Improving the estimation of alpine grassland fractional vegetation cover using optimized algorithms and multi-dimensional features.

Lin, Xingchen; Chen, Jianjun; Lou, Peiqing; Yi, Shuhua; Qin, Yu; You, Haotian; Han, Xiaowen

Lin, Xingchen; Chen, Jianjun; Lou, Peiqing; Yi, Shuhua; Qin, Yu; You, Haotian; Han, Xiaowen.

Afiliação

Lin X; College of Geomatics and Geoinformation, Guilin University of Technology, No.12 Jiangan Street, Guilin, 541006, China.
Chen J; College of Geomatics and Geoinformation, Guilin University of Technology, No.12 Jiangan Street, Guilin, 541006, China. chenjj@lzb.ac.cn.
Lou P; Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, 12 Jiangan Road, Guilin, 541004, China. chenjj@lzb.ac.cn.
Yi S; State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou, 730000, China.
Qin Y; Institute of Fragile Ecosystem and Environment, Nantong University, 999 Tongjing Road, Nantong, 226007, China.
You H; State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou, 730000, China.
Han X; College of Geomatics and Geoinformation, Guilin University of Technology, No.12 Jiangan Street, Guilin, 541006, China.

Plant Methods ; 17(1): 96, 2021 Sep 17.

Article em En | MEDLINE | ID: mdl-34535179

Palavras-chave

Accuracy evaluation; Alpine grassland; Feature selection; Fractional vegetation cover (FVC); Machine learning algorithms; Parameter tuning; Unmanned aerial vehicle (UAV) aerial imagery

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Plant Methods Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

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