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We present xBD, a new, large-scale dataset for the advancement of change detection and building damage assessment for humanitarian assistance and disaster recovery research.
Filtering to remove cloud cover in satellite imagery
O. R. Mitchell, E. J. Delp, and P. L. Chen · 1977
Earlier work this paper cites.
EMS-98 (european macroseismic scale)
G. Grünthal, R. Musson, J. Schwarz, and M. Stucchi · 1998
Earlier work this paper cites.
Classifications of structural types and damage patterns of buildings for earthquake field investigation
S. Okada and N. Takai · 1999
Earlier work this paper cites.
Physical Flood Vulnerability of Residential Properties in Coastal, Eastern England
I. Kelman · 2002
Earlier work this paper cites.
Methods for the evaluation of direct and indirect flood losses
A. Thieken, V. Ackermann, F. Elmer, H. Kreibich, B. Kuhlmann, U. Kunert, H. Maiwald, B. Merz, K. Piroth, J. Schwarz, R. Schwarze, I. Seifert, J. Seifert, and L.-F.-U. Innsbruck · 2008
Earlier work this paper cites.
Residential Building Damage from Hurricane Storm Surge: Proposed Methodologies to Describe, Assess and Model Building Damage
C. J. Friedland · 2009
Earlier work this paper cites.
The use of remote sensing for post-earthquake damage assessment: Lessons from recent events, and future prospects
R. Foulser-Piggott, R. Spence, K. Saito, D. M. Brown, and R. Eguchi · 2012
Earlier work this paper cites.
Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4)
L. Giglio, J. T. Randerson, and G. R. van der Werf · 2013
Cited alongside, same era.
U-Net: Convolutional Networks for Biomedical Image Segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Cloud detection for high-resolution satellite imagery using machine learning and multi-feature fusion
T. Bai, D. Li, K. Sun, Y. Chen, and W. Li · 2016
Cited alongside, same era.
Damage assessment operations manual: A guide to assessing damage and impact
Federal Emergency Management Agency · 2016
Cited alongside, same era.
Damage detection from aerial images via convolutional neural networks
A. Fujita, K. Sakurada, T. Imaizumi, R. Ito, S. Hikosaka, and R. Nakamura · 2017
Cited alongside, same era.
S. A. Chen, A. Escay, C. Haberland, T. Schneider, V. Staneva, and Y. Choe · 2018
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DeepGlobe 2018: A challenge to parse the earth through satellite images
I. Demir, K. Koperski, D. Lindenbaum, G. Pang, J. Huang, S. Basu, F. Hughes, D. Tuia, and R. Raska · 2018
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Hazus hurricane model user guidance
Federal Emergency Management Agency · 2018
Later among the works it cites.
Identifying collapsed buildings using post-earthquake satellite imagery and convolutional neural networks: A case study of the 2010 haiti earthquake
M. Ji, L. Liu, and M. Buchroithner · 2018
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Smear effect on high-resolution remote sensing satellite image quality
W. A. Wahballah, T. M. Bazan, and M. Ibrahim · 2018
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Building damage assessment in the city of mocoa
United States Geological Survey · 2017
Cited alongside, same era.
Remote sensing imaging simulation and cloud removal
X. Zhu, F. Wu, T. Wu, and C. Zhao · 2017
Cited alongside, same era.
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei
Cited in the paper.
GDAL/OGR Geospatial Data Abstraction Software Library
GDAL/OGR contributors · 2019
Closest in time.
Creating xBD: A dataset for assessing building damage from satellite imagery
R. Gupta, B. Goodman, N. Patel, R. Hosfelt, S. Sajeev, E. Heim, J. Doshi, K. Lucas, H. Choset, and M. Gaston · 2019
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