Literature DB >> 32801405

Automatic Boosted Flood Mapping from Satellite Data.

Brian Coltin1, Scott McMichael1, Trey Smith1, Terrence Fong1.   

Abstract

Numerous algorithms have been proposed to map floods from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, most require human input to succeed, either to specify a threshold value or to manually annotate training data. We introduce a new algorithm based on Adaboost which effectively maps floods without any human input, allowing for a truly rapid and automatic response. The Adaboost algorithm combines multiple thresholds to achieve results comparable to state-of-the-art algorithms which do require human input. We evaluate Adaboost, as well as numerous previously proposed flood mapping algorithms, on multiple MODIS flood images, as well as on hundreds of non-flood MODIS lake images, demonstrating its effectiveness across a wide variety of conditions.

Entities:  

Keywords:  Adaboost; MODIS; flood mapping; floods

Year:  2016        PMID: 32801405      PMCID: PMC7427812          DOI: 10.1080/01431161.2016.1145366

Source DB:  PubMed          Journal:  Int J Remote Sens        ISSN: 0143-1161            Impact factor:   3.151


  1 in total

1.  Comparative analysis of normalised difference spectral indices derived from MODIS for detecting surface water in flooded rice cropping systems.

Authors:  Mirco Boschetti; Francesco Nutini; Giacinto Manfron; Pietro Alessandro Brivio; Andrew Nelson
Journal:  PLoS One       Date:  2014-02-20       Impact factor: 3.240

  1 in total
  1 in total

1.  Satellite imaging reveals increased proportion of population exposed to floods.

Authors:  B Tellman; J A Sullivan; C Kuhn; A J Kettner; C S Doyle; G R Brakenridge; T A Erickson; D A Slayback
Journal:  Nature       Date:  2021-08-04       Impact factor: 49.962

  1 in total

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