Copernicus High Resolution Vegetation Phenology and Productivity for Doñana LTSER Platform

Dernière version publié le 18 septembre 2023
Date de publication:
18 septembre 2023
Publié par:
No organization
Licence:
CC-BY-NC 4.0

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Description

GeoTIFF rasters with the following phenometrics obtained from Sentinel 2 Data:. * Start of the season Day of the Year (SOSD) * Maximun of the Season Day of the Year (MAXD) * End of the Season Day of the Year (EOSD) * Start of the season Value (SOSV) * Maximun of the Season Value (MAXV) * End of the Season Value (EOSV) These rasters have been downloaded, mosaicked and croped with Doñana Natural Space DEIMS.ID through Pyvpp python package.

Versions

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Comment citer

Les chercheurs doivent citer cette ressource comme suit:

García Díaz D., Díaz-Delgado R. (2023). Copernicus High Resolution Vegetation Phenology and Productivity for Doñana Natural Space. Version 1.0. No organization. Metadata dataset. https://ipt-demo.gbif.es/resource?r=phenometrics_end&v=1.0

Droits

Les chercheurs doivent respecter la déclaration de droits suivante:

Ce travail est sous licence Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0.

Enregistrement GBIF

Cette ressource n'a pas été enregistrée sur le portail GBIF

Mots-clé

Metadata; Phenology; Phenometrics; Sentinel 2; SUMHAL; eLTER

Contacts

Diego García Díaz
  • Personne De Contact
  • GIS & Remote Sensing Technician
Estacion Biologica de Doñana
  • Avenida Amercio Vespucio 26
41092 Sevilla
SEVILLA
ES
  • 954466700
Diego García Díaz
  • Personne De Contact
  • GIS & Remote Sensing Technician
Estacion Biologica de Doñana
  • Avenida Amercio Vespucio 26
41092 Sevilla
SEVILLA
ES
  • 954466700
Ricardo Díaz-Delgado
  • Personne De Contact
  • Tenured scientist
Estacion Biologica de Doñana
  • Avenida Amercio Vespucio 26
41092 Sevilla
SEVILLA
ES
  • 954466700
Ricardo Díaz-Delgado Hernández
  • Utilisateur

Couverture géographique

Donana Natural Space, Gulf of Cádiz (Southwest Spain). Also see: https://deims.org/bcbc866c-3f4f-47a8-bbbc-0a93df6de7b2

Enveloppe géographique Sud Ouest [36,686, -6,943], Nord Est [37,788, -5,823]

Couverture temporelle

Date de début / Date de fin 2017-01-01 / 2022-12-31

Données sur le projet

The SUMHAL project, Sustainability for Mediterraean Hotspots in Andalusia integrating LifeWatch ERIC, is a European project within the ERDF programme of actions related to the pan-European distributed e-Science infrastructure LifeWatch ERIC, with headquarters in Andalusia-Spain. It is funded by the Spanish Ministry of Science and Innovation, through the European Regional Development Funds (ERDF) [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020]. The key purpose of the project is to contribute to the conservation of biodiversity in natural or semi-natural systems in the Western Mediterranean, making use of high-tech infrastructures, fieldwork, data integration and the development of virtual research environments (VREs), as well as the combination of highly specialised research staff and citizens through citizen science actions.

Titre SUMHAL: Sustainability for Mediterranean Hotspots in Andalusia integrating LifeWatch ERIC (SUMHAL)
Identifiant LWE2103022
Financement MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020]
Description du domaine d'étude / de recherche Doñana Long-Term Socio-ecological Research Platform (https://deims.org/bcbc866c-3f4f-47a8-bbbc-0a93df6de7b2)
Description du design Remote sensing is an essential tool to carry out all these long-term ecological monitoring tasks, thanks to the collection of data through satellite, aircraft, drone and in-situ images. In this sense, in work package 6 of the SUMHAL, PhenoApp (which is the app who integrate the current and some other datastes) application has been developed, enabling the integration of phenology remote sensing data into Virtual Research Environments (VRE). This application aims to integrate data obtained in situ by eight phenocameras installed in the Doñana Natural Area by the Doñana Singular Scientific-Technical Infrastructure (ICTS-RBD) together with images from ESA's Sentinel-2 satellites (Copernicus Programme) and MODIS.

Méthodes d'échantillonnage

These phenometric rasters have been created from the Seasonal Trajectories PPI Index gapfilled data. A product with out NoData created from and smoith curve of the real data obtained from the satellite. This gapfilled product allows the use of a mathematical approach to the phenological curve of every pixel from which phenometrics could be estimated.

Etendue de l'étude Year composites at 10 meters of spatial resolution with phenometrics for Doñana Long-Term Socio-ecological Research Platform derived from Sentinel 2 Satellite Imagery Data.
Contrôle qualité Quality control for product generation is made by Copernicus (European Spatial Agency). Besides, we apply cross validation with other satellite phenometrics derived data and with some Ground Control Data. Plus, we have 8 Phenocams distributed in Doñana National Park that are also used as ground truth data in the validation process. More info about the Copernicus product and its quality control can be retrieved here: https://doi.org/10.1016/j.rse.2021.112456

Description des étapes de la méthode:

  1. We have developed our own tool to download Wekeo data, a python package called "Pyvpp" that get profite of Deims python package to just type the eLTER site ID and the tool will do the search for the intersecting Sentinel 2 Tiles, perform the download, make a mosaic and crop it with the eLTER site boundaries. After that, the phenomterics mosaics are upload to Google Earth Engine, so that they can be accessed from our application.

Citations bibliographiques

  1. Tian, F., Cai, Z., Jin, H., Hufkens, K., Scheifinger, H., Tagesson, T., Smets, B., Van Hoolst, R., Bonte, K., Ivits, E., Tong, X., Ardö, J., Eklundh, L. 2021. Calibrating vegetation phenology from Sentinel-2 using eddy covariance, PhenoCam, and PEP725 networks across Europe. Remote Sensing of Environment, 260, https://doi.org/10.1016/j. rse.2021.112456
  2. Richardson, A., Hufkens, K., Milliman, T. et al., 2018. Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery. Scientific Data 5, 180028. https://doi.org/10.1038/s41597-019-0229-9
  3. Wu, Q. 2020. Geemap: A Python package for interactive mapping with Google Earth Engine. The Journal of Open Source Software, 5(51), 2305. https://doi. org/10.21105/joss.02305
  4. Wohner, C., Peterseil, J., Klug, H. 2022. Designing and implementing a data model for describing environmental monitoring and research sites. In Ecological Informatics, 70, p. 101708). Elsevier BV. https://doi.org/10.1016/j.ecoinf.2022.101708
  5. García-Díaz, D., Díaz-Delgado, R. 2023. PhenoApp. A Google Earth Engine based tool for monitoring phenology. Revista de Teledetección,61, 73-81. https://doi.org/10.4995/raet.2023.18767

Métadonnées additionnelles

Objet

This dataset have been created has part of the PhenoApp application and processing framework developed for SUMHAL and eLTER projcts. The goal of this work is the cross validation and downscaling of satellite and ground collected data.

Description de la fréquence de mise à jour This product will be updated every year when the new phenometrics were available.
Identifiants alternatifs https://ipt-demo.gbif.es/resource?r=phenometrics_end