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FEMA and NOAA.html
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<!doctype html>
<html lang="en">
<head>
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<title>Benchmark Datasets for Machine Learning for Natural Disasters</title>
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<h3><b>Benchmark Dataset for Automatic Damaged Building Detection from Post-Hurricane Remotely Sensed Imagery</b></h3> <!-- Title -->
<h5> Multimodal (Vector data and Image) | Hurricane | Response </h5> <!-- Type | Topic | Disaster phase -->
</div>
<div class="w3-container"> <!-- Data description -->
<p> FEMA and NOAA is a dataset for hurricane damaged building detection. It contains vector (FEMA) and image (NOAA) data and is introduced for image segmentation and multiclass (ordinal) classification.</p>
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<li class="list-group-item"><strong>ML task type:</strong> Image segmentation, multiclass (ordinal) classification</li>
<li class="list-group-item"><strong>Data Source:</strong> Official Data (national); Earth Observation Data and GeoSpatial Imagery</li>
<li class="list-group-item"><strong>Size:</strong> Around 156,099 damage assessments (FEMA original data); 400 GB Images (NOAA original data) </li>
<li class="list-group-item"><strong>Timespan:</strong> 2017</li>
<li class="list-group-item"> <strong>Geographical Coverage:</strong> Greater Houston Area </li>
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<li class="list-group-item"> <strong>Baseline Information</strong></li>
<li class="list-group-item"> <strong>Evaluated on:</strong> unreported</li>
<li class="list-group-item"> <strong>Metrics used:</strong> unreported </li>
<li class="list-group-item"> <strong>Results as reported in original paper:</strong> unreported </li>
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<li class="list-group-item"> <strong>Find out more by:</strong></li>
<li class="list-group-item"> <a href="https://arxiv.org/abs/1812.05581" target="_blank">Reading the research paper</a></li>
<li class="list-group-item"> <a href="https://ieee-dataport.org/open-access/benchmark-dataset-automatic-damaged-building-detection-post-hurricane-remotely-sensed" target="_blank">Checking out the dataset!</a> Note: The data are stored as ESRI Shapefiles and GeoTIFFs. You would need to sign up to access the data. </li>
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If you're using this resource, please cite:
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Sean Andrew Chen, Andrew Escay, Christopher Haberland, Tessa Schneider, Valentina Staneva, and Youngjun Choe.
Benchmark dataset for automatic damaged building detection from post-hurricane remotely sensed imagery. arXiv
preprint arXiv:1812.05581, 2018.
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