Low Altitude Disaster Imagery (LADI) Dataset

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/ladi-dataset")

fs.listdir("s3://ladi")

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 2015-2019. The initial release of LADI focuses on the Atlantic hurricane seasons and coastal states along the Atlantic Ocean and Gulf of Mexico. Annotations are included for major hurricanes of Harvey, Maria, and Florence. 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.

Contact:

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 2015-2019. The initial release of LADI focuses on the Atlantic hurricane seasons and coastal states along the Atlantic Ocean and Gulf of Mexico. Annotations are included for major hurricanes of Harvey, Maria, and Florence. 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

Managed By:

https://beaverworks.ll.mit.edu/

Collabs:

• ASDI:
  • Tags: disaster response

Resources:

1. resource:
   • Description: LADI dataset: images and labels
   • ARN: arn:aws:s3:::ladi
   • Region: us-west-2
   • Type: S3 Bucket
   • Explore: Browse Bucket

Tags:

aws-pds, aerial imagery, coastal, computer vision, disaster response, earth observation, earthquakes, geospatial, imaging, image processing, infrastructure, land, machine learning, mapping, natural resource, seismology, transportation, urban, water

Tutorials:

1. tutorial:
   • Title: LADI Tutorials
   • URL: https://github.com/LADI-Dataset/ladi-tutorial
   • AuthorName: Andrew Weinert, Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren, Ryan Earley, Nadia Dimitrova
   • AuthorURL: https://github.com/LADI-Dataset

Tools & Applications:

1. tools & applications:

   • Title: NIST TRECVID 2020 - Disaster Scene Description and Indexing (DSDI)
   • URL: https://www-nlpir.nist.gov/projects/tv2020/dsdi.html
   • AuthorName: TREC Video Retrieval Evaluation (TRECVID)

2. tools & applications:

   • Title: Remote Sensing for Disaster Response Course
   • URL: https://github.com/bwsi-hadr
   • AuthorName: Beaver Works Summer Institute
   • AuthorURL: https://beaverworks.ll.mit.edu/CMS/bw/bwsi

Publication:

1. publication:

   • Title: Large Scale Organization and Inference of an Imagery Dataset for Public Safety
   • URL: https://doi.org/10.1109/HPEC.2019.8916437
   • AuthorName: Jeffrey Liu, David Strohschein, Siddharth Samsi, Andrew Weinert

2. publication:

   • Title: Video Testing at the FirstNet Innovation and Test Lab Using a Public Safety Dataset
   • URL: https://doi.org/10.1109/LNET.2019.2955833
   • AuthorName: Chris Budny, Jeffrey Liu, Andrew Weinert

3. publication:

   • Title: Train and Deploy an Image Classifier for Disaster Response
   • URL: https://arxiv.org/abs/2005.05495
   • AuthorName: Jianyu Mao, Kiana Harris, Nae-Rong Chang, Caleb Pennell, Yiming Ren