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UID:pretalx-global-workshop-2026-X97YJS@pretalx.earthmonitor.org
DTSTART;TZID=Europe/Amsterdam:20261008T163000
DTEND;TZID=Europe/Amsterdam:20261008T164500
DESCRIPTION:As FAIR principles become increasingly central to open science 
 and research data stewardship\, a persistent gap remains between their bro
 ad endorsement and their consistent practical validation in real-world rep
 ositories. This challenge is particularly visible for geospatial datasets\
 , where domain-specific requirements such as spatial formats\, metadata ri
 chness\, and interoperability standards are not always captured by general
  FAIR assessment approaches. In this work\, a structured FAIR assessment w
 as applied to datasets produced within the Open-Earth-Monitor Cyberinfrast
 ructure (OEMC) project. To support the evaluation\, we developed a FAIR as
 sessment tool tailored to geospatial data entries published on Zenodo\, wh
 ile designing the underlying framework to remain flexible and transferable
  to other repository environments. The assessment identifies both strength
 s and recurring gaps in current data publication practices and provides ac
 tionable recommendations for improving the long-term usability\, transpare
 ncy\, and scientific value of geospatial datasets.
DTSTAMP:20260624T070205Z
LOCATION:Aula Magna
SUMMARY:How FAIR Is Geospatial Data? An Assessment of OEMC Datasets - Imma 
 Serra\, Mustafa Serkan Isik
URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/X97YJS/
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UID:pretalx-global-workshop-2026-E3KZMH@pretalx.earthmonitor.org
DTSTART;TZID=Europe/Amsterdam:20261007T171500
DTEND;TZID=Europe/Amsterdam:20261007T173000
DESCRIPTION:We present an updated generation of the Global Pasture Watch (G
 PW) gross primary productivity (GPP) products for grassland ecosystems at 
 30 m spatial resolution. This new release builds on the original Landsat-b
 ased light use efficiency framework by integrating improved MODIS land sur
 face temperature (MOD21) and updated photosynthetically active radiation i
 nputs\, while also introducing an experimental Sentinel-2-based GPP produc
 t. The combined use of Landsat and Sentinel-2 observations strengthens the
  capacity to monitor grassland productivity dynamics with improved spatial
  detail and temporal consistency across local to global scales. Beyond lon
 g-term ecosystem assessment and grassland monitoring\, the updated GPW GPP
  products are also intended to support near-real-time (NRT) grassland biom
 ass estimation within the Time2Graze project.
DTSTAMP:20260624T070205Z
LOCATION:Room 18
SUMMARY:High-Resolution Grassland GPP Estimation with Landsat and Sentinel-
 2 - Mustafa Serkan Isik
URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/E3KZMH/
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