Björn Waske

5.8k total citations · 3 hit papers
76 papers, 4.5k citations indexed

About

Björn Waske is a scholar working on Ecology, Media Technology and Environmental Engineering. According to data from OpenAlex, Björn Waske has authored 76 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Ecology, 40 papers in Media Technology and 28 papers in Environmental Engineering. Recurrent topics in Björn Waske's work include Remote-Sensing Image Classification (40 papers), Remote Sensing in Agriculture (39 papers) and Remote Sensing and Land Use (21 papers). Björn Waske is often cited by papers focused on Remote-Sensing Image Classification (40 papers), Remote Sensing in Agriculture (39 papers) and Remote Sensing and Land Use (21 papers). Björn Waske collaborates with scholars based in Germany, Iceland and France. Björn Waske's co-authors include Jón Atli Benediktsson, Mauro Dalla Mura, Lorenzo Bruzzone, Sebastian van der Linden, Matthias Braun, Patrick Hostert, Zhenhong Li, Sicong Liu, Peijun Du and Alim Samat and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Remote Sensing of Environment.

In The Last Decade

Björn Waske

75 papers receiving 4.4k citations

Hit Papers

Morphological Attribute P... 2010 2026 2015 2020 2010 2016 2015 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Björn Waske Germany 29 2.3k 1.7k 1.6k 1.1k 1.1k 76 4.5k
Jordi Inglada France 32 2.2k 0.9× 2.3k 1.3× 1.3k 0.8× 1.1k 1.0× 1.2k 1.1× 130 5.0k
Qunming Wang China 35 2.5k 1.1× 1.8k 1.0× 1.4k 0.9× 1.2k 1.0× 1.2k 1.0× 124 4.6k
Saeid Homayouni Canada 33 1.1k 0.5× 1.6k 0.9× 1.1k 0.7× 1.4k 1.2× 1.3k 1.2× 197 4.6k
Mattia Marconcini Germany 27 2.5k 1.1× 946 0.5× 1.9k 1.2× 915 0.8× 1.6k 1.4× 106 5.2k
Lei Ma China 27 1.6k 0.7× 1.6k 0.9× 997 0.6× 1.3k 1.2× 1.4k 1.3× 88 4.4k
Yifang Ban Sweden 41 1.8k 0.8× 1.4k 0.8× 1.3k 0.8× 1.0k 0.9× 1.8k 1.6× 182 5.2k
Allan Aasbjerg Nielsen Denmark 24 2.1k 0.9× 1.2k 0.7× 1.3k 0.8× 579 0.5× 566 0.5× 124 3.9k
Luis Gómez‐Chova Spain 37 2.9k 1.2× 1.9k 1.1× 1.8k 1.1× 647 0.6× 1.1k 1.0× 136 5.4k
Prashanth Marpu United Arab Emirates 28 1.9k 0.8× 574 0.3× 1.4k 0.9× 1.1k 1.0× 621 0.6× 119 3.8k
Pingxiang Li China 31 2.3k 1.0× 765 0.4× 1.5k 1.0× 1.7k 1.5× 1.2k 1.1× 168 5.1k

Countries citing papers authored by Björn Waske

Since Specialization
Citations

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

Fields of papers citing papers by Björn Waske

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Björn Waske

This figure shows the co-authorship network connecting the top 25 collaborators of Björn Waske. A scholar is included among the top collaborators of Björn Waske 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 Björn Waske. Björn Waske 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.
Waske, Björn, et al.. (2025). Multi-Modal Vision Transformer for high-resolution soil texture prediction of German agricultural soils using remote sensing imagery. Remote Sensing of Environment. 331. 114985–114985. 3 indexed citations
2.
Jarmer, Thomas, et al.. (2025). Comparative analysis of UAV-based LiDAR and photogrammetric systems for the detection of terrain anomalies in a historical conflict landscape. Science of Remote Sensing. 11. 100191–100191. 6 indexed citations
4.
Dasgupta, Antara, et al.. (2024). Farmland quality assessment using deep learning and UAVs. Remote Sensing Applications Society and Environment. 35. 101235–101235. 1 indexed citations
5.
Beckschäfer, Philip, et al.. (2024). Individual tree detection and crown delineation in the Harz National Park from 2009 to 2022 using mask R–CNN and aerial imagery. SHILAP Revista de lepidopterología. 13. 100071–100071. 4 indexed citations
6.
Dasgupta, Antara, et al.. (2024). Towards robust validation strategies for EO flood maps. Remote Sensing of Environment. 315. 114439–114439. 3 indexed citations
7.
Foerster, Saskia, Pedro Medeiros, José Carlos de Araújo, et al.. (2021). Mapping regional surface water volume variation in reservoirs in northeastern Brazil during 2009–2017 using high-resolution satellite images. The Science of The Total Environment. 789. 147711–147711. 11 indexed citations
8.
Fenske, Kristin, Hannes Feilhauer, Michael Förster, Marion Stellmes, & Björn Waske. (2020). Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series. International Journal of Applied Earth Observation and Geoinformation. 87. 102036–102036. 12 indexed citations
9.
Muro, Javier, Adrian Strauch, Anis Guelmami, et al.. (2020). Multitemporal optical and radar metrics for wetland mapping at national level in Albania. Heliyon. 6(8). e04496–e04496. 16 indexed citations
10.
Roscher, Ribana, et al.. (2017). Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data. International Journal of Applied Earth Observation and Geoinformation. 63. 244–256. 16 indexed citations
11.
Mack, Benjamin & Björn Waske. (2016). In-depth comparisons of MaxEnt, biased SVM and one-class SVM for one-class classification of remote sensing data. Remote Sensing Letters. 8(3). 290–299. 41 indexed citations
12.
Roscher, Ribana & Björn Waske. (2014). Shapelet-based sparse image representation for landcover classification of hyperspectral data. 12. 1–6. 4 indexed citations
13.
Waske, Björn, et al.. (2010). On the influence of feature reduction for the classification of hyperspectral images based on the extended morphological profile. International Journal of Remote Sensing. 31(22). 5921–5939. 36 indexed citations
14.
Mura, Mauro Dalla, Jón Atli Benediktsson, Björn Waske, & Lorenzo Bruzzone. (2010). Morphological Attribute Profiles for the Analysis of Very High Resolution Images. IEEE Transactions on Geoscience and Remote Sensing. 48(10). 3747–3762. 584 indexed citations breakdown →
15.
Waske, Björn, Jón Atli Benediktsson, K. Arnason, & Jóhannes R. Sveinsson. (2009). Mapping of hyperspectral AVIRIS data using machine-learning algorithms. Canadian Journal of Remote Sensing. 35(sup1). S106–S116. 114 indexed citations
16.
17.
Waske, Björn & Jón Atli Benediktsson. (2008). Semi-Supervised Classifier Ensembles for Classifying Remote Sensing Data. II–105. 2 indexed citations
18.
Waske, Björn, et al.. (2007). Remote sensing data assimilation for regional crop growth modelling in the region of Bonn (Germany). 3647–3650. 3 indexed citations
19.
Waske, Björn, et al.. (2006). Random Feature Selection for Decision Tree Classification of Multi-temporal SAR Data. 20. 168–171. 13 indexed citations
20.
Bach, Heike, et al.. (2005). Methodology for the Processing of ASAR-Wide Swath Data for the Derivation of Land Surface Properties of the Mosel Catchment. 572. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026