Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Semantic segmentation of water bodies in very high-resolution satellite and aerial images
2023101 citationsMarc Wieland, Sandro Martinis et al.Remote Sensing of Environmentprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Ralph Kiefl'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 Ralph Kiefl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ralph Kiefl more than expected).
This network shows the impact of papers produced by Ralph Kiefl. 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 Ralph Kiefl. The network helps show where Ralph Kiefl may publish in the future.
Co-authorship network of co-authors of Ralph Kiefl
This figure shows the co-authorship network connecting the top 25 collaborators of Ralph Kiefl.
A scholar is included among the top collaborators of Ralph Kiefl 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 Ralph Kiefl. Ralph Kiefl 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.
Wieland, Marc, Sandro Martinis, Ralph Kiefl, & Veronika Gstaiger. (2023). Semantic segmentation of water bodies in very high-resolution satellite and aerial images. Remote Sensing of Environment. 287. 113452–113452.101 indexed citations breakdown →
Taubenböck, Hannes, Joachim Post, Ralph Kiefl, et al.. (2008). RISK AND VULNERABILITY ASSESSMENT TO TSUNAMI HAZARD USING VERY HIGH RESOLUTION SATELLITE DATA - THE CASE STUDY OF PADANG, INDONESIA. elib (German Aerospace Center).5 indexed citations
12.
Taubenböck, Hannes, Joachim Post, Achim Roth, et al.. (2008). Multi-scale assessment of population distribution utilizing remotely sensed data - The case study Padang, West Sumatra, Indonesia. elib (German Aerospace Center).7 indexed citations
13.
Kiefl, Ralph, et al.. (2007). Geodatenmanagement und -dienste am Beispiel des Tsunami-Frühwarnsystems für den Indischen Ozean. elib (German Aerospace Center).1 indexed citations
Becker, Helmut, et al.. (2006). Detection of Looting Activities at Archaeological Sites in Iraq using Ikonos Imagery. elib (German Aerospace Center).14 indexed citations
16.
Keil, Mark, et al.. (2004). Examples and experiences of the update interpretation process for CLC2000 in Germany. elib (German Aerospace Center).3 indexed citations
17.
Keil, Mark, et al.. (2003). Update of the CORINE Land Cover Data Base in Germany. elib (German Aerospace Center).1 indexed citations
18.
Riedlinger, Torsten, Stefan Voigt, Gerhard Gesell, et al.. (2003). Multi-source satellite data facilitating disaster management during the 2003 forest fires in Portugal. elib (German Aerospace Center).
19.
Kiefl, Ralph, et al.. (2003). CORINE Land Cover 2000 - Stand des Teilprojektes in Deutschland. elib (German Aerospace Center).1 indexed citations
20.
Keil, Mark, et al.. (2002). Das Projekt CORINE Land Cover 2000 in Deutschland. elib (German Aerospace Center).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.