Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies-Reference-Cited by-同舟云学术

Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies

Published:2023-05-28 Issue:1 Volume:60 Page:
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Wang Yalan¹²^ORCID,Foody Giles³^ORCID,Li Xiaodong¹^ORCID,Zhang Yihang¹,Zhou Pu¹²,Du Yun¹

Affiliation:

1. Key Laboratory for Environment and Disaster Monitoring and Evaluation, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China

2. University of Chinese Academy of Sciences, Beijing, China

3. School of Geography, University of Nottingham, Nottingham, UK

Funder

the Natural Science Foundation of China

the International Science and Technology Cooperation

Science and Technology Partnership Program, Ministry of Science and Technology of China

Key Research Program of Frontier Sciences, Chinese Academy of Sciences

Young Top-notch Talent Cultivation Program

Application Foundation Frontier Project of Wuhan

the Hubei Provincial Natural Science Foundation of China for Distinguished Young Scholars

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2023.2217573

Reference80 articles.

1. Small water bodies mapped from Sentinel-2 MSI (MultiSpectral Imager) imagery with higher accuracy

2. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

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4. Automated Quantification of Surface Water Inundation in Wetlands Using Optical Satellite Imagery

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