Cristina Da Lio

67 total papers · 1.0k total citations
33 papers, 770 citations indexed

About

Cristina Da Lio is a scholar working on Earth-Surface Processes, Ecology and Aerospace Engineering. According to data from OpenAlex, Cristina Da Lio has authored 33 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Earth-Surface Processes, 13 papers in Ecology and 8 papers in Aerospace Engineering. Recurrent topics in Cristina Da Lio's work include Coastal and Marine Dynamics (23 papers), Coastal wetland ecosystem dynamics (13 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (8 papers). Cristina Da Lio is often cited by papers focused on Coastal and Marine Dynamics (23 papers), Coastal wetland ecosystem dynamics (13 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (8 papers). Cristina Da Lio collaborates with scholars based in Italy, Switzerland and United States. Cristina Da Lio's co-authors include Luigi Tosi, Andrea D’Alpaos, Marco Marani, Pietro Teatini, Tazio Strozzi, Eleonora Carol, Eduardo Emilio Kruse, Claudia Zoccarato, Sandra Donnici and Massimo Zecchin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and The Science of The Total Environment.

In The Last Decade

Cristina Da Lio

32 papers receiving 758 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Cristina Da Lio	373	357	209	151	123	33	770
Nicolas Le Dantec	267 0.7×	201 0.6×	137 0.7×	94 0.6×	103 0.8×	36	716
Gianluigi Di Paola	513 1.4×	185 0.5×	285 1.4×	72 0.5×	108 0.9×	40	785
Giovanni Alberto Cecconi	312 0.8×	377 1.1×	161 0.8×	71 0.5×	108 0.9×	36	666
Emmanuel Poizot	290 0.8×	190 0.5×	216 1.0×	114 0.8×	158 1.3×	39	722
Manuel Garçin	392 1.1×	290 0.8×	307 1.5×	40 0.3×	159 1.3×	47	898
France Floc’h	592 1.6×	395 1.1×	272 1.3×	40 0.3×	193 1.6×	37	771
Daniela Ruberti	362 1.0×	82 0.2×	298 1.4×	56 0.4×	94 0.8×	42	819
James C. Gibeaut	416 1.1×	362 1.0×	202 1.0×	23 0.2×	120 1.0×	47	768
Kakani Nageswara Rao	398 1.1×	321 0.9×	332 1.6×	27 0.2×	137 1.1×	56	898
Jeffrey G. Paine	502 1.3×	309 0.9×	261 1.2×	32 0.2×	112 0.9×	49	905

Countries citing papers authored by Cristina Da Lio

Since Specialization

Citations

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

Fields of papers citing papers by Cristina Da Lio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cristina Da Lio. 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 Cristina Da Lio. The network helps show where Cristina Da Lio may publish in the future.

Co-authorship network of co-authors of Cristina Da Lio

This figure shows the co-authorship network connecting the top 25 collaborators of Cristina Da Lio. A scholar is included among the top collaborators of Cristina Da Lio 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 Cristina Da Lio. Cristina Da Lio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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