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Effect of Hydro-geomorphological Environments on Surface Water Areas Extraction.

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Title: Effect of Hydro-geomorphological Environments on Surface Water Areas Extraction.
Authors: Jia, Yuan-Yuan1 (AUTHOR), Duan, Huan-Feng1 (AUTHOR), Yan, Xu-Feng2 (AUTHOR) xufeng.yan@scu.edu.cn
Source: Water Resources Management. Sep2025, Vol. 39 Issue 11, p5461-5479. 19p.
Subject Terms: *Geomorphology, *Hydrography, *Water management, *Water supply, *Geographic information systems, *Remote-sensing images
Abstract: Surface water is a critical component of the global ecological environment and plays a pivotal role in societal development. Accurate detection and mapping of these water bodies are essential for resource management, flood monitoring, and disaster response. This study aims to investigate the impact of hydro-geomorphological factors on water body extraction using Google Earth Engine (GEE) and Landsat-8 imagery. We employed the OTSU threshold algorithm and the two most widely used spectral water indices, the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI). Our objective is to identify the most suitable water index for 12 typical test sites, including lakes/reservoirs, mountainous regions, and urban areas across various climatic zones from humid to arid. Results indicate that both spectral water indices performed well at lakes/reservoirs test sites under varying humid and arid conditions, demonstrating approximately 97% accuracy. NDWI outperformed MNDWI in mountainous and arid/semi-arid conditions, with overall accuracy in mountainous areas exceeding 85%, which is more than 12% higher than MNDWI. NDWI also achieved an average accuracy of over 86% in arid sites. Conversely, MNDWI proved more effective in urban and humid/semi-humid settings, maintaining overall accuracy above 95% in both areas. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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DbLabel: Energy & Power Source
An: 188452492
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Effect of Hydro-geomorphological Environments on Surface Water Areas Extraction.
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  Data: <searchLink fieldCode="AR" term="%22Jia%2C+Yuan-Yuan%22">Jia, Yuan-Yuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Duan%2C+Huan-Feng%22">Duan, Huan-Feng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Xu-Feng%22">Yan, Xu-Feng</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> xufeng.yan@scu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Water+Resources+Management%22">Water Resources Management</searchLink>. Sep2025, Vol. 39 Issue 11, p5461-5479. 19p.
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  Data: *<searchLink fieldCode="DE" term="%22Geomorphology%22">Geomorphology</searchLink><br />*<searchLink fieldCode="DE" term="%22Hydrography%22">Hydrography</searchLink><br />*<searchLink fieldCode="DE" term="%22Water+management%22">Water management</searchLink><br />*<searchLink fieldCode="DE" term="%22Water+supply%22">Water supply</searchLink><br />*<searchLink fieldCode="DE" term="%22Geographic+information+systems%22">Geographic information systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Remote-sensing+images%22">Remote-sensing images</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Surface water is a critical component of the global ecological environment and plays a pivotal role in societal development. Accurate detection and mapping of these water bodies are essential for resource management, flood monitoring, and disaster response. This study aims to investigate the impact of hydro-geomorphological factors on water body extraction using Google Earth Engine (GEE) and Landsat-8 imagery. We employed the OTSU threshold algorithm and the two most widely used spectral water indices, the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI). Our objective is to identify the most suitable water index for 12 typical test sites, including lakes/reservoirs, mountainous regions, and urban areas across various climatic zones from humid to arid. Results indicate that both spectral water indices performed well at lakes/reservoirs test sites under varying humid and arid conditions, demonstrating approximately 97% accuracy. NDWI outperformed MNDWI in mountainous and arid/semi-arid conditions, with overall accuracy in mountainous areas exceeding 85%, which is more than 12% higher than MNDWI. NDWI also achieved an average accuracy of over 86% in arid sites. Conversely, MNDWI proved more effective in urban and humid/semi-humid settings, maintaining overall accuracy above 95% in both areas. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s11269-025-04212-8
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      – Code: eng
        Text: English
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        StartPage: 5461
    Subjects:
      – SubjectFull: Geomorphology
        Type: general
      – SubjectFull: Hydrography
        Type: general
      – SubjectFull: Water management
        Type: general
      – SubjectFull: Water supply
        Type: general
      – SubjectFull: Geographic information systems
        Type: general
      – SubjectFull: Remote-sensing images
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      – TitleFull: Effect of Hydro-geomorphological Environments on Surface Water Areas Extraction.
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            NameFull: Jia, Yuan-Yuan
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            NameFull: Duan, Huan-Feng
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            NameFull: Yan, Xu-Feng
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            – D: 01
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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              Value: 39
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            – TitleFull: Water Resources Management
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