K
Katja Kowalski
Researcher at Humboldt University of Berlin
Publications - 5
Citations - 80
Katja Kowalski is an academic researcher from Humboldt University of Berlin. The author has contributed to research in topics: Normalized Difference Vegetation Index & Grassland. The author has an hindex of 2, co-authored 4 publications receiving 27 citations.
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Characterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series
TL;DR: Estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series and EVI-based SOS showed higher correlation with ground observations compared to NDVI, and data density played an important role in estimating land surface phenology.
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Quantifying drought effects in Central European grasslands through regression-based unmixing of intra-annual Sentinel-2 time series
TL;DR: In this article, a regression-based unmixing framework was used to quantified the impact of severe droughts on grasslands in Central Europe in 2018 and 2019, and a Normalized Difference Fraction Index (NDFI) was derived based on the fractional cover estimates, contrasting NPV and soil cover relative to PV.
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Estimating Grassland Parameters from Sentinel-2: A Model Comparison Study
Marcel Schwieder,Marion Buddeberg,Katja Kowalski,Kira Pfoch,Julia Bartsch,Heike Bach,Jürgen Pickert,Patrick Hostert +7 more
TL;DR: In this paper, the authors compared two well-established methods to calculate the aboveground biomass and leaf area index (LAI), first using a random forest regression and second using the soil-leaf-canopy (SLC) radiative transfer model.
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Impacts of cutting frequency and position to tree line on herbage accumulation in silvopastoral grassland reveal potential for grassland conservation based on land use and cover information
Andrea Schmiedgen,Martin Komainda,Katja Kowalski,Patrick Hostert,Bettina Tonn,Manfred Kayser,Manfred Kayser,Johannes Isselstein +7 more
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A generalized framework for drought monitoring across Central European grassland gradients with Sentinel-2 time series
TL;DR: In this paper , a generalized spectral unmixing framework for Central European grasslands is proposed, which combines the spectral variability of photosynthetic vegetation (PV, NPV, and soil cover from 12 grassland areas distributed along typical environmental and land use gradients of Central Europe.