Detection of small-scale landscape elements with remote sensing
Nikita Murin
Estonian Land Board, Tartu, Estonia
Alexander Kmoch
Department of Geography, University of Tartu, Tartu, Estonia
Evelyn Uuemaa
Department of Geography, University of Tartu, Tartu, Estonia
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Evelyn Uuemaa, Marco Ciolli, and Marco Minghini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 1–2, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-1-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-1-2024, 2024
Alexander Kmoch, Benoit Bovy, Justus Magin, Ryan Abernathey, Alejandro Coca-Castro, Peter Strobl, Anne Fouilloux, Daniel Loos, Evelyn Uuemaa, Wai Tik Chan, Jean-Marc Delouis, and Tina Odaka
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 75–80, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-75-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-75-2024, 2024
Tahmin Sitab, Oleksandr Karasov, and Alexander Kmoch
AGILE GIScience Ser., 4, 43, https://doi.org/10.5194/agile-giss-4-43-2023, https://doi.org/10.5194/agile-giss-4-43-2023, 2023
Evelyn Uuemaa and Alexander Kmoch
AGILE GIScience Ser., 3, 65, https://doi.org/10.5194/agile-giss-3-65-2022, https://doi.org/10.5194/agile-giss-3-65-2022, 2022
Holger Virro, Alexander Kmoch, Marko Vainu, and Evelyn Uuemaa
AGILE GIScience Ser., 3, 66, https://doi.org/10.5194/agile-giss-3-66-2022, https://doi.org/10.5194/agile-giss-3-66-2022, 2022
Alexander Kmoch, Oleksandr Matsibora, Ivan Vasilyev, and Evelyn Uuemaa
AGILE GIScience Ser., 3, 41, https://doi.org/10.5194/agile-giss-3-41-2022, https://doi.org/10.5194/agile-giss-3-41-2022, 2022
Holger Virro, Giuseppe Amatulli, Alexander Kmoch, Longzhu Shen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021, https://doi.org/10.5194/essd-13-5483-2021, 2021
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Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.
Alexander Kmoch, Arno Kanal, Alar Astover, Ain Kull, Holger Virro, Aveliina Helm, Meelis Pärtel, Ivika Ostonen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 83–97, https://doi.org/10.5194/essd-13-83-2021, https://doi.org/10.5194/essd-13-83-2021, 2021
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The Soil Map of Estonia is the most detailed and information-rich dataset for soils in Estonia. But its information is not immediately usable for analyses or modelling. We derived parameters including soil layering, soil texture (clay, silt, and sand content), coarse fragments, and rock content and aggregated and predicted physical variables related to water and carbon cycles (bulk density, hydraulic conductivity, organic carbon content, available water capacity).