Michael Schlund

1.4k total citations
35 papers, 529 citations indexed

About

Michael Schlund is a scholar working on Environmental Engineering, Ecology and Aerospace Engineering. According to data from OpenAlex, Michael Schlund has authored 35 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Environmental Engineering, 14 papers in Ecology and 14 papers in Aerospace Engineering. Recurrent topics in Michael Schlund's work include Remote Sensing and LiDAR Applications (20 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (14 papers) and Remote Sensing in Agriculture (12 papers). Michael Schlund is often cited by papers focused on Remote Sensing and LiDAR Applications (20 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (14 papers) and Remote Sensing in Agriculture (12 papers). Michael Schlund collaborates with scholars based in Germany, Netherlands and Indonesia. Michael Schlund's co-authors include Stefan Erasmi, Malcolm Davidson, Christiane Schmullius, D.H. Hoekman, Klaus Scipal, Paul Magdon, S. Quegan, Nicolò Camarretta, Arne Wenzel and Brian Eaton and has published in prestigious journals such as Science, Remote Sensing of Environment and Geophysical Research Letters.

In The Last Decade

Michael Schlund

32 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Schlund Germany 14 337 214 205 119 109 35 529
F. G. Gonçalves Brazil 13 315 0.9× 182 0.9× 180 0.9× 143 1.2× 70 0.6× 38 523
P. Saich United Kingdom 7 355 1.1× 224 1.0× 160 0.8× 95 0.8× 107 1.0× 20 451
Takeshi Motooka Japan 6 349 1.0× 348 1.6× 144 0.7× 280 2.4× 102 0.9× 17 630
Matthew Brolly United Kingdom 10 436 1.3× 361 1.7× 88 0.4× 158 1.3× 37 0.3× 26 557
Franklin B. Sullivan United States 12 336 1.0× 195 0.9× 63 0.3× 133 1.1× 108 1.0× 22 508
Gulab Singh India 13 200 0.6× 101 0.5× 135 0.7× 91 0.8× 64 0.6× 31 360
Isabelle Champion France 11 392 1.2× 198 0.9× 284 1.4× 111 0.9× 238 2.2× 16 619
Amélie Beaudoin France 6 687 2.0× 255 1.2× 457 2.2× 121 1.0× 121 1.1× 6 802
Sandra Englhart Germany 7 323 1.0× 261 1.2× 118 0.6× 196 1.6× 47 0.4× 9 505
Peter Harrell United States 7 294 0.9× 218 1.0× 116 0.6× 369 3.1× 135 1.2× 10 591

Countries citing papers authored by Michael Schlund

Since Specialization
Citations

This map shows the geographic impact of Michael Schlund'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 Michael Schlund with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Schlund more than expected).

Fields of papers citing papers by Michael Schlund

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Schlund. 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 Michael Schlund. The network helps show where Michael Schlund may publish in the future.

Co-authorship network of co-authors of Michael Schlund

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Schlund. A scholar is included among the top collaborators of Michael Schlund 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 Michael Schlund. Michael Schlund is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schlund, Michael. (2025). Potential of Sentinel-1 time-series data for monitoring the phenology of European temperate forests. ISPRS Journal of Photogrammetry and Remote Sensing. 223. 131–145. 2 indexed citations
2.
Skidmore, Andrew K., et al.. (2025). Investigating LiDAR Metrics for Old-Growth Beech- and Spruce-Dominated Forest Identification in Central Europe. Remote Sensing. 17(2). 251–251. 1 indexed citations
3.
4.
Siegenthaler, Andjin, et al.. (2025). Effect of forest structural attributes on soil microbial diversity in mixed temperate forests. Plant and Soil. 517(1). 867–885.
5.
Griffin, Robert, Eric Anderson, F.D. van der Meer, et al.. (2025). Leveraging educational partnerships to integrate education for sustainable development into university geoscience curriculum. International Journal of Sustainability in Higher Education. 26(9). 131–148.
6.
Camarretta, Nicolò, Martin Ehbrecht, Michael Schlund, et al.. (2024). Comparing airborne and terrestrial LiDAR with ground-based inventory metrics of vegetation structural complexity in oil palm agroforests. Ecological Indicators. 166. 112306–112306. 2 indexed citations
7.
Schlund, Michael, John Armston, Martyna M. Kotowska, et al.. (2024). Mapping aboveground biomass in Indonesian lowland forests using GEDI and hierarchical models. Remote Sensing of Environment. 313. 114384–114384. 12 indexed citations
8.
Paterno, Gustavo B., Fabian Brambach, Nathaly R. Guerrero‐Ramírez, et al.. (2024). Diverse and larger tree islands promote native tree diversity in oil palm landscapes. Science. 386(6723). 795–802. 8 indexed citations
9.
Schlund, Michael, et al.. (2024). Mapping temperate old-growth forests in Central Europe using ALS and Sentinel-2A multispectral data. Environmental Monitoring and Assessment. 196(9). 841–841. 3 indexed citations
10.
Schlund, Michael, et al.. (2023). Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change. PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science. 91(2). 107–123. 2 indexed citations
11.
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
12.
Schlund, Michael, Arne Wenzel, Nicolò Camarretta, Christian Stiegler, & Stefan Erasmi. (2022). Vegetation canopy height estimation in dynamic tropical landscapes with TanDEM‐X supported by GEDI data. Methods in Ecology and Evolution. 14(7). 1639–1656. 15 indexed citations
13.
Camarretta, Nicolò, Martin Ehbrecht, Arne Wenzel, et al.. (2021). Using Airborne Laser Scanning to characterize different land uses in a tropical landscape based on their structural complexity. 4 indexed citations
14.
Camarretta, Nicolò, Martin Ehbrecht, Dominik Seidel, et al.. (2021). Using Airborne Laser Scanning to Characterize Land-Use Systems in a Tropical Landscape Based on Vegetation Structural Metrics. Remote Sensing. 13(23). 4794–4794. 15 indexed citations
15.
Schlund, Michael, et al.. (2021). Potential of Sentinel-1 Time Series Data for the Estimation of Season Length in Winter Wheat Phenology. University of Twente Research Information. 5917–5920. 2 indexed citations
16.
Schlund, Michael, et al.. (2021). Assessment of linear relationships between TanDEM-X coherence and canopy height as well as aboveground biomass in tropical forests. International Journal of Remote Sensing. 42(9). 3405–3425. 6 indexed citations
17.
Erasmi, Stefan, et al.. (2019). Sensitivity of Bistatic TanDEM-X Data to Stand Structural Parameters in Temperate Forests. Remote Sensing. 11(24). 2966–2966. 6 indexed citations
18.
Joetzjer, Émilie, Michiel Pillet, P. Ciais, et al.. (2017). Assimilating satellite‐based canopy height within an ecosystem model to estimate aboveground forest biomass. Geophysical Research Letters. 44(13). 6823–6832. 13 indexed citations
19.
Schlund, Michael, et al.. (2016). TanDEM-X elevation model data for canopy height and aboveground biomass retrieval in a tropical peat swamp forest. International Journal of Remote Sensing. 37(21). 5021–5044. 24 indexed citations
20.
Bargiel, Damian, et al.. (2014). Classification of crops in different European regions based on TerraSAR-X data. 1–4. 1 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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