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Processing of high-resolution temporal climate data for daily simulations of a complex agro-ecosystem

Bibliographic Data

ID21481025
AuthorsMaria Catarina Paz (0000-0001-8411-0896, Department of Medical Sciences), Sónia A P-Santos (0000-0003-1500-6360, Department of Medical Sciences), Raquel Barreira (0000-0002-8326-1593, Department of Medical Sciences)
Year2021
Issue42
Pages202-219
Publication date2021-01-01
Open AccessYes
TypeARTICLE
VenueRevista de Estudios Andaluces (JOURNAL)
Journal identifiersISSN: 0212-8594 • E-ISSN: 2340-2776
PublisherEditorial Universidad de Sevilla (PUBLISHER • ES)
DOI10.12795/rea.2021.i42.10
OpenAlexW3186471862
LanguageEN
Citations received1
References cited2

Ecosystem services, such as natural pest control, are essential tools to be incorporated in future agricultural methodologies. In this paper we focus on the processing of climate data series that feed to a system of computer models simulating daily interactions of a pest and its predator, in a dynamic landscape, the olive grove. We filled hourly climate data series and converted them to daily climate series using R language. The methodology used produces acceptable climate data series for the system to run and allows to segregate specific periods of the day while maintaining daily temporal resolution. We expect this paper can be helpful when dealing with similar data and purpose

Climate change · Ecosystem · Environmental resource management · Geography · Machine learning · Remote sensing · Temporal resolution · Time series · Climate change impacts on agriculture · Computer Science · Ecology and Vegetation Dynamics Studies · Environmental Science · Species Distribution and Climate Change · Ecology

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Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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