Disaster Response
33 papers with code • 1 benchmarks • 8 datasets
fMoW
xView
xBD
RoadTracer
CrisisMMD
MSAW
MEDIC
C2A: Human Detection in Disaster Scenarios
Most implemented papers
xBD: A Dataset for Assessing Building Damage from Satellite Imagery
DIUx-xView/xview2-baseline
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xBD is the largest building damage assessment dataset to date, containing 850, 736 building annotations across 45, 362 km\textsuperscript{2} of imagery.
Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones
In the second approach, although DeepSORT only processes a quarter of all frames due to hardware and time limitations, our model with DeepSORT (42. 9%) outperforms FairMOT (71. 4%) in terms of recall.
SpaceNet 6: Multi-Sensor All Weather Mapping Dataset
burakekim/MTL_homoscedastic_SRB
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The dataset and challenge focus on mapping and building footprint extraction using a combination of these data sources.
Towards Geospatial Foundation Models via Continual Pretraining
Geospatial technologies are becoming increasingly essential in our world for a wide range of applications, including agriculture, urban planning, and disaster response.
Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages
Microblogging platforms such as Twitter provide active communication channels during mass convergence and emergency events such as earthquakes, typhoons.
From Satellite Imagery to Disaster Insights
GogulaK/Disaster-Impact-Prediction-using-Aerial-Satellite-Imagery
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The use of satellite imagery has become increasingly popular for disaster monitoring and response.
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources
Such applications depend on classifying the situation across a region of interest, which can be depicted as a spatial "heatmap".
On Identifying Hashtags in Disaster Twitter Data
JRC1995/Tweet-Disaster-Keyphrase
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Moreover, only a small number of tweets that contain actionable hashtags are useful for disaster response.
Uneven Coverage of Natural Disasters in Wikipedia: the Case of Flood
We also note how coverage of floods in countries with the lowest income, as well as countries in South America, is substantially lower than the coverage of floods in middle-income countries.
Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response
Multimedia content in social media platforms provides significant information during disaster events.
