World's Best Scientists 2026 revealed!
Filippo Catani

Filippo Catani

D-Index & Metrics

Earth Science

D-Index
63
Citations
12967
World Ranking
1615
National Ranking
17

Filippo Catani publication distribution in Earth Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Earth Science in 2026. The highlighted bar marks where Filippo Catani sits on this spectrum.

38–47 publications: 5 scientists 48–57 publications: 33 scientists 58–67 publications: 94 scientists 68–77 publications: 161 scientists 78–87 publications: 278 scientists 88–97 publications: 376 scientists 98–107 publications: 404 scientists 108–117 publications: 484 scientists 118–127 publications: 540 scientists 128–137 publications: 557 scientists 138–147 publications: 491 scientists 148–157 publications: 495 scientists 158–167 publications: 458 scientists 168–177 publications: 490 scientists 178–187 publications: 414 scientists 188–197 publications: 401 scientists 198–207 publications: 333 scientists 208–217 publications: 292 scientists 218–227 publications: 290 scientists 228–237 publications: 262 scientists 238–247 publications: 243 scientists 248–257 publications: 208 scientists 258–267 publications: 185 scientists 268–277 publications: 147 scientists 278–287 publications: 128 scientists 288–297 publications: 119 scientists 298–307 publications: 120 scientists 308–317 publications: 107 scientists 318–327 publications: 93 scientists 328–337 publications: 87 scientists 338–347 publications: 64 scientists 348–357 publications: 87 scientists 358–367 publications: 60 scientists 368–377 publications: 60 scientists 378–387 publications: 34 scientists 388–397 publications: 50 scientists 398–407 publications: 44 scientists 408–417 publications: 31 scientists 418–427 publications: 39 scientists 428–437 publications: 27 scientists 438–447 publications: 36 scientists 448–457 publications: 27 scientists 458–467 publications: 29 scientists 468–477 publications: 30 scientists 478–487 publications: 19 scientists 488–497 publications: 15 scientists 498–507 publications: 18 scientists 508–517 publications: 19 scientists 518–527 publications: 16 scientists 528–537 publications: 10 scientists 538–547 publications: 11 scientists 548–557 publications: 14 scientists 558–567 publications: 11 scientists 568–577 publications: 7 scientists 578–587 publications: 14 scientists 588–597 publications: 5 scientists 598–602 publications: 4 scientists 603+ publications: 100 scientists
38 publications 603+

This scientist: 207 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 603 publications or more.

Filippo Catani D-index placement in Earth Science in 2026

The chart shows the D-index (discipline H-index) distribution of Earth Science scientists ranked by Research.com in 2026. The highlighted bar marks where Filippo Catani sits on this spectrum.

30 D-Index: 144 scientists 31 D-Index: 215 scientists 32 D-Index: 278 scientists 33 D-Index: 379 scientists 34 D-Index: 366 scientists 35 D-Index: 372 scientists 36 D-Index: 389 scientists 37 D-Index: 366 scientists 38 D-Index: 344 scientists 39 D-Index: 349 scientists 40 D-Index: 296 scientists 41 D-Index: 289 scientists 42 D-Index: 277 scientists 43 D-Index: 279 scientists 44 D-Index: 248 scientists 45 D-Index: 257 scientists 46 D-Index: 212 scientists 47 D-Index: 202 scientists 48 D-Index: 207 scientists 49 D-Index: 204 scientists 50 D-Index: 183 scientists 51 D-Index: 178 scientists 52 D-Index: 182 scientists 53 D-Index: 178 scientists 54 D-Index: 163 scientists 55 D-Index: 117 scientists 56 D-Index: 163 scientists 57 D-Index: 120 scientists 58 D-Index: 113 scientists 59 D-Index: 136 scientists 60 D-Index: 135 scientists 61 D-Index: 96 scientists 62 D-Index: 103 scientists 63 D-Index: 83 scientists 64 D-Index: 103 scientists 65 D-Index: 83 scientists 66 D-Index: 89 scientists 67 D-Index: 92 scientists 68 D-Index: 89 scientists 69 D-Index: 78 scientists 70 D-Index: 75 scientists 71 D-Index: 53 scientists 72 D-Index: 62 scientists 73 D-Index: 54 scientists 74 D-Index: 35 scientists 75 D-Index: 52 scientists 76 D-Index: 50 scientists 77 D-Index: 32 scientists 78 D-Index: 37 scientists 79 D-Index: 20 scientists 80 D-Index: 33 scientists 81 D-Index: 36 scientists 82 D-Index: 34 scientists 83 D-Index: 34 scientists 84 D-Index: 24 scientists 85 D-Index: 19 scientists 86 D-Index: 18 scientists 87 D-Index: 26 scientists 88 D-Index: 30 scientists 89 D-Index: 17 scientists 90 D-Index: 21 scientists 91 D-Index: 19 scientists 92 D-Index: 15 scientists 93 D-Index: 14 scientists 94 D-Index: 20 scientists 95 D-Index: 9 scientists 96 D-Index: 10 scientists 97 D-Index: 15 scientists 98 D-Index: 13 scientists 99 D-Index: 3 scientists 100 D-Index: 13 scientists 101 D-Index: 3 scientists 102 D-Index: 9 scientists 103 D-Index: 4 scientists 104 D-Index: 6 scientists 105 D-Index: 6 scientists 106+ D-Index: 98 scientists
30 D-Index 106+

This scientist: 63 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 106 D-Index or more.

Overview

Filippo Catani is affiliated with the University of Florence in Italy. Their research primarily focuses on environmental science and engineering, with significant contributions to the study of landslides and related hazards. The scholar's work spans multiple subfields, including management, monitoring, policy and law; atmospheric science; global and planetary change; safety, risk, reliability and quality; and mechanical engineering.

Catani's research addresses a range of topics such as landslides and related hazards, cryospheric studies and observations, flood risk assessment and management, geotechnical engineering and analysis, tree root and stability studies, fire effects on ecosystems, and synthetic aperture radar (SAR) applications and techniques.

They have a record of publishing in several notable venues, frequently contributing to:

  • Landslides
  • Remote Sensing
  • Journal of Rock Mechanics and Geotechnical Engineering
  • Engineering Geology
  • Scientific Reports

Among recent publications featuring Catani's work are the following papers:

  • "Landslide detection by deep learning of non-nadiral and crowdsourced optical images," 2020, Landslides
  • "Landslide detection in the Himalayas using machine learning algorithms and U-Net," 2022, Landslides
  • "Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors," 2022, Journal of Rock Mechanics and Geotechnical Engineering
  • "Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization," 2020, Landslides
  • "Effect of antecedent rainfall conditions and their variations on shallow landslide-triggering rainfall thresholds in South Korea," 2020, Landslides

Catani collaborates frequently with peers in their field. Notable co-authors include:

  • Faming Huang
  • Jinsong Huang
  • Lorenzo Nava
  • Sansar Raj Meena
  • Kushanav Bhuyan

The researcher's interdisciplinary approach integrates engineering principles with environmental science, supporting the development of predictive models and risk assessment methods related to hillslope stability and landslide phenomena. Their work often involves the application of machine learning algorithms and remote sensing techniques.

Best Publications

  • Recommendations for the quantitative analysis of landslide risk

    J. Corominas;C.J. van Westen;P. Frattini;L. Cascini

  • Artificial Neural Networks applied to landslide susceptibility assessment

    Leonardo Ermini;Filippo Catani;Nicola Casagli

  • Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues

    F. Catani;D. Lagomarsino;S. Segoni;V. Tofani

  • Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

    Chao Zhou;Chao Zhou;Kunlong Yin;Ying Cao;Bayes Ahmed

  • Landslide prediction, monitoring and early warning: a concise review of state-of-the-art

    Byung-Gon Chae;Hyuck-Jin Park;Filippo Catani;Alessandro Simoni

  • Monitoring, prediction, and early warning using ground-based radar interferometry

    Nicola Casagli;Filippo Catani;Chiara Del Ventisette;Guido Luzi

  • Statistical analysis of drainage density from digital terrain data

    Gregory E Tucker;Filippo Catani;Andrea Rinaldo;Rafael L Bras

  • Landslide hazard and risk mapping at catchment scale in the Arno River basin

    F. Catani;N. Casagli;L. Ermini;Gaia Righini

  • Rainfall thresholds for the forecasting of landslide occurrence at regional scale

    G. Martelloni;S. Segoni;R. Fanti;F. Catani

  • Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring

    Veronica Tofani;Federico Raspini;Filippo Catani;Nicola Casagli

  • The new landslide inventory of Tuscany (Italy) updated with PS-InSAR: geomorphological features and landslide distribution

    A. Rosi;V. Tofani;L. Tanteri;C. Tacconi Stefanelli

  • Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

    Unknown

  • An empirical geomorphology-based approach to the spatial prediction of soil thickness at catchment scale

    Filippo Catani;Samuele Segoni;Giacomo Falorni

  • Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method

    Chao Zhou;Chao Zhou;Kunlong Yin;Ying Cao;Emanuele Intrieri

  • Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity-duration thresholds

    Samuele Segoni;Guglielmo Rossi;Ascanio Rosi;Filippo Catani

  • HIRESSS: a physically based slope stability simulator for HPC applications

    Guglielmo Rossi;Filippo Catani;Lorenzo Leoni;Samuele Segoni

  • Technical note: use of remote sensing for landslide studies in Europe

    Veronica Tofani;Samuele Segoni;Andrea Agostini;Filippo Catani

  • On the application of SAR interferometry to geomorphological studies: estimation of landform attributes and mass movements

    Filippo Catani;Paolo Farina;Sandro Moretti;Giovanni Nico

  • Geomorphic indexing of landslide dams evolution

    Carlo Tacconi Stefanelli;Samuele Segoni;Nicola Casagli;Filippo Catani

  • Landslide susceptibility map refinement using PSInSAR data

    Andrea Ciampalini;Federico Raspini;Daniela Lagomarsino;Filippo Catani

  • Persistent Scatterers Interferometry Hotspot and Cluster Analysis PSI-HCA for detection of extremely slow-moving landslides

    Ping Lu;Nicola Casagli;Filippo Catani;Veronica Tofani

  • Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale

    Samuele Segoni;Veronica Tofani;Ascanio Rosi;Filippo Catani

Frequent Co-Authors

Nicola Casagli
Nicola Casagli University of Florence
Samuele Segoni
Samuele Segoni University of Florence
Veronica Tofani
Veronica Tofani University of Florence
Sandro Moretti
Sandro Moretti University of Florence
Federico Raspini
Federico Raspini University of Florence
Silvia Bianchini
Silvia Bianchini University of Florence
Adam Emmer
Adam Emmer University of Graz
Paolo Frattini
Paolo Frattini University of Milano-Bicocca
Simonetta Paloscia
Simonetta Paloscia National Research Council (CNR)
Gabriele Moser
Gabriele Moser University of Genoa

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