Copernicus High Resolution Vegetation Phenology and Productivity for Doñana LTSER Platform

Только метаданные
Последняя версия опубликовано 18 сентября 2023 г.
Домой:
https://zenodo.org/record/7958093
Дата публикации:
18 сентября 2023 г.
Опубликовано:
No organization
Лицензия:
CC-BY-NC 4.0

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Описание

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.

Версии

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Как оформить ссылку

Исследователи должны дать ссылку на эту работу следующим образом:

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

Права

Исследователи должны соблюдать следующие права:

Эта работа находится под лицензией Creative Commons Attribution Non Commercial (CC-BY-NC 4.0).

Регистрация в GBIF

Этот ресурс не был зарегистрирован в GBIF

Ключевые слова

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

Контакты

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

Географический охват

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

Ограничивающие координаты Юг Запад [36,686, -6,943], Север Восток [37,788, -5,823]

Временной охват

Дата начала / Дата окончания 2017-01-01 / 2022-12-31

Данные проекта

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.

Название SUMHAL: Sustainability for Mediterranean Hotspots in Andalusia integrating LifeWatch ERIC (SUMHAL)
Идентификатор LWE2103022
Финансирование MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020]
Описание района исследования Doñana Long-Term Socio-ecological Research Platform (https://deims.org/bcbc866c-3f4f-47a8-bbbc-0a93df6de7b2)
Описание плана выполнения исследований 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.

Методы сбора

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.

Охват исследования 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.
Контроль качества 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

Описание этапа методики:

  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.

Библиографические ссылки

  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

Дополнительные метаданные

Цель

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.
Описание частоты обновления ресурса This product will be updated every year when the new phenometrics were available.
Альтернативные идентификаторы https://ipt-demo.gbif.es/resource?r=phenometrics_end