M. Poscolieri

22 papers receiving 400 citations

Peers

M. Poscolieri
Comparison fields: 5 of 74
  • Space and Planetary Science 58
  • Media Technology 100
  • Environmental Engineering 115
  • Geology 42
  • Geophysics 90
Replace Gino Dardanelli with:
Gino Dardanelli Italy
Jan J. Nossin Netherlands
Francesca Giannone Italy
Nicolas Le Dantec France
Issaak Parcharidis Greece
Håvard D. Enge Norway
Jerome A. Bellian United States
Maurizio Barbarella Italy
Łukasz Janowski Poland
S. P. Scheidt United States
M. Poscolieri relative to Gino Dardanelli Italy Gino Dardanelli's profile →
Citations per field
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Gino Dardanelli · 1×
Citations per year

Countries citing papers authored by M. Poscolieri

Since Specialization
Citations

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

Fields of papers citing papers by M. Poscolieri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Poscolieri, 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 M. Poscolieri Line = papers co-authored together M. Poscolieri links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200875
2 200371
3 200768
4 199242
5 200830
6 201026
7 200521
8 200617
9 201716
10 199012
11 201110
12 20067
13 20066
14 20185
15 19905
16 20174
17
Statistical reconstruction of a Martian scene - G-mode cluster analysis results from multispectral data population
19803
18 20073
19 20063
20
Relationships between morphological units and vegetation categories of Soratte Mount (Italy) as inferred by processing elevation and MIVIS hyperspectral data
20033

About M. Poscolieri

M. Poscolieri is a scholar working on Artificial Intelligence, Environmental Engineering, Geophysics, Media Technology and Management, Monitoring, Policy and Law, having authored 24 papers that have together received 431 indexed citations. Recurring topics across this work include Geochemistry and Geologic Mapping (9 papers), earthquake and tectonic studies (5 papers), Remote-Sensing Image Classification (5 papers), Landslides and related hazards (5 papers), Earthquake Detection and Analysis (5 papers), Seismic Waves and Analysis (4 papers), Remote Sensing and LiDAR Applications (4 papers) and Soil Geostatistics and Mapping (4 papers). The work is most often cited by research in Space and Planetary Science (58 citations), Media Technology (100 citations), Environmental Engineering (115 citations), Geology (42 citations) and Geophysics (90 citations). M. Poscolieri has collaborated with scholars based in Italy, Greece and Argentina. Frequent co-authors include Rosa Maria Cavalli, Stefano Pignatti, Simone Pascucci, Angelo Palombo, Kosmas Pavlopoulos, Issaak Parcharidis, G. Paparo, Lorenzo Fusilli, Federico Santini and V. Cuomo. Their work appears in journals such as Natural hazards and earth system sciences, Geological Society London Special Publications, Remote Sensing of Environment, ISPRS Journal of Photogrammetry and Remote Sensing and Journal of South American Earth Sciences.

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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