Inland water body extraction in complex reliefs from Sentinel-1 satellite data

Juan Carlos Valdiviezo Navarro; Adan Salazar-Garibay; Alejandro Téllez-Quiñones; Mauricio Orozco-del-Castillo; Alejandra A. López-Caloca

doi:10.1117/1.JRS.13.016524

14 March 2019 Inland water body extraction in complex reliefs from Sentinel-1 satellite data

Juan Carlos Valdiviezo Navarro, Adan Salazar-Garibay, Alejandro Téllez-Quiñones, Mauricio Orozco-del-Castillo, Alejandra A. López-Caloca

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 13, Issue 1, 016524 (March 2019). https://doi.org/10.1117/1.JRS.13.016524

Abstract

Water body classification is a topic of great interest, especially for the effective management of floods. Synthetic aperture radar (SAR) imaging has demonstrated a great potential for water monitoring, given its capacity to register images independent of weather conditions. Several algorithms for water detection using SAR images are based on optimal thresholding techniques. However, these simple methodologies produce false classification results when small water bodies embedded in mountain ranges are presented in the image. We present an unsupervised and easy-to-implement methodology, based on local Moran index of spatial association in combination with morphological closing operations, for inland water body extraction. According to several experiments, we demonstrate that our method is capable of effectively extracting lakes and rivers located at different land surface reliefs without the requirement of a training step. In addition, comparisons with the state-of-the-art techniques demonstrate the effectiveness of our procedure, performing an overall accuracy of 96.37% and Kappa = 0.927.

Citation Download Citation

Juan Carlos Valdiviezo Navarro, Adan Salazar-Garibay, Alejandro Téllez-Quiñones, Mauricio Orozco-del-Castillo, and Alejandra A. López-Caloca "Inland water body extraction in complex reliefs from Sentinel-1 satellite data," Journal of Applied Remote Sensing 13(1), 016524 (14 March 2019). https://doi.org/10.1117/1.JRS.13.016524

Received: 25 November 2018; Accepted: 22 February 2019; Published: 14 March 2019

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