Overcoming Data Scarcity in Earth Science

heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable...

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Detalles Bibliográficos
Otros Autores:	Etcheverry Venturini, Lorena (auth), Chreties Ceriani, Christian, Castro Casales, Alberto, Gorgoglione, Angela
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	MDPI - Multidisciplinary Digital Publishing Institute 2020
Materias:	geophysical monitoring data scarcity missing data climate extreme indices (CEIs) rule extraction Dataset Licensedatabase data assimilation data imputation support vector machines environmental observations multi-class classification earth-science data remote sensing magnetotelluric monitoring soil texture calculator machine learning ClimPACT invasive species species distribution modeling 3D-Var ensemble learning data quality water quality microhabitat k-Nearest Neighbors Expert Team on Climate Change Detection and Indices (ETCCDI) decision trees processing attribute reduction Expert Team on Sector-specific Climate Indices (ET-SCI) core attribute rough set theory GLDAS arthropod vector environmental modeling statistical methods
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009427455506719