Matthias Dees

689 total citations
26 papers, 475 citations indexed

About

Matthias Dees is a scholar working on Environmental Engineering, Ecology and Nature and Landscape Conservation. According to data from OpenAlex, Matthias Dees has authored 26 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Environmental Engineering, 12 papers in Ecology and 8 papers in Nature and Landscape Conservation. Recurrent topics in Matthias Dees's work include Remote Sensing and LiDAR Applications (13 papers), Remote Sensing in Agriculture (10 papers) and Forest ecology and management (8 papers). Matthias Dees is often cited by papers focused on Remote Sensing and LiDAR Applications (13 papers), Remote Sensing in Agriculture (10 papers) and Forest ecology and management (8 papers). Matthias Dees collaborates with scholars based in Germany, Pakistan and Austria. Matthias Dees's co-authors include Barbara Koch, Pawan Datta, Sami Ullah, Holger Weinacker, Marcus Lindner, Joanne Fitzgerald, Sergey Zudin, Geerten Hengeveld, Pieter Johannes Verkerk and Mathias Schardt and has published in prestigious journals such as International Journal of Remote Sensing, Remote Sensing and Biodiversity and Conservation.

In The Last Decade

Matthias Dees

25 papers receiving 451 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthias Dees Germany 13 261 216 193 141 78 26 475
E. O. Figueiredo Brazil 13 265 1.0× 216 1.0× 168 0.9× 178 1.3× 63 0.8× 45 523
Alfonso Fernández-Sarría Spain 13 345 1.3× 275 1.3× 157 0.8× 165 1.2× 66 0.8× 29 642
Tomáš Bucha Slovakia 16 232 0.9× 227 1.1× 233 1.2× 213 1.5× 132 1.7× 37 553
Juan Picos Spain 13 169 0.6× 257 1.2× 187 1.0× 104 0.7× 47 0.6× 45 482
Ivan Balenović Croatia 14 378 1.4× 200 0.9× 114 0.6× 174 1.2× 119 1.5× 43 525
Shaban Shataee Iran 14 364 1.4× 360 1.7× 193 1.0× 230 1.6× 32 0.4× 47 608
Diego Giuliarelli Italy 13 149 0.6× 146 0.7× 149 0.8× 121 0.9× 113 1.4× 23 367
Russell Turner Australia 12 240 0.9× 174 0.8× 85 0.4× 155 1.1× 85 1.1× 17 352
Glenn P. Catts United States 6 328 1.3× 231 1.1× 135 0.7× 120 0.9× 91 1.2× 11 470
Adrián Pascual United States 16 548 2.1× 316 1.5× 272 1.4× 374 2.7× 108 1.4× 44 686

Countries citing papers authored by Matthias Dees

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Dees

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Dees

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Dees. A scholar is included among the top collaborators of Matthias Dees 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 Matthias Dees. Matthias Dees 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.
Ullah, Sami, Matthias Dees, Pawan Datta, et al.. (2019). Potential of Modern Photogrammetry Versus Airborne Laser Scanning for Estimating Forest Variables in a Mountain Environment. Remote Sensing. 11(6). 661–661. 8 indexed citations
2.
Ullah, Sami, et al.. (2019). Evaluating the potential of sentinel-2, landsat-8, and irs satellite images in tree species classification of hyrcanian forest of iran using random forest. Journal of Sustainable Forestry. 38(7). 615–628. 25 indexed citations
3.
Pirker, J., et al.. (2019). Determining a Carbon Reference Level for a High-Forest-Low-Deforestation Country. Forests. 10(12). 1095–1095. 6 indexed citations
4.
Tuomasjukka, Diana, Marcus Lindner, Dimitris Athanassiadis, et al.. (2018). Sustainability impacts of increased forest biomass feedstock supply – a comparative assessment of technological solutions. International Journal of Forest Engineering. 29(2). 99–116. 12 indexed citations
5.
Latifi, Hooman, et al.. (2018). Integrating LiDAR and high-resolution imagery for object-based mapping of forest habitats in a heterogeneous temperate forest landscape. International Journal of Remote Sensing. 39(23). 8859–8884. 39 indexed citations
6.
Dees, Matthias, B.S. Elbersen, John F. Fitzgerald, et al.. (2017). Atlas with regional cost supply biomass potentials for EU 28, Western Balkan countries, Moldavia, Turkey and Ukraine. Jukuri (Natural Resources Institute Finland (Luke)). 15 indexed citations
7.
Hirschmugl, Manuela, Heinz Gallaun, Matthias Dees, et al.. (2017). Review of Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data.. arXiv (Cornell University).
8.
Ullah, Sami, Matthias Dees, Pawan Datta, Petra Adler, & Barbara Koch. (2017). Comparing Airborne Laser Scanning, and Image-Based Point Clouds by Semi-Global Matching and Enhanced Automatic Terrain Extraction to Estimate Forest Timber Volume. Forests. 8(6). 215–215. 25 indexed citations
9.
Hirschmugl, Manuela, Heinz Gallaun, Matthias Dees, et al.. (2017). Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review. Current Forestry Reports. 3(1). 32–45. 66 indexed citations
10.
11.
Dees, Matthias, B.S. Elbersen, John F. Fitzgerald, et al.. (2017). Atlas With Regional Cost Supply Biomass Potentials For Eu 28, Western Balkan Countries, Moldavia, Turkey And Ukraine. S2Biom Project Report 1.8. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
12.
Ullah, Sami, Petra Adler, Matthias Dees, et al.. (2017). Comparing image-based point clouds and airborne laser scanning data for estimating forest heights. iForest - Biogeosciences and Forestry. 10(1). 273–280. 12 indexed citations
13.
Pantaleo, Antonio, et al.. (2016). D8.1 Overview report on the current status of biomass for bioenergy, biofuels and biomaterials in Europe. Socio-Environmental Systems Modeling. 1 indexed citations
14.
Dees, Matthias, et al.. (2014). Analysis of the growth characteristics of a 450-year-old silver fir tree. Archives of Biological Sciences. 67(1). 155–160. 2 indexed citations
15.
Dees, Matthias, et al.. (2012). Status of forest resources of Montenegro.. The Journal Agriculture and Forestry. 57(3). 39–52. 4 indexed citations
16.
Straub, Christoph, Matthias Dees, Holger Weinacker, & Barbara Koch. (2009). Using Airborne Laser Scanner Data and CIR Orthophotos to Estimate the Stem Volume of Forest Stands. Photogrammetrie - Fernerkundung - Geoinformation. 2009(3). 277–287. 23 indexed citations
17.
Koch, Barbara, et al.. (2009). Airborne laser data for stand delineation and information extraction. International Journal of Remote Sensing. 30(4). 935–963. 52 indexed citations
18.
Koch, Barbara, Markus Jochum, Éva Ivits, & Matthias Dees. (2003). Pixelbasierte Klassifizierung im Vergleich und zur Ergänzung zum objektbasierten Verfahren. FreiDok plus (Universitätsbibliothek Freiburg). 4 indexed citations
19.
Dees, Matthias, et al.. (2000). COMBINING REMOTE SENSING DATA SOURCES AND TERRESTRIAL SAMPLE-BASED INVENTORY DATA FOR THE USE IN FOREST MANAGEMENT INVENTORIES. FreiDok plus (Universitätsbibliothek Freiburg). 4 indexed citations
20.
Kleinn, Christoph, et al.. (1996). Calibrating AVHRR Tropical Forest Area Estimates with TM Sample Images. DORA WSL (Swiss Federal Institute for Forest, Snow and Landscape Research). 229–239. 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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