OpenDataScience Europe - Workshop 2021
The EU-funded GeoHarmonizer project organized the Open Data Science Europe Workshop, a 5-day hybrid event held in Wageningen (NL), providing two days of training sessions in processing data cubes and using machine learning to extract content, and three days of oral talks and discussion panels around the science, technology and business in open data. The special theme of the workshop 2021 was “Spatiotemporal modeling of European Landscapes and Climate 2000–2020: using EO and Machine Learning.”
DOI (series): 10.5446/s_1146
57
2021
6,917
1 day 15 hours
Results 1-36 out of 57
23:40
99Masiliūnas, DainiusDainius Masiliūnas is University Lecturer at Wageningen University & Research. Dainius spoked about automated global land cover disturbance monitoring using BFAST Lite.
2021OpenGeoHub Foundation
41:29
98Vitolo, ClaudiaClaudia Vitolo, Scientist at European Centre for Medium-Range Weather Forecasts (ECMWF), focussed her presentation on forest fire mapping. Although forest fires are an integral part of the natural Earth system dynamics, they are becoming more devastating and less predictable as anthropogenic climate change exacerbates their impacts. Longer and more extreme fire seasons,fed by rain-free days globally, are inducing significant variations in wildfire danger. In this talk, Claudia presented the complete wildfire-related data offering, tools for efficient data processing and visualisation as well as results from recent research projects. The European Centre for Medium-range Weather Forecasts (ECMWF) and Copernicus have created a wealth of datasets related to the forecasting of wildfire danger as well as the detection of wildfire events and related emissions in the atmosphere. These products contribute to the operational services provided by the Copernicus Emergency Management Service (CEMS) and the Copernicus Atmosphere Monitoring Service (CAMS) and consists of real time forecasts as well as historical datasets based on ECMWF reanalysis database ERA5. Data is open and available through the Copernicus Climate Data Store (CDS), the European Commission’s Global Wildfire Information System (GWIS) and European Forest Fire Information System (EFFIS).
2021OpenGeoHub Foundation
37:47
321Schratz, PatrickPatrick Schratz is an R consultant at cynkra, Zurich, and in this talk he presented the mlr3 package for R. This package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
2021OpenGeoHub Foundation
24:49
60Hengl, Tomislav et al.2021OpenGeoHub Foundation
48:20
31Sluiter, RaymondRaymond Sluiter, Senior Advisor Data & Applications at Netherlands Space Office (NSO) discussed an overview and outlook of the EU Copernicus programme around Open European Earth Observation Data.
2021OpenGeoHub Foundation
16:15
20Gräler, Benedikt2021OpenGeoHub Foundation
39:20
32Cheesbrough, SarahSarah Cheesbrough, Earth Observation Specialist at Satellite Applications Catapult Ltd, UK, spoke about the EO Data Cube based in the South Pacific region (Fiji, Solomon Islands and Vanuatu) as part of the IPP CommonSensing project, funded by the UK Space Agency's International Partnership Programme (https://www.commonsensing.org.uk/).
2021OpenGeoHub Foundation
15:57
201Dijk, Michiel vanMichiel van Dijk is a senior researcher in the international policy department at Wageningen Economic Research, Wageningen University and Research. In his presentation, Michiel’s work showed how gridded maps with information on the location of crops are essential to inform national food and agricultural policies and are an important input for land use change models. Despite rapid advancement in machine learning approaches to identify the location of crops, national and global level crop distribution maps that cover a large number of crops are not readily available yet, in particular for African countries. One of the most used sources of crop distribution information is the IFPRI Spatial Production Allocation Model (SPAM, www.mapspam.info), which presents global-level plausible spatial estimates of the location of 40 crops (groups) that represent total agricultural production. SPAM uses a cross-entropy optimization approach to allocate national and subnational crop statistics of four production systems (subsistence, low-input, high-input, irrigated), informed by spatial information on both biophysical (e.g. crop suitability) and socio-economic (e.g. accessibility) drivers of crop location. In this talk, Michiel explained the use of MAPSPAM-C, and R package that implements the SPAM procedure to create crop distribution maps and facilitates the pre-processing steps to harmonize spatial input layers and post-processing steps to create harvested area, physical area, yield and production maps. The package can be used to reproduce and validate the new generation of SPAM products and will be useful for researchers that want to create their own maps using country specific input data.
2021OpenGeoHub Foundation
20:33
31Bajat, BranislavBranislav Bajat, Faculty Member of the University of Belgrade, illustrated the CERES project. In this talk, he explained how the use of AI in agriculture should be especially important in Serbia, as agriculture is one of the crucial sectors of Serbian economy. This project will be an important step forward in the application of a wide range of relevant data generated on a daily basis and offering a huge potential for improving agricultural production and developing the concept of smart and regenerative agriculture.
2021OpenGeoHub Foundation
37:39
41Vamborg, FrejaFreja Vamborg, Senior researcher at Copernicus Climate Change Service, illustrated the European State of the Climate report: this annual report on behalf of the European Commission provides an analysis of the monitoring for Europe for the past calendar year, with descriptions of climate conditions and events.
2021OpenGeoHub Foundation
10:01
23Pavelka, Karel Jr.Karel Pavelka works at the Czech Technical University in Prague. In this presentation, Karel took the audience through an interactive journey with recently developed 3D ODSE viewer.
2021OpenGeoHub Foundation
15:15
17Križan, JosipJosip Križan is the owner of MultiOne. In this talk, Josip introduced how the rapidly increasing amount of publically available remotely sensed data in recent decades has revolutionized large-scale research and context-informed decision making. However, these data are generally not freely available as homogenized products ready for analysis at continental (or larger) scales. This is widely observed with datasets generated by EO satellites, particularly those with optical sensors and those capable of high-resolution imaging, where the process of mosaicking imagery to produce a homogenous, cloudless dataset across a particular area of interest often grows increasingly cumbersome at larger scales.
2021OpenGeoHub Foundation
17:29
12Pawlik, ŁukaszLukasz Pawlik is a PhD candidate at University of Silesia in Katowice at the Institute of Earth Sciences. His research focuses on the effects of windstorms on European forest ecosystems. In his presentation, Lukasz explained how the combination of several data sets on tree features, bioclimatic and geomorphic conditions, and the level of forest damage in the Sudety Mountains over the period 2004-2010, to map forest damage probability based on forest data from 202. Eventually, Lukasz focusses on how,using only 11 variables based on the open source datasets, his research effort was able to obtain predictive models of good accuracy.
2021OpenGeoHub Foundation
42:54
48Panagos, PanosPanos Panagos is part of the Joint Research Centre, European Soil Data Centre, and in this talk, he described the work of the European Soil Data Centre (ESDAC), which is producing several interesting new data sets based on predictive soil mapping.
2021OpenGeoHub Foundation
21:01
109Parente, LeandroLeandro Parente is a postdoctoral researcher at OpenGeoHub, supporting the foundation's current and future European Commission-funded and other international projects where there is a need to develop new solutions for geocomputing, optimize and automate modeling frameworks and deliver scientific outputs. In this talk, Leandro illustrated how to detect land degradation using time-series analysis of EO Vegetation products (MODIS EVI, Proba-V, Landsat).
2021OpenGeoHub Foundation
21:31
67Bonannella, CarmeloCarmelo Bonnanella, PhD candidate & research assistant at OpenGeoHub, presented the results of modeling species distribution maps for both potential and actual natural vegetation through spatiotemporal machine learning using a data-driven, robust, objective and fully reproducible workflow. The presentation focussed on the benefits of using ensemble machine learning for species distribution modeling to capture patterns of niche changes in both space and time: yearly (from 2000 to 2020) probability distribution maps for both potential and actual natural vegetation were shown for forest tree species that live in different climatic conditions across Europe. The high spatial (30 m) and temporal (1 year) resolution of the outputs should allow us to enhance and better understand the patterns of niche change.
2021OpenGeoHub Foundation
18:10
54Witjes, MartijnMartijn Witjes is a PhD candidate at OpenGeoHub foundation. In this talk, he expounded the first results of his research on land cover time-series data stack for Europe between 2000 and 2019. The classification sees 33 different land use / land cover (LULC) classes between 2000 and 2019 using a single spatiotemporal ensemble machine learning model in a fully automated, free and open source workflow. This workflow includes harmonization and preprocessing of several high-resolution publically available covariate datasets and over five million training samples, spatial K-fold cross-validation, hyperparameter optimization, and multiple methods for LULC change analysis. Martijn also showed how the per-class probability predictions facilitated useful prediction uncertainty metrics, informed use case-tailored post-processing strategies, and enabled a novel way to quantify LULC change dynamics without relying on hard-class predictions. The results of his study suggest that the method developed by his team, enables land cover classification for subsequent years without waiting for new training data, while facilitating improved training data collection through analysing variable importance, per-class performance, and uncertainty metrics.
2021OpenGeoHub Foundation
25:13
55Herold, MartinMartin Herold is Professor of Geoinformation Science and Remote Sensing, Wageningen University. In his talk, he explored different projects and initiatives, also at European level, that aim at enhancing the availability of global land cover mapping and the progress in their assessment.
2021OpenGeoHub Foundation
35:36
264Câmara, GilbertoGilberto Câmara is part of the INPE, the National Institute for Space Research. In his talk, Gilberto described an open-source R package for satellite image time series analysis using machine learning. It supports the complete cycle of data analysis for land classification, while its API provides a simple but powerful set of functions. The software works in different cloud computing environments, including AWS, MS-Azure, and Digital Earth Africa. In sits, satellite image time series are input to machine learning classifiers, and the results are post-processed using spatial smoothing. Since machine learning methods need accurate training data, sits includes methods for quality assessment of training samples. The software also provides methods for validation and accuracy measurement. The package thus comprises a production environment for big EO data analysis. The package is available on https://github.com/e-sensing/sits and the documentation is available on https://e-sensing.github.io/sitsbook/.
2021OpenGeoHub Foundation
12:35
40Habib, WahajWahaj Habib is a Postgraduate (PhD) Student at the Trinity College Dublin, and he illustrated the results of his study on peatlands monitoring in Ireland. Peatlands have been under severe pressure globally due to anthropogenic activities, ans in Ireland, approximately 90 % of the peatlands have been degraded to some extent due to these activities. Peatlands play also an important role to achieve temperature goals agreed in the Paris agreement and in fulfilling the EU’s commitment to quantifying the Carbon/Green House Gases (C/GHG) emissions from land use, land-use change forestry. Therefore, accurate mapping and identification of management related activities (land use) on peatlands has become a research and management priority.
2021OpenGeoHub Foundation
18:12
48Schneider, RochelleRochelle Schneider is a Research Fellow in Artificial Intelligence for Earth Observation at European Space Agency (ESA), and she expounded the development of a multi-stage satellite-based machine learning (ML) model to estimate daily PM2.5 levels across Great Britain during 2008-2018. Stage-1 estimated PM2.5 concentrations in monitors with only PM10 records. Stage-2 imputed missing satellite aerosol-optical-depth due to cloudiness and bad retrievals. Stage-3 applied the Random Forest algorithm to estimate PM2.5 concentrations using a combined dataset from Stage-1, Stage-2, and a list of spatiotemporally synchronised predictors. Stage-4 estimated daily PM2.5 using Stage-3 model. The relatively high precision allowed these estimates (approximately 950 million points) to be used in epidemiological analyses to assess health risks associated with both short- and long-term exposure to PM2.5.
2021OpenGeoHub Foundation
38:29
44Tzotzos, AngelosAngelos Tzotzos, presented the Open Source Geospatial Foundation (OSGeo), a not-for-profit organization whose mission is to foster global adoption of open geospatial technology by being an inclusive software foundation devoted to an open philosophy and participatory community driven development. Angelos is the president of the OSGeo.
2021OpenGeoHub Foundation
19:08
178Chaves, Pablo PérezIn his talk, Pablo outlined the Environmental Impact Assessments (EIA) process to assess project’s impacts on the environment, including biodiversity, a powerful tool to propose mitigation measures when tackling negative impacts. However, these assessments often underestimate the impacts on biodiversity due to lack of continuous biological information covering the whole targeted area.
Pablo’s work explored the potential of combining existing biological field-data with satellite images, such as Landsat Satellite images,as a cost-effective way to predict biodiversity patterns in areas far beyond the location of field-data, offering the possibility of reliable continuous biodiversity patterns for EIAs. This innovative biodiversity mapping method allows for properly quantifying a project footprint’s impact on biodiversity and identifying suitable areas for “like-for-like” compensation schemes.
2021OpenGeoHub Foundation
32:01
25Reuter, HannesHannes Reuter, Statistical Officer - EUROSTAT, outlined the ‘Geographical Information System of the COmmission’ (GISCO), a permanent service of Eurostat that fulfils the requirements of both Eurostat and the European Commission for geographic information and related services at European Union (EU), Member State and regional levels. These services are also provided to European citizens at large. GISCO’s goal is to promote and stimulate the use of geographic information within the European Statistical System and the European Commission.
2021OpenGeoHub Foundation
25:41
11Simonis, IngoIngo Simonis is chief technology innovation officer at the Open Geospatial Consortium (OGC). At the ODSE conference,he explained how platforms for the Exploitation of Earth Observation (EO) data have been developed by public and private companies in order to foster the usage of EO data and expand the market of Earth Observation-derived information. His talk described the general architecture, demonstrates the Best Practices, and includes recommendations for the application design patterns, package encoding, container and data interfaces for data stage-in and stage-out strategies. The session further outlined how to interact with a respective system using Jupyter Notebooks and OGC Web APIs.
2021OpenGeoHub Foundation
24:40
38Ilie, CodrinaThe Free and Open Source paradigm is no longer a novelty in the geospatial world. There are numerous, stable and powerful solutions, services, libraries built and maintained in the spirit of FOSS. The movement has long overcome the status of a garage hobby, infiltrating all sectors. There are hundreds of relevant events around the world each year, from conferences to hackathons, workshops and seminars, studies and reports analysing open source business models, funding schemas and explicit requests for projects that build software to make it open source. In this agile context, it is difficult, if not impossible to keep up to the speedy developments, to make use of what is already out there and investing resources in improving and not building from scratch.
2021OpenGeoHub Foundation
21:29
24Muskat, Mark VellaMark Vella Muskat is the project officer at European Health and Digital Executive Agency (HaDEA). In this talk, he showed examples of Public Open Data projects supported by the European Commission.
2021OpenGeoHub Foundation
28:42
21Rizzi, DanieleDaniele Rizzi is the principal administrator and policy officer at the European Commission. His presentation at the ODSE overviewd the European legislative support on data, with attention to open data.
2021OpenGeoHub Foundation
1:33:34
350Hengl, TomislavSoftware requirements: opengeohub/r-geo docker image (R, rgdal, terra, mlr3), QGIS, Google Earth Pro
This tutorial is an introduction to RStudio, and shows how to start packages and load data. It also serves as an introduction to spatiotemporal datasets, eumap spatiotemporal datasets, as for example: landcover 2000-2020 training dataset (Witjes et al, 2021). It also focuses on visualizing spatiotemporal data and data summaries.
2021OpenGeoHub Foundation
1:20:32
115Hengl, TomislavSoftware requirements: opengeohub/r-geo docker image (R, rgdal, terra, mlr3), QGIS, Google Earth Pro This tutorial shows how to access COG files using QGIS, how to use gdaltiler to produce plots in Google Earth (local copy), and how to use plotKML package to visualize data in Google Earth.
2021OpenGeoHub Foundation
1:35:29
81Parente, LeandroSoftware requirements: opengeohub/py-geo docker image (gdal, rasterio, eumap, scikit-learn) What are the possibilities to improve the performance of computation in Python? This tutorial shows how to performe Numpy operations using multicore processing, how to accelerate python functions using Numba, how to calculate fast numerical expression using NumExpr, how to use the TilingProcessing to distribute raster operations in multiple cores.
2021OpenGeoHub Foundation
1:31:26
222Parente, Leandro et al.Software requirements: opengeohub/py-geo docker image (gdal, rasterio, eumap, scikit-learn) This tutorial covers the theoretical background for Ensemble ML and python implementations, exploring the general concepts and main advantages of spatiotemporal machine learning. Why use LandMapper? The tutorial also shows how to prepare the training sample via spacetime overlay, how to evaluate the EML model performance via spacetime cross-validation, how to tune the EML model via hyperparameter optimization, to finally fit the final EML model.
2021OpenGeoHub Foundation
1:28:43
1,128Parente, Leandro et al.Software requirements: opengeohub/py-geo docker image (gdal, rasterio, eumap, scikit-learn)
This tutorial covers the theoretical background for machine learning and python implementations, as well as integrating raster data with scikit-learn models.
Why use pyeumap.LandMapper?
The tutorial shows how to prepare the training samples with spatial overlay, how to evaluate the ML model performance with spatial cross-validation, how to tune the ML model with hyperparameter optimization, how to get the final ML model ,and finally how to generate spatial predictions using the fitted model.
2021OpenGeoHub Foundation
1:28:45
651Antonić, LukaSoftware requirements: opengeohub/py-geo docker image (gdal, rasterio, geopandas, eumap) This tutorial explores the basics of spatial referencing, reading/writing raster datasets and vector datasets. It also shows how to access the datasets produced by the Geo-harmonizer with eumap, working with time-series datasets, and finally how to visualize the results.
2021OpenGeoHub Foundation
1:33:15
131Landa, Martin et al.Software requirements: GRASS GIS 8 This is an introduction to the new version 8 of GRASS GIS, showcasing the heavily redesigned graphical user interface. It also explores the interaction with data (visualization, styling, map elements), the analysis of data from different domains, and it introduces to automated processing. The second part introduces the Python 3 scripting, the spatio-temporal data analysis, and more. Candidate datasets: improved ERA5 land air temperature, surface temperature and precipitation (daily data).
2021OpenGeoHub Foundation