C. Schmullius

937 total citations
33 papers, 715 citations indexed

About

C. Schmullius is a scholar working on Environmental Engineering, Atmospheric Science and Aerospace Engineering. According to data from OpenAlex, C. Schmullius has authored 33 papers receiving a total of 715 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Environmental Engineering, 16 papers in Atmospheric Science and 15 papers in Aerospace Engineering. Recurrent topics in C. Schmullius's work include Remote Sensing and LiDAR Applications (16 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (15 papers) and Cryospheric studies and observations (9 papers). C. Schmullius is often cited by papers focused on Remote Sensing and LiDAR Applications (16 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (15 papers) and Cryospheric studies and observations (9 papers). C. Schmullius collaborates with scholars based in Germany, Austria and Switzerland. C. Schmullius's co-authors include Sören Hese, Christian Berger, Michael Voltersen, Christian Thiel, Wolfgang Lucht, А. Shvidenko, Maurizio Santoro, Christian Beer, Andreas Wiesmann and Kathleen Neumann and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Geophysical Research Letters.

In The Last Decade

C. Schmullius

27 papers receiving 680 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. Schmullius Germany 11 503 308 201 185 152 33 715
Sören Hese Germany 14 514 1.0× 410 1.3× 248 1.2× 206 1.1× 181 1.2× 42 899
Angela Erb United States 12 322 0.6× 423 1.4× 284 1.4× 291 1.6× 71 0.5× 23 717
Vicente García‐Santos Spain 16 486 1.0× 303 1.0× 310 1.5× 187 1.0× 60 0.4× 26 691
Pierre Guillevic United States 18 762 1.5× 528 1.7× 467 2.3× 327 1.8× 34 0.2× 31 1.0k
Zhao-Liang Li China 8 648 1.3× 324 1.1× 535 2.7× 128 0.7× 36 0.2× 17 888
Tamás Jancsó Hungary 10 204 0.4× 446 1.4× 114 0.6× 160 0.9× 132 0.9× 26 642
Donald E. Sabol United States 6 300 0.6× 196 0.6× 181 0.9× 205 1.1× 39 0.3× 12 555
Nicolas Lauret France 17 874 1.7× 575 1.9× 146 0.7× 907 4.9× 55 0.4× 50 1.3k
Joan M. Galve Spain 17 983 2.0× 471 1.5× 700 3.5× 177 1.0× 91 0.6× 29 1.3k
Javier Muro Germany 13 196 0.4× 337 1.1× 112 0.6× 249 1.3× 38 0.3× 23 553

Countries citing papers authored by C. Schmullius

Since Specialization
Citations

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

Fields of papers citing papers by C. Schmullius

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. Schmullius

This figure shows the co-authorship network connecting the top 25 collaborators of C. Schmullius. A scholar is included among the top collaborators of C. Schmullius 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 C. Schmullius. C. Schmullius 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.
Toit, Justin du, Jussi Baade, Andreas Kaiser, et al.. (2020). A Multi-Scale Remote Sensing Approach to Understanding Vegetation Dynamics in the Nama Karoo-Grassland Ecotone of South Africa. elib (German Aerospace Center). 4501–4504. 2 indexed citations
2.
3.
Eberle, Jonas & C. Schmullius. (2017). DUE GlobBiomass - Estimates of Biomass on a Global Scale. AGU Fall Meeting Abstracts. 2017.
4.
Berger, Christian, et al.. (2017). Spatio-temporal analysis of the relationship between 2D/3D urban site characteristics and land surface temperature. Remote Sensing of Environment. 193. 225–243. 254 indexed citations
5.
McCallum, Ian, Oskar Franklin, Elena Moltchanova, et al.. (2013). Improved light and temperature responses for light-use-efficiency-based GPP models. Biogeosciences. 10(10). 6577–6590. 37 indexed citations
6.
Hese, Sören, et al.. (2013). LAND COVER CLASSIFICATION OF SATELLITE IMAGES USING CONTEXTUAL INFORMATION. SHILAP Revista de lepidopterología. II-3/W1. 1–6. 39 indexed citations
7.
Schepaschenko, Dmitry, Linda See, Steffen Fritz, et al.. (2012). Observing forest biomass globally. IIASA PURE (International Institute of Applied Systems Analysis). 4 indexed citations
8.
Shvidenko, А., Dmitry Schepaschenko, Ian McCallum, Maurizio Santoro, & C. Schmullius. (2011). USE OF REMOTE SENSING PRODUCTS IN A TERRESTRIAL ECOSYSTEMS VERIFIED FULL CARBON ACCOUNT: EXPERIENCES FROM RUSSIA. ESASP. 688. 14. 3 indexed citations
9.
Schmullius, C., Johannes Reiche, Reik Leiterer, et al.. (2010). Forest Dragon 2: Mid-term results of the European partners. Zurich Open Repository and Archive (University of Zurich). 684(684). 55. 1 indexed citations
10.
Quegan, S., Christian Beer, А. Shvidenko, et al.. (2010). Estimating the carbon balance of central Siberia using a landscape-ecosystem approach, atmospheric inversion and Dynamic Global Vegetation Models. Global Change Biology. 17(1). 351–365. 33 indexed citations
11.
Schmullius, C., Alexandre Bouvet, Oliver Cartus, et al.. (2006). MID-TERM STATUS OF THE FOREST DRAGON PROJECT. ESASP. 611. 1 indexed citations
12.
Eriksson, Leif E. B., et al.. (2005). Forest change detection with spaceborne L-band SAR. Chalmers Publication Library (Chalmers University of Technology).
13.
Li, Zengyuan, Yong Pang, C. Schmullius, & Maurizio Santoro. (2005). Forest mapping using ENVISAT and ERS SAR data in Northeast of China. 8. 5670–5673. 7 indexed citations
14.
Hese, Sören, Wolfgang Lucht, C. Schmullius, et al.. (2004). Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D. Remote Sensing of Environment. 94(1). 94–104. 104 indexed citations
15.
Eriksson, Leif E. B., Maurizio Santoro, C. Schmullius, & Andreas Wiesmann. (2004). The potential of ALOS single polarization INSAR for estimation of growing stock volume in Boreal forest. 3. 1939–1941. 1 indexed citations
16.
Eriksson, Leif E. B., Thuy Le Toan, Andreas Wiesmann, et al.. (2004). SAR Repeat-Pass Coherence in Winter for Boreal Forest Applications. A First Comparison between ASAR and JERS-1 SAR. 550. 32.
17.
18.
Eriksson, Leif E. B., Maurizio Santoro, Andreas Wiesmann, & C. Schmullius. (2003). Multitemporal jers repeat-pass coherence for growing-stock volume estimation of siberian forest. IEEE Transactions on Geoscience and Remote Sensing. 41(7). 1561–1570. 39 indexed citations
19.
Schmullius, C., W. C. Wagner, Achim Roth, et al.. (1999). SIBERIA-SAR imaging for boreal ecology and radar interferometry applications. IIASA PURE (International Institute of Applied Systems Analysis). 18 indexed citations
20.
Schmullius, C., Andrés Holz, & R. Zimmermann. (1998). SIBERIA-first ERS tandem results from the IGBP boreal forest transect. 1. 1815–1817 vol.4. 3 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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