Luke
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Jukuri

Tervetuloa käyttämään Jukuria, Luonnonvarakeskuksen (Luke) avointa julkaisuarkistoa. Jukurissa on tiedot Luken julkaisutuotannosta. Osa julkaisuista on vapaasti ladattavissa. Luken muodostaneiden tutkimuslaitosten aikaisemmasta julkaisutuotannosta osan tiedot ovat järjestelmässä jo nyt ja kattavuus paranee jatkuvasti.

Kokoelmat

Viimeksi tallennetut

  • Sisävesien kalansaalis pysynyt vakaana
    Rahikainen, Mika; Söderkultalahti, Pirkko
    Suomen kalastuslehti : 3/2026 (2026)
  • Biokaasu - sittenkin?
    Aakkula, Jyrki
    Käytännön maamies : 3 (Terramedia oy, 2026)
  • Downscaling Satellite-derived Optical Trapezoid Model with Uncrewed Aerial Vehicle Data for Peatland Water Table Monitoring
    Heikkinen, Saara; Räsänen, Aleksi; Kuzmin, Anton; Korpelainen, Pasi; Kumpula, Timo; Isoaho, Aleksi
    Journal of photogrammetry, remote sensing and geoinformation science (Springer Nature, 2026)
    Optical remote sensing, particularly satellite-derived optical trapezoid model (OPTRAM), can be used as a proxy to monitor peatland water table (WT), a key determinant for peatland condition. So far, OPTRAM has been used only in temporal monitoring of WT at coarse spatial resolution while it has not been tested to detect spatial patterns of WT in spatially heterogeneous northern peatlands. To address the abovementioned gap, we downscale four differently parameterized Sentinel‑2 OPTRAMs with the help of optical, thermal, and topographic uncrewed aerial vehicle (UAV) variables and random forest modeling in two open peatlands in northern Finland covered by spatially extensive field measurements of WT (n = 95). We (1) assess how parameterization of OPTRAM affects OPTRAM-WT correlation, (2) test whether downscaled OPTRAM correlates stronger with WT than the original OPTRAM, and (3) compare OPTRAM to other remote sensing variables calculated from Sentinel‑2 and UAV data. Our results showed that OPTRAM parameterization strongly affects OPTRAM-WT correlation, with Spearman correlation (rs) ranging between 0.23–0.53. Random forest-based downscaling models had a relatively high explained variance (45.6–72.4%). Downscaling increased rs by 0.09–0.16 units, up to 0.62 with the best-performing parameterization, and revealed the spatial patterns of WT more realistically than Sentinel‑2 OPTRAM. Other UAV and Sentinel-2 variables had differing correlations with WT, with greenness and water cover indices having stronger correlations with WT than OPTRAM (|rs| up to 0.67). Our results encourage the use of downscaling methods at high spatial resolutions and integrating multi-sensor and machine learning methods to generate high spatial and temporal resolution peatland WT monitoring approaches.
  • Playgrounds as microbial interfaces: strategies to enhance soil microbiomes and support healthy childhoods
    Manninen, Juulia; Korhonen, Aku; Johnson, Karen L.; Tahvonen, Outi; Luukkonen, Anna; Saarenpää, Mika; Puhakka, Riikka; Uimonen, Laura; Kummola, Laura; Skevaki, Chrysanthi; Renz, Harald; Rajaniemi, Juho; Laitinen, Olli H.; Roslund, Marja I.
    MSystems (American Society for Microbiology, 2026)
  • Changes in plant protection in Finnish open field vegetable production in the 21st century : The importance of regulation and ecotoxicological information
    Räsänen, Kati
    Publications of the University of Eastern Finland : dissertations in Science, Forestry and Technology : 138 (Itä-Suomen yliopisto, 2026)