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Institute of

AK Climate-Smart Agriculture

Peer-reviewed scientific paper by Tom Brög

  1. 0

    Brög T, Don A, Scholten T, Erasmi S (2026) Reducing bias in cropland soil organic carbon and clay predictions using Sentinel-2 composites and data balancing. Remote Sens Environ 333:115109, DOI:10.1016/j.rse.2025.115109

    https://literatur.thuenen.de/digbib_extern/dn070359.pdf

  2. 1

    Lobert F, Schwieder M, Alsleben J, Brög T, Kowalski K, Okujeni A, Hostert P, Erasmi S (2025) Unveiling year-round cropland cover by soil-specific spectral unmixing of Landsat and Sentinel-2 time series. Remote Sens Environ 318:114594, DOI:10.1016/j.rse.2024.114594

    https://literatur.thuenen.de/digbib_extern/dn069411.pdf

  3. 2

    Brög T, Don A, Wiesmeier M, Scholten T, Erasmi S (2024) Spatiotemporal monitoring of cropland soil organic carbon changes from space. Global Change Biol 30(12):e17608, DOI:10.1111/gcb.17608

    https://literatur.thuenen.de/digbib_extern/dn069232.pdf

  4. 3

    Brög T, Don A, Gocht A, Scholten T, Taghizadeh-Mehrjardi R, Erasmi S (2024) Using local ensemble models and Landsat bare soil composites for large-scale soil organic carbon maps in cropland. Geoderma 444:116850, DOI:10.1016/j.geoderma.2024.116850

    https://literatur.thuenen.de/digbib_extern/dn067810.pdf

  5. 4

    Brög T, Blaschek M, Seitz S, Taghizadeh-Mehrjardi R, Zepp S, Scholten T (2023) Transferability of covariates to predict soil organic carbon in cropland soils. Remote Sensing 15(4):876, DOI:10.3390/rs15040876

    https://literatur.thuenen.de/digbib_extern/dn066098.pdf

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