{"schedule": {"version": "0.9", "base_url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/schedule/", "conference": {"acronym": "opengeohub-summer-school-2025", "title": "OpenGeoHub EO-council Summer School 2025", "start": "2025-09-01", "end": "2025-09-06", "daysCount": 6, "timeslot_duration": "00:05", "rooms": [{"name": "HugoTECH", "guid": null, "description": null, "capacity": null}, {"name": "Expert Room 2", "guid": null, "description": null, "capacity": null}, {"name": "Expert Room 3", "guid": null, "description": null, "capacity": null}, {"name": "W-Invite", "guid": null, "description": null, "capacity": null}], "days": [{"index": 1, "date": "2025-09-01", "day_start": "2025-09-01T04:00:00+02:00", "day_end": "2025-09-02T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 372, "guid": "ee2142e0-74a8-51e8-94df-f39615eccf54", "logo": "", "date": "2025-09-01T09:00:00+02:00", "start": "09:00", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-372-plenary-introduction-including-introduction-to-the-hackathons", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/Y9SSP9/", "title": "Plenary introduction, including introduction to the hackathons", "subtitle": "", "track": null, "type": "Tutorials", "language": "en", "abstract": "Plenary introduction Plenary introduction Plenary introduction Plenary introduction Plenary introduction Plenary introduction", "description": "Plenary introduction Plenary introduction Plenary introduction Plenary introduction Plenary introduction Plenary introduction Plenary introduction", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}, {"id": 382, "guid": "46f4a933-c561-520f-97bb-f5ad56c95fac", "logo": "", "date": "2025-09-01T11:00:00+02:00", "start": "11:00", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-382-spatiotemporal-machine-learning-15-practical-lessons-on-how-to-organize-monitoring-modeling-and-updating-of-predictions", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/THLTRJ/", "title": "Spatiotemporal Machine Learning: 15 practical lessons on how to organize monitoring, modeling and updating of predictions", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "Training points (ground observations and measurements of environmental variables) that are referenced in space and time, and are available for longer periods, can be used to build spatiotemporal Machine Learning models (stmlm). Such stmlm's can then be used to generate time-series of predictions, which can then be used to run time-series analysis. Spatiotemporal modeling is different from purely spatial mapping is in the following three aspects: (1) points and covariate layers are matched in spacetime (usually a day or month-year period of ground observations or at least the year of ground observations); (2) covariate layers are based on time-series of usually EO-based images (spatiotemporal data cubes) and include also accumulative indices (e.g. cumulative rainfall, cumulative snow cover, cumulative cropping fraction, and similar) and derivatives; (3) during model training and validation, points are subset in both spacetime to avoid overfitting and bias in predictions. This talk will address 15 practical lessons from running stml including how to organize monitoring networks, how to prevent overfitting, how to derive prediction errors in spacetime, how to use time-series of predictions to detect changes and similar.", "description": "For more details see: https://www.nature.com/articles/s41467-022-32693-3", "recording_license": "", "do_not_record": false, "persons": [{"id": 1, "code": "8QMFTU", "public_name": "Tom Hengl (OpenGeoHub)", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 364, "guid": "42aa7966-e54f-52ab-813d-d4803340aee3", "logo": "", "date": "2025-09-01T11:30:00+02:00", "start": "11:30", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-364-monitoring-global-grassland-and-pasture-areas-an-integrated-approach-based-data-fusion-and-regional-calibration", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/PAUHGU/", "title": "Monitoring global grassland and pasture areas: An integrated approach based data-fusion and regional calibration", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "Global Pasture Watch (GPW) initiative addresses the critical need for monitoring grasslands and pastures, which cover 40% of Earth's surface and are vital for carbon sequestration, food, biodiversity, and cultural heritage.", "description": "GPW is developing four global, consistent, time-series datasets (2000 to 2024+): 30-m grassland class and extent, 30-m short vegetation height, 1-km livestock densities, and 30-m bi-monthly gross primary productivity. These flexible datasets serve as building blocks, enabling local calibration and fusion with other land cover products. For example, the GPW products can be combined into a harmonized map that identifies active grazing areas and pastures with varying management intensities, using global and continental thresholds for grassland classes, livestock densities, heights, and productivity trends, incorporating per-pixel uncertainty information. This approach relies on open data and open-source solutions, making it adaptable for various regional and local contexts. GPW also uses online tools like Geo-Wiki to collect and incorporate user feedback for future product enhancements. All data, including reference samples, are publicly available in cloud-native formats on platforms like Zenodo, STAC, and Google Earth Engine, with the source code accessible on GitHub https://github.com/wri/global-pasture-watch.", "recording_license": "", "do_not_record": false, "persons": [{"id": 40, "code": "K8AZA9", "public_name": "Leandro Parente", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 288, "guid": "b782a7db-8c49-5768-b9dc-12f9328b1e0c", "logo": "", "date": "2025-09-01T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-288-introduction-of-cloud-native-vector-format-hands-on-in-python-environment", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/C9G99Y/", "title": "Introduction of cloud-native vector format: hands-on in Python environment", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "As vector data size increases, the demand of cloud computing is also getting more attention. This lecture aims to tackle the big vector data problem and how to tackle it in the cloud environment. The introduction of cloud-native vector formats such as Flatgeobuf, GeoParquet and PMtile. We will have the hand-on visualization and process the big vector dataset such as ICESat-2 and GEDI. The introduction and hand-on will combine with explanation of Vector \r\nTile and Lazy Loading theories behind.\r\nThe first half is the lecture about the theory and algorithm behind the cloud-native format and spatial indexing. The duration is about 30 minutes. The second half is hands-on using DuckDB, Polars, and other python packages to work with cloud-native format. In addition, we also will go through the parallel processing for big vector data, including parallelization using semaphore for writing in a single big file and partitioning big data into smaller chunks in parallel.\r\n\r\nOther links:\r\nhttps://docs.google.com/presentation/d/1B-Z7PPErQfGBqlhqdBn1tJ0CRov9e2XJWHi_Bio1QwA/edit?usp=drive_link", "description": "The tutorial is co-hosted by Yu-Feng HO and Serkan Isik", "recording_license": "", "do_not_record": false, "persons": [{"id": 176, "code": "9S9G3L", "public_name": "Yu-Feng Ho", "biography": "Research Assistant | Geoinformatician at OpenGeoHub Foundation, focus on big data analysis and processing", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 384, "guid": "e9948319-1348-535c-b611-92c848a2c5c1", "logo": "", "date": "2025-09-01T15:30:00+02:00", "start": "15:30", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-384-hackathon-workshops", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DXWHKG/", "title": "Hackathon workshops", "subtitle": "", "track": "Hackathons", "type": "Hackathon", "language": "en", "abstract": "Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops", "description": "Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops Hackathon workshops", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}], "Expert Room 2": [{"id": 286, "guid": "94b1e302-c3c4-5e3e-8fc4-61d024355c97", "logo": "", "date": "2025-09-01T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-286-automatic-acquisition-and-processing-of-satellite-data-in-r", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/LCUE87/", "title": "Automatic acquisition and processing of satellite data in R", "subtitle": "", "track": "R training", "type": "Tutorials", "language": "en", "abstract": "This practical workshop will introduce participants to the basics of acquiring and processing satellite data using the R programming language, with a focus on the popular `terra` and `rstac` packages.\r\n\r\nThe workshop is designed for beginners with some very basic R knowledge who want to incorporate remote sensing data into their research. Participants will learn how to search, access, and download satellite imagery from various providers through the SpatioTemporal Asset Catalog (STAC) using the `rstac` package and how to handle spatial data using the `terra` package, including reading and writing data, raster processing and visualization techniques.\r\n\r\nThrough hands-on exercises, participants will gain experience working with real satellite datasets and creating efficient and reproducible workflows. Ultimately, the knowledge and skills learned during the workshop will help use these data and processing methods for own research or projects.", "description": "Automatic acquisition and processing of satellite data in R using `rstac` and `terra`\r\n\r\n\r\nOther links:\r\nhttps://drive.google.com/file/d/1wcn3c63moIFeaG0Tnr-Yo-JtoROWWJLD/view?usp=drive_link\r\nhttps://drive.google.com/file/d/1iBylfHF_o-fLXr6LwOautpu08DWJK1an/view?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [{"id": 368, "code": "DRGAKC", "public_name": "Krzysztof Dyba", "biography": "I recently defended my PhD thesis on using machine learning methods to analyze geospatial data. I'm now a senior lecturer at Adam Mickiewicz University in Poznan (Poland). I'm interested in remote sensing (especially in agriculture) and programming in R.", "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 3": [{"id": 304, "guid": "563d26ca-c369-58a0-8a98-bb7cf4e0f64b", "logo": "", "date": "2025-09-01T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-304-introduction-to-grass-gis-as-a-spatial-analysis-engine", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/LBXSVE/", "title": "Introduction to GRASS GIS as a spatial analysis engine", "subtitle": "", "track": null, "type": "Tutorials", "language": "en", "abstract": "Project, Mapset, Region. Types of modules and their documentation. Pipeline programming", "description": "This session provides an overview of GRASS GIS as a spatial analysis engine. The main concepts of the software are introduced with then a more detailed outline of the modules focused on Earth Observation products.\r\nContents:\r\n- Essential GRASS concepts:\r\n  - Project: and Coordinate Reference Systems\r\n  - Mapset: user acces and permissions\r\n  - Zone: the compute area\r\n- GRASS internal data structures:\r\n  - Raster\r\n  - Vector\r\n  - Imagery\r\n- Dataset impot/export, making use of GDAL/OGR\r\n- Processing module families:\r\n  - dataset management\r\n  - processing\r\n  - database management\r\n- The Earth Observation (Imagery) modules", "recording_license": "", "do_not_record": false, "persons": [{"id": 362, "code": "SEAZQV", "public_name": "Lu\u00eds Moreira de Sousa", "biography": "Lu\u00eds Moreira de Sousa completed the Degree on Informatics and Computers\r\nEngineering at the University of Lisbon in 2002, which he complemented with a\r\nMasters on Geographic Information Systems in 2005. In the Department of Civil\r\nEngineering of this university he was a junior researcher from 2002 to 2008,\r\ncontributing to applied research projects with Instituto da \u00c1gua and Estradas\r\nde Portugal. After a year as consultant with SIQuant at the National Laboratory\r\nof Civil Engineering (LNEC), in 2009 he became an independent consultant,\r\nsupporting de development of the spatial data infrastructure of the newly\r\ncreated Administra\u00e7\u00e3o da Regi\u00e3o Hidrogr\u00e1fica do Tejo (ARH-Tejo).\r\n\r\nIn 2011 he joined the Henri Tudor institute in Luxembourg as Research Engineer,\r\nwhere he contributed to the development of Spatial Decision Support Systems on\r\nthe domains of Energy and Urban Planning. At the time he was already a PhD\r\ncandidate on Informatics Engineering at the University of Lisbon, promoted by\r\nProf. Alberto Silva.  In 2016 he concluded this graduation with a thesis on\r\ndomain specific languages for the development of spatial simulation programmes.\r\nStill that year he started a post-doc position at EAWAG (Swiss Federal\r\nInstitute of Research on the Water Domain) during which he conducted research\r\non rapid flood modelling and storm water network management. In 2017 Lu\u00eds\r\njoined ISRIC - World Soil Information in The Netherlands where he conducted\r\nresearch on the geography and ontology of world soils. In July of 2024 Lu\u00eds \r\nreturned to the University of Lisbon, this time as Assistant Professor.", "answers": []}], "links": [], "attachments": [], "answers": []}], "W-Invite": [{"id": 370, "guid": "012c2f37-41f4-5271-becd-0807de31b4cf", "logo": "", "date": "2025-09-01T16:30:00+02:00", "start": "16:30", "duration": "02:00", "room": "W-Invite", "slug": "opengeohub-summer-school-2025-370-research-speed-dating", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/VAVRCX/", "title": "Research speed dating", "subtitle": "", "track": null, "type": "Social Event", "language": "en", "abstract": "Social event Social event Social event Social event Social event Social event", "description": "Social event Social event Social event Social event Social event Social event", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}]}}, {"index": 2, "date": "2025-09-02", "day_start": "2025-09-02T04:00:00+02:00", "day_end": "2025-09-03T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 362, "guid": "5ac49e79-afab-5b2f-b0d5-08ba4ba313f5", "logo": "", "date": "2025-09-02T09:00:00+02:00", "start": "09:00", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-362-learning-from-global-earth-observation-data", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/JE8JLY/", "title": "Learning From Global Earth Observation Data", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "The volume of unlabeled Earth observation (EO) data is huge. To interpret this vast amount of data, efficient modelling approaches are needed that can generalize to large geographic areas and are robust to inherent noise. Data-driven approaches promise great potential for interpreting and combining data from different space missions. In this talk, I will present our work on global canopy height mapping (https://langnico.github.io/globalcanopyheight/) with optical satellite images and sparse spaceborne lidar data and discuss a recent project called MMEarth (https://vishalned.github.io/mmearth/) that explored multi-modal pretext tasks for learning representations that are suitable for a range of downstream tasks with limited training data.", "description": "The volume of unlabeled Earth observation (EO) data is huge. To interpret this vast amount of data, efficient modelling approaches are needed that can generalize to large geographic areas and are robust to inherent noise. Data-driven approaches promise great potential for interpreting and combining data from different space missions. In this talk, I will present our work on global canopy height mapping (https://langnico.github.io/globalcanopyheight/) with optical satellite images and sparse spaceborne lidar data and discuss a recent project called MMEarth (https://vishalned.github.io/mmearth/) that explored multi-modal pretext tasks for learning representations that are suitable for a range of downstream tasks with limited training data.", "recording_license": "", "do_not_record": false, "persons": [{"id": 419, "code": "9PTJVH", "public_name": "Nico Lang", "biography": "Nico is an Assistant Professor at the University of Copenhagen associated with the Global Wetland Centre and the Pioneer Centre for AI. He is also a core member of the Climate AI Nordics network. Before moving to Denmark for a Postdoc, Nico has received a PhD from ETH Zurich. His research focuses on computer vision, machine learning, and remote sensing, and on developing new methods to support environmental sciences. More information can be found on his website: https://langnico.github.io/", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 379, "guid": "5ad8e7c4-3dc8-55f0-9e9a-a4b6ab05e099", "logo": "", "date": "2025-09-02T09:30:00+02:00", "start": "09:30", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-379-cloud-based-analysis-of-earth-observation-data-using-open-source-software", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/BDVFTR/", "title": "Cloud-based analysis of Earth Observation data using open-source software", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "The lecture will address how we analyse Earth Observation data\r\nToday, local or cloud-based, and how we ended up in the current\r\nsituation. It will also address to which extent cloud platforms\r\nare built on open source software, and how the Earth Observation\r\ncommunity can continue working towards a scientific practice that\r\nis sustainable, FAIR, and that complies to open science requirements.", "description": "The lecture will address how we analyse Earth Observation data\r\nToday, local or cloud-based, and how we ended up in the current\r\nsituation. It will also address to which extent cloud platforms\r\nare built on open source software, and how the Earth Observation\r\ncommunity can continue working towards a scientific practice that\r\nis sustainable, FAIR, and that complies to open science requirements.", "recording_license": "", "do_not_record": false, "persons": [{"id": 425, "code": "CKTCDQ", "public_name": "Edzer Pebesma", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 376, "guid": "4f48b90a-7590-55ca-9a69-7b156be4f952", "logo": "", "date": "2025-09-02T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-376-what-does-high-resolution-mean-space-based-spectrometry-for-air-quality-climate", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/8ESEJW/", "title": "What does high resolution mean? Space-based spectrometry for air quality & climate", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "Together we will investigate what \u201chigh resolution\u201d means by working through the specifications of a \u201ctruly\u201d hyperspectral satellite.", "description": "The primary aim is explain the methodology starting at instrument level to illustrate the data chain of how absorption lines result in a better understanding of the distribution and variability of trace gas species relevant to air quality and climate change. A short data interactive module will be presented to tie together the lecture.", "recording_license": "", "do_not_record": false, "persons": [{"id": 424, "code": "ER7ZEG", "public_name": "Deborah C. Stein Zweers", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 380, "guid": "0501b3cf-b4e3-5c46-8b60-e48ce01414e5", "logo": "", "date": "2025-09-02T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-380-raster-and-vector-data-cubes-in-r-and-python", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/ZFRDCW/", "title": "Raster and vector data cubes in R and Python", "subtitle": "", "track": "R training", "type": "Tutorials", "language": "en", "abstract": "The workshop will repeat some theory about what multidimensional\r\narrays are in computer science as well as in R and Python, and\r\ndiscuss how they can be used for solving Earth Observations problems.\r\nIn particular it will discuss the use of arrays for time series\r\ndata, for spatial data (raster maps, stacks of raster maps), for\r\nspatiotemporal data (time series of raster maps or stacks), and for\r\ntime series of feature (point or polygon) data (vector data cubes).\r\nAll will be illustrated by examples in R and Python, in parallel.\r\nExamples will be (mostly) reproducible by participants.", "description": "The workshop will repeat some theory about what multidimensional\r\narrays are in computer science as well as in R and Python, and\r\ndiscuss how they can be used for solving Earth Observations problems.\r\nIn particular it will discuss the use of arrays for time series\r\ndata, for spatial data (raster maps, stacks of raster maps), for\r\nspatiotemporal data (time series of raster maps or stacks), and for\r\ntime series of feature (point or polygon) data (vector data cubes).\r\nAll will be illustrated by examples in R and Python, in parallel.\r\nExamples will be (mostly) reproducible by participants.", "recording_license": "", "do_not_record": false, "persons": [{"id": 425, "code": "CKTCDQ", "public_name": "Edzer Pebesma", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 305, "guid": "5731b18b-d10d-5276-ba71-df73f909905f", "logo": "", "date": "2025-09-02T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-305-grass-gis-automation-for-earth-observation-with-python-r-and-julia", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/8A3E7Z/", "title": "GRASS GIS automation for Earth Observation with Python, R and Julia", "subtitle": "", "track": "Julia", "type": "Tutorials", "language": "en", "abstract": "Scripting with GRASS: Bash, R, Python, Julia (?), matching students\u2019 preferences and EO theme", "description": "This session is mean for students with a basic understanding of GRASS, its underlying concepts and data strucutres. In a mostly hands-on exercise, students will be automating several Earth Observation taks from a programming environment of their choice: Bash, Python, R, Julia (?).\r\nContents:\r\n- The GRASS environment\r\n- Internal and external datasets\r\n- Access to Imagery catalogues\r\n- Using GRASS GIS modules with:\r\n  - Python\r\n  - R\r\n  - Bash\r\n  - Julia (?)\r\n\r\nOther links:\r\nhttps://drive.google.com/file/d/1f43r-dC3Q3PYbQTyePhBUzMZWLu_cAJu/view?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [{"id": 362, "code": "SEAZQV", "public_name": "Lu\u00eds Moreira de Sousa", "biography": "Lu\u00eds Moreira de Sousa completed the Degree on Informatics and Computers\r\nEngineering at the University of Lisbon in 2002, which he complemented with a\r\nMasters on Geographic Information Systems in 2005. In the Department of Civil\r\nEngineering of this university he was a junior researcher from 2002 to 2008,\r\ncontributing to applied research projects with Instituto da \u00c1gua and Estradas\r\nde Portugal. After a year as consultant with SIQuant at the National Laboratory\r\nof Civil Engineering (LNEC), in 2009 he became an independent consultant,\r\nsupporting de development of the spatial data infrastructure of the newly\r\ncreated Administra\u00e7\u00e3o da Regi\u00e3o Hidrogr\u00e1fica do Tejo (ARH-Tejo).\r\n\r\nIn 2011 he joined the Henri Tudor institute in Luxembourg as Research Engineer,\r\nwhere he contributed to the development of Spatial Decision Support Systems on\r\nthe domains of Energy and Urban Planning. At the time he was already a PhD\r\ncandidate on Informatics Engineering at the University of Lisbon, promoted by\r\nProf. Alberto Silva.  In 2016 he concluded this graduation with a thesis on\r\ndomain specific languages for the development of spatial simulation programmes.\r\nStill that year he started a post-doc position at EAWAG (Swiss Federal\r\nInstitute of Research on the Water Domain) during which he conducted research\r\non rapid flood modelling and storm water network management. In 2017 Lu\u00eds\r\njoined ISRIC - World Soil Information in The Netherlands where he conducted\r\nresearch on the geography and ontology of world soils. In July of 2024 Lu\u00eds \r\nreturned to the University of Lisbon, this time as Assistant Professor.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 371, "guid": "8b79a493-8c35-5e5e-8a44-af40d8641171", "logo": "", "date": "2025-09-02T17:00:00+02:00", "start": "17:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-371-hackathon-consultation", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/XQYRQW/", "title": "Hackathon Consultation", "subtitle": "", "track": null, "type": "Hackathon", "language": "en", "abstract": "Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation", "description": "Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation Hackathon Consultation", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}], "Expert Room 2": [{"id": 307, "guid": "6145b870-790f-5de4-9e57-382838980e28", "logo": "", "date": "2025-09-02T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-307-overview-of-passive-optical-instruments-for-earth-observation", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/RELHCA/", "title": "Overview of passive optical instruments for earth observation", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "In this lecture, an overview of the different types of passive optical instruments for earth observation is given. Their limitations are outlined, and possible future development paths of such instruments are discussed.", "description": "Passive optical instruments on satellites such as spectrometers and radiometers detect sunlight reflected from the earth. They allow us to measure land and atmospheric properties for applications such as agriculture and climate science.  In this lecture, at first the most prevalent types of such instruments are introduced, such as for example spectral band-pass imagers and grating spectrometers. Some of the design trade-offs and performance limitations are discussed, and possible sources of errors in available earth observation data are outlined. After that, more innovative instrument designs from the recent time are introduced. The lecture will finish with a speculation on the future of passive optical instruments for earth observation, which will likely see a deeper integration of instrument design and data science in the future.", "recording_license": "", "do_not_record": false, "persons": [{"id": 379, "code": "MMJGML", "public_name": "Ralf Kohlhaas", "biography": "Head of the OptX section at SRON Space Research Organization Netherlands, touching in this role on optical design, performance and calibration engineering, and management of optical research activities.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 295, "guid": "161d03d4-68b6-59a9-8ea0-a60bcabc70c8", "logo": "/media/opengeohub-summer-school-2025/submissions/EWFPYV/gee_sticker_150px_p6uvB5m.png", "date": "2025-09-02T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-295-crash-course-on-google-earth-engine-api", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/EWFPYV/", "title": "Crash Course on Google Earth Engine API", "subtitle": "", "track": "Javascript", "type": "Tutorials", "language": "en", "abstract": "This tutorial introduces the Google Earth Engine (GEE) API. Participants will learn to filter, process, and export images, extract insights from temporal data, and export results using the API.", "description": "GEE is a cloud-based platform for geospatial analysis. GEE provides an API (application programming interface) for image collection manipulation, time series processing, and spatial data transformations. JavaScript is the primary scripting language in the GEE Code Editor, allowing users to directly interact with the API for advanced workflows.\r\n\r\nThis course covers coding techniques for transforming image collections and analyzing time series. It starts with API interactions, including loading and visualizing satellite imagery. Then, it moves to collection transformations, where participants filter datasets, compute statistical reductions, and generate composites. Next, it covers time series analysis, allowing participants to extract trends and plot variations. Finally, the session covers exporting results for further use.\r\n\r\nBy the end, participants will develop a structured approach to writing JavaScript scripts in GEE. They will understand how the API enables geoprocessing workflows. This course is for researchers and GIS professionals looking to use cloud computing for geospatial analysis. It focuses on practical applications and offers hands-on experience with the entire process.\r\n\r\nOther links:\r\nhttps://docs.google.com/presentation/d/1zCIssZLp7ckRakl5HosKLYy5OGlk-FZHKtWptF3IrPg/edit?usp=sharing", "recording_license": "", "do_not_record": false, "persons": [{"id": 247, "code": "FWUSQK", "public_name": "Mustafa Serkan Isik", "biography": "Mustafa Serkan Isik is a post-doctoral researcher at the OpenGeoHub Foundation, focusing on time-series analysis of Earth Observation data and space-time modelling. He holds a PhD in Geomatics and has a background in geodesy and remote sensing.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 313, "guid": "ee25b684-1d58-5e9f-ad69-82460f8b4f68", "logo": "", "date": "2025-09-02T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-313-monitoring-eo-workflows-with-precision-for-better-performance-and-resource-utilization", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/PXMTDT/", "title": "Monitoring EO workflows with precision for better performance and resource utilization", "subtitle": "", "track": null, "type": "Tutorials", "language": "en", "abstract": "The tutorial will guide participants on effectively monitoring and benchmarking their analysis workflows in a reliable and reproducible way, enabling them to identify performance bottlenecks and explore potential solutions.\r\n\r\nOther links:\r\nhttps://doi.org/10.5281/zenodo.17036542\r\nhttps://data.crib.utwente.nl/geobench/demo.zip", "description": "I will provide a tutorial. The tutorial title is: \"Monitoring Earth Observation workflows with precision for better performance and resource utilization.\" The tutorial will guide participants on effectively monitoring and benchmarking their analysis workflows in a reliable and reproducible way, enabling them to identify performance bottlenecks and explore potential solutions.\r\n\r\nOther links:\r\nhttps://drive.google.com/file/d/1FeANLwwcY5ALd9Hi_9uwkcCYfPPUw6of/view?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [{"id": 390, "code": "AAQJT3", "public_name": "Serkan Girgin", "biography": "Dr. Serkan Girgin is an Associate Professor in the Geo-information Processing Department at the Faculty of Geo-information Science and Earth Observation (ITC), University of Twente. He has established and is currently leading ITC's Center of Expertise in Big Geodata Science (CRIB), a facility dedicated to advancing geospatial big data and cloud computing technologies by developing and sharing operational expertise.  Dr. Girgin's research focuses on big data and cloud computing tools and infrastructures, with a particular emphasis on optimizing the performance and energy efficiency of geocomputing workflows. He also designs and develops tools and platforms that promote best practices in research software development and research data management, including fairly toolset, Open Data Explorer, and OpenSTAC. With over 30 years of experience in software development, his expertise spans geocomputing platforms, GIS and remote sensing applications, environmental information systems, and large-scale web applications.", "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 3": [{"id": 287, "guid": "af6c7534-f214-5d58-8a04-73dc5f6d144c", "logo": "/media/opengeohub-summer-school-2025/submissions/JWWLJK/sits_sticker_150px_OBXNql8.png", "date": "2025-09-02T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-287-land-use-and-land-cover-classification-with-satellite-image-time-series-in-r", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/JWWLJK/", "title": "Land Use and Land Cover Classification with Satellite Image Time Series in R", "subtitle": "", "track": "R training", "type": "Tutorials", "language": "en", "abstract": "This tutorial introduces `sits`, an R package for Land use and land cover (LULC) classification using satellite image time series.", "description": "LULC classification are essential for environmental monitoring, agriculture, and climate change analysis. LULC maps provide key data for decision-making. `sits` offers an integrated framework to generate data cubes and classify satellite image time series. It provides an end-to-end solution integrating data management, machine learning, and validation.\r\n\r\nThe course covers the full LULC classification workflow. It starts with building data cubes and organizing satellite images in a structured way. Then, it moves to extracting and preparing time series samples. Next, participants train machine learning models to recognize LULC patterns. After that, they classify new satellite data using trained models. Finally, they validate results by assessing classification accuracy.\r\n\r\nThis course is for remote sensing experts, GIS professionals, and students interested in using machine learning for LULC analysis. It focuses on practical applications and offers hands-on experience with the entire process.", "recording_license": "", "do_not_record": false, "persons": [{"id": 368, "code": "DRGAKC", "public_name": "Krzysztof Dyba", "biography": "I recently defended my PhD thesis on using machine learning methods to analyze geospatial data. I'm now a senior lecturer at Adam Mickiewicz University in Poznan (Poland). I'm interested in remote sensing (especially in agriculture) and programming in R.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 289, "guid": "62307396-8766-5ebc-a1bb-50df7c291d80", "logo": "", "date": "2025-09-02T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-289-geomorphometry-high-performance-computing-using-grass-gis-and-whitboxtools-in-python", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/FGVXKV/", "title": "Geomorphometry: high-performance computing using GRASS GIS, and WhitboxTools in Python", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "Digital Elevation Model provides knowledge of topography, hydrology, geomorphology. Geomorphometry is a domain to extract the land surface parameters from DEMs. This tutorial introduces leveraging the state-of-art geo-processing softwares to create spatial information from DEMs.", "description": "The tutorial starts with the introduction of DEMs and provides a first fully opened ~30m digital terrain model as the material. A single COG DTM would be provided and the code to crop the small area of interest. Aftermath, we will run the geo-processing from GRASS and WhiteboxTools. \r\n\r\nThe first part is local land surface parameters such as slope, hillshade, and northerness, etc. Equi7 projection system is implemented to create accurate parameters.\r\n\r\nThe second part is regional surface parameters. We focus on running topographic wetness index, which involves generating specific catchment area and slope. The border effect would be introduced and we  introduce the overlapping technique.\r\n\r\nLast but not least, we would provide the 15 land surface parameters of the world in COG for comparison with the generated result.\r\n\r\nOther links:\r\nhttps://docs.google.com/presentation/d/1xNoDH3HRkFhm7laYPmtit6j3fuPrEuAJoUnLoczcGC8/edit?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [{"id": 176, "code": "9S9G3L", "public_name": "Yu-Feng Ho", "biography": "Research Assistant | Geoinformatician at OpenGeoHub Foundation, focus on big data analysis and processing", "answers": []}, {"id": 247, "code": "FWUSQK", "public_name": "Mustafa Serkan Isik", "biography": "Mustafa Serkan Isik is a post-doctoral researcher at the OpenGeoHub Foundation, focusing on time-series analysis of Earth Observation data and space-time modelling. He holds a PhD in Geomatics and has a background in geodesy and remote sensing.", "answers": []}], "links": [], "attachments": [], "answers": []}]}}, {"index": 3, "date": "2025-09-03", "day_start": "2025-09-03T04:00:00+02:00", "day_end": "2025-09-04T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 366, "guid": "aa9d31b4-df37-5b9f-8473-7bfc237eef04", "logo": "", "date": "2025-09-03T09:00:00+02:00", "start": "09:00", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-366-introduction-to-the-eo-council", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/BUPMPE/", "title": "Introduction to the EO Council", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "Overview of earth observation activities in the Netherlands, focusing on solid earth and deformation", "description": "Netherlands hosts a range of earth observation activities, and it is difficult for industry, government, students to find their way. There was a need to cooperate more and the Earth Observation Council was formed with representatives from different disciplines and organizations in the Netherlands. We aim to contribute to education through a separate summer school in the future. \r\nThis presentation will show some of the earth observation activities in the Netherlands. the focus will be on Solid Earth, Ocean and Land surface; Atmosphere and Cryosphere have a separate lecture later in the summer school.", "recording_license": "", "do_not_record": false, "persons": [{"id": 366, "code": "CWUZZU", "public_name": "Wouter van der Wal", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 367, "guid": "f8ee7002-366c-5d8c-a847-6346b974f5c2", "logo": "", "date": "2025-09-03T09:30:00+02:00", "start": "09:30", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-367-introduction-to-surf", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/NCL9GY/", "title": "Introduction to SURF", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided", "description": "To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided", "recording_license": "", "do_not_record": false, "persons": [{"id": 421, "code": "ZXEEC3", "public_name": "Haili Hu", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 368, "guid": "028e94ca-c613-53a5-a2ee-a8b6f7be7286", "logo": "", "date": "2025-09-03T10:00:00+02:00", "start": "10:00", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-368-introduction-to-nso", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/FF88PV/", "title": "Introduction to NSO", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided", "description": "To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided To be provided", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}, {"id": 312, "guid": "35812b6b-ac97-5b49-8375-73f5fd9b442a", "logo": "", "date": "2025-09-03T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-312-data-use-in-remote-sensing-of-the-atmosphere", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/RF8TPX/", "title": "Data use in remote sensing of the atmosphere", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "This lecture discusses the use of models and data processing methods for efficient use of large volumes of satellite data, with application to atmospheric remote sensing. The lecture will come with exercises to gain hands-on experience using some of the techniques that are discussed.", "description": "With advancing satellite technology enabling improvements in spatial, temporal, and spectral resolution of every new missions that is launched, the data rate is rapidly increasing also. This calls for computationally efficient methods for processing the data that come down, preferably in near real time. The focus of this lecture is on the final steps in the data processing chain, where large volumes of data our combined using models to extract and interpret the most useful information in the data. We'll discuss data assimilation and inverse modeling methods that are used, for example, in weather forecasting and the estimation of air pollutant and greenhouse gas emissions. \r\nRecently, the toolbox is being enriched with machine learning methods that are starting to outcompete some of the conventional methods, not only in processing speed but even in forecasting skill. The lecture will come with tutorials offering the opportunity to gain hands-on experience with some of these techniques.\r\n\r\nOther links:\r\nhttps://docs.google.com/presentation/d/1hah19DnS-ivigQhh1PpsVdYE2Rxwdw4F/edit?usp=drive_link&ouid=102861749140673074260&rtpof=true&sd=true", "recording_license": "", "do_not_record": false, "persons": [{"id": 385, "code": "PPX3BC", "public_name": "Sander Houweling", "biography": "Sander Houweling is professor in Atmosphere, Greenhouse Gases, and Climate of the Earth Sciences department of the Vrije Universiteit Amsterdam and affiliated also with NWO-i SRON Netherlands Institute for Space Research. His research focuses on the global cycles of long-lived greenhouse gases in the atmosphere and climate impacts of human activities. His research group at the Vrije Universiteit develops methods for estimating greenhouse gas emissions from atmospheric measurements using inverse modeling techniques at global, regional, and local scale.  As member of the scientific steering committee of the Integrated Global Greenhouse Gas Information System (IG3IS) of the World Meteorological Organization (WMO) he is committed to independent evaluation of national greenhouse gas emission reports to the United Nations Convention on Climate Change (UNFCCC) using atmospheric measurements.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 283, "guid": "7eccb873-7115-57bf-abc5-0c0acc69fcf4", "logo": "", "date": "2025-09-03T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-283-space-time-mapping-at-30-m-resolution-based-on-landsat-arco-data-hands-on-for-real-case-applications-python-", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/GDNV9D/", "title": "Space-time mapping at 30 m resolution based on Landsat ARCO data: hands-on for real case applications (python)", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "This tutorial will offer a practical, step-by-step guide on accessing and using Landsat ARCO data for space-time mapping. Participants will work with real data to generate 30-meter resolution maps of the Netherlands from 2000 to 2024. The session will cover the entire workflow, including data acquisition, preprocessing, spatial and temporal analysis, and visualization. All code will be based on the Scikit-map library.\r\n\r\nThe workshop is designed to be interactive, with participants using either Google Colab or Docker containers to follow along. Key topics will include retrieving Landsat ARCO data, handling large-scale remote sensing datasets, applying spatial and temporal filters, and analyzing changes in land cover over time. The focus will be on implementing a reproducible workflow that can be adapted for similar projects.\r\n\r\nThis session is intended for participants with some experience in remote sensing or geospatial analysis. Prior knowledge of Python and GIS tools will be useful but not strictly required. Throughout the session, there will be opportunities for discussion and troubleshooting. By the end of the workshop, participants will have a working pipeline for generating and interpreting time-series maps from Landsat ARCO data. All provided input data will also be openly available at global scale for large scale applications.", "description": "This tutorial will offer a practical, step-by-step guide on accessing and using Landsat ARCO data for space-time mapping. Participants will work with real data to generate 30-meter resolution maps of the Netherlands from 2000 to 2024. The session will cover the entire workflow, including data acquisition, preprocessing, spatial and temporal analysis, and visualization. All code will be based on the Scikit-map library.\r\n\r\nThe workshop is designed to be interactive, with participants using either Google Colab or Docker containers to follow along. Key topics will include retrieving Landsat ARCO data, handling large-scale remote sensing datasets, applying spatial and temporal filters, and analyzing changes in land cover over time. The focus will be on implementing a reproducible workflow that can be adapted for similar projects.\r\n\r\nThis session is intended for participants with some experience in remote sensing or geospatial analysis. Prior knowledge of Python and GIS tools will be useful but not strictly required. Throughout the session, there will be opportunities for discussion and troubleshooting. By the end of the workshop, participants will have a working pipeline for generating and interpreting time-series maps from Landsat ARCO data. All provided input data will also be openly available at global scale for large scale applications.", "recording_license": "", "do_not_record": true, "persons": [{"id": 181, "code": "XXHGN8", "public_name": "Davide Consoli", "biography": "Post-doctoral researcher at OpenGeoHub Foundation. Working cross-projects to large scale space-time mapping with high-throughput computing.", "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 2": [{"id": 311, "guid": "a503892e-14a1-578c-9b74-13ee67d69d0f", "logo": "", "date": "2025-09-03T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-311-discrete-global-grid-systems-awareness-raising-about-the-future-of-gis", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/FD3Z9H/", "title": "Discrete Global Grid Systems - Awareness raising about the future of GIS", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "This introduction talk will introduce advantages, technical challenges and currently available softwares.", "description": "A Conventional Coordinate Reference System (CRS) represents the Earth's surface as a continuous field of points for navigation and geometry, but this approach is less suitable to relate point observations to larger areas. In contrast, a Discrete Global Grid System (DGGS) partitions the planet into a hierarchical grid of discrete cells, optimizing data integration, processing, and analysis by using fixed spatial units instead of continuous coordinates.\r\n\r\nWhile potentially more effective for GIS applications, DGGS are not yet commonly used. However, several initiatives are trying to create standards and softwares that will enable the transition. This introduction talk will introduce advantages, technical challenges and currently available softwares.", "recording_license": "", "do_not_record": false, "persons": [{"id": 181, "code": "XXHGN8", "public_name": "Davide Consoli", "biography": "Post-doctoral researcher at OpenGeoHub Foundation. Working cross-projects to large scale space-time mapping with high-throughput computing.", "answers": []}, {"id": 362, "code": "SEAZQV", "public_name": "Lu\u00eds Moreira de Sousa", "biography": "Lu\u00eds Moreira de Sousa completed the Degree on Informatics and Computers\r\nEngineering at the University of Lisbon in 2002, which he complemented with a\r\nMasters on Geographic Information Systems in 2005. In the Department of Civil\r\nEngineering of this university he was a junior researcher from 2002 to 2008,\r\ncontributing to applied research projects with Instituto da \u00c1gua and Estradas\r\nde Portugal. After a year as consultant with SIQuant at the National Laboratory\r\nof Civil Engineering (LNEC), in 2009 he became an independent consultant,\r\nsupporting de development of the spatial data infrastructure of the newly\r\ncreated Administra\u00e7\u00e3o da Regi\u00e3o Hidrogr\u00e1fica do Tejo (ARH-Tejo).\r\n\r\nIn 2011 he joined the Henri Tudor institute in Luxembourg as Research Engineer,\r\nwhere he contributed to the development of Spatial Decision Support Systems on\r\nthe domains of Energy and Urban Planning. At the time he was already a PhD\r\ncandidate on Informatics Engineering at the University of Lisbon, promoted by\r\nProf. Alberto Silva.  In 2016 he concluded this graduation with a thesis on\r\ndomain specific languages for the development of spatial simulation programmes.\r\nStill that year he started a post-doc position at EAWAG (Swiss Federal\r\nInstitute of Research on the Water Domain) during which he conducted research\r\non rapid flood modelling and storm water network management. In 2017 Lu\u00eds\r\njoined ISRIC - World Soil Information in The Netherlands where he conducted\r\nresearch on the geography and ontology of world soils. In July of 2024 Lu\u00eds \r\nreturned to the University of Lisbon, this time as Assistant Professor.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 310, "guid": "8d727f7e-e688-5669-8cf6-577b8be041c5", "logo": "", "date": "2025-09-03T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-310-high-performance-computing-with-pyhton-rs-dat", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/9TLLZZ/", "title": "High performance computing with Pyhton/RS-DAT", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "This summer school session will introduce participants to a Python/Dask-based ecosystem, familiarizing them with the use of the Remote Sensing Deployable Analysis environmenT (RS-DAT) framework to scale EO and RS data analysis using HTC/HPC systems and associated storage resources. The session will cover the tools for data access, retrieval and storage, and demonstrate the scaling up of processing and analysis workflows focused on EO data-sets.", "description": "Data volumes are increasing across the natural and engineering sciences, with this being particularly relevant in the context of remote-sensing (RO) and Earth observation (EO) data, which have become a mainstay in fields ranging from the geosciences to \u2018green\u2019 life sciences, agriculture, and even social sciences, as well as an invaluable tool in defining policy. \r\n\r\nAlthough a community driven software ecosystem has evolved to support exploitation of these data, existing and future workflows often must be scaled up beyond the computational and storage resources available in workstations, taxing the tooling available and presenting a challenge to the use of these data.\r\n\r\nIn this regard, solutions using high-throughput and high-performance computing (HTC/HPC) systems, as an additional alternative to cloud-based solutions, are of particular relevance for the academic community. Offering full control over available hardware, software, and data, these systems are excellently suited to highly-customized academic workflows and can readily support the migration of existing workflows. Furthermore, they are generally available through national infrastructure providers on a merit-driven no-cost basis. \r\n\r\nThis summer school session will introduce participants to a Python/Dask-based ecosystem, familiarizing them with the use of the Remote Sensing Deployable Analysis environmenT (RS-DAT) framework to scale EO and RS data analysis using HTC/HPC systems and associated storage resources. The session will cover the tools for data access, retrieval and storage, and demonstrate the scaling up of processing and analysis workflows focused on EO data-sets.", "recording_license": "", "do_not_record": false, "persons": [{"id": 384, "code": "XWVGYL", "public_name": "Meiert Willem Grootes", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 3": [{"id": 297, "guid": "8183eb48-72d4-564c-b611-be08dc9b7e05", "logo": "/media/opengeohub-summer-school-2025/submissions/9G333N/pace_rotator_emblem_800w_800h-3_7YAz1YH.jpg", "date": "2025-09-03T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-297-processing-pace-data-with-python-get-a-polarized-hyperspectral-view-of-the-earth", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/9G333N/", "title": "Processing PACE data with Python: get a polarized hyperspectral view of the Earth", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "This tutorial lets you dive into the world of data from PACE, NASA's Plankton, Aerosol, Clouds and ocean Ecosystem mission using Python notebooks with a focus on SPEXone.", "description": "PACE, the NASA Plankton, Aerosol, Clouds and ocean Ecosystem satellite was launched in February 2024 and carries three scientific instruments. The Ocean Color Instrument takes hyperspectral data at a 1 km x 1 km resolution and 2-day global coverage with very high radiometric accuracy. The two multiangle polarimeters, HARP2 and SPEXone, yield polarized data at a 5 km x 5 km resolution. HARP2 has 10-60 viewing angles at 4 spectral bands, while SPEXone (developed in the Netherlands) takes hyperspectral data at 5 viewing angles. Together, these instruments generate an unprecedented dataset that enables the characterization of ocean, land, clouds and the atmosphere.\r\n\r\nThis tutorial aims to give the audience a jump-start into using data from the PACE mission using Python notebooks. We will explore Level-1 data (calibrated radiometry and multi-angle polarimetry) to create (hyperspectral) images of the Earth and look at Level-2 data and beyond in order to view higher level geophysical products, such as maps of atmospheric properties (e.g. aerosol and clouds), oceanic properties (e.g. phytoplankton), and land (e.g. vegetation).\r\n\r\nRequired background knowledge: some proficiency in Python and experience running Jupyter notebooks.\r\nIt is advised to setup your python environment prior to the workshop in orde to not loose valuable time.\r\n\r\nTutorial link: https://drive.google.com/drive/folders/1lg__rXY6ukO7u0L4StkEX2gG53n4wPOX", "recording_license": "", "do_not_record": false, "persons": [{"id": 372, "code": "DMZYEM", "public_name": "Jeroen Rietjens", "biography": "Jeroen Rietjens is a Senior Instrument Scientist at SRON Space Research Organisation Netherlands. He is the SPEXone Product Development Lead for the NASA PACE mission and in this role responsible for instrument operations. He is also the Lead Performance Engineer for SPEXone and thereby responsible for the data quality. Via this role he has been involved in almost every aspect of the SPEXone signal chain, from hardware design and procurement to calibration and data processing.", "answers": []}, {"id": 373, "code": "EKNYES", "public_name": "Laura van der Schaaf", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}], "W-Invite": [{"id": 369, "guid": "55e66baa-292a-5174-8d33-a6d6d28aba02", "logo": "", "date": "2025-09-03T15:30:00+02:00", "start": "15:30", "duration": "02:00", "room": "W-Invite", "slug": "opengeohub-summer-school-2025-369-nso-companies-fair-networking-borrel", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/YM3HPE/", "title": "NSO Companies Fair + Networking borrel", "subtitle": "", "track": null, "type": "Social Event", "language": "en", "abstract": "Social event Social event Social event Social event Social event Social event", "description": "Social event Social event Social event Social event Social event Social event\r\n\r\nCompanies presentations: https://drive.google.com/drive/folders/1eCPN0qmIyh-4NcKYTU6B4ECJ8hlel8KC?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}]}}, {"index": 4, "date": "2025-09-04", "day_start": "2025-09-04T04:00:00+02:00", "day_end": "2025-09-05T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 386, "guid": "c4d8757c-b794-5b62-956c-61c99c9d20a0", "logo": "", "date": "2025-09-04T09:00:00+02:00", "start": "09:00", "duration": "00:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-386-introduction-to-openeo-within-the-copernicus-data-space-ecosystem", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/XKNKGR/", "title": "Introduction to openEO within the Copernicus Data Space Ecosystem", "subtitle": "", "track": "Theoretical sessions", "type": "Keynote", "language": "en", "abstract": "Traditionally way to process Earth Observation (EO) data could be complex and time-consuming, requiring users to discover, download, and pre-process large datasets locally.", "description": "Consequently, cloud-based processing platforms have emerged as a popular and standard solution. The Copernicus Data Space Ecosystem offers the openEO API as one such solution for seamless access and efficient analysis of Copernicus EO data on a cloud infrastructure.\r\n\r\nOpenEO is a community-driven standard that simplifies geospatial data access, processing, and analysis by offering a unified platform. It allows developers, researchers, and data scientists to use cloud-based resources and distributed computing environments to tackle complex geospatial challenges. By following FAIR principles (Findable, Accessible, Interoperable, and Reusable), openEO supports the global sharing and reuse of algorithms, enhancing collaboration and scalability.\r\n\r\nOther links:\r\nhttps://drive.google.com/file/d/1dNQM4vx55UHKPVpi-ErB6cDCZQ_XjU2G/view?usp=drive_link\r\nhttps://docs.google.com/presentation/d/1DPDmfqkY6tSXJo5OWWPffGZaPkiD0mAB/edit?usp=drive_link&ouid=102861749140673074260&rtpof=true&sd=true", "recording_license": "", "do_not_record": false, "persons": [{"id": 400, "code": "ZWLPJE", "public_name": "Pratichhya Sharma", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 282, "guid": "bb079f5e-59e8-5238-863d-28751727bb72", "logo": "", "date": "2025-09-04T09:30:00+02:00", "start": "09:30", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-282-observing-earth-system-dynamics-on-weather-and-climate-scales", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DMJANT/", "title": "Observing earth system dynamics on weather and climate scales", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "Clearly, climate change produces more extreme weather and associated ocean anomalies, hence calling for 1) improved weather advisories in the future for loss reduction and 2) for climate projections for adaptation. A better understanding of earth system dynamics may provide benefits in both areas. Earth-orbiting satellites have this century been proven indispensible for monitoring the earth system, both for tracking the weather and for understanding earth system processes. The value of satellite observations is being further exploited by novel future satellite missions.  An overview of needs and EO systems will be provided. Winds determine weather, hurricanes, waves and surges, energy production, ocean forcing, heat and carbon budgets, sea ice decline, climate change, andsoforth. Hence, satellite winds are extensively used by marine forecasters, in NWP, by oceanographers, wind engineers, off-shore industry, safety authorities and climate scientists alike. More dynamical information is becoming available due to new and extending virtual constellations of satellite wind-sensing instruments. This new information is hence beneficial for above-mentioned applications. However, it is clear that a remaining gap in the understanding of earth system dynamics remains in the intricate coupling between the atmosphere and the ocean and in the presentation this aspect will also be further elaborated. As an example of the interplay between different professional disicplines, a furthermore interesting and related topic is how to measure and monitor winds in hurricanes?", "description": "- Earth system modelling of dynamics;\r\n- The dynamics and the scales of the ocean and the atmosphere; \r\n- The interactions at different scales;\r\n- Different variables and processes;\r\n- How to effectively measure dynamics for model initialization and for parameterized processes;\r\n- Data assimilation; how to relate models and observations?\r\n- What to measure?\r\n- Data science", "recording_license": "", "do_not_record": true, "persons": [{"id": 360, "code": "KQ9ME9", "public_name": "Ad Stoffelen", "biography": "My career is dedicated to all aspects of satellite wind measurements. From new concepts, cal/val, wind retrieval optimization, operational production to applications and training in weather nowcasting. It involves data science, machine learning, NWP data assimilation, climate data records, ocean forcing, marine boundary layer and air-sea interaction research. I'm now leading a group on active remote sensing from satellites using radar and lidar for ocean winds, clouds and aerosol, and involved in the ESA Aeolus, EarthCare and HARMONY missions and participating in the EUMETSAT and Copernicus ground segment services. I am an IEEE fellow (http://www.ieee.org/) and my publications are on Google Scholar, ResearchGate and Orcid. You can also find some material on YouTube.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 377, "guid": "4eb415bb-fb2c-5579-a948-8ba0269517dc", "logo": "", "date": "2025-09-04T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-377-discussion-panel-how-to-build-an-open-decentralized-eo-fediverse-", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DQANYK/", "title": "Discussion panel: How to build an open decentralized EO fediverse?", "subtitle": "", "track": null, "type": "Theoretical lectures", "language": "en", "abstract": "Discussion panel: How to build an open decentralized EO fediverse? Discussion panel: How to build an open decentralized EO fediverse?", "description": "Discussion panel: How to build an open decentralized EO fediverse? Discussion panel: How to build an open decentralized EO fediverse? Discussion panel: How to build an open decentralized EO fediverse? Discussion panel: How to build an open decentralized EO fediverse? Discussion panel: How to build an open decentralized EO fediverse?\r\n\r\nhttps://docs.google.com/presentation/d/19UDgFDm-kxDA6hj6CS0r15RNgXV4QV67SJKgLOFGJ8M/edit?usp=sharing", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}, {"id": 318, "guid": "b21f7017-d53e-5a57-ad96-1c09fa294630", "logo": "", "date": "2025-09-04T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-318-build-advanced-eo-workflows-with-custom-functions-in-openeo-within-the-copernicus-data-space-ecosystem", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/8YHQU9/", "title": "Build Advanced EO Workflows with Custom Functions in openEO within the Copernicus Data Space Ecosystem", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "In the Earth Observation (EO) domain, data analysis ranges from simple image processing tasks like dilation to complex workflows involving Machine Learning (ML) and Deep Learning (DL). While openEO provides numerous features and functions for data analysis, but given the broad scope of the field, not all potential needs are covered out of the box. To address this, openEO supports User-Defined Functions (UDFs). These UDFs are implemented as standard Python scripts using libraries such as Xarray or Numpy. They allow users to implement custom workflows tailored to specific research requirements.\r\n\r\nThus, in this course, we offer a high-level introduction to openEO with a focus on UDFs and include an example of an advanced EO workflow that applies this concept in practice.", "description": "The only requirement for the participants would be:\r\n\r\n- Basic understanding of Earth Observation data\r\n- Basic knowledge of Python\r\n- An account in the Copernicus Data Space Ecosystem\r\n \r\nWe will use the Jupyter Environment offered by the ecosystem.\r\n\r\nFor users already familiar with these, they can already explore examples available here: https://github.com/Open-EO/openeo-community-examples/tree/main/python\r\n\r\nOther links:\r\nCDSE: https://dataspace.copernicus.eu/\r\nCDSE documentation: https://documentation.dataspace.copernicus.eu/#/\r\nopenEO community examples: https://github.com/Open-EO/openeo-community-examples/tree/main/python\r\nMOOC on cubes and cloud: https://eo-college.org/courses/cubes-and-clouds/\r\nExample on openEO load_stac: https://github.com/Open-EO/openeo-community-examples/tree/main/python/LoadStac\r\nAPEx algorithm catalogue: https://algorithm-catalogue.apex.esa.int/\r\nopenEO algorithm plaza: https://marketplace-portal.dataspace.copernicus.eu/", "recording_license": "", "do_not_record": false, "persons": [{"id": 400, "code": "ZWLPJE", "public_name": "Pratichhya Sharma", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 365, "guid": "a5bc74cd-ffb6-5abb-9c92-bc6cd4d2d425", "logo": "", "date": "2025-09-04T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-365-automl-automating-machine-learning-applied-to-areal-regression-modeling", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/MTHQXF/", "title": "AutoML: Automating machine learning applied to areal regression modeling", "subtitle": "", "track": "Theoretical sessions", "type": "Tutorials", "language": "en", "abstract": "In this tutorial, an AutoML framework (EvalML) will be used for modeling livestock density at polygon level (areal regression) and produce spatial predictions at pixel level.", "description": "A compilation of subnational livestock census data will be used to retrieve the headcount information, while the grazing areas will be estimated based on GPW grassland class and extent. You will learn how to run benchmark, feature selection and hyper-parameter tuning for several modeling pipelines, as well as evaluate the model performance using robust spatial cross-validation. The final modeling output will be spatial layer with livestock density and headcount at 1-km for pilot area.\r\n\r\nOther links:\r\nhttps://docs.google.com/presentation/d/1qePs0puoVaVaVysztSlqLadb4_YIxQNf2JeuaF5GWlI", "recording_license": "", "do_not_record": false, "persons": [{"id": 40, "code": "K8AZA9", "public_name": "Leandro Parente", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 383, "guid": "d7bd94e3-e3fb-5826-ada0-ecaac8d70e5e", "logo": "", "date": "2025-09-04T17:00:00+02:00", "start": "17:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-383-hackathon-consultation", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/9TY7AD/", "title": "Hackathon Consultation", "subtitle": "", "track": "Hackathons", "type": "Hackathon", "language": "en", "abstract": "Hackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation", "description": "Hackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation \tHackathon Consultation", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}], "Expert Room 2": [{"id": 291, "guid": "c4539b77-0b3a-5ca8-a0bf-5540dc5acb32", "logo": "", "date": "2025-09-04T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-291-application-packages-in-the-xcube-ecosystem", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/UHZMFT/", "title": "Application Packages in the xcube ecosystem", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "Introduces the xcube core libraries and associated software components, and presents recent developments in integrating OGC Earth Observation Application Packages into the xcube ecosystem.", "description": "xcube is a mature and steadily growing data cube framework based around    Python and xarray; the core data processing functionality is complemented    by a wide selection of additional tools and associated libraries, including    an interactive viewer, a versatile API server, and a range of data access    plug-ins. This talk introduces the xcube ecosystem and presents a recent    addition, xcengine, developed as part of the Open-Earth-Monitor    Cyberinfrastructure project. xcengine turns Python Jupyter notebooks into    self-contained \u2018compute engines\u2019 based on Docker containers. Compute    engines can be run as OGC Earth Observation Application Packages to    integrate them into OGC workflows; they can also be run in an interactive    mode with an integrated xcube server and viewer, providing easy integration    of user code with xcube's extensive API and visualization support.\r\n\r\nOther links:\r\nhttps://github.com/xcube-dev/summerschool25/blob/main/slides.pdf\r\nhttps://github.com/xcube-dev/summerschool25\r\nhttps://xcube-dev.github.io/summerschool25/", "recording_license": "", "do_not_record": false, "persons": [{"id": 198, "code": "DMPAEC", "public_name": "Pontus Lurcock", "biography": "Pontus Lurcock is a software engineer at Brockmann Consult GmbH., with a strong focus on geodatacubes and analysis-ready earth observation data. He has extensive experience of working at the interface between informatics and geosciences, and holds an MSc in Computer Science and a PhD in Geology.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 284, "guid": "5db6c112-a426-54ea-bebc-e31aa579404a", "logo": "/media/opengeohub-summer-school-2025/submissions/DAN9MN/dest_4GN0H4J.png", "date": "2025-09-04T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-284-less-distorted-analyses-of-satellite-imagery-using-discrete-global-grid-systems-in-julia", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DAN9MN/", "title": "Less distorted analyses of satellite imagery using Discrete Global Grid Systems in Julia", "subtitle": "", "track": "Julia", "type": "Tutorials", "language": "en", "abstract": "Discrete Global Grid Systems (DGGS) have emerged as a transformative approach to minimizing spatial distortions in geospatial data processing. Unlike traditional methods that merely name locations, DGGS offer a highly efficient data structure capable of reducing storage requirements by up to 33% compared to the current Sentinel-2 UTM tiling grid. The performance of operations on DGGS native data cubes is intrinsically linked to the cell index, which plays a crucial role in data management and retrieval.\r\n\r\nMost DGGS implementations utilize a hierarchical one-dimensional index to name and sort cells, optimizing them for parent-child queries. This structure is particularly beneficial for operations such as upscaling and downscaling, which are essential for integrating data with varying spatial resolutions. However, many real-world applications, such as visualization, fluid dynamics, and convolutions, require efficient handling of distant neighbor queries based on spatial distances. These applications often rely on bounding boxes or moving windows, which are not optimally supported by traditional DGGS implementations.\r\n\r\nIn response to these challenges, we introduce DGGS.jl, a Julia package specifically developed to create and utilize DGGS native data cubes optimized for distant neighbor queries. Our package employs the DGGRID Q2DI index to store data on a hexagonal ISEA4H grid, enabling compact and efficient data cube arrays. We have implemented methods to seamlessly convert raster data between geographic and Q2DI coordinates, access neighbor disks around a given cell, and visualize these data on a global scale.\r\n\r\nTo demonstrate the practical application of DGGS.jl, we present a hands-on workshop of our Julia package DGGS.jl to convert traditional geographical data cubes into DGGS native data cubes. Furthermore, we show how to process those data cubes and how to access neighbors and regions around given coordinates.", "description": "Around 33% of the Sentinel-2 data is duplicated (Bauer-Marschallinger and Falkner, 2023)\u200b that needs to be downloaded, stored, and processed. This workshop introduces Discrete Global Grid Systems (DGGS) as a way to store satellite imagery in an efficient and distortion-less way. Then, we learn how to convert and process DGGS native data cubes in a hands-on session using the Julia package DGGS.jl.\r\n\r\nOther links: \r\nhttps://docs.google.com/presentation/d/1WIEBoGG6Basbu_TBdtZRoru3swD3yo93/edit?usp=drive_link&ouid=102861749140673074260&rtpof=true&sd=true\r\n\r\nStudy materials are uploaded at:\r\n\r\nhttps://gist.github.com/danlooo/02dda9b15c001cb384181dd50421329f\r\n\r\nhttps://danlooo.github.io/DGGS.jl", "recording_license": "", "do_not_record": true, "persons": [{"id": 91, "code": "REJEED", "public_name": "Daniel Loos", "biography": "PostDoc at Max Planck Institute for Biogeochemistry in Jena, Germany. Develops software for ESA and Open Earth Monitor Project. Focused on Discrete Global Grid Systems and cloud workflows.", "answers": []}, {"id": 362, "code": "SEAZQV", "public_name": "Lu\u00eds Moreira de Sousa", "biography": "Lu\u00eds Moreira de Sousa completed the Degree on Informatics and Computers\r\nEngineering at the University of Lisbon in 2002, which he complemented with a\r\nMasters on Geographic Information Systems in 2005. In the Department of Civil\r\nEngineering of this university he was a junior researcher from 2002 to 2008,\r\ncontributing to applied research projects with Instituto da \u00c1gua and Estradas\r\nde Portugal. After a year as consultant with SIQuant at the National Laboratory\r\nof Civil Engineering (LNEC), in 2009 he became an independent consultant,\r\nsupporting de development of the spatial data infrastructure of the newly\r\ncreated Administra\u00e7\u00e3o da Regi\u00e3o Hidrogr\u00e1fica do Tejo (ARH-Tejo).\r\n\r\nIn 2011 he joined the Henri Tudor institute in Luxembourg as Research Engineer,\r\nwhere he contributed to the development of Spatial Decision Support Systems on\r\nthe domains of Energy and Urban Planning. At the time he was already a PhD\r\ncandidate on Informatics Engineering at the University of Lisbon, promoted by\r\nProf. Alberto Silva.  In 2016 he concluded this graduation with a thesis on\r\ndomain specific languages for the development of spatial simulation programmes.\r\nStill that year he started a post-doc position at EAWAG (Swiss Federal\r\nInstitute of Research on the Water Domain) during which he conducted research\r\non rapid flood modelling and storm water network management. In 2017 Lu\u00eds\r\njoined ISRIC - World Soil Information in The Netherlands where he conducted\r\nresearch on the geography and ontology of world soils. In July of 2024 Lu\u00eds \r\nreturned to the University of Lisbon, this time as Assistant Professor.", "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 3": [{"id": 300, "guid": "db8c09f6-7d94-5c87-a9bc-fe629a73a8a7", "logo": "", "date": "2025-09-04T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-300-an-introduction-to-julia", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/ZTXMAE/", "title": "An introduction to Julia", "subtitle": "", "track": "Julia", "type": "Tutorials", "language": "en", "abstract": "An introduction lecture to Julia, focused on the installation, usage and other first steps. Useful if you plan on following subsequent lectures/tutorials on Julia and have no previous experience.", "description": "This lecture will introduce Julia as a programming language, and will have hands-on exercises to prepare you for the subsequent lectures using Julia. It will cover the installation of Julia, the installation of packages and environments, and using the geospatial stack. In between we will discuss the concepts that make Julia fast, and give you tips and tricks to work with Julia beyond the summer school.", "recording_license": "", "do_not_record": false, "persons": [{"id": 130, "code": "VV3KTG", "public_name": "Maarten Pronk", "biography": "Maarten Pronk is a researcher at Deltares and an external PhD candidate at the Delft University of Technology. He holds a cum laude MSc in Geomatics and a BSc in Architecture, both from the Delft University of Technology (NL). His research concerns elevation modelling, especially in lowlands prone to coastal flooding. He aims to combine his interests in remote sensing and software engineering for societal impact. He promotes open and reproducible research and is the author of several open-source software packages for handling geospatial data, written in the Julia programming language. His work often involves handling trillions of elevation measurements, requiring a careful selection and design of both spatial storage formats and processing algorithms. Currently, he works on applying data from ICESat-2, a LiDAR satellite, on global elevation models.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 299, "guid": "3e47d944-2985-5849-8005-8636c1139b23", "logo": "", "date": "2025-09-04T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-299-geomorphometry-in-julia", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/PYWBXY/", "title": "Geomorphometry in Julia", "subtitle": "", "track": "Julia", "type": "Tutorials", "language": "en", "abstract": "Lecture on geomorphometry and elevation modelling, alternated by hands-on exercises in Julia on downloading, visualizing and analyzing elevation models.", "description": "We discuss (global) elevation modelling, including recent advances, and follow up with a hands-on session in Julia, where we will use Rasters.jl and Geomorphometry.jl to download, analyze and visualize a subset of a global elevation model. These operations include hydrological functions such as flow accumulation methods, and the differences between several common algorithms. The importance of the correct coordinate reference systems and cellsize of a raster will be demonstrated.\r\n\r\nKey (geospatial) concepts in Julia will be introduced, including the performance gains made possible with Julia, although prior exposure (can be by watching previous lectures) is expected. An introduction lecture to Julia will be given beforehand.", "recording_license": "", "do_not_record": false, "persons": [{"id": 130, "code": "VV3KTG", "public_name": "Maarten Pronk", "biography": "Maarten Pronk is a researcher at Deltares and an external PhD candidate at the Delft University of Technology. He holds a cum laude MSc in Geomatics and a BSc in Architecture, both from the Delft University of Technology (NL). His research concerns elevation modelling, especially in lowlands prone to coastal flooding. He aims to combine his interests in remote sensing and software engineering for societal impact. He promotes open and reproducible research and is the author of several open-source software packages for handling geospatial data, written in the Julia programming language. His work often involves handling trillions of elevation measurements, requiring a careful selection and design of both spatial storage formats and processing algorithms. Currently, he works on applying data from ICESat-2, a LiDAR satellite, on global elevation models.", "answers": []}], "links": [], "attachments": [], "answers": []}]}}, {"index": 5, "date": "2025-09-05", "day_start": "2025-09-05T04:00:00+02:00", "day_end": "2025-09-06T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 363, "guid": "d050fde7-df48-5f08-ac30-4dab881800fc", "logo": "", "date": "2025-09-05T09:00:00+02:00", "start": "09:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-363-learning-representations-from-engineering-features-to-engineering-pretext-tasks", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/UNKX8N/", "title": "Learning Representations: From Engineering Features to Engineering Pretext Tasks", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "Machine learning has become an important toolbox for analyzing complex Earth observation data to derive information from the raw data. In particular, supervised deep learning has achieved great success in solving EO tasks where the relationship between input and output is not clearly understood. However, applications with limited reference data cannot directly benefit from advances in supervised deep learning. This lecture will first introduce the concepts of supervised deep learning and then provide an overview of research in the field of self-supervised learning (SSL), which aims to learn transferable representations (i.e., features) from unlabeled data.", "description": "Machine learning has become an important toolbox for analyzing complex Earth observation data to derive information from the raw data. In particular, supervised deep learning has achieved great success in solving EO tasks where the relationship between input and output is not clearly understood. However, applications with limited reference data cannot directly benefit from advances in supervised deep learning. This lecture will first introduce the concepts of supervised deep learning and then provide an overview of research in the field of self-supervised learning (SSL), which aims to learn transferable representations (i.e., features) from unlabeled data.", "recording_license": "", "do_not_record": false, "persons": [{"id": 419, "code": "9PTJVH", "public_name": "Nico Lang", "biography": "Nico is an Assistant Professor at the University of Copenhagen associated with the Global Wetland Centre and the Pioneer Centre for AI. He is also a core member of the Climate AI Nordics network. Before moving to Denmark for a Postdoc, Nico has received a PhD from ETH Zurich. His research focuses on computer vision, machine learning, and remote sensing, and on developing new methods to support environmental sciences. More information can be found on his website: https://langnico.github.io/", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 293, "guid": "7099cac9-a635-54df-a4f4-eb823710fe71", "logo": "", "date": "2025-09-05T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-293-synthetic-aperture-radar-system-specificaitons-and-performance-trade-offs", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/U88UXR/", "title": "Synthetic Aperture Radar: system specificaitons and performance trade offs", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "Spaceborne Synthetic Aperture Radar systems are an important component of our Earth Observation space infrastructure. This tutorial will guide the students through the main parameters that define a SAR system (antenna dimensions, available average power, etc.) and link them to the key performance indicators (radiometric sensitivity, spatial resolution, ambiguities, etc).", "description": "While users of Synthetic Aperture Radar data can often get away with ignoring how the data is generated, there are many cases in which a fundamental understanding of the trade-offs involved in the design or operation of a SAR system are relevant. This tutorial will\r\n- Introduce the concept of a Synthetic Aperture Radar\r\n- Discuss the relevant performance indicators, some more general like spatial resolution or image size, and some more SAR specific, such as the noise equivalent sigma zero (NESZ) or how well ambiguities are suppressed.\r\n- Link these performance indicators to fundamental system parameters, such as antenna dimensions and available power.\r\nThe students will work with a  Python notebook to explore interactively how changing system design (or processing) parameters impacts the imaging performance.", "recording_license": "", "do_not_record": false, "persons": [{"id": 367, "code": "SWABRT", "public_name": "Paco Lopez Dekker", "biography": "Paco Lopez-Dekker ( was born in Nijmegen, The Netherlands, in 1972. He received the Ingeniero degree in telecommunication engineering from the Universitat Polit\u00e8cnica de Catalunya (UPC), Barcelona, Spain, in 1997, the M.S. degree in electrical and computer engineering from the University of California at Irvine, Irvine, CA, USA, in 1998, under the Balsells Fellowship, and the Ph.D. degree from the University of Massachusetts, Amherst, MA, USA, in 2003, with a focus on clear-air imaging radar systems to study the atmospheric boundary layer.,In 2003, he joined Starlab Barcelona, Barcelona, where he was involved in the development of GNSS-R sensors and techniques. From 2004 to 2006, he was a Visiting Professor with the Department of Telecommunications and Systems Engineering, Universitat Aut\u00f2noma de Barcelona, Barcelona, where he taught courses on signals and systems, signal processing, communications systems and radiation, and guided waves. From 2009 to 2016, he led the SAR Missions Group, Microwaves and Radar Institute, German Aerospace Center, We\u00dfling, Germany, with a focus on the study of future synthetic aperture radar (SAR) missions, including the development of novel mission concepts and detailed mission performance analyses. He has been a faculty member at the Geoscience and Remote Sensing Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology.  Since March 2025 he is Professor in Radar Satellite Systems and Earth System Observation.  He was the lead proposer and currently principal investigator of the Harmony mission, ESA's 10th Earth Explorer Mission, which is expected to be launched towards the end of 2029.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 317, "guid": "a15b67e6-29da-53b7-986b-31f998c55d66", "logo": "", "date": "2025-09-05T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-317-atmospheric-greenhouse-gases-and-the-determination-of-their-concentrations-through-satellite-observations", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/SGUUY7/", "title": "Atmospheric Greenhouse Gases and the Determination of Their Concentrations Through Satellite Observations", "subtitle": "", "track": null, "type": "Tutorials", "language": "en", "abstract": "The absorption of telluric greenhouse gases in the Earth's atmosphere and the\r\nmethodology for determining the concentrations of CO 2 and CH 4 through satellite\r\nobservations are the focal points of this tutorial. For this tutorial, relevant aspects are\r\ndiscussed in the lecture on Radiative Transfer. The tutorial will guide participants in\r\nsimulating the solar spectrum that is reflected by the Earth's atmosphere and\r\nsubsequently measured by satellites. Emphasis will be placed on the 1.6 \u00b5m spectral\r\nrange that encompasses the absorption bands of CO 2 , CH 4 , and water vapor. It is\r\nused by several satellite missions to infer greenhouse gas abundances from\r\nradiometric observations. The model that we will use will incorporate fundamental\r\ninstrument characteristics such as spectral resolution and sampling, facilitating a\r\ncomparison between our simulation and actual observations obtained from the\r\nGOSAT satellite. By adjusting the input parameters of the model, we strive to\r\nenhance the concordance between the model's predictions and observed data,\r\nthereby allowing us to ascertain the total quantities of CO 2 and CH 4 present in the\r\nmonitored atmosphere.", "description": "Requirements for this tutorial include an updated installation of Python and\r\nfoundational skills in Python programming. It is essential to ensure that the following\r\nlibraries are correctly installed: netCDF4 or xarray, numpy, and scipy. The use of\r\nJupyter notebooks is anticipated, so familiarity with utilizing notebooks in a web\r\nbrowser or Visual Studio would be beneficial.\r\n\r\nOther links:\r\nhttps://owncloud2.sron.nl/index.php/s/rtiUpCL11nxcwXm  pw: Tutorial", "recording_license": "", "do_not_record": false, "persons": [{"id": 393, "code": "X7FFFV", "public_name": "Jochen Landgraf", "biography": "Jochen Landgraf is a senior scientist at SRON Netherlands Institute for Space Research and a guest professor at the Institute for Environmental Physics, University Heidelberg. At SRON he is head of a research group focusing on atmospheric remote sensing of trace gases from TANGO, TROPOMI, S5, and GOSAT observations. His group developed the algorithm and SW for the operational CO and CH4 data processing of the Sentinel-5P and Sentinel 5 mission. In several studies, his team demonstrated higher-level data applications of S5P CO and CH4 data. He is a member of the S4/S5 and CO2M mission advisory group and has led and contributed to many projects, including several for ESA and EUMETSAT. His scientific focus is on atmospheric radiative transfer and measurement inversion techniques but also includes new measurement concepts and instrument specifications.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 378, "guid": "dc8f50c4-d7c9-5ed4-ae20-f5d947f1c898", "logo": "", "date": "2025-09-05T15:30:00+02:00", "start": "15:30", "duration": "01:30", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-378-closing-and-announcement-of-hackathon-winners", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/DVDQRH/", "title": "Closing and announcement of hackathon winners", "subtitle": "", "track": null, "type": "Tutorials", "language": "en", "abstract": "Closing and announcement of hackathon winners Closing and announcement of hackathon winners Closing and announcement of hackathon winners", "description": "Closing and announcement of hackathon winners Closing and announcement of hackathon winners Closing and announcement of hackathon winners Closing and announcement of hackathon winners", "recording_license": "", "do_not_record": false, "persons": [{"id": 1, "code": "8QMFTU", "public_name": "Tom Hengl (OpenGeoHub)", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 2": [{"id": 315, "guid": "fb958de8-47ae-5bdd-9364-81810bb31a10", "logo": "/media/opengeohub-summer-school-2025/submissions/F7A3SC/RTT_VSthRoc.jpg", "date": "2025-09-05T11:00:00+02:00", "start": "11:00", "duration": "01:00", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-315-the-radiative-transfer-theory", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/F7A3SC/", "title": "The Radiative Transfer Theory", "subtitle": "", "track": "Theoretical sessions", "type": "Theoretical lectures", "language": "en", "abstract": "Radiative Transfer Theory provides a robust framework for understanding how matter interacts with light, enabling us to interpret radiometric observations of planetary atmospheres. This theory allows us to explore photochemical processes and calculate heating rates in atmospheres, both of which are crucial for studying atmospheric chemistry and modeling the climate.", "description": "Solving the Maxwell equations of electrodynamics and the Schr\u00f6dinger equation of quantum mechanics can be quite complex, especially when dealing with intricate objects like planets. Instead, we focus on the Radiative Transfer Theory, which allows us to study radiometric observations of stellar objects and the Earth's atmosphere effectively. This theory combines aspects of both fundamental physics theories.\r\n In this lecture, we will explore this powerful theory, starting with the foundational radiative transfer equation and its applications to remote sensing of celestial objects and the Earth's atmosphere.\r\n\r\nOther links:\r\nhttps://owncloud2.sron.nl/index.php/s/gCxJuHn3MqcwqMD pw: RRT25", "recording_license": "", "do_not_record": false, "persons": [{"id": 393, "code": "X7FFFV", "public_name": "Jochen Landgraf", "biography": "Jochen Landgraf is a senior scientist at SRON Netherlands Institute for Space Research and a guest professor at the Institute for Environmental Physics, University Heidelberg. At SRON he is head of a research group focusing on atmospheric remote sensing of trace gases from TANGO, TROPOMI, S5, and GOSAT observations. His group developed the algorithm and SW for the operational CO and CH4 data processing of the Sentinel-5P and Sentinel 5 mission. In several studies, his team demonstrated higher-level data applications of S5P CO and CH4 data. He is a member of the S4/S5 and CO2M mission advisory group and has led and contributed to many projects, including several for ESA and EUMETSAT. His scientific focus is on atmospheric radiative transfer and measurement inversion techniques but also includes new measurement concepts and instrument specifications.", "answers": []}], "links": [], "attachments": [], "answers": []}, {"id": 285, "guid": "3ab25c3a-64f0-5434-a845-73773838fb16", "logo": "", "date": "2025-09-05T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 2", "slug": "opengeohub-summer-school-2025-285-cryosphere-tutorial-in-python", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/HWFDTU/", "title": "Cryosphere Tutorial in Python", "subtitle": "", "track": "Python", "type": "Tutorials", "language": "en", "abstract": "This tutorial session is designed for Cryosphere applications, focusing on the processing and analysis of satellite remote sensing data over ice sheets and sea ice regions. The session will introduce key satellite missions, including Sentinel-1 SAR, CryoSat-2 radar altimetry, and ICESat-2 laser altimetry, with hands-on exercises in Python.\r\nParticipants will gain experience in:\r\nSynthetic Aperture Radar (SAR) processing using Sentinel-1 data for ice type classification.\r\nRadar altimetry (CryoSat-2) data analysis, including elevation and freeboard estimation.\r\nLaser altimetry (ICESat-2) data processing, focusing on surface elevation change detection, and sea ice thickness estimation.\r\nThe tutorial will cover Python-based tools and libraries, including rasterio, xarray, h5py, and geopandas, to facilitate the analysis of large-scale remote sensing datasets. By the end of the session, participants will be able to apply these techniques to monitor ice sheet dynamics, track sea ice changes, and assess the impact of climate variability on the cryosphere.", "description": "The cryosphere plays a crucial role in Earth's climate system and sea level changes. Satellite remote sensing provides essential observations for understanding ice sheet dynamics, sea ice variability, and snowpack conditions. This Python-based tutorial introduces practical techniques for analyzing Sentinel-1, CryoSat-2, and ICESat-2 data in cryospheric studies.\r\nTopics Covered\r\nSentinel-1 SAR Processing\r\nAccessing and preprocessing Sentinel-1 GRD and SLC data.\r\nGenerating backscatter composites for sea ice classification.\r\nCryoSat-2 Radar Altimetry Analysis\r\nUnderstanding radar waveforms over ice surfaces.\r\nDeriving sea ice freeboard and thickness from CryoSat-2 Level-2 products.\r\nComparing altimetry measurements with in-situ validation data.\r\nICESat-2 Photon Counting Altimetry\r\nExtracting surface elevation from ICESat-2 ATL07 and ATL10 datasets.\r\nEstimating ice sheet elevation change and sea ice thickness.\r\nVisualizing ICESat-2 track data over polar regions.\r\nTools & Libraries\r\nParticipants will work with:\r\nrasterio, geopandas, shapely \u2013 for geospatial data handling.\r\nh5py, xarray, numpy \u2013 for working with large satellite datasets.\r\nmatplotlib, cartopy, seaborn \u2013 for visualization of polar data.", "recording_license": "", "do_not_record": false, "persons": [{"id": 363, "code": "DKUNZE", "public_name": "Lu Zhou", "biography": "Assistant Professor at Utrecht University, working over the remote sensing of Cryosphere", "answers": []}], "links": [], "attachments": [], "answers": []}], "Expert Room 3": [{"id": 375, "guid": "36fa09eb-15af-5d2d-9661-90ca3cb3012b", "logo": "", "date": "2025-09-05T13:30:00+02:00", "start": "13:30", "duration": "01:30", "room": "Expert Room 3", "slug": "opengeohub-summer-school-2025-375-processing-large-grids-and-raster-algebra-using-terra-package-r-", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/7WDD97/", "title": "Processing large grids and raster algebra using terra package (R)", "subtitle": "", "track": "R training", "type": "Tutorials", "language": "en", "abstract": "Terra package in R (developed by Robert Hijmans; https://rspatial.github.io/terra/) is one of the finest libraries in R for processing gridded/raster data. It is an evolved version of the raster package and is fit for use with large rasters including time-series of raster images / EO images. The tutorial will demonstrate some processing steps used to aggregate time-series of images in parallel, run space-time overlay, combine interpolation functions on raster images and do more complex raster algebra. More examples are available also via: https://opengeohub.github.io/spatial-prediction-eml/", "description": "Example code and data is available: https://doi.org/10.5281/zenodo.14833052\r\n\r\nhttps://differ.blog/p/processing-large-rasters-using-terra-package-for-r-combining-tiling-69d47a\r\nhttps://drive.google.com/file/d/1DsSV7ip7--BoWZ8J3R2On1D3H0oJ4fvP/view?usp=drive_link\r\nhttps://drive.google.com/file/d/1TLUTVs2-rGCZwCGybmNGxQHqBA6G4Kkv/view?usp=drive_link", "recording_license": "", "do_not_record": false, "persons": [{"id": 1, "code": "8QMFTU", "public_name": "Tom Hengl (OpenGeoHub)", "biography": null, "answers": []}, {"id": 434, "code": "CXWXAG", "public_name": "Alexandre Wadoux", "biography": null, "answers": []}], "links": [], "attachments": [], "answers": []}]}}, {"index": 6, "date": "2025-09-06", "day_start": "2025-09-06T04:00:00+02:00", "day_end": "2025-09-07T03:59:00+02:00", "rooms": {"HugoTECH": [{"id": 385, "guid": "ec6cedaf-ad48-57ac-b818-a76d85b2bab8", "logo": "", "date": "2025-09-06T08:30:00+02:00", "start": "08:30", "duration": "08:00", "room": "HugoTECH", "slug": "opengeohub-summer-school-2025-385-field-excursion-doorwerth-castle", "url": "https://pretalx.earthmonitor.org/opengeohub-summer-school-2025/talk/HMUU8R/", "title": "Field Excursion - Doorwerth castle", "subtitle": "", "track": null, "type": "Social Event", "language": "en", "abstract": "Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle", "description": "Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle Field Excursion - Doorwerth castle", "recording_license": "", "do_not_record": false, "persons": [], "links": [], "attachments": [], "answers": []}]}}]}}}