Overcoming Data Scarcity in Earth Science

The Data Scarcity problem is repeatedly encountered in environmental research. This may induce an inadequate representation of the response’s complexity in any environmental system to any input/change (natural and human-induced). In such a case, before getting engaged with new expensive studies to g...

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Bibliographic Details
Published in:Data (Basel) 2020-03, Vol.5 (1), p.5
Main Authors: Gorgoglione, Angela, Castro, Alberto, Chreties, Christian, Etcheverry, Lorena
Format: Article
Language:English
Subjects:
data imputation
data quality
data scarcity
earth-science data
environmental modeling
environmental observations
machine learning
missing data
statistical methods
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Summary:The Data Scarcity problem is repeatedly encountered in environmental research. This may induce an inadequate representation of the response’s complexity in any environmental system to any input/change (natural and human-induced). In such a case, before getting engaged with new expensive studies to gather and analyze additional data, it is reasonable first to understand what enhancement in estimates of system performance would result if all the available data could be well exploited. The purpose of this Special Issue, “Overcoming Data Scarcity in Earth Science” in the Data journal, is to draw attention to the body of knowledge that leads at improving the capacity of exploiting the available data to better represent, understand, predict, and manage the behavior of environmental systems at meaningful space-time scales. This Special Issue contains six publications (three research articles, one review, and two data descriptors) covering a wide range of environmental fields: geophysics, meteorology/climatology, ecology, water quality, and hydrology.
ISSN:2306-5729
2306-5729
DOI:10.3390/data5010005