Massimo Melillo

41 papers receiving 2.3k citations

Massimo Melillo's Hit Papers

Deep learning forecast of rainfall-induced shallow landslides 2023 · 107 citations
1070+3+6Years since publication100200300

Peers

Massimo Melillo
Comparison fields: 5 of 71
  • Management, Monitoring, Policy and Law 2.0k
  • Atmospheric Science 1.2k
  • Global and Planetary Change 1.3k
  • Safety, Risk, Reliability and Quality 292
  • Civil and Structural Engineering 419
Replace Ivan Marchesini with:
Ivan Marchesini Italy
Federica Fiorucci Italy
Ascanio Rosi Italy
Kang-Tsung Chang Taiwan
Diego Di Martire Italy
Rainer Bell Austria
Gerald F. Wieczorek United States
Amar Deep Regmi China
Settimio Ferlisi Italy
Alexander L. Handwerger United States
Massimo Melillo relative to Ivan Marchesini Italy Ivan Marchesini's profile →
Citations per field
00.5×1.6×
Ivan Marchesini · 1×
Citations per year

Countries citing papers authored by Massimo Melillo

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Melillo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Geographical landslide early warning systems
Hit paper breakdown →
2019343
2
Rainfall thresholds for possible landslide occurrence in Italy
Hit paper breakdown →
2017287
3 2014236
4 2018145
5 2016133
6 2018120
7 2014120
8 2018110
9
Deep learning forecast of rainfall-induced shallow landslides
Hit paper breakdown →
2023107
10 201996
11 201574
12 201862
13 201761
14 201752
15 202334
16 202134
17 202334
18 202333
19 202333
20 202033

About Massimo Melillo

Massimo Melillo is a scholar working on Management, Monitoring, Policy and Law, Global and Planetary Change, Atmospheric Science, Civil and Structural Engineering and Safety, Risk, Reliability and Quality, having authored 42 papers that have together received 2.3k indexed citations. Recurring topics across this work include Landslides and related hazards (36 papers), Cryospheric studies and observations (28 papers), Flood Risk Assessment and Management (20 papers), Fire effects on ecosystems (9 papers), Geotechnical Engineering and Analysis (4 papers), Soil and Unsaturated Flow (3 papers), Tree Root and Stability Studies (3 papers) and Precipitation Measurement and Analysis (2 papers). The work is most often cited by research in Management, Monitoring, Policy and Law (2.0k citations), Atmospheric Science (1.2k citations), Global and Planetary Change (1.3k citations), Safety, Risk, Reliability and Quality (292 citations) and Civil and Structural Engineering (419 citations). Massimo Melillo has collaborated with scholars based in Italy, Spain and Netherlands. Frequent co-authors include Silvia Peruccacci, Maria Teresa Brunetti, Fausto Guzzetti, Stefano Luigi Gariano, Mauro Rossi, Ivan Marchesini, Alessandro Mondini, Carmela Vennari, Giulio Iovine and O. Terranova. Their work appears in journals such as Landslides, Geomorphology, Natural hazards and earth system sciences, Water and Scientific Data.

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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