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2020 | OriginalPaper | Buchkapitel

Historical Weather Data Recovery and Estimation

verfasst von : Fadoua Rafii, Tahar Kechadi

Erschienen in: Innovations in Smart Cities Applications Edition 3

Verlag: Springer International Publishing

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Abstract

In order to make efficient decisions in agriculture, it is imperative to analyse the weather data collected from various sources. These data are generated by automated weather stations. Unfortunately, weather observations may be missing or altered since weather stations may be stopped for maintenance or became out of order. Thus, it would affect significantly the process of data analysis. The purpose of this study is to estimate those missing values by using interpolation methods and others. We study the effectiveness of each method and compare them on different weather attributes. The methods were applied on different patterns of missing values and outliers. The experimental results prove that the two methods based on geographical proximity are performing better.

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Titel: Historical Weather Data Recovery and Estimation
verfasst von: Fadoua Rafii
Tahar Kechadi
Verlag: Springer International Publishing
Buch: Innovations in Smart Cities Applications Edition 3
Print ISBN: 978-3-030-37628-4

Electronic ISBN: 978-3-030-37629-1

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-37629-1_85

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