Daniel Spengler

1.8k total citations
40 papers, 1.0k citations indexed

About

Daniel Spengler is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Daniel Spengler has authored 40 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Ecology, 17 papers in Environmental Engineering and 13 papers in Global and Planetary Change. Recurrent topics in Daniel Spengler's work include Remote Sensing in Agriculture (20 papers), Land Use and Ecosystem Services (11 papers) and Remote Sensing and LiDAR Applications (9 papers). Daniel Spengler is often cited by papers focused on Remote Sensing in Agriculture (20 papers), Land Use and Ecosystem Services (11 papers) and Remote Sensing and LiDAR Applications (9 papers). Daniel Spengler collaborates with scholars based in Germany, Switzerland and Italy. Daniel Spengler's co-authors include Sibylle Itzerott, Cornelia Weltzien, Wilbert E. Fordyce, Jo Ann Brockway, Birgit Kleinschmit, Angela Lausch, Daniel Doktor, Martin Thurner, Karl Segl and Theres Kuester and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Daniel Spengler

39 papers receiving 965 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Spengler Germany 20 517 391 226 202 137 40 1.0k
Roberto Filgueiras Brazil 16 309 0.6× 217 0.6× 212 0.9× 365 1.8× 27 0.2× 64 756
J.B. Boisvert Canada 14 277 0.5× 375 1.0× 231 1.0× 261 1.3× 11 0.1× 30 827
Alain A. Viau Canada 17 602 1.2× 506 1.3× 374 1.7× 354 1.8× 9 0.1× 64 1.4k
José González-Piqueras Spain 20 576 1.1× 372 1.0× 393 1.7× 760 3.8× 9 0.1× 59 1.3k
Bahram Daneshfar Canada 14 344 0.7× 165 0.4× 140 0.6× 260 1.3× 5 0.0× 33 700
José Carlos Neves Epiphânio Brazil 13 313 0.6× 295 0.8× 113 0.5× 130 0.6× 5 0.0× 41 560
Lamin R. Mansaray China 23 566 1.1× 404 1.0× 307 1.4× 426 2.1× 4 0.0× 46 1.3k
Mohammad Shawkat Hossain Malaysia 21 580 1.1× 245 0.6× 100 0.4× 231 1.1× 7 0.1× 61 1.3k
Yulin Zhan China 16 415 0.8× 312 0.8× 174 0.8× 333 1.6× 4 0.0× 71 942

Countries citing papers authored by Daniel Spengler

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Spengler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Spengler

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Spengler. A scholar is included among the top collaborators of Daniel Spengler 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 Daniel Spengler. Daniel Spengler 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.
Ruddick, Kevin, Agnieszka Białek, Vittorio Brando, et al.. (2024). HYPERNETS: a network of automated hyperspectral radiometers to validate water and land surface reflectance (380–1680 nm) from all satellite missions. SHILAP Revista de lepidopterología. 5. 5 indexed citations
2.
3.
Behling, Robert, et al.. (2023). Early Crop Classification via Multi-Modal Satellite Data Fusion and Temporal Attention. Remote Sensing. 15(3). 799–799. 23 indexed citations
4.
Neelmeijer, Julia, et al.. (2023). WRaINfo: An Open Source Library for Weather Radar INformation for FURUNO Weather Radars Based on Wradlib. Journal of Open Research Software. 11. 1 indexed citations
5.
Lehmann, Anthony, P. Mazzetti, Mattia Santoro, et al.. (2022). Essential earth observation variables for high-level multi-scale indicators and policies. Environmental Science & Policy. 131. 105–117. 18 indexed citations
6.
Itzerott, Sibylle, et al.. (2021). Suitability of satellite remote sensing data for yield estimation in northeast Germany. Precision Agriculture. 23(1). 52–82. 42 indexed citations
7.
Spengler, Daniel, et al.. (2021). Analysis of Weather-Related Growth Differences in Winter Wheat in a Three-Year Field Trial in North-East Germany. Agronomy. 11(9). 1854–1854. 4 indexed citations
8.
Itzerott, Sibylle, et al.. (2021). Agricultural Monitoring Using Polarimetric Decomposition Parameters of Sentinel-1 Data. Remote Sensing. 13(4). 575–575. 38 indexed citations
9.
Ward, Kathrin, Sabine Chabrillat, Maximilian Brell, et al.. (2020). Mapping Soil Organic Carbon for Airborne and Simulated EnMAP Imagery Using the LUCAS Soil Database and a Local PLSR. Remote Sensing. 12(20). 3451–3451. 27 indexed citations
10.
Itzerott, Sibylle, et al.. (2019). Delineation of management zones with spatial data fusion and belief theory. Precision Agriculture. 21(4). 802–830. 28 indexed citations
11.
Spengler, Daniel, et al.. (2019). Analyzing Temporal and Spatial Characteristics of Crop Parameters Using Sentinel-1 Backscatter Data. Remote Sensing. 11(13). 1569–1569. 78 indexed citations
12.
Kuechly, Helga U., Annett Frick, Michael Förster, et al.. (2018). Indicator-Based Soil Moisture Monitoring of Wetlands by Utilizing Sentinel and Landsat Remote Sensing Data. PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science. 86(2). 71–84. 11 indexed citations
13.
Borg, Erik, et al.. (2018). Joint Experiment for Crop Assessment and Monitoring (JECAM) - Test Site DEMMIN 2018. elib (German Aerospace Center). 2 indexed citations
14.
Spengler, Daniel, et al.. (2017). Automatic delineation algorithm for site-specific management zones based on satellite remote sensing data. Precision Agriculture. 19(4). 684–707. 79 indexed citations
15.
Blasch, Gerald, Daniel Spengler, Sibylle Itzerott, & Gerd Wessolek. (2015). Organic Matter Modeling at the Landscape Scale Based on Multitemporal Soil Pattern Analysis Using RapidEye Data. Remote Sensing. 7(9). 11125–11150. 27 indexed citations
16.
Somers, Ben, Laurent Tits, Karl Segl, et al.. (2015). Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale. Remote Sensing. 7(11). 15361–15387. 39 indexed citations
17.
Rogaß, Christian, Christian Mielke, Daniel Scheffler, et al.. (2014). Reduction of Uncorrelated Striping Noise—Applications for Hyperspectral Pushbroom Acquisitions. Remote Sensing. 6(11). 11082–11106. 37 indexed citations
18.
Rogaß, Christian, Luis Guanter, Christian Mielke, et al.. (2014). AN AUTOMATED PROCESSING CHAIN FOR THE RETRIEVAL OF GEOREFERENCED REFLECTANCE DATA FROM HYPERSPECTRAL EO-1 HYPERION ACQUISITIONS. Publication Database GFZ (GFZ German Research Centre for Geosciences). 7 indexed citations
19.
Spengler, Daniel, Theres Kuester, Annett Frick, Daniel Scheffler, & Hannes Kaufmann. (2013). Correcting the influence of vegetation on surface soil moisture indices by using hyperspectral artificial 3D-canopy models. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8887. 88870Y–88870Y. 3 indexed citations
20.
Kuester, Theres, Karl Segl, Daniel Spengler, & Hermann Kaufmann. (2012). Correction of BRDF-Effects in Vegetation Indices Using Simulated Sentinel-2 Data. ESASP. 707. 14. 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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