Leveraging Citizen Science for Flood Extent Detection using Machine Learning Benchmark Dataset Article Swipe

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Muthukumaran Ramasubramanian , Iksha Gurung , Shubhankar Gahlot , Ronny Hänsch , Andrew Molthan , Manil Maskey ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2311.09276

Accurate detection of inundated water extents during flooding events is crucial in emergency response decisions and aids in recovery efforts. Satellite Remote Sensing data provides a global framework for detecting flooding extents. Specifically, Sentinel-1 C-Band Synthetic Aperture Radar (SAR) imagery has proven to be useful in detecting water bodies due to low backscatter of water features in both co-polarized and cross-polarized SAR imagery. However, increased backscatter can be observed in certain flooded regions such as presence of infrastructure and trees - rendering simple methods such as pixel intensity thresholding and time-series differencing inadequate. Machine Learning techniques has been leveraged to precisely capture flood extents in flooded areas with bumps in backscatter but needs high amounts of labelled data to work desirably. Hence, we created a labeled known water body extent and flooded area extents during known flooding events covering about 36,000 sq. kilometers of regions within mainland U.S and Bangladesh. Further, We also leveraged citizen science by open-sourcing the dataset and hosting an open competition based on the dataset to rapidly prototype flood extent detection using community generated models. In this paper we present the information about the dataset, the data processing pipeline, a baseline model and the details about the competition, along with discussion on winning approaches. We believe the dataset adds to already existing datasets based on Sentinel-1C SAR data and leads to more robust modeling of flood extents. We also hope the results from the competition pushes the research in flood extent detection further.

Related Topics

Flood Myth

Synthetic-Aperture Radar

Remote Sensing

Computer Science

Rendering (Computer Graphics)

Machine Learning

Environmental Science

Artificial Intelligence

Concepts

Flood myth Synthetic aperture radar Remote sensing Computer science Flooding (psychology) Rendering (computer graphics) Hyperspectral imaging Baseline (sea) Backscatter (email) Machine learning Environmental science Artificial intelligence Geography Geology Telecommunications Oceanography Psychology Psychotherapist Archaeology Wireless

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2311.09276
PDF: https://arxiv.org/pdf/2311.09276
OA Status: green
Cited By: 1
Related Works: 10
OpenAlex ID: https://openalex.org/W4388787360

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DOI: https://doi.org/10.48550/arxiv.2311.09276

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Title: Leveraging Citizen Science for Flood Extent Detection using Machine Learning Benchmark Dataset

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-11-15

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Authors: Muthukumaran Ramasubramanian, Iksha Gurung, Shubhankar Gahlot, Ronny Hänsch, Andrew Molthan, Manil Maskey

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Landing page: https://arxiv.org/abs/2311.09276

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Concepts: Flood myth, Synthetic aperture radar, Remote sensing, Computer science, Flooding (psychology), Rendering (computer graphics), Hyperspectral imaging, Baseline (sea), Backscatter (email), Machine learning, Environmental science, Artificial intelligence, Geography, Geology, Telecommunications, Oceanography, Psychology, Psychotherapist, Archaeology, Wireless

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Cited by: 1

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abstract_inverted_index.models.	178
abstract_inverted_index.present	183
abstract_inverted_index.rapidly	170
abstract_inverted_index.regions	72, 144
abstract_inverted_index.results	235
abstract_inverted_index.science	155
abstract_inverted_index.winning	206
abstract_inverted_index.Accurate	0
abstract_inverted_index.Aperture	36
abstract_inverted_index.Further,	150
abstract_inverted_index.However,	63
abstract_inverted_index.Learning	94
abstract_inverted_index.baseline	194
abstract_inverted_index.covering	138
abstract_inverted_index.dataset,	188
abstract_inverted_index.datasets	216
abstract_inverted_index.efforts.	19
abstract_inverted_index.existing	215
abstract_inverted_index.extents.	31, 230
abstract_inverted_index.features	55
abstract_inverted_index.flooding	7, 30, 136
abstract_inverted_index.further.	246
abstract_inverted_index.imagery.	62
abstract_inverted_index.labelled	116
abstract_inverted_index.mainland	146
abstract_inverted_index.modeling	227
abstract_inverted_index.observed	68
abstract_inverted_index.presence	75
abstract_inverted_index.provides	24
abstract_inverted_index.recovery	18
abstract_inverted_index.research	241
abstract_inverted_index.response	13
abstract_inverted_index.Satellite	20
abstract_inverted_index.Synthetic	35
abstract_inverted_index.community	176
abstract_inverted_index.decisions	14
abstract_inverted_index.detecting	29, 46
abstract_inverted_index.detection	1, 174, 245
abstract_inverted_index.emergency	12
abstract_inverted_index.framework	27
abstract_inverted_index.generated	177
abstract_inverted_index.increased	64
abstract_inverted_index.intensity	87
abstract_inverted_index.inundated	3
abstract_inverted_index.leveraged	98, 153
abstract_inverted_index.pipeline,	192
abstract_inverted_index.precisely	100
abstract_inverted_index.prototype	171
abstract_inverted_index.rendering	81
abstract_inverted_index.Sentinel-1	33
abstract_inverted_index.desirably.	120
abstract_inverted_index.discussion	204
abstract_inverted_index.kilometers	142
abstract_inverted_index.processing	191
abstract_inverted_index.techniques	95
abstract_inverted_index.Bangladesh.	149
abstract_inverted_index.Sentinel-1C	219
abstract_inverted_index.approaches.	207
abstract_inverted_index.backscatter	52, 65, 110
abstract_inverted_index.competition	164, 238
abstract_inverted_index.inadequate.	92
abstract_inverted_index.information	185
abstract_inverted_index.time-series	90
abstract_inverted_index.co-polarized	58
abstract_inverted_index.competition,	201
abstract_inverted_index.differencing	91
abstract_inverted_index.thresholding	88
abstract_inverted_index.Specifically,	32
abstract_inverted_index.open-sourcing	157
abstract_inverted_index.infrastructure	77
abstract_inverted_index.cross-polarized	60
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	6
citation_normalized_percentile