Adaptiveness of RGB-image derived algorithms in the measurement of fractional vegetation coverage.

Song, Chuangye; Sang, Jiawen; Zhang, Lin; Liu, Huiming; Wu, Dongxiu; Yuan, Weiying; Huang, Chong

Song, Chuangye; Sang, Jiawen; Zhang, Lin; Liu, Huiming; Wu, Dongxiu; Yuan, Weiying; Huang, Chong.

Afiliação

Song C; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
Sang J; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
Zhang L; University of Chinese Academy of Sciences, Beijing, 100049, China.
Liu H; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
Wu D; Satellite Application Centre for Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100094, China.
Yuan W; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
Huang C; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.

BMC Bioinformatics ; 23(1): 358, 2022 Aug 30.

Article em En | MEDLINE | ID: mdl-36042415

Assuntos

Algoritmos; Ecologia; Plantas

Palavras-chave

Canopy density; Digital image; Field survey; Grassland; Mobile smart phone

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Ecologia Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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