The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/aca56a60-8fcc-45b5-b817-50b68d4b5c63

Zurita-Milla, Raúl; Izquierdo-Verdiguier, Emma (2024): A high spatial resolution Extended Spring Indices database over American and European regions. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/aca56a60-8fcc-45b5-b817-50b68d4b5c63.v1

Software

• Artificial Intelligence and Image Processing
• Ecological Applications
• Plant Biology
• Environmental Science and Management
• Ecosystem Assessment and Management
• Physical Geography and Environmental Geoscience
• Climate and Climate Change
• Earth Sciences
• Information and Computing Sciences
• Biological Sciences
• Environmental Sciences
• Environment

Citizen Science, Climate change, Cloud computing, Ground phenological observations, Honeysuckle, Lilac, Phenology

1950-2022

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Raúl Zurita-Milla , Emma Izquierdo-Verdiguier

This repository contains a high spatial resolution database of spring onset indicators derived from the Extended Spring Indices (SI-x) phenological models as well as the code used to generate these phenological products. The SI-x models transform daily minimum and maximum temperatures into a set of consistent indices that track the timing of first leaf and first bloom for key indicator species, and that also allow the calculation of the so-called damage index by subtracting the date of first leaf from the date of the last freeze.

This dataset is available at 1 km spatial resolution and covers American (1980 to 2022) and European regions (1950 to 2020).

The first leaf and first bloom indices are validated with ground phenological observations collected over both regions.

The American product is based on DAYMET version 4 (https://daymet.ornl.gov/) and the European region on a downscaled E-Obs database version 3 (ftp://palantir.boku.ac.at/Public/ClimateData).

This product can support both scientists and decision makers in their quest to hind- and forecast climate change impacts in these areas

In the USA this product is recognized as an official climate change indicator (https://www.globalchange.gov/indicators/start-of-spring)

An interactive visualization of this database is available here: https://emma.users.earthengine.app/view/spring-onset

For more information see our publications:

• A Matlab© toolbox for calculating spring indices from daily meteorological data (https://doi.org/10.1016/j.cageo.2015.06.015 )
• Development and analysis of spring plant phenology products: 36 years of 1-km grids over the conterminous US (https://doi.org/10.1016/j.agrformet.2018.06.028)
• A long-term 1 km gridded database of continental-scale spring onset products (under review)

• 2024-03-19 first online, published, posted

4TU.ResearchData

Cloud optimized geotiff

• A Matlab© toolbox for calculating spring indices from daily meteorological data (https://doi.org/10.1016/j.cageo.2015.06.015 )
• Development and analysis of spring plant phenology products: 36 years of 1-km grids over the conterminous US (https://doi.org/10.1016/j.agrformet.2018.06.028)

• 4TU.ResearchData FAIR Data Fund

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente (UT);
Institute of Geomatics, University of Natural Resources and Life Sciences (BOKU)