Weiter zum Inhalt
Landwirtschaftliche geprägte Landschaft, im Vordergrund eine Bank, im Hintergrund ein Ort
Landwirtschaftliche geprägte Landschaft, im Vordergrund eine Bank, im Hintergrund ein Ort
Institut für

LV Lebensverhältnisse in ländlichen Räumen

Alle Publikationen am Thünen-Institut von Ann-Kathrin Holtgrave

  1. 0

    Wallis CIB, Holtgrave A-K, Prati D, Förster M, Kleinschmit B (2025) Modeling grassland parameters with hyperspectral satellite data : comparison of sensors, acquisition times and spectral transformations. Int J Appl Earth Observ Geoinf 144:104857, DOI:10.1016/j.jag.2025.104857

    https://literatur.thuenen.de/digbib_extern/dn070474.pdf

  2. 1

    Holtgrave A-K, Lobert F, Erasmi S, Röder N, Kleinschmit B (2023) Grassland mowing event detection using combined optical, SAR, and weather time series. Remote Sens Environ 295:113680, DOI:10.1016/j.rse.2023.113680

    https://literatur.thuenen.de/digbib_extern/dn066527.pdf

  3. 2

    Holtgrave A-K, Förster M, Rossi M, Morel J, Ali I, Burchard-Levine V, Raya Serano MD, Fastnacht F, Rocchini D, Schwieder M, Hostert P, Kleinschmit B (2023) Remote sensing indices for environmental grassland monitoring in Europe. In: Brückner D, Kietzmann K (eds) Book of abstracts : 52nd Annual Meeting of the Ecological Society of Germany, Austria and Switzerland ; Leipzig - 12-16 September 2023. Berlin: Gesellschaft für Ökologie, p 697

  4. 3

    Lobert F, Holtgrave A-K, Schwieder M, Pause M, Gocht A, Vogt J, Erasmi S (2021) Detection of mowing events from combined Sentinel-1, Sentinel-2, and Landsat 8 time series with machine learning. Grassl Sci Europe 26:123-125

  5. 4

    Schulz C, Holtgrave A-K, Kleinschmit B (2021) Large-scale winter catch crop monitoring with Sentinel-2 time series and machine learning - An alternative to on-site controls? Comput Electron Agric 186:106173, DOI:10.1016/j.compag.2021.106173

  6. 5

    Lobert F, Holtgrave A-K, Schwieder M, Pause M, Vogt J, Gocht A, Erasmi S (2021) Mowing event detection in permanent grasslands: Systematic evaluation of input features from Sentinel-1, Sentinel-2, and Landsat 8 time series. Remote Sens Environ 267:112751, DOI:10.1016/j.rse.2021.112751

    https://literatur.thuenen.de/digbib_extern/dn064075.pdf

  7. 6

    Holtgrave A-K, Röder N, Ackermann A, Erasmi S, Kleinschmit B (2020) Comparing Sentinel-1 and -2 data and indices for agricultural land use monitoring. Remote Sensing 12:2919, DOI:10.3390/rs12182919

    https://literatur.thuenen.de/digbib_extern/dn062663.pdf

  8. 7

    Holtgrave A-K, Ackermann A, Röder N, Kleinschmit B (2020) Towards a dual-polarisation radar vegetation index for Sentinel-1 for grassland monitoring. Grassl Sci Europe 25:596-598

  9. 8

    Holtgrave A-K, Röder N, Kleinschmit B (2019) Detecting grassland management strategies with sentinel-1 and fuzzy data in different regions of Germany. In: Living Planet Symposium, Milan (Italy), May 13-17 2019.

    Nach oben