Low Altitude Disaster Imagery (LADI) Dataset

Description

The Low Altitude Disaster Imagery (LADI) Dataset consists of human and machine annotated airborne images collected by the Civil Air Patrol in support of various disaster responses from 2015-2023. Two key distinctions are the low altitude, oblique perspective of the imagery and disaster-related features, which are rarely featured in computer vision benchmarks and datasets.

Update Frequency

Periodically

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Documentation

https://github.com/LADI-Dataset/ladi-overview

Managed By

MIT Lincoln Laboratory Humanitarian Assistance and Disaster Relief group

See all datasets managed by MIT Lincoln Laboratory Humanitarian Assistance and Disaster Relief group.

Contact

ladi-dataset-admin@mit.edu

How to Cite

Low Altitude Disaster Imagery (LADI) Dataset was accessed on DATE from https://registry.opendata.aws/ladi.

Usage Examples

Tutorials

• LADI v1 Tutorials by Andrew Weinert, Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren, Ryan Earley, Nadia Dimitrova
  
• LADI v2 Overview by Jeffrey Liu, Sam Scheele, Katherine Picchione
  

Tools & Applications

• NIST TRECVID 2020 - Disaster Scene Description and Indexing (DSDI) by TREC Video Retrieval Evaluation (TRECVID)
  
• Remote Sensing for Disaster Response Course by Beaver Works Summer Institute
  

Publications

• Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI by Vamshi Krishna Enabothala, Morgan Dutton, and Sandeep Verma
  
• An overview on the evaluated video retrieval tasks at TRECVID 2022 by George Awad, Keith Curtis, Asad Butt, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Lukas Diduch, Jeffrey Liu, Yvette Graham, Georges Quenot
  
• Evaluating Multiple Video Understanding and Retrieval Tasks at TRECVID 2021 by George Awad, Asad Butt, Keith Curtis, Jonathan G. Fiscus, Afzal A. Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Yvette Graham, Gareth Jones, Georges Quenot
  
• Large Scale Organization and Inference of an Imagery Dataset for Public Safety by Jeffrey Liu, David Strohschein, Siddharth Samsi, Andrew Weinert
  
• Train and Deploy an Image Classifier for Disaster Response by Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren
  
• TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains by George Awad, Asad A. Butt, Keith Curtis, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Jesse Zhang, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Alan F. Smeaton, Yvette Graham, Gareth J. F. Jones, Wessel Kraaij, Georges Quenot
  
• Video Testing at the FirstNet Innovation and Test Lab Using a Public Safety Dataset by Chris Budny, Jeffrey Liu, Andrew Weinert