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Teaching Staff

Biography

Pedro Sarmento is a researcher at NOVA Cidade – Urban Analytics Lab. He holds a PhD in Information Management – Geographic Information Systems (GIS) by NOVA Information Management School of Universidade Nova de Lisboa and previously obtained an MSc in Science & Geographic Information Systems by the same institution and a graduation in Biophysics Engineering from the University of Évora. His main research areas are related with urban analytics, GIS and remote sensing. Beside his previous work in private and public institutions working in GIS and remote sensing projects, he has a rich background in research, having published several papers in peer review journals related with urban analytics, and the production/accuracy assessment of land-cover maps derived from aerial and satellite images. Currently he analyses spatial data and manage projects, developing research and technical work that explore the potential of data science and GIS to promote social, economic and environmental well-being at city, regional and national level.

Scientific Publications

Simões, P., de Castro Neto, M., Sarmento, P., & Barriguinha, A. (2023)

Oeste smart region: An intermunicipal integrated analytical territorial intelligence platform. Mapping, 32(211), 50-61. [5]. https://doi.org/10.59192/mapping.395

Jardim, B., Alpalhão, N., Sarmento, P., & Neto, M. D. C. (2022)

The Illegal Parking Score: Understanding and predicting the risk of parking illegalities in Lisbon based on spatiotemporal features. Case Studies on Transport Policy, 10(3), 1816-1826. https://doi.org/10.1016/j.cstp.2022.07.011

Sarmento, P., Motta, M., Scott, I., Pinheiro, F. L., & De Castro Neto, M. (2022)

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon. Waste Management, 138(February), 189-198. [Advanced online publication on 7th  December 2021]. https://doi.org/10.1016/j.wasman.2021.12.002

Alpalhão, N., Sarmento, P., Pinheiro, F. L., Tremoceiro, J., & Neto, M. D. C. (2022)

Prediction and simulation of the risk of traffic accidents using neural networks and gradient boosting with an hybrid classification/regression modelling approach in urban context. In Livro de Resumos da Conferência do Projeto de Investigação Científica “Fatores de Transformação Urbana (DRIVIT-UP)” em conjunto com I Conferência sobre Ciência de Dados para Ciências Sociais e VI Conferência de Planeamento Regional e Urbano. [Abstract book from the Conference of the Scientific Research Project “Drivers of urban transformation (DRIVIT-UP)” a joitly event with I Conference on Data Science for the Social Sciences And VI Conference on Regional and Urban Planning] (pp. 52-55). UA Editora. https://doi.org/10.48528/pkzd-wz70

Neto, M. de C. & Sarmento, P. (2019)

Assessing Lisbon Trees’ Carbon Storage Quantity, Density, and Value Using Open Data and Allometric Equations. Special Issue: Open Data for Open Cites (OD4OC): Reuse of Open Data through Spatial Analysis. Information, 10(4), 133. doi: https://doi.org/10.3390/info10040133

Neto, M. D. C., Nascimento, M., Sarmento, P., Ribeiro, S., Rodrigues, T., & Painho, M. (2019)

A Dashboard for Security Forces Data Visualization and Storytelling. In I. Ramos, R. Quaresma, P. R. D. Silva, & T. Oliveira (Eds.), Information Systems for Industry 4.0: Proceedings of the 18th  Conference of the Portuguese Association for Information Systems (pp. 47-62). (Lecture Notes in Information Systems and Organisation; Vol. 31). Springer International Publishing. https://doi.org/10.1007/978-3-030-14850-8_4. eISBN: 978-3-030-14850-8; ISBN: 978-3-030-14849-2. Link: https://www.springer.com/us/book/9783030148492

Neto, M de C., Motta, M., Sarmento, P. & Ribeiro, S. (2018)

Implementação de um dashboard para visualização e análise de dados de segurança. In T. Rodrigues, & M. Painho (Eds.), Modelos preditivos e segurança pública (pp. 281-302). Porto: Fronteira do Caos. ISBN: 978-989-54148-7-1

Neto, M. D. C., Nascimento, M., Sarmento, P., Ribeiro, S., Rodrigues, T., & Painho, M. (2018)

Implementation of a Dashboard for security forces data visualization. In P. Silva, R. Quaresma, & T. Oliveira (Eds.), Atas da 18ª Conferência da Associação Portuguesa de Sistemas de Informação: a indústria 4.0 e os sistemas de informação (pp. 37). Associação Portuguesa de Sistemas de Informação.