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Preliminary risk assessment of regional industrial enterprise sites based on big data.
Jiang, Yefeng; You, Qihao; Chen, Xueyao; Jia, Xiaolin; Xu, Kang; Chen, Qianqian; Chen, Songchao; Hu, Bifeng; Shi, Zhou.
Afiliação
  • Jiang Y; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
  • You Q; Eco-Environmental Science & Research Institute of Zhejiang Province, Hangzhou 310012, China.
  • Chen X; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
  • Jia X; College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou 450000, China.
  • Xu K; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
  • Chen Q; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
  • Chen S; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China.
  • Hu B; Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China.
  • Shi Z; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: shizhou@zju.edu.cn.
Sci Total Environ ; 838(Pt 4): 156609, 2022 Sep 10.
Article em En | MEDLINE | ID: mdl-35690217
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Rios / Big Data Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Sci Total Environ Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Rios / Big Data Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Sci Total Environ Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China