Pedro Henrique Muniz Lima

I am

About

Researcher, Data Scientist, Map lover and Coding curious

  • Age: 36
  • City: Vienna, Austria
  • Nationality: Brazilian - Open labor market access (EU).
  • Degree: PhD
  • Emails: pedrohe@gmail.com; pedro.lima@univie.ac.at

Skills and Languages

Find here bellow an approximated grade of the skills and languages I use.

GEOSPATIAL ANALYSIS TOOLS (ArcGIS, QGIS) Advanced
R Advanced
LATEX; OFFICE; GIT/GITHUB Good/Advanced
SQL Intermediate
Python, Power BI Beginner/Intermediate
HTML & CSS Beginner
PORTUGUESE Mother tongue
ENGLISH Fluent
GERMAN Good listening and comprehension; while inferior speaking ability

Resume

Summary

Scientist by career, I have always been enthusiastic about data manipulation and visualization. As a map lover, I am passionate about turning data into insights and knowledge.

I recently worked as a researcher within the MoNOE and NoeMOTION projects at the University of Vienna. With Cooperation with Geological survey of the Lower Austria.

    Education

    PhD in Physical Geography

    2015 - 2022

    University of Vienna, Institute of Geography and Regional Research, Vienna, Austria.

    "Landslide susceptibility mapping at varied scales. Methodological designs adaptations to cope with common input data related challenges"

    Master in Physical Geography

    2013 - 2015

    Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, Brazil

    "The Drainage Efficiency Index (DEI) as a subsidy for a spatial analysis of areas susceptible to landslides occurrence."

    Bachelor in Biology with a minor in Environmental Sciences

    2007 - 2012

    Fluminense Federal University - UFF, Niterói, Rio de Janeiro, Brazil

    "Extreme rainfall events and sediment production in two different forested catchments in the Tijuca Massif - RJ: Influences of recovering landslide, roads and trails on rates of sediment yield and transport."

    Recent Professional Experience

    Researcher

    2019 - 2023

    University of Vienna, Vienna, Austria

    • I worked as a researcher within the MoNOE project (Methodenentwicklung für die Gefährdungsmodellierung von landslides in Niederösterreich) at the University of Vienna. This project was conducted in cooperation with the Geological Survey of Lower Austria (Land Niederösterreich; Amt der NÖ Landesregierung. Abteilung Allgemeiner Baudienst. Geologischer Dienst).
    • Re-evaluation of old landslide prediction models previously used in spatial planning and urban development, applied over newer landslide data to assess the quality of old predictive models.
    • Integration of a large database of landslides into a newer landslide predictive model using statistical predictive modelling, which involved data handling, modelling, validation, and interpretation.
    • Writing publications and participating in conferences.
    • Main tech tools used were ArcGIS, R, QGIS, and Git.

    Data Scientist

    2019 - 2021

    Ubiq, Vienna, Austria

    • Elaboration of spatial and temporal dynamic models for shared mobility demand prediction.
    • Building predictive models for car and moped fleets in cities like Berlin, Budapest, Vienna, Dubai, and Washington DC, among others.
    • Large database pre-processing, engineering, and preparation for the demand-prediction pipeline.
    • Analysis of historic data for reports and presentations to clients.
    • Handling, managing, and collecting large datasets.
    • Participation in hiring processes.
    • Main tech tools used were R, SQL, FME, QGIS, and Git.

    Scientific contributions

    Find here bellow the collection of varied reseach contributions which I have participation.

    2024

  • Lima P., Donato AJ, Arango MI, Mergili M, Kanta R, Glade T (2024). NoeMOTION: Mobility, Hazard, and Risk Analysis of Selected Landslides in Lower Austria. Springer International Publishing, XV, 104 pages. ISBN: 978-3-031-55981-5. Expected publication: June 2024. See here

    • 2023

  • Lima P., Steger S, Mergili M and Glade T (2023). Conventional statistical based landslide susceptibility models may only tell us half of the story: potential underestimation of landslide impact areas depending on the modelling design. Geomorphology, 108638. ISSN: 0169-555X DOI:10.1016/j.geomorph.2023.108638 See here

    • 2022

  • Lima P., Steger S., Murillo-Garcia F. and Glade T. (2022). Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility. Journal of Mountain Sciences. 19(6): 1670–1698. DOI:10.1007/s11629-021-7254-9. See here

    • 2021

  • Lin Q., Lima P., Steger S., Glade T., Jiang T., Zhang J., Liu T. and Wang Y. (2021) National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data. Geoscience Frontiers 12(6): 101248. DOI:https://doi.org/10.1016/j.gsf.2021.101248. See here
  • Lima P., Steger S. and Glade T. (2021) Counteracting flawed landslide data in statistically based landslide susceptibility modelling for very largeareas: a national-scale assessment for Austria. Landslides 18, 3531–3546. DOI:10.1007/s10346-021-01693-7. See here

    • 2017

  • Lima P., Steger S., Glade T., Tilch N., Schwarz L. and Kociu A. (2017) Landslide Susceptibility Mapping at National Scale: A First Attempt for Austria. In: Mikos M, Tiwari B, Yin Y and Sassa K (eds.) Advancing Culture of Living with Landslides. WLF 2017. Cham: Springer International Publishing. ISBN 978-3-319-53498-5, pp. 943–951. DOI:10.1007/978-3-319-53498-5. See here
  • Fernandes M.C., Oliveira L.F.B., Colares I.V.V., Araújo R.S. and Lima P., (2017) Comportamento de análises em superfície planimétrica e modelada frente a representações cartograficas e índices geomorfologicos - bacia do Rio Cuiabá - Petrópolis (RJ). Revista Brasileira de Geomorfologia 18(4). DOI:10.20502/rbg.v18i4.1210. See here

    • 2016

  • Coelho Netto A.L., SILVA R., FACADIO A.C. and Lima P., (2016) Movimentos gravitacionais de massa e evolução das encostas montanhosas em regioes tropicais: estudos em Nova Friburgo, RJ. Outras Letras, pp. 235–241

    • 2014

  • Lima P. , Coutinho B.H., Gomes G.B., Fernandes M.C. and Coelho Netto A.L. (2014) Parâmetros morfométricos relacionados às bacias de 1º ordem e a ocorrência de deslizamentos rasos na bacia do Córrego Dantas: Nova Friburgo - RJ. Revista Geonorte - Edição Especial 4: SINAGEO - Geomorfologia de Encostas 5(14): 218 – 223. See here
  • Borges G.F., Lima P., and Avelar A.S. (2014) Geomorfologia, solos e movimentos de massa ocorridos em janeiro de 2011 na bacia do Córrego Dantas, Nova Friburgo (RJ). REVISTA GEONORTE – Edição Especial 4: SINAGEO - Geomorfologia de Encostas 5(14): 141 – 144. See here
  • Coelho Netto A.L., Avelar A.D.S., Sato A.M., Fernandes M.D.C., Oliveira R.R., Costa R.V., Barbosa L.S., Lima P., and Lacerda W.A. (2014) Landslides Susceptibility and Risk Zoning at Angra Dos Reis, Rio de Janeiro State, SE-Brazil: a quali-quantitative approach at 1: 5,000 scale. São Paulo, SP. Brazil: Oficina de Textos. ISBN 978-85-7975-150-9, pp. 263–296. See here

    • 2013

  • Coelho Netto A.L., Sato A.M., Avelar A.S., Vianna L.G.G., Araújo I.S., Ferreira D.L.C., Lima P., Silva A.P.A. and Silva R.P. (2013) January 2011: The Extreme Landslide Disaster in Brazil. Berlin, Heidelberg: Springer Berlin Heidelberg. ISBN 978-3-642-31319-6, pp. 377–384. DOI:10.1007/978-3-642-31319-6 51. See here

    • 2023

  • Lima P., Steger, S., Petschko, H., Goetz, J., Bertagnoli, M., Schweigl, J., and Glade, T. (2023d) UPDATE LANDSLIDE SUSCEPTIBILITY MODELLING - A NEW FRAMEWORK TO COMPARE AND UPDATE A REGIONAL SCALE LANDSLIDE SUSCEPTIBILITY MODEL. In: Tofani V, Casagli N, Bandecchi E, Gargini E and Armignacco D (eds.) Landslide Science for Sustainable Development. Proceedings of the 6th World Landslide Forum. Firenze, Italy: OIC S.r.l. ISBN 9791221048063. See here
  • Lima P., Moreno M, Steger S, Camarinha PI, Coelho LCT, Mandarino FC and Glade T (2023a) DEVELOPING A SPATIOTEMPORAL MODEL TO INTEGRATE LANDSLIDE SUSCEPTIBILITY AND CRITICAL RAINFALL CONDITIONS. A PRACTICAL MODEL APPLIED TO RIO DE JANEIRO MUNICIPALITY. In: Tofani V, Casagli N, Bandecchi E, Gargini E and Armignacco D (eds.) Landslide Science for Sustainable Development. Proceedings of the 6th World Landslide Forum. Firenze, Italy: OIC S.r.l. ISBN 9791221048063. See here
  • Lima P., Steger, S., Petschko, H., Goetz, J., Bertagnoli, M., Schweigl, J., and Glade, T. (2023) A framework to update 10-year-old landslide susceptibility predictions - assessing the accuracy of existing landslide susceptibility models. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7080, https://doi.org/10.5194/egusphere-egu23-7080, 2023. See here

    • 2022

  • Lima P., Steger S, Petschko H, Goetz J, Schweigl J, Bertagnoli M and Glade T (2022b) How well do landslide susceptibility maps hold up over time? reviewing the accuracy of maps implemented for spatial planning in Lower Austria. 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022 ICG2022-154. See here
  • Lima P., Arango Carmona MI and Glade T (2022) Risk assessment of earth mass movements in Lower Austria. case study: NoeMOTION project. 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022 ICG2022-616. See here
  • Lima P., Steger S, Petschko H, Goetz J, Schweigl J, Bertagnoli M and Glade T (2022a) Exploiting newly available landslide data to verify existing landslide susceptibility maps a decade after their implementation. Geophysical Research Abstracts Vol. 22 (EGU22-7351). See here
  • Arango Carmona MI, Lima P., Mergili M and Glade T (2022) Mobility and hazard analysis of selected landslides in Lower Austria. Geophysical Research Abstracts Vol. 22 (EGU22-8646). See here

    • 2020

  • Lima P., Steger S, Glade T and Mergili M (2020) Enhancing the completeness of statistical landslide susceptibility modeling by integration of release and propagation zones. Geophysical Research Abstracts Vol. 20 (2020-8630). URL See here

    • 2019

  • Lima P., Steger S and Glade T (2019) Evaluation of statistical and machine learning based landslide susceptibility models for very large areas – coping with error prone input data. Geophysical Research Abstracts Vol.21 (EGU2019-11314). See here
  • Lima P., Steger S, Glade T and Mergili M (2019b) Combining landslide susceptibility with potential runout: an integrative approach combining data-driven methods. Abstract book of the IAG, Regional conference on Geomorphology 2019 S06. Geomorphological hazards and risks. See here

    • 2018

  • Lima P., Steger S and Glade T (2018b) Modelling strategies to cope with limitations of statistical landslide susceptibility models applied for large areas. A national scale study for the Austrian territory. Geophysical Research Abstracts Vol. 20 (EGU2018-9067). See here
  • Lima P., Steger S and Glade T (2018a) Landslide susceptibility mapping at national scale for Austria. Scientific challenges within applicable solutions. 3.Geographie-Werkstatt Österreich 2018: ’Von Anthropozän bis Digitalisierung? Geographische Forschung und gesellschaftliche Herausforderungen’.

    • 2017

  • Lima P., Steger S and Glade T (2017b) Comparison of non-landslide sampling strategies to counteract inventory-based biases within national-scale statistical landslide susceptibility models. Geophysical Research Abstracts Vol. 19 (EGU2017-13523). See here
  • Coelho Netto AL, Facadio AC, Silva R and Lima P. (2017) Bioclimatic changes and landslide recurrence in the mountainous region of Rio de Janeiro: are we ready to face the next landslide disaster? Geophysical Research Abstracts Vol. 19 (EGU2017-17718). URL See here

    • 2016

  • Lima P., Coelho Netto AL and Fernandes MC (2016) The drainage efficiency index (DEI) as a morphological indicator of landslide spatial occurrence in mountainous catchments. a case of study applied in the mountainous region of Brazilian Southeastern. Geophysical Research Abstracts Vol. 18, EGU2016-7750. See here

    • 2015

  • Lima P., Coutinho BH, Gomes GB and Coelho Netto AL (2015) Topographic parameters related to translational landslide occurrence and susceptibility mapping at Córrego Dantas, Nova Friburgo, RJ. II International Workshop on Landslide History, Mechanisms and Controlling Variables: scientific basis for risk assessment.

    • 2014

  • Lima P. and Avelar AS (2014) Geomorfologia, solos e movimentos de massa ocorridos em janeiro de 2011 na bacia do Córrego Dantas, Nova Friburgo (RJ). Anais do 4: SINAGEO - Geomorfologia de Encostas.

    • 2012

  • Lima P., Barbosa LS, Negreiros AB and Coelho Netto AL (2012) Impulsos variáveis de chuvas e descarga de sedimentos em duas diferentes bacias no Maciço da Tijuca (Rio de Janeiro, Brasil): influências de clareiras de deslizamentos, estradas pavimentadas e trilhas. I Congresso Internacional Geociências na CPLP.
  • Barbosa LS, Lima P., Negreiros AB and Coelho Netto AL (2012b) Respostas hidrológicas e produção de sedimentos em uma clareira de deslizamento em ambiente montanhoso florestal, Maciço da Tijuca, Rio de Janeiro, Brasil. I Congresso Internacional Geociências na CPLP.
  • Negreiros AB, Lima P., Barbosa LS and Coelho Netto AL (2012b) Recuperation of atlantic forest and hydro-erosive responses in landslides scars on steep slopes, Rio de Janeiro, Brasil. Newport. The US-IALE 2012 Abstract Book,2012.
  • Negreiros AB, Lima P., Barbosa LS and Coelho Netto AL (2012a) Avaliação da recuperação vegetal e respostas hidro-erosivas em cicatrizes de deslizamentos em área montanhosa de floresta atlântica, Maciço da Tijuca, RJ. Geomorfologia e eventos catastróficos: passado, presente e futuro. Anais do 9 Sinageo: Geomorfologia de encostas. See here
  • Araujo IS, Barbosa LS, Lima P., Avelar AS and Rotunno Filho OC (2012) Modelagem hidrológica das interações de uso urbano e cobertura vegetal na bacia do Rio Cachoeira, Maciço da Tijuca - RJ. Geomorfologia e eventos catastróficos: passado, presente e futuro. Anais do 9 Sinageo: Geomorfologia de encostas. URL See here
  • Barbosa LS, Lima P., Araújo IS, Sato AM and Avelar AS (2012a) Carta geomorfológica em base funcional como subsidio a carta de suscetibilidade aos movimentos de massa: estudo de caso no município de Angra dos Reis, RJ. XXXIV Jornada de Iniciação científica, UFRJ.

    • 2011

  • Lima P., Silva RP, Barbosa LS and Coelho Netto AC (2011) Impulsos variáveis de chuvas e descarga de sedimentos em pequenas bacias florestadas no Maciço da Tijuca: influência de clareiras de deslizamentos, estradas pavimentadas e trilhas. XXXIII Jornada Giulio Massarani de Iniciação Científica, Artística e Cultural, UFRJ.
  • Silva RP, Barbosa LS, Lima P. and Coelho Netto AC (2011) Mapeamento de fontes de produção de sedimentos em encostas montanhosas sob floresta atlântica: Parque Nacional da Tijuca (PNT), Maciço da Tijuca, Rio de Janeiro. XXXIII Jornada Giulio Massarani de Iniciação científica, Artística e Cultural, UFRJ.
  • Barbosa LS, Silva RP, Lima P. and Coelho Netto AC (2011) Respostas hidrológica e produção de sedimentos numa clareira de deslizamento em ambiente montanhoso. XXXIII Jornada Giulio Massarani de Iniciação científica, Artística e Cultural, UFRJ.

    • 2010

  • Lima P., Faria FHC and Coelho Netto AC (2010) Reabilitação funcional em clareiras de deslizamentos na floresta atlântica e efeitos na produção de sedimentos em períodos chuvosos. XXXII Jornada Giulio Massarani de Iniciação Científica, Artística e Cultural, UFRJ.

    • Highlights

    GeoSpatial analysis

    Large expertise in GIS softwares, including ArcGIS, QGIS and FME.

    Data insights and statistical analysis

    Expertise on building, validating and interpreting statistical and ML predictive models.

    Data Visialization

    Passion to transform raw data to visialization, helping to extract insights and knowledge.

    Big data analysis

    Ability to deal with very large datasets. Especially spatial-temporal analysis.

    Proactiveness

    Used to challenges. Strong strategic, analytical and problem solving skills.

    Codding curious

    For me codding is like playing a game. Love to transform pieces of codes in usefull stuff.

    Portfolio

    - Under construction -

    • All
    • Landslide models
    • GIS
    • Varied stuff

    Updated landslide susceptibility map for Zell am See, Salzburg.

    Number of (historically) observed landslides: 235

    Link here: https://link.springer.com/article/10.1007/s10346-021-01693-7

    Number of mapped landslides per federal states (a). The bottom map (b) portrays the density of mapped landslides (landslides per square kilometer).

    Source: Lima, P. 2022

    Landslide models

    Statistical landslide susceptibility model

    Landslide models

    r.avaflow

    Landslide models

    r.avaflow

    Landslide models

    Landslide downslope propagation - ggplot

    R studio

    test

    Card

    Random colors in Viennese buildings.

    Original streets and buildings
    database from Google maps.

    Fun

    Landslide prediction for Austria. Source: Lima, P. et al., 2023

      Image A Image B Image C Image D Image E Image F Image G Image H Image I

    Portfolio (continuation...)

    Landslide occurrence heatmap in Lower Austria.
    Source: MoNEW project; Lima, P. et al., 2023(unpublished).

    Contact

    Email:

    pedrohe@gmail.com

    pedro.lima@univie.ac.at