BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//pretalx.earthmonitor.org// BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-GE9KCU@pretalx.earthmon itor.org DTSTART:20250917T090000Z DTEND:20250917T093000Z DESCRIPTION:The OEMC project in a nutshell by the project coordinator\, Tom Hengl\, Director of Opengeohub Foundation DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Introduction to the OEMC Project by Tomislav Hengl - Tom Hengl (Ope nGeoHub) URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/GE9KCU/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-SKHBW7@pretalx.earthmon itor.org DTSTART:20250917T092500Z DTEND:20250917T102500Z DESCRIPTION:Drought–flood abrupt alternation poses a growing threat to wa ter security and climate resilience in the Northwestern Mediterranean regi on. Despite the increasing availability of Earth Observation (EO) data\, t here is a lack of operational\, scalable tools to detect early signals of these sudden hydrological transitions. This study presents an open EO-base d framework to monitor such events by fusing anomalies in soil moisture (S M)\, evapotranspiration (ET)\, and precipitation (P).\n\nStandardized mont hly deviations are computed over the last 10 years using high-resolution d atasets from the Digital Twin Earth (DTE) platform and Copernicus services . These anomaly patterns are processed through a cloud-based geospatial en vironment to capture spatiotemporal divergence across key Mediterranean ba sins\, reflecting the complex interactions of SM\, ET\, and P under climat e stress.\n\nThe resulting study identifies zones exhibiting frequent and intense transitions\, which are prioritized for detailed monitoring and ea rly warning. The proposed approach is reproducible and scalable\, offering valuable support for open monitoring systems and anticipatory water risk management in vulnerable regions. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Open EO-Based Monitoring of Drought–Flood Abrupt Alternation in N orthwestern Mediterranean Basins - imane serbouti URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/SKHBW7/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-WDHNZE@pretalx.earthmon itor.org DTSTART:20250917T093000Z DTEND:20250917T100000Z DESCRIPTION:The presentation will study some recent EO implications of EU G reen Deal policies and the discussion around their evolution\, also in lig ht of the Copernicus expansion missions and “new space” developments. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Evolving FAIR and Open Earth Observations in the Technology-Science -Policy Nexus - Martin Herold URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/WDHNZE/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-98CNWA@pretalx.earthmon itor.org DTSTART:20250917T102500Z DTEND:20250917T112500Z DESCRIPTION:The open source software for geospatial is today a mature\, rel iable and ever-expanding ecosystem. Paramount FOSS4G projects\, such as GR ASS\, GDAL\, QGIS\, Geoserver\, PostGIS and many others\, have been develo ping for decades\, ever improving and adding to their functionalities\, as well as a community of developers and users alike. Furthermore\, given th e fundamental principles of the open source paradigm\, the plethora of FOS S4G is constantly increasing\, following the technology trends and ever re newing requirements of users. Even so\, given the economics of open source \, the viability question still remains. What makes an open source for geo spatial project successful\, viable over time? \nBased on the more extensi ve initiative - the FOSS4G Observatory - the authors will present an in-d epth analysis on the potential connections between the heart of a “healt h open source project” and “software metrics” in regards to the proj ect viability over the long term. Expanding on sustainability matters in t he open source\, efforts have been invested in deciphering what are the el ements that support the uptake of FOSS4G within operational activity\, be it scientific-\, policy- or commercially related activities\, irrespectiv e of its language. All of the three sectors are governed by different driv ing principles and best practices when it comes to addressing the develop ment\, management and use of the open source environment. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Bridging communities: How open source geospatial software stays rel evant in science\, policy\, and industry - Codrina Maria Ilie URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/98CNWA/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-BMLFHF@pretalx.earthmon itor.org DTSTART:20250917T110000Z DTEND:20250917T112000Z DESCRIPTION:The Planetary Health Index (PHI) framework has been proposed as an innovative tool to summarize and analyze complex data about the state of the planet. The idea is to create an index composed of three separate i nterpretable axes\, each representing one of the domain "spheres" of inter est (atmosphere\, biosphere and socio-economy). The resulting framework al lows one to identify how one sphere affects another for a given region dur ing a given time frame. The statistical method behind is a 3-way canonical correlation analysis (CCA). A first global prototype was demonstrated at global level combining yearly world bank data and the Earth System Data Cu be (ESDL) gridded at quarter degree spatial resolution. However\, this spa tio-temporal configuration may be too coarse to properly characterize the complexity of global interlinkages between atmosphere\, biosphere and soci o-economy. We have thus ported the PHI framework to a finer spatio-tempora l resolution by testing it at European level\, leveraging on the daily 5km data cube of input and outputs of FLUXCOM-X-BASE along with EUROSTAT soci o-economic data. We will present first results exploring whether we can us e this framework to answer questions pertaining to implications of nature degradation on price inflation. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Adapting the Planetary Health Index framework to sub-national scale for Europe - Gregory Duveiller URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/BMLFHF/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-H9SJ8C@pretalx.earthmon itor.org DTSTART:20250917T112000Z DTEND:20250917T114000Z DESCRIPTION:The Horizon Europe EvoLand - Evolution of the Copernicus Land S ervice Portfolio - project aims to enhance the Copernicus Land Monitoring Service (CLMS) by advancing innovative methods\, algorithms\, and prototyp es for monitoring land use/land cover dynamics and land surface characteri stics at high spatial and temporal resolutions. EvoLand targets the develo pment of eleven next-generation CLMS product candidates across Forest\, Ag riculture\, Water\, Urban and General land cover domains\, leveraging cutt ing-edge methods such as data fusion\, machine learning and continuous mon itoring alongside novel Earth Observation (EO) and in-situ data sources. \ n\nThe project emphasizes aligning its prototype services with policy\, da ta\, and infrastructure requirements by engaging closely with Entrusted En tities and key Copernicus Land stakeholders and users. These requirements guide all methodological developments\, ensuring relevance and impact. The methods include i) the integration of relevant novel EO datasets\; ii) th e acquisition of fit-for-purpose in-situ and training data\; as well as th e development of algorithms for iii) Weakly Supervised Learning\; iv) impr oved spatial\, temporal and thematic resolution\; v) continuous monitoring \n\n(i.e. change detection and continuous land cover mapping) and vi) bio mass mapping. EvoLand designs\, tests\, and implements algorithms on open- source\, modular\, and scalable platforms\, using representative test site s both within Europe and globally. In the demonstration phase\, these cand idate services were deployed over larger regions\, addressing critical the matic areas. \n\nTo ensure continuous improvement\, the candidate services are systematically assessed for their innovation potential\, policy relev ance\, technical excellence\, and operational readiness. EvoLand also prop oses a strategy for transitioning these services to operational use. The p roject’s ultimate goal is to support Entrusted Entities by delivering re search-driven\, tangible advancements to the CLMS. This includes enhancing the information content\, quality\, and timeliness of services\, thereby enabling evidence-based decision-making and demonstrating the potential fo r the ongoing evolution of the CLMS. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Evolution of the Copernicus Land Monitoring Service (EvoLand) – project\, results and public dissemination - Daniel Thiex URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/H9SJ8C/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-DGXU8Y@pretalx.earthmon itor.org DTSTART:20250917T112500Z DTEND:20250917T122500Z DESCRIPTION:The frequency of flash droughts\, characterized by their sudden and intense onset\, is rising globally\, posing significant challenges in drought monitoring. However\, consensus on whether flash droughts are bec oming the new norm remains unclear\, as slow-developing droughts may also be increasing. Flash droughts have transient but severe consequences on ag riculture productivity\, water resources\, and ecosystems. Despite the urg ency\, researchers have not thoroughly investigated the key features of fl ash droughts in India\, and they have not adequately addressed the mechani sms behind rapid soil moisture depletion during these events. This study p roposes a framework for detecting flash droughts\, which defines them base d on the rapidity of soil drying at the onset of the drought and extends t o its duration. The analysis further focused on flash drought characteriza tion\, i.e.\, frequency\, mean duration\, mean severity\, and mean onset s peed under observed climate continuous from 1981 to 2022 over India. Atmos pheric aridity likely creates flash drought-prone environments. The combin ed effects of atmospheric aridity and soil moisture depletion increase the frequency of flash droughts. Under observed climate conditions\, the freq uency of regional flash droughts remained high in the core monsoon region. The north-west (NW) and central north-east (CNE) regions experienced more frequent flash droughts. The west-central (WC) and peninsular region (PR) experienced moderate to low magnitudes of flash drought events. In additi on\, the average length of time and severity of the events stayed high in the CNE and NW regions\, while the flash droughts were very short and mild in the WC and PR regions during the adapted period. These findings emphas ize the need to adapt to the increasing occurrence of rapid-onset droughts in a changing climate\, which can significantly impact crop production an d pose challenges for agricultural irrigation. Understanding of the charac teristics of these rapid and severe drought events is essential for enhanc ing resilience and preparedness.\n\nKeywords: Flash droughts\, Soil-moistu re\, Drought characterization\, India. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:From Dry to Desiccated: A New Paradigm for Flash Drought Monitoring over India - VAIBHAV KUMAR URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/DGXU8Y/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-XDAQCZ@pretalx.earthmon itor.org DTSTART:20250917T114000Z DTEND:20250917T120000Z DESCRIPTION:The risks of climate change impacting the private sector is a d ire reality for any community\, anywhere\, considered at a larger or small er scale (local\, national\, regional) and at all of its different levels\ , be it with respect to the public sector\, the private sector and down to every citizen. Consequences of such impacts are already discernible\, esp ecially in the case of the (re)insurance industry\, also due to the immedi ate catastrophic consequences that\, more and more often\, involve human l osses as well. Given the fundamental characteristic of the private sector - making a profit - overall results of extensive internal analysis of the financial impact of extreme weather events have been made public by variou s reinsurance companies. Furthermore\, there is a significant body of know ledge to define\, characterize and monitor climate change risks with consi deration to the financial impact towards different sectors of the markets and\, as well\, proposed mitigation measures and resilience building strat egies. In these endeavours\, the geospatial component\, encompassing data\ , technology\, methodologies\, are essential. \n\nIn this talk\, the autho rs propose a simplified methodology dedicated to the use of the generated OpenEarthMonitor Cyberinfrastructure geospatial products relevant for asse ssing the risk for the European private sector\, with an emphasis on the r einsurance sector. \nThe work presented will also pinpoint on the difficul ties that arise from the complexity of accurately defining the geographica l extent of the impact chain\, as well as for the geographic footprint of the particular assets to be analysed. For interoperability reasons\, in th e assessment the Global Exposure Database for All schema will be considere d because it is aligned with the Risk Data Hub as well as with the OpenStr eetMap tags\, both datasets being considered in the simplified methodology . DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Assessing Climate Change Risk for the Private Sector: A Geospatial Approach Using OpenEarthMonitor in the European Reinsurance Sector - Codri na Maria Ilie URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/XDAQCZ/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-QYZZJE@pretalx.earthmon itor.org DTSTART:20250917T122500Z DTEND:20250917T132500Z DESCRIPTION:In the context of climate change\, increasing competition for f reshwater use across various sectors is intensifying pressures on water re sources\, placing many countries at heightened risk of water scarcity. To mitigate the growing risk of water scarcity\, it is imperative to reduce w ater usage intensity across agriculture\, industry\, energy production\, a nd domestic sectors. Achieving this requires a comprehensive and detailed understanding of water consumption patterns in each sector\, and estimatin g water storage in groundwater\, reservoirs\, and snowpack is essential to safeguard water availability for future generations.\nThe Po River basin in northern Italy has experienced significant hydrological droughts in rec ent decades (1990-2023)\, highlighting the need to understand the complex interactions between climate factors and human activities. This study\, co nducted as part of the INTERROGATION project funded by the Italian Ministr y of Universities and Research\, presents an integrated approach for water resource management during drought events.\nThe study employs a flexible conceptual hydrological model (MISDc - Modello Idrologico Semistribuito in Continuo) that incorporates both natural processes and anthropogenic infl uences. The model is driven by three distinct precipitation datasets: long -term (2000-2023) daily in-situ measurements\, high-resolution (1.8km) rea nalysis data\, and high-resolution (1km) satellite precipitation data. The Bluecat tool (Montanari et al.\, 2022) is utilized to evaluate the uncert ainty in modelled river discharge.\nThe model's performance is validated u sing multiple satellite-derived observations including soil moisture\, eva poration\, groundwater\, irrigation\, and snow accumulation data developed within the framework of European Space Agency Digital Twin Earth (DTE) Hy drology Next project. The model is capable to reproduce both natural hydro logical processes and anthropogenic activities such as irrigation and rese rvoir operations. \nResults demonstrate the effectiveness of combining acc urate satellite observations with a well-calibrated hydrological model for capturing spatiotemporal variations in the hydrological cycle within high ly anthropized basins. This integrated framework provides valuable insight s for developing a decision support system to guide stakeholders in managi ng water resources during future drought events in the Po River basin. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Improving the Reconstruction of the Hydrological Cycle through Sat ellite Observations: The Case Study of the Po River Basin - Sindhu Kalim isetty URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/QYZZJE/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-KPNRVV@pretalx.earthmon itor.org DTSTART:20250917T133000Z DTEND:20250917T135000Z DESCRIPTION:With this contribution we present a unified system for accessin g and downloading the datasets of the FLUXNET network independently on the ir station of origin\, named the FLUXNET Shuttle. FLUXNET is a global cons ortium of regional networks monitoring greenhouse gas exchanges at the eco system level\, coordinated by three regional hubs – ICOS\, AmeriFlux\, O zFlux. With the participation of several hundreds of stations\, it represe nts the most widespread effort of GHG flux monitoring at the global scale. Output files are harmonised across all the stations contributing to FLUXN ET with the definition of a common set of variables – made possible by t he use of the same processing software (ONEFlux). Despite that\, some diff erences among the networks exist\, especially in terms of data repositorie s accessibility\, while the FLUXNET portal provides access to the latest c omplete data release (FLUXNET2015). The FLUXNET Shuttle is an API-based Py thon tool for querying FLUXNET datasets from any participating station in the world\, thus overcoming these differences. To be used both by command line and via graphical interface\, its technical implementation is a corne rstone of the FLUXNET Data System Initiative\, which aims at extending the spatial coverage of FLUXNET stations and at surmounting the current syste m of fixed releases\, in favour of a more dynamic one based on continuous updates. We expect this initiative to improve usability and discoverabilit y of FLUXNET datasets\, facilitating the users and increasing the FAIRness of the data\, also in the context of the OEMC project. With the definitiv e version expected for December 2025\, here we demonstrate the main featur es of the FLUXNET Shuttle in its current development\, including accessing data of the three regional hubs\, implemented search criteria (e.g. geogr aphical areas\, time periods\, station names)\, and example of application s. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:A UNIFIED TOOL TO ACCESS FLUX TOWERS DATA WORLDWIDE: THE FLUXNET SH UTTLE - Simone Sabbatini URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/KPNRVV/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-GFBHAC@pretalx.earthmon itor.org DTSTART:20250917T133000Z DTEND:20250917T150000Z DESCRIPTION:The workshop will provide instructions on how to access and use OpenLandMap-soildb: a global 30-m spatial resolution dynamic soil databas e showing distribution of soil carbon\, soil pH\, soil texture fractions\, bulk density and soil types (USDA subgroups)\; soil carbon\, pH are model ed as dynamic soil properties with 5--year interval\; soil texture fractio ns\, bulk density and soil type as static variables. This is the first 30- m dynamic soildb with properties mapped through depth (0-30\, 30-60\, 60-1 00) and time. Two tutorials will be provided: (1) in R\, and (2) in python . In both tutorials we will show how to list available layers\, retrieve v alues per point or polygon and how to correctly use and interpret the valu es. The OpenLandMap-soildb data is available from https://stac.openlandmap .org. The tutorials will be made available via https://github.com/openland map/soildb. DTSTAMP:20260525T005335Z LOCATION:Aula 2 (workshops) SUMMARY:OpenLandMap-soildb global dynamic soil data tutorial - Tom Hengl (O penGeoHub) URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/GFBHAC/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-DRGTVD@pretalx.earthmon itor.org DTSTART:20250917T135000Z DTEND:20250917T141000Z DESCRIPTION:Abstract\nWe monitor the impact of 320 nature-based climate sol utions (NBS) implemented through carbon offset projects across 55 countrie s using a standardized methodology based on Earth Observations (EO) Big Da ta. Our objective is to demonstrate the feasibility for using free and ope n EO data at high and low moderate spatial resolutions to support M&E. We identify current gaps and provide recommendations both for technical enhan cements and for the design of restoration policies. Finally\, we deploy a Google Earth Engine app called ‘’Monitor-EO’’\, which allows the e nd user to perform the analysis described in the paper\, using a graphic u ser interface (GUI). \nWe employ an ecosystem-based approach to assess imp acts\, by simultaneously monitoring three key ecosystem variables such as vegetation cover\, land surface temperature and soil moisture. We assume t hat a positive outcome from a restoration measure would lead to increased vegetation levels\, increased soil moisture\, and decreased temperature of the soil surface.\nComparison areas are defined for each project restorat ion site using a 2km buffer around each restoration area and one additiona l comparison area which i) is randomly created within a radius of 3 kilome tres from the restoration area\, and ii) has equal area than the restorati on site?.\nWe measure across restoration and control sites three variables \, the Normalized Difference Vegetation Index (NDVI)\, the Normalized Diff erence Water Index (NDWI)\, and the Land Surface Temperature (LST)\, thre e years before the restoration activity was implement and then for the yea rs following until 2024. We use different EO products from MODIS data (NDV I and NDWI at 500 meters spatial resolution and the LST at 1000 meters spa tial resolution)\nFor each variable we measure the Difference-in-Differenc e (DiD)\, and we perform a trend analysis. We run a series of statistical tests to ascertain the statistical significance of changes in order to inf er causality of the project interventions. Finally\, for selected project sites\, we perform a Spatial Autocorrelation Analysis to assess the degree of spatial clustering of positive changes (indicative of restoration succ ess) compared to a random distribution.\n\nThe Monitor-EO application iden tified significant trends in at least one environmental indicator (NDVI\, LST\, or NDWI) in 62% (199) of the 320 projects analysed\, covering all re gions except Europe. Globally\, NDVI exhibited predominantly positive tren ds\, with 92% of projects showing increases\, particularly in North Americ a\, Asia\, Latin America and the Caribbean (LAC)\, and Africa\, indicating favourable environmental changes. In contrast\, LST displayed decreasing trends in 54% of the projects\, with the most pronounced reductions observ ed in Africa and Asia. NDWI\, however\, exhibited declining trends in the majority of projects\, with only 19% showing increases\, primarily in Afri ca and North America. Projects demonstrating the highest rates of change w ere initiated in 2011 and are projected to extend for over 20 years. Small er projects (less than 1\,000 hectares) exhibited more pronounced trends c ompared to larger projects\, while longer monitoring periods (exceeding 10 years) were associated with more substantial and statistically significan t trends.\n\nKeywords: earth observations\, monitoring and evaluation\, la ndscape restoration\, ecosystem health\, climate change adaptation\, food security\, DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Monitor-EO: an online tool for monitoring and evaluating impacts on land resources and ecosystems from restoration activities - Lorenzo De Si mone URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/DRGTVD/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-KFU7BK@pretalx.earthmon itor.org DTSTART:20250917T141000Z DTEND:20250917T143000Z DESCRIPTION:This study explores transfer learning in the Brazilian Amazon o ver the period from 2015 to 2022. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Transfer Learning as a Solution for the Large Areas Classification Dilemma - Gilberto Camara\, Felipe Carvalho URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/KFU7BK/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-STMSRS@pretalx.earthmon itor.org DTSTART:20250917T142500Z DTEND:20250917T152500Z DESCRIPTION:Sun-Induced Fluorescence (SIF) is considered to be a valuable s ignal detectable from space that provides direct information about Gross P rimary Production (GPP). Previous studies have shown a high correlation be tween SIF estimated from satellite observations and GPP predicted using sa tellite images and machine learning techniques. Many times\, SIF and GPP p roducts are trained and validated from in-situ measurements\, however\, of ten a perfect match is assumed between the area sensed by the satellite an d the area sensed in-situ. For this reason\, it is important to quantify t he representativeness of the in-situ observations when compared with satel lite products at coarser resolution. In the present work\, we evaluated th e representativeness of different eddy covariance towers footprints when c ompared with TROPOMI SIF ungridded product. To quantify the representative ness\, we quantify the amount of information shared by the vegetation aro und the tower and the vegetation sensed by the Sentinel-5p satellite based on Sentinel-2 data cubes and Jensen-Shannon distance. We expect that char acterizing the mismatch with this Jensen-Shannon distance will help improv e the correlation between SIF from the satellite and GPP estimations from the tower. Finally\, to guarantee that our analysis fulfills the FAIR prin ciples\, we will also present a general workflow to run the analysis on-de mand using the Copernicus Data Space Ecosystem infrastructure. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Using Jensen-Shannon distance to better understand the role of land scape heterogeneity in the relationship between TROPOMI SIF product and G ross Primary Production - Daniel E. Pabon-Moreno URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/STMSRS/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-KT7B8A@pretalx.earthmon itor.org DTSTART:20250917T143000Z DTEND:20250917T145000Z DESCRIPTION:The EuroGEO Green Deal Data Space Action Group (GDDS-AG) is a f orum to coordinate the activities of the projects contributing on research and development towards the realization of the GDDS. The key recommendati on for the GDDS-AG is to monitor emerging technologies that can be benefic ial for the GEO infrastructure to support technical and semantic interoper ability between the GDDS datasets\, with GEOSS\, Destination Earth\, Coper nicus Data Space Ecosystem\, INSPIRE\, and European Open Science Cloud pla tforms.\nHighlighting the GDDS-AG member projects such as OEMC (Open-Earth -Monitor Cyberinfrastructure) and SAGE (Sustainable Green Europe Data Spac e)\, use cases in forest monitoring are presented to enhance data interope rability by integrating remote sensing\, in-situ observations\, and biodiv ersity indicators\, which are key to decision-making for forest management and biodiversity conservation. The main challenges and opportunities of data integration at different spatial and temporal scales are addressed in relation to the implementation of the GDDS. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:EuroGEO Green Deal Data Space Action Group - interoperability of fo rest monitoring data at regional\, national\, European\, and global scales - Kaori Otsu\, Imma Serra URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/KT7B8A/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-KKRARH@pretalx.earthmon itor.org DTSTART:20250917T152500Z DTEND:20250917T162500Z DESCRIPTION:The initiatives to facilitate access to open data cubes and res ults of digital twins for Earth systems analysis and early warning are gai ning momentum. Successful experiences like the Open Earth Monitor Cyberinf rastructure are leading to an increasing awareness and experience in the g overnance of these datasets. However\, data providers (i.e. models\, earth observation missions) increasingly offer data in a near-real-time basis p resenting the next challenge in the comprehensive integration of datasets into open Earth cyberinfrastructures. \n\nSoil moisture is one of the cru cial state variables that are currently transitioning to near-real-time da ta provision. In this study\, we explore the potential of two soil moistur e near-real-time data providers to generate end-user early warning drought monitoring capabilities. The study evaluates the feasibility of generatin g near-real-time (daily) merged soil moisture anomaly maps by merging the recent EUMETSAT ASCAT H122 6.25km resolution surface soil moisture product with the near-real-time outputs of GLOFAS4 modelling system from the Euro pean Flood Awareness System (EFAS) at a continental scale. Experiences gai ned on assessing the strengths and weaknesses of the two types of data in the framework of the Open Earth Monitor Cyberinfraestructure across scales are contrasted with the insights collected in the near-real-time workflow design for the aim of this study. In particular\, from the side of data a pplicability\, the study assesses both the coverage and consistency of nea r-real time anomalies ‘dynamic’ estimates compared to ‘static’ est imates from the ones generated using climate data records of the same prod ucts trying to elucidate the actual worth and capabilities of the claim ne ar-real time capacity of the input products. The study secondarily focuses on the strengths and weaknesses of merging data from distinct data types (e.g. model-based and remote-sensing) with special attention to their suit ability for identifying the different ranges of events relevant for monito ring (i.e. the progressive changes in anomalies versus those of extreme ev ents). \n\nTherefore\, the purpose of this study is to provide an outlook on the incoming opportunities and barriers of processing data at near-real -time for its integration into data cubes and digital twin systems within the framework of the accelerating community efforts to provide readily acc essible and operational eErth system data for end-users. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Incremental steps towards near-real time enhanced drought monitorin g combining remote sensing and model-based soil moisture products - Jaime Gaona URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/KKRARH/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-YET9ZL@pretalx.earthmon itor.org DTSTART:20250917T153000Z DTEND:20250917T161500Z DESCRIPTION:The SITS package (Satellite Image Time Series) is designed for the analysis and classification of satellite image time series using machi ne learning. It provides a comprehensive framework for managing\, modellin g\, and classifying time series data derived from remote sensing imagery. In version 1.5.3\, SITS supports both R and Python APIs and has included s upport for CDSE and OGH cloud providers. SITS supports large-scale operati onal analysis on data cubes\, and has state-of-the-art functions for deep learning\, post-processing\, uncertainty estimation\, and texture measures . It allows the merging of Sentinel-1 and Sentinel-2 data\, as well as Lan dsat data with Sentinel-2\, and enables the inclusion of DEM and climate d ata as additional bands. DTSTAMP:20260525T005335Z LOCATION:Aula 2 (workshops) SUMMARY:Multi-language support for image time series analysis using SITS - Gilberto Camara URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/YET9ZL/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-8NFGGH@pretalx.earthmon itor.org DTSTART:20250917T153000Z DTEND:20250917T155000Z DESCRIPTION:GEDTM30 (github.com/openlandmap/GEDTM30) is a open source globa l digital terrain model at 1 arc second. It is the first permissive licens e 1 arc-second terrain model of the world (under CC-BY license). Upon this model\, we are presenting a framework to merge national\, state-based or individual digital terrain model to improve GEDTM30 data quality locally. Due to permissive license\, GEDTM30 can be used as a base layer to create derive products. By merging local lidar DTMs with GEDTM30\, it opens the g ate to federation of data\, sharing the common goods but keeps the best in terests for individuals. This framework will be tested by GEDTM30 with lid ar data from several countries (e.g. Romania\, Italy\, the Netherlands\, B razil\, etc)\, and the land surface variables are included to assess the m erged GEDTM30 quality. In the end\, the code and framework will be open to serve any stakeholders to improve DTM quality of their area of interest a nd have freedom to decide for contribution. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:A framework of federal global ensemble digital terrain model - Yu-F eng Ho URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/8NFGGH/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-QQGPVH@pretalx.earthmon itor.org DTSTART:20250917T155000Z DTEND:20250917T161000Z DESCRIPTION:OpenLandMap-soildb (https://doi.org/10.5194/essd-2025-336) cont ains global dynamic predictions of soil organic carbon content\, soil orga nic carbon density\, bulk density\, soil pH in H2O\, soil texture fraction s (clay\, sand and slit) and USDA subgroup soil types (USDA soil taxonomy subgroups) at 30 m spatial resolution based on spatiotemporal Machine Le arning (Quantile Regression Random Forest with output predictions showing the mean plus the lower and upper prediction intervals of 68 % probabili ty). Predictions are provided at 3 standard depth intervals 0-30\, 30-60 a nd 60-100 cm and for 5-year intervals. Data is available via STAC.OpenLand Map.org and via Google Earth Engine under the CC-BY license. This is the f irst ever global 30-m spatial resolution soildb that can be used to serve various land monitoring projects and was specifically created to support t he UNCCD's Land Degradation Neutrality programme and similar international programmes where focus is on improving soil health\, increasing SOC and d ecreasing soil degradation (soil erosion\, loss of soil biodiversity\, com paction\, salinization and similar). DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Global soil carbon and soil pH predictions for 2000-2024 at 30-m ba sed on spatiotemporal Machine Learning and harmonized legacy soil samples and observations - Tom Hengl (OpenGeoHub) URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/QQGPVH/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-MAHPTK@pretalx.earthmon itor.org DTSTART:20250917T161000Z DTEND:20250917T163000Z DESCRIPTION:Cocoa cultivation serves as a cornerstone of many agricultural economies across the globe\, supporting millions of livelihoods and contri buting significantly to global cocoa production. However\, accurately mapp ing cocoa farm locations remains a challenging endeavor due to the complex and heterogeneous nature of the landscapes where cocoa is cultivated. Tra ditional mapping techniques often fall short in capturing the intricate sp atial patterns of cocoa farming amidst dense vegetation\, varying land cov er types\, farming practices and growing stages (Masolele et at.\, 2024). Moreover\, the current mapping efforts mainly focus on two major producing countries\, Ivory Coast\, and Ghana (Kalischek et al.\, 2023). Thus\, lit tle is known about the location of cocoa farms in other cocoa producing re gions\, posing a challenge to the sustainability and economic contribution s of the cocoa crop. \nTo address this challenge\, we first present a benc hmarking approach for mapping commodity crops worldwide. Here we compare d ifferent spectral\, spatial\, temporal and spatial-temporal methods for ma pping commodity crops. The benchmarking is based on a variable combination of Sentinel-1 and Sentinel-2\, locational and environmental variables (te mperature and precipitation). We use a comprehensive list of reference dat a spanning 36 cocoa-producing countries to do this task. Higher accuracy ( F1-score 87%) is obtained when using a model that employs spatial-temporal remote sensing images plus locational and environmental information\, com pared to other models without locational and environmental information.\nS econdly\, for demonstration\, we employ the developed deep learning method ologies to map the locations of cocoa farms across the Globe with an F1-Sc ore of 88%. By leveraging the rich spatio-temporal information provided by Sentinel-1 and Sentinel-2 satellite data\, complemented by location enc odings\, temperature and precipitation data\, we have developed a robust a nd accurate cocoa mapping framework. The developed deep learning algorithm extracts meaningful features from multi-source satellite imagery and effe ctively identifies cocoa farming areas. The integration of Sentinel-1 and Sentinel-2 data offers a synergistic approach\, combining radar and optica l sensing capabilities to overcome the limitations of individual sensor mo dalities. Furthermore\, incorporating location encodings into the modeling process enhances the contextual understanding of cocoa farm distributions within their geographical surroundings. \nThrough this research effort\, we provide the first high-resolution global cocoa map giving\, valuable in sights into cocoa farm locations\, facilitating sustainable cocoa producti on practices\, land management strategies\, and conservation efforts acros s the pan-tropical forests\, where cocoa farming occurs. The work aligns w ith recent European Union (EU) regulations to curb the EU market’s impac t on global deforestation and provides valuable information for monitoring land use following deforestation\, crucial for environmental initiatives and carbon neutrality goals (European Commission.\, 2024). Specifically\, our product can support monitoring and compliance of the European Union (E U) Regulation on Deforestation-free Products (EUDR\, No 2023/1115) by iden tifying the previous existing and current cocoa farm expansion after the c ut-off date of December 31\, 2020.\nWithin the framework of the ESA funded WorldAgroCommodities project\, this mapping approach is now being convert ed into an operational cloud-based service on the Copernicus Data Space Ec osystem\, allowing easy access to these crucial tools for the National Com petent Authorities in light of enforcing the EUDR regulation. Furthermore\ , our findings hold significant implications for cocoa farmers\, agricultu ral policymakers\, and environmental stakeholders\, paving the way for inf ormed decision-making and targeted interventions to support the resilience \, sustainability and traceability of cocoa farming systems worldwide. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:High-Resolution Global Maps of Cocoa Farms Extent - Robert Masolele URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/MAHPTK/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-MXHPBU@pretalx.earthmon itor.org DTSTART:20250917T162500Z DTEND:20250917T172500Z DESCRIPTION:Digital public infrastructure (DPI) have been a recently coined term for a framework for digitally delivering delivering public services. Characterized by 3 core tenets: open data\, open standards and open sourc e software\, it has already found governments across the world interested in adopting solutions for identity management\, financial transactions and e-commerce. Through our research paper\, we explore how these principles can be applied to disseminate data and insights collected by remote sensin g and geosciences departments and how they can inform climate action strat egies\, such as the formulation of heat action plans. The paper highlights the current problems in the ecosystem collecting\, processing and distrib uting this data in India today\, formulates design principles that can hel p mitigate these challenges\, and proposes the way forward. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Digital Public Infrastructure for Ecological Variables: An Indian a pproach to public service delivery meets global best practices for dissemi nating climate data - Trishal Kumar URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/MXHPBU/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-B3GWYZ@pretalx.earthmon itor.org DTSTART:20250917T163000Z DTEND:20250917T165000Z DESCRIPTION:The development of a national ground motion monitoring system h as become an essential tool of remote sensing for addressing geological ha zards\, urban planning\, and infrastructure management. Over the past few years\, several countries have successfully implemented such services\, hi ghlighting their importance in mitigating risks and supporting sustainable development. Inspired by these global trends and the advancements in sate llite technology\, this research proposes the creation of a Serbian Ground Motion Service (GMS-Serbia). Leveraging the Sentinel-1 mission\, operatio nal since 2014\, and its advanced Interferometric Synthetic Aperture Radar (InSAR) capabilities\, GMS-Serbia would provide high-resolution ground mo tion data to monitor subsidence\, landslides\, and other deformation pheno mena across Serbia. GMS-Serbia will rely on advanced Differential InSAR te chniques (ADinSAR)\, such as Persistent Scatterer and Small Baseline InSAR . The recent launch of Sentinel-1C has further enhanced data availability\ , offering improved coverage and revisit frequency\, making this an ideal time to establish a dedicated national service. This research emphasizes t he necessity of GMS-Serbia\, particularly as Serbia is not covered in the European Ground Motion Service (EGMS)\, a regional initiative covering muc h of Europe. By filling this gap\, GMS-Serbia would not only address natio nal needs but also contribute to regional and global efforts in ground mot ion monitoring. The proposed service would provide actionable insights for disaster risk reduction\, urban planning\, and infrastructure development \, while also fostering collaboration with existing international initiati ves. This work outlines the conceptual framework\, methodological approach \, and future directions for GMS-Serbia\, highlighting its potential to en hance Serbia's resilience to geological hazards and support sustainable de velopment in the context of a rapidly changing environment. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Towards the Development of a Serbian Ground Motion Service (GMS-Ser bia) Using Sentinel-1 InSAR Data: Necessity\, Opportunities\, and Future D irections - Miloš Basarić URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/B3GWYZ/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-ACUVCN@pretalx.earthmon itor.org DTSTART:20250917T172500Z DTEND:20250917T182500Z DESCRIPTION:Snow cover plays a crucial role in Mediterranean water resource s\, serving as a\nnatural reservoir that regulates seasonal water availabi lity and supports hydrological\nprocesses across mountainous catchments. H owever\, monitoring snow across this\ndiverse and topographically complex region remains challenging due to the limited\navailability of in-situ obs ervations and high spatial variability. This study analyzes long-\nterm sn ow cover dynamics across the Mediterranean region and its four major river \nbasins (Po\, Tiber\, Crati\, and Ebro) using three satellite datasets: t he Advanced Very\nHigh Resolution Radiometer (AVHRR)\, the Moderate Resolu tion Imaging Spectroradiometer\n(MODIS)\, and the Sentinel-1 (S-1). Throug h a systematic comparison of Snow Cover\nGround Fraction (SCGF) data\, we characterized spatial patterns\, temporal trends\, and\nresponses to extre me events across the Mediterranean region. Mean annual SCGF patterns\nexhi bit distinct spatial gradients\, with mountainous regions displaying the h ighest\nsnow accumulation while coastal and lowland areas remain predomina ntly snow-free\nthroughout the year. MODIS data\, benefiting from superior spatial resolution\,\ncaptures finer-scale spatial patterns compared to A VHRR observations.\nAnomaly analyses during extreme climatic events\, incl uding the 2005 and 2022 droughts\,\nshow spatially coherent patterns acros s both AVHRR and MODIS. The 2022 drought is\nmarked by widespread negative anomalies over the Mediterranean region. Cross-sensor\nvalidation confirm s a strong agreement between AVHRR and MODIS across most areas\, with\nS-1 snow depth data further supporting the accuracy of snow detection. Perfor mance\nconsistency varies substantially by basin when AVHRR is compared wi th S-1:\nmountainous regions\, such as the Po basin\, exhibit the highest inter-sensor\nagreement\, while smaller basins\, including Crati and Tiber \, show greater variability\ndue to their topography and geographic locati on.\nRegional-scale trend analysis using AVHRR data reveals statistically significant\ndeclines in snow cover over recent decades\, although basin-l evel trends remain\nobscured by pronounced interannual variability. These findings demonstrate the\nvalue of multi-sensor satellite observations for monitoring snow cover dynamics in\nthis climatically sensitive Mediterran ean region\, highlighting both the complementary\nnature of different remo te sensing platforms and the spatial heterogeneity of snow\ncover response s to climate variability. DTSTAMP:20260525T005335Z LOCATION:Aula 3 (Posters) SUMMARY:Multi-Sensor Snow Cover Assessment over the Mediterranean Region - Mohsin Tariq URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/ACUVCN/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-9K3D9B@pretalx.earthmon itor.org DTSTART:20250918T093000Z DTEND:20250918T100000Z DESCRIPTION:This presentation showcases innovative tools—from user-friend ly apps for visual interpretation and machine learning–ready data collec tion to in-situ observation tools embedded in the Geo-Quest app—that emp ower citizens to contribute meaningfully to land-use monitoring and climat e action. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Preventing Catastrophic Climate Change: The Role of In-Situ Data an d Citizen-Collected Observations - Steffen Fritz URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/9K3D9B/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-GEDAFD@pretalx.earthmon itor.org DTSTART:20250918T100000Z DTEND:20250918T103000Z DESCRIPTION:Over the past decade\, Sentinel-1 has become vital for radar-ba sed forest disturbance monitoring. Its cloud-penetrating radar delivers co nsistent\, gap-free observations every 6–12 days in the tropics and near ly daily in northern latitudes\, enabling reliable near-real-time monitori ng even in cloudy regions. With 10 m detail and sensitivity to vegetatio n structure\, Sentinel-1 has transformed detection of fine-scale disturban ces like small-scale farming\, road building\, and selective logging.\n \n We show how Sentinel-1 has advanced forest monitoring. Early efforts devel oped near-real-time change detection\, demonstrating that frequent observa tions can offset C-band radar’s lower sensitivity. Open data access\, co mbined with cloud computing and open-source tools\, allowed us to scale up methods into the operational Radar for Detecting Deforestation (RADD) ale rts. Updated weekly and covering 55 pan-tropical countries\, RADD alerts a re freely available through Global Forest Watch and support law enforcemen t\, supply chain monitoring\, and research.\n\nWe also share lessons from expanding RADD to new regions\, including Europe. Advances include radar t exture-based detection\, monitoring in temperate and boreal forests\, and monthly road mapping. New developments enable tracking of forest loss driv ers and intra-annual carbon loss\, and continental-scale commodity mapping . Future improvements will benefit from combining Sentinel-1 with optical sensors and upcoming radar missions (NISAR\, BIOMASS). DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Ten years of Advancing Forest Disturbance Monitoring with Sentinel- 1 radar - Johannes Reiche URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/GEDAFD/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-9FWUEC@pretalx.earthmon itor.org DTSTART:20250918T110000Z DTEND:20250918T112000Z DESCRIPTION:OpenEO is an emerging open standard for processing large Earth Observation datasets on cloud infrastructure. The most well-known openEO b ackend providers are Copernicus Data Space Ecosystem and OpenEO Platform\, both running on European cloud infrastructure. Several Monitors in the Op en Earth Monitor Cyberinfrastructure project have been ported to openEO\, which makes their workflow more transparent and accessible for a wider aud ience. Namely\, these are the pantropical monitor of land use following de forestation\, the European monitor of wet snow\, and the European monitor of air quality. This presentation will go over how these use cases were im plemented on openEO\, the current status and remaining challenges of the o penEO implementation\, and future outlook. In addition\, the participants will be provided with an opportunity to try out the monitors themselves. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Open Earth Monitor implementation on openEO - Dainius Masiliunas URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/9FWUEC/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-PEZNQY@pretalx.earthmon itor.org DTSTART:20250918T112000Z DTEND:20250918T114000Z DESCRIPTION:Tropical forests are biodiversity hotspots\, providing critical ecosystem services that sustain millions of plant and animal species. How ever\, these forests are increasingly threatened by human activities\, thr ough the expansion of commodity crops such as soy\, oil palm\, rubber\, co coa\, coffee\, corn\, logging\, avocado\, and pasture (Masolele et al.\, 2 022\, 2024). While significant efforts have been made to monitor deforesta tion using satellite imagery\, most initiatives stop at detecting forest l oss without tracking the land use that follows (Hansen et al.\, 2013). Und erstanding post-deforestation land use is crucial for addressing deforesta tion's root causes and mitigating its impacts (Masolele et al.\, 2022\, 20 24).\nCurrently\, there is no global monitoring system capable of providin g annual\, spatially detailed updates on the land use that follows after d eforestation. Existing datasets and methods frequently lack the spatial\, thematic\, and temporal resolution necessary to accurately map post-defore station land uses (Curtis et al.\, 2018)\, limiting their utility for targ eted rapid policy response and regulatory compliance\, such as the Europea n Union’s Deforestation Regulation (EUDR) (European Commission.\, 2024). This gap poses challenges for ensuring EUDR compliance\, limiting the cap acity to detect and mitigate deforestation linked to commodity production. Here\, we present the first high-resolution (10 m) maps of land use foll owing deforestation covering the entire pan-tropics. We utilize an extensi ve reference database containing 23 different land use types (including\, soy\, oil palm\, rubber\, cocoa\, coffee\, corn\, logging\, avocado\, mini ng\, cashew\, corn\, sugar\, rice\, and pasture)\, and employ Sentinel-1 a nd Sentinel-2 data combined with deep learning algorithms\, to map land us e following tropical deforestation from 2001 to 2023 with an F1-score of 8 3%. Our approach incorporates location encodings and environmental variabl es\, such as elevation\, temperature\, and precipitation\, to enhance the model’s ability to distinguish various land uses across diverse geograph ies. In general our results shows increased deforestation as a result of e xpansion of key commodity crops such as cocoa in Liberia\, Cameroon\, Ivor y Coast\, Ghana\, Ecuador\, Peru\, Papua New Guinea\; oil palm\, in Indone sia\, Malaysia\; rubber in Malyasia\, Thailand\, Laos\, Indonesia\; coffee in Central America (Guatemala\, Nicaragua\, Costa rica)\, Peru\, Ethiopia \, Colombia\, Vietnam\; soy in Brazil\; pasture in Paraguay\, Bolivia\, Me xico\, Brazil\, Cashew in in Cambodia\, Tanzania\, Mozambique\, Benin and\ , logging in Suriname\, Guyana\, Papua New Guinea\, Equatorial Guinea\, Ga bon\, Republic of Congo\, and Cameroon.\nThis work directly supports the E uropean Union’s Deforestation Regulation (EUDR)\, aimed at curbing the E U market’s contribution to global deforestation (European Commission.\, 2024). Our research offers crucial insights for monitoring land use follow ing deforestation\, aiding environmental conservation initiatives and adva ncing carbon neutrality goals by providing detailed\, high-resolution maps on land use that follows after deforestation events. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Mapping Land Use Following Deforestation Across the Pan-Tropics wit h Sentinel Data - Robert Masolele URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/PEZNQY/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-ABRPXE@pretalx.earthmon itor.org DTSTART:20250918T114000Z DTEND:20250918T120000Z DESCRIPTION:Drought is a natural hazard caused by a precipitation deficit a nd consequent hydrological imbalance (Pachauri et al.\, 2014\; Trenberth e t al.\, 2014)\, with significant economic and environmental impacts\, part icularly in agriculture and forests. Although\, ground-based observations provide high accuracy for drought-related parameters such as precipitation \, temperature\, and soil moisture\, they lack in coverage and cost\, maki ng them unsuitable for large-scale\, high-resolution assessments. In contr ast\, remote sensing technologies offer a cost-effective alternative\, pro viding continuous spatial information over large regions. \nThis study is conducted as part of the Open Earth Monitor (OEMC) project\, which aims to develop a global\, high-resolution system for drought monitoring. Our res earch focuses on identifying and improving existing approaches to create h igh-resolution monthly drought maps by exploiting drought indicators from ground station meteorological data and remotely sensed soil moisture. Soil moisture plays a key role in drought monitoring and prediction\, especial ly in water-limited ecosystems (D'Odorico et al.\, 2007\; Moran et al.\, 2 004\; Peters-Lidard et al.\, 2008)\, such as the Ebro Basin at northeast o f Spain\, the study area.\nIn terms of the available soil moisture dataset s\, existing datasets often lack the resolution and reliability required f or an effective assessment. To address this\, a thorough review was conduc ted\, various soil moisture products provide global coverage\, but their c oarse spatial resolution requires downscaling techniques to improve usabil ity at local and regional scales. Since our focus is on developing a droug ht monitoring system with an agricultural emphasis\, we prioritized produc ts with spatial resolution 1km. A recent review (Brocca et al.\, 2024) on soil moisture products in Italy demonstrated that Sentinel-1 products show good agreement in terms of drought detection. Considering that drought is a long-term phenomenon\, a minimum timescale is necessary for meaningful anomalies detection. However\, high-resolution soil moisture data are avai lable for a shorter period than meteorological data\, that span from 1950 till today. \n\nBased on these\, we selected two high-resolution datasets: the Sentinel-1 dual-polarization SAR (DPA) with a 1 km spatial resolution (Fan et al.\, 2025)\, and downscaled SMOS soil moisture data at 1 km reso lution (Escorihuela et al.\, 2018\; Merlin et al.\, 2013) (*)\, provides a longer temporal record. Our analysis compares these data sets across time scale to determine whether soil moisture data compliment the drought monit oring approaches.\n(*) The SMOS dataset used in this work was produced wit hin the ACCWA project which has received funding from the European Union's H2020-MSCA-RISE-2018 programme under grant agreement No. 823965." DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Advancing High-Resolution Drought Monitoring: Evaluating Remote Sen sing Soil Moisture Products for Integration in OEMC Drought Monitoring - E irini Trypidaki URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/ABRPXE/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-Y3FBNN@pretalx.earthmon itor.org DTSTART:20250918T133000Z DTEND:20250918T141500Z DESCRIPTION:Snow monitoring plays a crucial role in the effective managemen t of water resources. The increasing availability of remote sensing data o ffers significant advantages but also introduces challenges related to dat a accessibility\, processing\, and storage. Leveraging a cloud-based platf orm such as the Copernicus Data Space Ecosystem (CDSE) offers an efficient solution by enabling data processing directly where the data are stored. Specificaaly\, our workflows are built using the openEO API\, providing a standardized interface for accessing and processing large Earth observatio n datasets.\n\nIn this practical session\, we will demonstrate fundamental yet powerful applications for snow monitoring. Participants will explore examples including snow cover classification using state-of-the-art and ad vanced machine learning techniques\, wet snow detection\, and snow albedo estimation. The exercises will highlight how various sensors and methods c an be exploited to achieve desired outputs. By the end of the workshop\, a ttendees will gain hands-on experience with openEO tools and understand ho w cloud-based infrastructures can streamline large-scale environmental dat a processing. DTSTAMP:20260525T005335Z LOCATION:Aula 2 (workshops) SUMMARY:Streamlining Snow Monitoring with openEO and CDSE - Valentina Premi er URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/Y3FBNN/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-XJETFR@pretalx.earthmon itor.org DTSTART:20250918T133000Z DTEND:20250918T135000Z DESCRIPTION:Monitoring ecosystem restoration efforts at scale remains a sig nificant challenge\, despite their critical importance for ecosystem recov ery and biodiversity conservation. Publicly funded satellite missions such as Sentinel-2 and Landsat offer opportunities for global-scale monitoring \, thanks to their high spatial and temporal resolution\, provided these d ata can be meaningfully linked to ecosystem characteristics. Here\, we use a variety of remote sensing time-series products developed within the sco pe of the OEMC project consortium\, including variables that quantify vege tation traits\, indices\, and soil health characteristics. These datasets are available at annual intervals for a period of up to 25 years\, with a spatial resolution of 30 meters or higher. This is crucial for monitoring restoration efforts of smallholder farmers\, given the often sub-hectare p lot sizes. We apply our methodology to three restoration project data base s: (1) a controlled scientific experiment comparing the effects of differe nt reforestation practices in Costa Rica\, (2) a large global database of nature-based carbon offset projects\, and (3) sites from the Restor.eco da tabase\, a global network of restoration projects. For each site\, we anal yze changes over time by comparing pre- and post-intervention trends and e xplore methods for identifying suitable control sites to isolate the effec ts of restoration. Altogether\, this work supports global restoration trac king\, empowering local farmers and smallholders by demonstrating that the ir efforts have an impact at a global scale. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Restoration at scale: Evaluating the progress of global restoration efforts using high spatial resolution time-series information of vegetati on traits and indices - Felix Specker URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/XJETFR/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-AV9QP3@pretalx.earthmon itor.org DTSTART:20250918T135000Z DTEND:20250918T141000Z DESCRIPTION:To support climate-resilient forest planning across Europe\, we are developing high-resolution suitability maps for 50 common tree specie s under future climate scenarios. The approach builds on a harmonized pres ence–absence dataset derived from over 270\,000 National Forest Inventor y (NFI) plots from 11 countries\, complemented with publicly available rec ords to ensure broad spatial coverage. Species–climate relationships are modeled using a suite of machine learning algorithms trained on historica l climatologies and projected using bias-corrected outputs from five GCM –RCM chains within the EUR-11 domain\, under RCP4.5 and RCP8.5. The mode ling pipeline is designed to produce decadal projections at 1 km spatial r esolution\, allowing fine-scale exploration of ecological suitability from 2030 to 2100. To enhance predictive robustness\, multiple algorithms are combined through ensemble methods\, including stacking\, using a limited s et of ecologically relevant predictors. This work complements existing eff orts in species distribution modeling by integrating high spatial and temp oral granularity with a multi-model climate ensemble and a harmonized pan- European observational dataset. The resulting maps will be integrated into the EU reforestation planner tool\, supporting long-term\, spatially expl icit strategies for tree species selection under changing climatic conditi ons. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Predicting future tree species suitability across Europe with harmo nized forest data and climate ensembles - Carmelo Bonannella URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/AV9QP3/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-7YX37V@pretalx.earthmon itor.org DTSTART:20250918T141000Z DTEND:20250918T143000Z DESCRIPTION:This work integrates optical and radar data cubes to detect for est disturbances in tropical regions.\n\nOur method identifies initial deg radation and selective logging\, often precursors to deforestation\, demon strating its utility in early-warning systems. These results emphasizes th e crucial role of integrating optical and radar data to improve the precis ion and dependability of monitoring systems\, essential for sustainable fo rest management. These findings highlight the value of integrating multi-s ource data cubes to enhance precision in monitoring forest disturbances\, thereby supporting more responsive and reliable environmental management. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Integration of Radar and Optical Data for Identifying Tropical Fore st Disturbances - Gilberto Camara\, Felipe Carvalho URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/7YX37V/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-TMLCVN@pretalx.earthmon itor.org DTSTART:20250918T143000Z DTEND:20250918T145000Z DESCRIPTION:This study introduces a global-scale framework for statisticall y downscaling monthly precipitation data to a high spatial resolution of 1 km for the period 2000–2024. We integrate satellite-derived\, reanalysi s-based\, and in situ observational datasets using an ensemble fusion appr oach that leverages the strengths of multiple global products\, including ERA5\, CHELSA\, and IMERG. Statistical downscaling methodology is implemen ted using ground-based meteorological station data to improve the represen tativeness of local precipitation patterns. The framework incorporates spa tial predictors and temporal dynamics to transform coarse-resolution input s into fine-scale monthly precipitation fields. The resulting dataset prov ides improved consistency and detail across diverse climatic regions and d ata-sparse environments. This high-resolution precipitation product is des igned to support a range of applications\, including hydrological modeling \, drought and flood risk assessment\, and climate change impact analysis. Overall\, the proposed approach offers a scalable and replicable methodol ogy for generating detailed precipitation estimates by harmonizing global datasets with in situ observations. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Multi-source Fusion Framework for Statistical Downscaling of Global Monthly Precipitation - Mustafa Serkan Isik URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/TMLCVN/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-YAQHQA@pretalx.earthmon itor.org DTSTART:20250918T153000Z DTEND:20250918T155000Z DESCRIPTION:Several Digital Twins of the Earth are being developed in recen t years\, driven by the growing\ninterest in integrating the latest advanc ements in Earth Observation (EO)\, modeling\, artificial\nintelligence\, a nd computational power to make them accessible to the scientific community and\ninterested parties. Such platforms are highly valuable in supporting sustainability efforts and\ncombating climate change\, enabling the visua lization\, analysis\, and prediction of the natural system\n- including hu man activities and their influence.\nThe European Space Agency (ESA) also shown interest in this framework by launching the DTE\nHydrology project\, which focuses on analyzing the water cycle and its key components using t he\nlatest satellite observations and models. A critical aspect of the pro ject involves the development of\nhigh-resolution (at least 1 km\, daily) datasets for essential water cycle variables\, aimed at\nreplicating hydro logical behavior and understanding interactions with human systems. Among these\nvariables\, precipitation plays a central role due to its impact on agriculture\, economic stability\,\nwater resource planning\, and disaste r risk reduction. Globally\, ground-based observation networks\nfor precip itation monitoring are declining due to political and economic constraints \, forcing many\nregions to rely on less accurate precipitation datasets\, affected by the decreasing gauge density. In\nthis context\, satellite-de rived precipitation estimates have the potential to improve precipitation\ nestimates by filling both spatial and temporal data gaps. However\, numer ous precipitation products\nhave emerged over the years\, each with their own strengths and limitations\, making it challenging\nfor users to determ ine the most suitable product for their study area.\nTo overcome this issu e and capitalize on the individual strengths of each datasets\, the DTE-\n Hydrology initiative has developed a combined precipitation product that m erges multiple sources\,\nincluding satellite-based and reanalysis dataset s\, into a unified\, enhanced product. Specifically\,\nprecipitation estim ates from IMERG-Late Run\, SM2RAIN ASCAT (H SAF)\, and ERA5 Land are\ndown scaled at 1 km spatial resolution and subsequently merged using pixel-base d weights derived\nfrom the application of the Triple Collocation method. The final merged product was thoroughly\nvalidated and compared against a wide range of datasets—both coarse-resolution sources such as H\nSAF\, I MERG-LR\, ERA5\, EOBS\, PERSIANN\, CHIRP\, GSMAP\, and fine-resolution dat asets like\nEMO\, SAIH\, COMEPHORE\, and MCM—demonstrating its high reli ability and strong\nperformance. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Developing Precipitation within Digital Twin Earth Hydrology – Le veraging the individual strengths of multiple products - Paolo Filippucci\ , Luca Ciabatta\, Luca Brocca\, Christian Massari URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/YAQHQA/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-QZBPBM@pretalx.earthmon itor.org DTSTART:20250918T153000Z DTEND:20250918T161500Z DESCRIPTION:This workshop provides a hands-on tutorial to merge to improve global digital terrain models (DTMs) by high-quality local LiDAR data whil e maintaining consistency with a standardized global framework. \n\nThe se ssion complements the oral presentation "A Framework of Federal Global Ens emble Terrain Model" and offers participants a practical workflow to empow er GEDTM30 data users to improve GEDTM30 for local application.\n\nThe wor kshop is structured in three parts:\n\n(1) Introduction and Data Access: P articipants will learn to access and visualize GEDTM30 elevation data thro ugh STAC-compliant endpoints and understand its spatial structure and meta data.\n\n(2) Local LiDAR Integration: This section focuses on preprocessin g local high-quality LiDAR-derived DTMs\, resampling them to match the GED TM30 30-meter grid\, and incorporating them into the ensemble model to enh ance local accuracy while preserving global consistency.\n\n(3) Land Surfa ce variable Derivation and Validation: Participants will derive surface pa rameters (e.g.\, slope\, aspect) from the enhanced terrain model and perfo rm validation analyses to quantify improvements and ensure consistency wit h the global baseline.\n\nThis workshop is intended for researchers\, data scientists\, and GIS professionals interested in terrain modeling\, geosp atial data fusion\, and scalable environmental data processing workflows. DTSTAMP:20260525T005335Z LOCATION:Aula 2 (workshops) SUMMARY:Federal workflow to acess GEDTM30\, and improve it with airborne li dar - Yu-Feng Ho URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/QZBPBM/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-XD9SXB@pretalx.earthmon itor.org DTSTART:20250918T155000Z DTEND:20250918T161000Z DESCRIPTION:Precipitation estimation\, SM2RAIN\, TWS\, NGGM\, MAGIC\, Synth etic experiments DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Assessing the Impact of Next Generation Gravity Missions on Precipi tation Estimation over Europe - Muhammad Usman Liaqat URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/XD9SXB/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-ENZYEY@pretalx.earthmon itor.org DTSTART:20250918T161000Z DTEND:20250918T163000Z DESCRIPTION:Water resources are essential for agricultural\, industrial\, a nd domestic uses\, ensuring high standards of living. Among these\, agricu lture accounts for the vast majority of global water ab-stractions\, far s urpassing the uses referring to other sectors. Par-adoxically\, it remains one of the least understood. Detailed\, ex-plicit information on irrigati on practices is still largely unavaila-ble or inadequately monitored at th e global scale. In recent years\, Earth Observation (EO) technologies have opened up new possibilities for monitoring irrigation dynamics\, both in detect-ing irrigation occurrence in space and time and in quantifying the volumes of water used. This work presents recent advances in monitoring ir rigation dynamics through innovative satellite-based approaches: the TSIMA P (Temporal-Stability-derived Irri-gation MAPping) method\, aimed at mappi ng irrigated areas us-ing satellite data\, and the Soil Moisture (SM)-base d inversion approach\, which estimates irrigation water use. TSIMAP is a v ersatile methodology\, successfully applied across various cli-matic regio ns and at different spatial resolutions. The SM-based approach\, on the ot her hand\, has enabled the creation of the first-ever high-resolution data sets of irrigation water use an im-portant step for evaluating the hydrolo gical impact of irrigation. Recently\, this method has also been implement ed operationally\, demonstrating its potential for building satellite-base d agricul-tural water monitoring systems. Along with results from the meth odologies above\, this contribution will also focus on future challenges i n the field of irrigation monitoring from space. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Leveraging Earth Observation to monitor the most impactful (yet unk nown) human activity on the water cycle: irrigation - Jacopo Dari URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/ENZYEY/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-CNVZJU@pretalx.earthmon itor.org DTSTART:20250919T093000Z DTEND:20250919T095000Z DESCRIPTION:Climate change alters familiar environments and impacts our dai ly lives. In this circumstances it essential to monitor river discharge fo r a range of activities\, including water resource management and flood ri sk reduction. However\, in-situ stations have some limitations\, such as l ow density\, incomplete temporal coverage\, and data access delays\, which make continuous spatio-temporal monitoring of river discharge a challengi ng task. For this reason\, researchers and space agencies have developed n ew satellite-based methods for estimating runoff and river discharge. Amon g these\, the European Space Agency (ESA) has funded the STREAM (SaTellite -based Runoff Evaluation And Mapping) and STREAM-NEXT projects\, which exp loit satellite observations of precipitation\, soil moisture\, terrestrial water storage\, altimetric water level\, and snow cover fraction within a conceptually parsimonious model\, STREAM\, to estimate runoff and river d ischarge.\nApplied to more than 40 basins worldwide including the largest basins in the world (e.g.\, Mississippi-Missouri\, Amazon\, Danube\, Murra y-Darling\, and Niger)\, the STREAM model has shown good ability to replic ate observed river discharge\, even in basins with a high degree of human pressure where flow is regulated by dams\, reservoirs\, or floodplains\, o r in heavily irrigated areas. The positive results achieved have paved the way for regionalizing the parameters of the STREAM model to make it appli cable on a global scale. Through the calibration of the STREAM model on t he 40 pilot catchments\, it was possible to obtain a large set of paramete rs that were linked\, through specific relationships\, to various features including climate\, soil characteristics\, vegetation and topographic att ributes. This approach yielded regionalized STREAM parameters. This study aims to evaluate the efficacy of the STREAM runoff and river discharge es timates\, derived from regionalized parameters\, across a diverse range of basins. To this end\, a comparative analysis will be conducted between ob served and simulated river discharge\, as well as between simulated and mo deled land surface runoff estimates.\nThis contribution aims to demonstrat e how the use of readily available information processed through a concept ual regionalized hydrological model can bring benefits in estimating river discharge and producing runoff maps\, even in basins characterised by int ricate interactions between natural and anthropogenic phenomena. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Toward a global scale runoff estimation through satellite observati ons: the STREAM model - Francesco Leopardi URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/CNVZJU/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-8Q8CVW@pretalx.earthmon itor.org DTSTART:20250919T095000Z DTEND:20250919T101000Z DESCRIPTION:In response to the European Union Deforestation Regulation (EUD R)\, EU member states must verify that imported forest risk commodities (F RCs) such as coffee\, cacao\, soy\, and timber are not sourced from defore sted land. At Meise Botanic Garden\, we have established an ICP-OES labora tory to determine the mineral composition of these commodities. In collabo ration with Ghent University\, we further enhance this analysis using ICP- MS and isotope ratio techniques. We connect our results to evaluation plat forms and databases as those provided by World Forest ID. To further conte xtualize our findings and assess the plausibility of declared origins\, we complement the lab work with dry lab estimations\, drawing on global soil grids and satellite-derived spectral data to approximate local soil miner al compositions. We also present preliminary insights into how post-harves t processing\, particularly decaffeination of coffee\, alters the mineral signature of the final product and complicates provenance verification. Th is hybrid approach provides a valuable indication of origin in cases where our reference database is still under development. Ultimately\, the integ ration of laboratory analysis with geospatial estimation offers a pragmati c tool for EUDR enforcement and opens new pathways for innovation in EU Gr een Deal-aligned services. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:From Soil Grids and Spectral Analysis to Soil Mineral Composition E stimates - Christophe Van Neste URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/8Q8CVW/ END:VEVENT BEGIN:VEVENT UID:pretalx-open-earth-monitor-global-workshop-2025-VGPKKZ@pretalx.earthmon itor.org DTSTART:20250919T110000Z DTEND:20250919T114500Z DESCRIPTION:Spaceborne Lidar\, such as ICESat-2 and GEDI\, is global missio ns for land surface monitor tools across terrain\, vegetation and ice moni toring. The huge terabytes volume of data and non-cloud-optimized format t hwarts the usage and access for the dataset. In the workshop\, we are pres enting an algorithm to reorganize spaceborne lidar and a STAC visualizatio n solution. The functionalities will be demonstrated in Jupyter notebook. covering accessing STAC collections of ICESat-2 and GEDI respectively\, sp atial and temporal lazy-loading from DuckDB\, and data exportation to desi red format. The workshop will be in Python to connect various software API s. DTSTAMP:20260525T005335Z LOCATION:Aula Magna SUMMARY:Accessing Big Satellite LiDAR from Cloud - Yu-Feng Ho URL:https://pretalx.earthmonitor.org/open-earth-monitor-global-workshop-202 5/talk/VGPKKZ/ END:VEVENT END:VCALENDAR