A method for tidal creek extraction using multi-source time-series remote sensing and Google Earth Engine

doi:10.13474/j.cnki.11-2246.2025.1008

Abstract

Abstract: This study focuses on tidal creek extraction in the central Jiangsu coastal zone using a semi-automatic method based on multi-source time-series remote sensing imagery, including Sentinel-1 and Sentinel-2A data, within the Google Earth Engine (GEE)platform.The method integrates spectral, index, texture, and polarization features, employing a Random Forest supervised classification algorithm for extraction.Time-series analysis enhances multispectral data, and various vegetation and water indices, along with texture features, are calculated for classification.The results show an overall accuracy of 0.95, outperforming single-data-source methods and providing accurate tidal creek boundary information.This approach offers technical support for ecological conservation and sustainable management in estuarine tidal creek regions.

Key words: tidal channel extraction, remote sensing imagery, Sentinel satellites, random forest, collaborative classification

CLC Number:

P237

TONG Haodong, ZHOU Yuwei, SHEN Yongming. A method for tidal creek extraction using multi-source time-series remote sensing and Google Earth Engine[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 43-49.

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