BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//pretalx.earthmonitor.org//global-workshop-2026//VLMNWP BEGIN:VTIMEZONE TZID:Europe/Madrid BEGIN:STANDARD DTSTART:20001029T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-global-workshop-2026-EN3X39@pretalx.earthmonitor.org DTSTART;TZID=Europe/Madrid:20261008T144500 DTEND;TZID=Europe/Madrid:20261008T150000 DESCRIPTION:Increasing forest cover is generally perceived positively. Pote ntially\, more trees can capture more carbon\, along with bringing other b eneficial ecosystem services if they become sustainable ecosystems. Howeve r\, this also changes some key properties of the surface of the Earth (e.g . albedo\, latent heat flux\, etc) that can affect the local climate throu gh biophysical mechanisms\, notably by changing the local land surface tem perature (LST). This aspect is still largely ignored by policy-makers\, in part because they are difficult to model given they depend much on local context which is spatio-temporally variable. As demonstrated by several st udies\, satellite remote sensing has a role to play here. In this presenta tion we will illustrate how\, within a dedicated OEMC use case\, we adapte d an established methodology to retrieve the local effect of forest cover change on LST and made the processing pipeline openly available and reprod ucible. We applied it for the first time on geostationary satellite data w ith a 15 minute revisit frequency over Europe and Africa to generate estim ations of the change of LST along the entire daily cycle. This was done in collaboration with the European Commission Joint Research Centre on their BDAP platform opening the possibility to expand results within their EU F orest Observatory. In parallel work we also explored how the spatial heter ogeneity of tree cover could also have an effect on LST and further into c loud formation across Africa. DTSTAMP:20261023T012318Z LOCATION:Rooms 12+14 SUMMARY:Assessing how changing local forest cover affects diurnal surface t emperature across Europe and Africa - Gregory Duveiller URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/EN3X39/ END:VEVENT BEGIN:VEVENT UID:pretalx-global-workshop-2026-MFS9JK@pretalx.earthmonitor.org DTSTART;TZID=Europe/Madrid:20261007T154500 DTEND;TZID=Europe/Madrid:20261007T160000 DESCRIPTION:There is a growing need to understand the inter-relationships b etween our atmosphere\, the biosphere\, and what we could call the anthrop osphere. These interactions are complex and not always evident\, complicat ing their analysis through a traditional modelling framework. On the other hand\, we do have large amounts of climatic and environmental data in the form of spatio-temporal layers\, along with socio-economic data expressin g human behaviour\, which could be combined in a data-driven perspective. Past work has shown that it is possible to summarize the state of the terr estrial biosphere in a few dimensions by applying statistical techniques t o Earth system data cubes. Similarly\, socio-economic development data can be statistically reduced to some key dimensions.\nTo investigate correlat ions between the biosphere\, atmosphere and the sociosphere\, we developed the initial concept of the planetary health index (PHI). Towards this goa l\, data from FLUXCOM-X and Eurostat was collected and resampled at quarte rly temporal frequency and NUTS3 spatial level. We then developed an inter active dashboard in R Shiny based on interpretable and holistic Canonical Correlation Analysis to visualize spatio-temporal patterns of features and relationships between the 3 spheres. Additional data can be added later o n for customisation. This tool was designed and developed for a particular stakeholder\, the European Central Bank\, who is interested in the physic al risk and the impacts that financial institutions have on climate change \, biodiversity loss\, ecosystem services and their degradation\, but also on how these processes also have impacts on financial institutions. DTSTAMP:20261023T012318Z LOCATION:Aula Magna SUMMARY:Planet health index: A framework to investigate relationships betwe en the atmosphere\, biosphere and sociosphere - Gregory Duveiller URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/MFS9JK/ END:VEVENT BEGIN:VEVENT UID:pretalx-global-workshop-2026-LD9XBP@pretalx.earthmonitor.org DTSTART;TZID=Europe/Madrid:20261007T144500 DTEND;TZID=Europe/Madrid:20261007T150000 DESCRIPTION:Gross Primary Productivity (GPP) is an essential variable to mo nitor carbon uptake by terrestrial ecosystems. Mapping GPP is thus of grea t interest to establish estimates of the global carbon budget\, especially when this needs to be done at regional scale such as with the 'REgional C arbon Cycle Assessment and Processes' (RECCAP) initiative coordinated by t he Global Carbon Project. While GPP is not directly measurable from space by remote sensing\, sun-induced chlorophyll fluorescence (SIF) can\, and i t has been shown to correlate well with GPP. SIF is a weak signal that can be retrieved from hyperspectral remote sensing and which is emitted by th e photosynthetic machinery itself. The downside is that current and past s atellite instruments from which SIF can be derived have a very coarse spat ial resolution (5 km at best) and are usually very noisy due to the subtle nature of the signal. In this use case\, we have thus developed some tool s to improve the situation. First\, we collaborated to derive a new retrie val method leveraging on machine learning to reduce the noise. Second\, we adapted a spatial enhancement methodology enabling users to increase the spatial resolution by combining other remote sensing variables with a simp le modelling framework of their choice. This was done on the Copernicus Da ta Space Ecosystem (CDSE) using the OpenEO framework\, allowing users to d esign their own downscaling approach and applying it lazily to their zones of interest. To compare with in-site GPP estimations from eddy covariance flux towers\, we further designed a methodology to characterize the heter ogeneity around these towers based on data cubes of Sentinel-2 data. DTSTAMP:20261023T012318Z LOCATION:Rooms 12+14 SUMMARY:Getting SIF closer to GPP: developing tools towards reaching such g oal - Gregory Duveiller URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/LD9XBP/ END:VEVENT END:VCALENDAR