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Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 32, Number 11(4) (2020)
Copyright(C) MYU K.K.
pp. 3813-3822
S&M2377 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2769
Published in advance: May 16, 2020
Published: November 30, 2020

Inundation Analysis Method for Urban Mountainous Areas Based on Soil Conservation Service Curve Number (SCS-CN) Model Using Remote Sensing Data [PDF]

Xinyue He, Chao Chen, Yue Liu, and Yanli Chu

(Received January 15, 2020; Accepted April 25, 2020)

Keywords: SCS-CN model, inundation analysis, land use, urban mountain, rainfall-runoff calculation

Flooding and waterlogging are frequent disasters that pose serious threats to the safety of human lives and infrastructure. We propose a method of estimating the inundation area in urban mountainous zones based on the soil conservation service curve number (SCS-CN) model. Remote sensing data are used to localize parameters and ensure model accuracy, and are combined with topographic maps to determine land-use type, slope, and waterlogged ground. Watershed analysis based on the SCS-CN model is performed to obtain rainfall-runoff data. The inundation area is then estimated from the rainfall data, and the spatial and temporal distribution characteristics of the flood inundation area are analyzed from the perspective of land use. Experimental results from a case study in Mingxi, China, verify the effectiveness of this method for the analysis of flood inundation in urban mountainous areas.

Corresponding author: Chao Chen


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Xinyue He, Chao Chen, Yue Liu, and Yanli Chu, Inundation Analysis Method for Urban Mountainous Areas Based on Soil Conservation Service Curve Number (SCS-CN) Model Using Remote Sensing Data, Sens. Mater., Vol. 32, No. 11, 2020, p. 3813-3822.



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