Marcel Schwieder

1.6k total citations · 1 hit paper
35 papers, 1.2k citations indexed

About

Marcel Schwieder is a scholar working on Ecology, Global and Planetary Change and Ecological Modeling. According to data from OpenAlex, Marcel Schwieder has authored 35 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Ecology, 23 papers in Global and Planetary Change and 11 papers in Ecological Modeling. Recurrent topics in Marcel Schwieder's work include Remote Sensing in Agriculture (27 papers), Land Use and Ecosystem Services (21 papers) and Species Distribution and Climate Change (11 papers). Marcel Schwieder is often cited by papers focused on Remote Sensing in Agriculture (27 papers), Land Use and Ecosystem Services (21 papers) and Species Distribution and Climate Change (11 papers). Marcel Schwieder collaborates with scholars based in Germany, Brazil and United States. Marcel Schwieder's co-authors include Patrick Hostert, Pedro J. Leitão, Stefan Erasmi, Claas Nendel, Stefan Suess, Sebastian van der Linden, Dirk Pflugmacher, Lukas Blickensdörfer, Andreas Rabe and Akpona Okujeni and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and IEEE Access.

In The Last Decade

Marcel Schwieder

34 papers receiving 1.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany

2021 235 citations Lukas Blickensdörfer, Marcel Schwieder et al. Remote Sensing of Environment profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Marcel Schwieder Germany	16	887	510	385	238	213	35	1.2k
Laurence Hubert‐Moy France	21	818 0.9×	615 1.2×	430 1.1×	193 0.8×	187 0.9×	80	1.5k
David Morin France	13	1.2k 1.3×	618 1.2×	548 1.4×	266 1.1×	291 1.4×	26	1.5k
Valerie J. Pasquarella United States	13	758 0.9×	673 1.3×	345 0.9×	220 0.9×	118 0.6×	27	1.3k
Ran Meng China	24	1.0k 1.2×	865 1.7×	598 1.6×	253 1.1×	114 0.5×	45	1.6k
Julie Betbeder France	18	840 0.9×	507 1.0×	467 1.2×	232 1.0×	147 0.7×	39	1.3k
Zixiao Jiang China	4	1.4k 1.5×	744 1.5×	699 1.8×	267 1.1×	118 0.6×	10	1.7k
H.K. Zhang United States	5	900 1.0×	782 1.5×	462 1.2×	286 1.2×	156 0.7×	7	1.4k
Xiangqin Wei China	23	1.1k 1.3×	872 1.7×	583 1.5×	407 1.7×	275 1.3×	50	1.9k
Marcela Arias France	6	852 1.0×	420 0.8×	335 0.9×	250 1.1×	305 1.4×	8	1.1k
Ruyin Cao China	19	1.1k 1.2×	764 1.5×	542 1.4×	468 2.0×	148 0.7×	45	1.6k

Countries citing papers authored by Marcel Schwieder

Since Specialization

Citations

This map shows the geographic impact of Marcel Schwieder's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcel Schwieder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel Schwieder more than expected).

Fields of papers citing papers by Marcel Schwieder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcel Schwieder. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcel Schwieder. The network helps show where Marcel Schwieder may publish in the future.

Co-authorship network of co-authors of Marcel Schwieder

This figure shows the co-authorship network connecting the top 25 collaborators of Marcel Schwieder. A scholar is included among the top collaborators of Marcel Schwieder based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcel Schwieder. Marcel Schwieder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Schwieder, Marcel, et al.. (2025). Unveiling year-round cropland cover by soil-specific spectral unmixing of Landsat and Sentinel-2 time series. Remote Sensing of Environment. 318. 114594–114594. 4 indexed citations

Muro, Javier, Lukas Blickensdörfer, Axel Don, et al.. (2025). Hedgerow mapping with high resolution satellite imagery to support policy initiatives at national level. Remote Sensing of Environment. 328. 114870–114870. 1 indexed citations

Klimek, Sebastian, Marcel Schwieder, Norbert Röder, et al.. (2024). Woody semi‐natural habitats modulate the effects of field size and functional crop diversity on farmland birds. Journal of Applied Ecology. 61(5). 987–999. 8 indexed citations

Hemmerling, Jan, et al.. (2024). Multi-Modal Vision Transformers for Crop Mapping from Satellite Image Time Series. OpenAgrar. 1937–1941. 1 indexed citations

Viet, Nguyen Duc, et al.. (2024). An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022. Scientific Data. 11(1). 1242–1242.

Schwieder, Marcel, et al.. (2023). A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level. Remote Sensing of Environment. 298. 113800–113800. 29 indexed citations

Schwieder, Marcel, et al.. (2023). Comparison of an Optimised Multiresolution Segmentation Approach with Deep Neural Networks for Delineating Agricultural Fields from Sentinel-2 Images. PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science. 91(4). 295–312. 13 indexed citations

Weber, Dominique, Marcel Schwieder, Achilleas Psomas, et al.. (2023). Grassland‐use intensity maps for Switzerland based on satellite time series: Challenges and opportunities for ecological applications. Remote Sensing in Ecology and Conservation. 10(3). 312–327. 12 indexed citations

Rufin, Philippe, Daniel Müller, Marcel Schwieder, Dirk Pflugmacher, & Patrick Hostert. (2021). Landsat time series reveal simultaneous expansion and intensification of irrigated dry season cropping in Southeastern Turkey. Journal of Land Use Science. 16(1). 94–110. 11 indexed citations

10.

Gocht, Alexander, et al.. (2021). Evaluation of Sentinel-1 and Sentinel-2 Feature Sets for Delineating Agricultural Fields in Heterogeneous Landscapes. IEEE Access. 9. 116702–116719. 13 indexed citations

11.

Gocht, Alexander, et al.. (2020). Unsupervised Parameterization for Optimal Segmentation of Agricultural Parcels from Satellite Images in Different Agricultural Landscapes. Remote Sensing. 12(18). 3096–3096. 13 indexed citations

12.

Bendini, Hugo do Nascimento, Leila María García Fonseca, Philippe Rufin, et al.. (2020). Applying A Phenological Object-Based Image Analysis (Phenobia) for Agricultural Land Classification: A Study Case in the Brazilian Cerrado. 1078–1081. 2 indexed citations

13.

Bendini, Hugo do Nascimento, Leila María García Fonseca, Marcel Schwieder, et al.. (2020). COMBINING ENVIRONMENTAL AND LANDSAT ANALYSIS READY DATA FOR VEGETATION MAPPING: A CASE STUDY IN THE BRAZILIAN SAVANNA BIOME. SHILAP Revista de lepidopterología. XLIII-B3-2020. 953–960. 12 indexed citations

14.

Bendini, Hugo do Nascimento, Leila María García Fonseca, Marcel Schwieder, et al.. (2019). Comparing Phenometrics Extracted From Dense Landsat-Like Image Time Series for Crop Classification. 10. 469–472. 2 indexed citations

15.

Leitão, Pedro J., Marcel Schwieder, Fernando Pedroni, et al.. (2018). Mapping woody plant community turnover with space‐borne hyperspectral data – a case study in the Cerrado. Remote Sensing in Ecology and Conservation. 5(1). 107–115. 6 indexed citations

16.

Leitão, Pedro J., Marcel Schwieder, Florian Pötzschner, et al.. (2018). From sample to pixel: multi‐scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes. Ecosphere. 9(8). 27 indexed citations

17.

Leitão, Pedro J., Marcel Schwieder, & Cornelius Senf. (2017). sgdm: An R Package for Performing Sparse Generalized Dissimilarity Modelling with Tools for gdm. ISPRS International Journal of Geo-Information. 6(1). 23–23. 8 indexed citations

18.

Schwieder, Marcel, et al.. (2015). Mapping Cerrado physiognomies using Landsat time series based phenological profiles. Biblioteca Digital da Memória Científica do INPE (National Institute for Space Research). 2 indexed citations

19.

Suess, Stefan, Sebastian van der Linden, Akpona Okujeni, et al.. (2015). Using Class Probabilities to Map Gradual Transitions in Shrub Vegetation from Simulated EnMAP Data. Remote Sensing. 7(8). 10668–10688. 20 indexed citations

20.

Buchhorn, Marcel, Donald A. Walker, Birgit Heim, et al.. (2013). Ground-Based Hyperspectral Characterization of Alaska Tundra Vegetation along Environmental Gradients. Remote Sensing. 5(8). 3971–4005. 35 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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