Prepared by: Carmelo Bonannella (OpenGeoHub), Valentina Delconte (OpenGeoHub), Ichsani Wheeler (OpenGeoHub / EnvirometriX) and Tom Hengl (OpenGeoHub / EnvirometriX) The growing interest in climate change and the potential threat it poses have seen an increasing demand for tools and solutions to the world’s greatest environmental problems. Forests are part of…

Prepared by: Tom Hengl (OpenGeoHub), Ichsani Wheeler (OpenGeoHub), Robert A. McMillan (OpenGeoHub), Kris Deveria (OpenGeoHub), Leandro Parente (OpenGeoHub), Chris van Diemen (OpenGeoHub), Valentina Delconte (OpenGeoHub) Land degradation is a systematic loss of function in terrestrial ecosystems: a serious drop in primary productivity, biomass and biodiversity. This means the land produces…

Prepared by: Carson Ross (OpenGeoHub), Tom Hengl (OpenGeoHub), Leandro Parente (OpenGeoHub), Vasile Crăciunescu (TerraSigna) Data Cubes are highly organised data infrastructures enabling users to run new analyses and generate insights into processes, patterns and trends. In the context of Earth Observation (EO) projects, data cubes are commonly time-series of spatiotemporal…

Prepared by: Tom Hengl (OpenGeoHub / EnvirometriX), Leandro Parente (OpenGeoHub / EnvirometriX), Ichsani Wheeler (OpenGeoHub / EnvirometriX) and Carmelo Bonannella (OpenGeoHub) Soils symbolize fertility and are a foundation of our civilization. There is an increasing focus on soils due to their significant ecosystem services — from growing crops, to filtering…

Prepared by: Valentina Delconte (OpenGeoHub), Insights from OpenGeoHub’s seminar series “Biodiversity: how big is our global biodiversity debt and what can we do about it?” on December 23, 2021. To help us answer the question: “Can nature keep up with human-induced environmental changes and can ecosystem regeneration be enough to…

Prepared by: Tom Hengl (OpenGeoHub), Leandro Parente (OpenGeoHub) and Ichsani Wheeler (OpenGeoHub) Samples collected in soil, vegetation science, ecology, geology can be used to build predictive mapping models and produce predictions i.e. maps. Increasingly, Machine Learning methods such Random Forest and similar are used to train models and produce maps…

Prepared by: Tom Hengl (OpenGeoHub) Some popular tree-based Machine Learning (ML) algorithms such as Random Forest (RF) and/or Gradient Boosting have been criticized about over-fitting effects and prediction / extrapolation in feature space that can lead to serious blunders and artifacts. Extrapolation seems to be especially cumbersome for regression problems…

Prepared by: Tom Hengl (OpenGeoHub) and Leandro Parente (OpenGeoHub) Earth Observation, soil, terrain, land cover and land use, climate data are increasingly available for Africa for research and businesses. This tutorial explains: how to access the iSDAsoil property and nutrient maps for Africa and number of Sentinel-2 cloud-free bands and…

Prepared by: Leandro Parente (OpenGeoHub), Martijn Witjes (OpenGeoHub), Tom Hengl (OpenGeoHub), Codrina Maria Ilie (Terrasigna) and Martin Landa (CVUT Prague) OpenGeoHub together with partners CVUT Prague, mundialis, Terrasigna, MultiOne and GiLAB, has released Open Data Science Europe data portal on 1st of March 2021. It comprises terabytes of gridded data…