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Zenghui Sun

Dados Biográficos

ID6274813
NOMEZenghui Sun
PRENOMESZenghui
SOBRENOMESun
ASSINATURASUN Z
AFILIAÇÕESMinistry of Natural Resources
ORCID0009-0005-6450-7905
VERIFICADOSim
TOTAL DE OBRAS3
TOTAL DE CITAÇÕES2
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2020
ANO MAIS RECENTE DE PUBLICAÇÃO2025
ÍNDICE H1
  • Lagged and cumulative effects of drought on global vegetation greenness, coverage, and productivity

    Open Access•Lei Zhang, Xia Jia et al.•ARTICLE•Environmental Impact Assessment…•2025•Citada por: 2•Referências: 67

  • Vegetation Coverage Prediction for the Qinling Mountains Using the CA–Markov Model

    Open Access•Lu Cui, Yonghua Zhao et al.•ARTICLE•ISPRS International Journal of…•2021

    The Qinling Mountains represent the dividing line of the natural landscape of north-south in China. The prediction on vegetation coverage is important for protecting the ecological environment of the Qinling Mountains. In this paper, the data accuracy and reliability of three vegetation index data (GIMMS NDVI, SPOT NDVI, and MODIS NDVI) were compared at first. SPOT, NDVI, and MODIS NDVI were used for calculating the vegetation coverage in the Qin…

  • Performance Evaluation and Comparison of Bivariate Statistical-Based Artificial Intelligence Algorithms for Spatial Prediction of Landslides

    Open Access•Wei Chen, Zenghui Sun et al.•ARTICLE•ISPRS International Journal of…•2020

    The purpose of this study is to compare nine models, composed of certainty factors (CFs), weights of evidence (WoE), evidential belief function (EBF) and two machine learning models, namely random forest (RF) and support vector machine (SVM). In the first step, fifteen landslide conditioning factors were selected to prepare thematic maps, including slope aspect, slope angle, elevation, stream power index (SPI), sediment transport index (STI), top…

  • Lagged and cumulative effects of drought on global vegetation greenness, coverage, and productivity

    Open Access•Lei Zhang, Xia Jia et al.•ARTICLE•Environmental Impact Assessment…•2025•Citada por: 2•Referências: 67

  • Performance Evaluation and Comparison of Bivariate Statistical-Based Artificial Intelligence Algorithms for Spatial Prediction of Landslides

    Open Access•Wei Chen, Zenghui Sun et al.•ARTICLE•ISPRS International Journal of…•2020

    The purpose of this study is to compare nine models, composed of certainty factors (CFs), weights of evidence (WoE), evidential belief function (EBF) and two machine learning models, namely random forest (RF) and support vector machine (SVM). In the first step, fifteen landslide conditioning factors were selected to prepare thematic maps, including slope aspect, slope angle, elevation, stream power index (SPI), sediment transport index (STI), top…

  • Vegetation Coverage Prediction for the Qinling Mountains Using the CA–Markov Model

    Open Access•Lu Cui, Yonghua Zhao et al.•ARTICLE•ISPRS International Journal of…•2021

    The Qinling Mountains represent the dividing line of the natural landscape of north-south in China. The prediction on vegetation coverage is important for protecting the ecological environment of the Qinling Mountains. In this paper, the data accuracy and reliability of three vegetation index data (GIMMS NDVI, SPOT NDVI, and MODIS NDVI) were compared at first. SPOT, NDVI, and MODIS NDVI were used for calculating the vegetation coverage in the Qin…

  • Lagged and cumulative effects of drought on global vegetation greenness, coverage, and productivity

    Open Access•Lei Zhang, Xia Jia et al.•ARTICLE•Environmental Impact Assessment…•2025•Citada por: 2•Referências: 67

Geography (3 obras) · Ecology (2 obras) · Environmental Science (2 obras) · Mathematics (2 obras) · Normalized Difference Vegetation Index (2 obras) · Statistics (2 obras) · Agroforestry (1 obras) · Algorithm (1 obras) · Artificial Intelligence (1 obras) · Biology (1 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae