International Association
A U.S. Geological Survey team has begun a seismic sensor deployment in an effort to capture aftershock data following the 4.8 magnitude earthquake that rattled New Jersey April 5, 2024, and was felt for hundreds of miles.
United States Geological Survey
The activity was carried out first in the classroom where children were allowed to express their experience living with flood through drawings and artistic expression.
Global Resilience Partnership
Equipment on a farm
UConn researchers has found a way to drastically cut the lag time for these assessments using remote sensing data and machine learning, bringing disturbance assessment closer to near real-time (NRT) monitoring.
University of Connecticut
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This research analyzed Twitter communications about wildfires and smoke from 2022 authored by institutional public health and environmental accounts in Washington and Oregon.
Disasters are often perceived as acts of nature, unavoidable and inevitable. However, this is far from the truth.
United Nations University Institute for Environment and Human Security
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This paper evaluates the extent to which artificial intelligence (AI) trained on open, public datasets can be used to improve global access to forecasts of extreme events in global rivers.

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