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Qunou Jiang

Biographic Data

ID9445744
NAMEQunou Jiang
GIVEN NAMESQunou
FAMILY NAMEJiang
SIGNATUREJIANG Q
AFFILIATIONSBeijing Forestry University
ORCID0000-0001-7177-9523
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2025
H-INDEX0
  • Application of Graph Convolutional Neural Networks and multi-sources data on urban functional zones identification, A case study of Changchun, China

    Open Access•Siyu Wang, Chunhong Zhao et al.•ARTICLE•Sustainable Cities and Society•2025

    Urban functional zones (UFZs) identification is integral to comprehensive city management. However, current methods often fail to effectively leverage multiple data sources to enhance identification accuracy and overlook the spatial interconnections between neighboring units. In this study, we employed a Graph Convolutional Neural Networks (GCNNs) model to consolidate information from adjacent units and enhance the accuracy of UFZs identification…

  • Payments for ecosystem services as an essential approach to improving ecosystem services

    Open Access•Haiming Yan, Huicai Yang et al.•ARTICLE•Ecological Economics•2022

  • Analysis on net primary productivity change of forests and its multi–level driving mechanism – A case study in Changbai Mountains in Northeast China

    Open Access•Chunli Wang, Qunou Jiang et al.•ARTICLE•Technological Forecasting and…•2020

No prominent works on this page.

  • Analysis on net primary productivity change of forests and its multi–level driving mechanism – A case study in Changbai Mountains in Northeast China

    Open Access•Chunli Wang, Qunou Jiang et al.•ARTICLE•Technological Forecasting and…•2020

  • Payments for ecosystem services as an essential approach to improving ecosystem services

    Open Access•Haiming Yan, Huicai Yang et al.•ARTICLE•Ecological Economics•2022

  • Application of Graph Convolutional Neural Networks and multi-sources data on urban functional zones identification, A case study of Changchun, China

    Open Access•Siyu Wang, Chunhong Zhao et al.•ARTICLE•Sustainable Cities and Society•2025

    Urban functional zones (UFZs) identification is integral to comprehensive city management. However, current methods often fail to effectively leverage multiple data sources to enhance identification accuracy and overlook the spatial interconnections between neighboring units. In this study, we employed a Graph Convolutional Neural Networks (GCNNs) model to consolidate information from adjacent units and enhance the accuracy of UFZs identification…

China (2 works) · Conservation, Biodiversity, and Resource Management (2 works) · Ecology (2 works) · Ecosystem (2 works) · Environmental resource management (2 works) · Geography (2 works) · Land Use and Ecosystem Services (2 works) · Artificial Intelligence (1 works) · Biology (1 works) · Business (1 works)

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