Marco Veloso
Biographic Data
| ID | 4418016 |
|---|---|
| NAME | Marco Veloso |
| GIVEN NAMES | Marco |
| FAMILY NAME | Veloso |
| SIGNATURE | VELOSO M |
| AFFILIATIONS | Polytechnic Institute of Coimbra |
| ORCID | 0000-0001-5925-8442 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Socioeconomic and functional zoning characterization in a city: A Clustering Approach
Sensing Mobility and Routine Locations through Mobile Phone and Crowdsourced Data: Analyzing Travel and Behavior during Covid-19
The COVID-19 pandemic affected many aspects of human mobility and resulted in unprecedented changes in population dynamics, including lifestyle and mobility. Recognizing the effects of the pandemic is crucial to understand changes and mitigate negative impacts. Spatial data on human activity, including mobile phone data, has the potential to provide movement patterns and identify regularly visited locations. Moreover, crowdsourced geospatial info…
Identification and Classification of Routine Locations Using Anonymized Mobile Communication Data
Digital location traces are a relevant source of insights into how citizens experience their cities. Previous works using call detail records (CDRs) tend to focus on modeling the spatial and temporal patterns of human mobility, not paying much attention to the semantics of places, thus failing to model and enhance the understanding of the motivations behind people’s mobility. In this paper, we applied a methodology for identifying individual user…
Identification and Classification of Routine Locations Using Anonymized Mobile Communication Data
Digital location traces are a relevant source of insights into how citizens experience their cities. Previous works using call detail records (CDRs) tend to focus on modeling the spatial and temporal patterns of human mobility, not paying much attention to the semantics of places, thus failing to model and enhance the understanding of the motivations behind people’s mobility. In this paper, we applied a methodology for identifying individual user…
Sensing Mobility and Routine Locations through Mobile Phone and Crowdsourced Data: Analyzing Travel and Behavior during Covid-19
The COVID-19 pandemic affected many aspects of human mobility and resulted in unprecedented changes in population dynamics, including lifestyle and mobility. Recognizing the effects of the pandemic is crucial to understand changes and mitigate negative impacts. Spatial data on human activity, including mobile phone data, has the potential to provide movement patterns and identify regularly visited locations. Moreover, crowdsourced geospatial info…
Socioeconomic and functional zoning characterization in a city: A Clustering Approach
Artificial Intelligence (3 works) · Computer Science (3 works) · Human Mobility and Location-Based Analysis (3 works) · Cluster analysis (2 works) · Demography (2 works) · Geography (2 works) · Impact of Light on Environment and Health (2 works) · Population (2 works) · World Wide Web (2 works) · Cartography (1 works)