Dust detection and susceptibility mapping by aiding satellite imagery time series and integration of ensemble machine learning with evolutionary algorithms.

Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Naqvi, Rizwan Ali; Choi, Soo-Mi

Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Naqvi, Rizwan Ali; Choi, Soo-Mi.

Afiliación

Razavi-Termeh SV; Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone, XR Research Center, Sejong University, Seoul, Republic of Korea. Electronic address: razavi@sejong.ac.kr.
Sadeghi-Niaraki A; Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone, XR Research Center, Sejong University, Seoul, Republic of Korea. Electronic address: a.sadeghi@sejong.ac.kr.
Naqvi RA; Department of Intelligent Mechatronics Engineering, Sejong University, Seoul, Republic of Korea. Electronic address: rizwanali@sejong.ac.kr.
Choi SM; Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone, XR Research Center, Sejong University, Seoul, Republic of Korea. Electronic address: smchoi@sejong.ac.kr.

Environ Pollut ; 335: 122241, 2023 Oct 15.

Article en En | MEDLINE | ID: mdl-37482338

Asunto(s)

Polvo; Imágenes Satelitales; Humanos; Factores de Tiempo; Algoritmos; Aprendizaje Automático

Palabras clave

Dust source; Ensemble machine learning; Evolutionary algorithms; Satellite imagery; Spatial modeling

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Polvo / Imágenes Satelitales Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

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