Daniel Mandl

884 citations
52 papers · 656 · h-index 11

Impact in

Papers in

Daniel Mandl

48 papers receiving 626 citations

Peers

Daniel Mandl
Comparison fields: 5 of 75
  • Media Technology 138
  • Ecological Modeling 47
  • Global and Planetary Change 199
  • Ecology 215
  • Environmental Engineering 105
Replace Stephen Ungar with:
Stephen Ungar United States
Ioannis Papoutsis Greece
Patrick Nigri Happ Brazil
Gonzalo Mateo‐García Spain
Javier Calpe Spain
Jianwen Ma China
W. Kleynhans South Africa
Xiaoping Du China
Dariush Abbasi‐Moghadam Iran
Gintautas Palubinskas Germany
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Mandl

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Mandl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Mandl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Mandl Line = papers co-authored together Daniel Mandl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015269
2 2013104
3 201039
4 200926
5 201319
6 201619
7 201314
8 201114
9 201314
10 201110
11 200810
12
Matsu: An Elastic Cloud Connected to a SensorWeb for Disaster Response
20119
13 20129
14 20179
15 20128
16 20137
17
Improving the Operations of the Earth Observing One Mission via Automated Mission Planning
20106
18 20055
19 20105
20
A Multi-agent Space, In-situ Volcano Sensorweb
20105

About Daniel Mandl

Daniel Mandl is a scholar working on Aerospace Engineering, Artificial Intelligence, Computer Networks and Communications, Global and Planetary Change and Astronomy and Astrophysics, having authored 52 papers that have together received 656 indexed citations. Recurring topics across this work include Spacecraft Design and Technology (9 papers), Advanced Computational Techniques and Applications (9 papers), Flood Risk Assessment and Management (5 papers), Planetary Science and Exploration (5 papers), Calibration and Measurement Techniques (5 papers), Geochemistry and Geologic Mapping (4 papers), Remote Sensing in Agriculture (4 papers) and Remote-Sensing Image Classification (4 papers). The work is most often cited by research in Media Technology (138 citations), Ecological Modeling (47 citations), Global and Planetary Change (199 citations), Ecology (215 citations) and Environmental Engineering (105 citations). Daniel Mandl has collaborated with scholars based in United States, Vietnam and Thailand. Frequent co-authors include Elizabeth M. Middleton, Christine Lee, Simon J. Hook, Robert O. Green, Morgan L. Cable, Susan L. Ustin, Stuart Frye, Steve Chien, A. G. Davies and Stephen Ungar. Their work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Scientific Reports, IEEE Intelligent Systems, Bulletin of the American Meteorological Society and Journal of Geophysical Research Solid Earth.

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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