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Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations

COPING TEAM—Coastal and Ocean Planning Governance, CESAM—Centre for Environmental and Marine Studies, Department of Environment and Planning, University of Aveiro, 3810–120 Aveiro, Portugal
Department of Earth, Environmental and Physical Sciences, University of Siena, 53100 Siena, Italy
CIMA Research Foundation, 17100 Savona, Italy
Department of Information Engineering, Electronics and Telecommunications, Sapienza US, 00184 Rome, Italy
Águeda School of Technology and Management, Aveiro University, 3750–127 Águeda, Portugal
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(11), 1305;
Received: 3 May 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 31 May 2019
(This article belongs to the Section Remote Sensing Image Processing)
Satellite remote sensing data are often used to extract water surfaces related to extreme events like floods. This study presents the Multi INDEx Differencing (MINDED) method, an innovative procedure to estimate flood extents, aiming at improving the robustness of single water-related indices and threshold-based approaches. MINDED consists of a change detection approach integrating specific sensitivities of several indices. Moreover, the method also allows to quantify the uncertainty of the Overall flood map, based on both the agreement level of the stack of classifications and the weight of every index obtained from the literature. Assuming the lack of ground truths to be the most common condition in flood mapping, MINDED also integrates a procedure to reduce the subjectivity of thresholds extraction focused on the analysis of water-related indices frequency distribution. The results of the MINDED application to a case study using Landsat images are compared with an alternative change detection method using Sentinel-1A data, and demonstrate consistency with local fluvial flood records. View Full-Text
Keywords: remote sensing; optical satellites; Landsat; change detection; flood mapping; Portugal remote sensing; optical satellites; Landsat; change detection; flood mapping; Portugal
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MDPI and ACS Style

Oliveira, E.R.; Disperati, L.; Cenci, L.; Gomes Pereira, L.; Alves, F.L. Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations. Remote Sens. 2019, 11, 1305.

AMA Style

Oliveira ER, Disperati L, Cenci L, Gomes Pereira L, Alves FL. Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations. Remote Sensing. 2019; 11(11):1305.

Chicago/Turabian Style

Oliveira, Eduardo R., Leonardo Disperati, Luca Cenci, Luísa Gomes Pereira, and Fátima L. Alves 2019. "Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations" Remote Sensing 11, no. 11: 1305.

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