A New Extraction Method of Surface Water Based on Dense Time-Sequence Images-Reference-Cited by-同舟云学术

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A New Extraction Method of Surface Water Based on Dense Time-Sequence Images

Published:2024 Issue: Volume:17 Page:3151-3166
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Liu Hanyuan¹^ORCID,Shi Yue²,Chang Qinnan³,Guluzade Rufat¹^ORCID,Pan Xin⁴^ORCID,Xu Nan⁴^ORCID,Hu Penghua¹^ORCID,Kong Xuechun¹^ORCID,Yang Yingbao⁴^ORCID

Affiliation:

1. School of Earth Sciences and Engineering, Hohai University, Nanjing, China

2. College of Defense Engineering, The Army Engineering University of PLA, Nanjing, China

3. Jincheng Urban District Housing and Urban-Rural Development Bureau, Shanxi, China

4. College of Geography and Remote Sensing, Hohai University, Nanjing, China

Funder

General Programs of the National Natural Science Foundation of China

Jiangsu Marine Science and Technology Innovation Project

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10378698.pdf?arnumber=10378698

Reference47 articles.

1. High-resolution mapping of global surface water and its long-term changes

2. Landsat 8 OLI image based terrestrial water extraction from heterogeneous backgrounds using a reflectance homogenization approach

3. Automated Surface Water Extraction Combining Sentinel-2 Imagery and OpenStreetMap Using Presence and Background Learning (PBL) Algorithm

4. Detecting Coastline Change with All Available Landsat Data over 1986–2015: A Case Study for the State of Texas, USA

5. Extraction of Urban Water Bodies from High-Resolution Remote-Sensing Imagery Using Deep Learning

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1. A New Classification Rule-Set for Mapping Surface Water in Complex Topographical Regions Using Sentinel-2 Imagery;Water;2024-03-25

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