IJGI, Free Full-Text

To create quality decision-making tools that would contribute to transport sustainability, we need to build models relying on accurate, timely, and sufficiently disaggregated data. In spite of today’s ubiquity of big data, practical applications are still limited and have not reached technology readiness. Among them, passively generated telecom data are promising for studying travel-pattern generation. The objective of this study is twofold. First, to demonstrate how telecom data can be fused with other data sources and used to feed up a traffic model. Second, to simulate traffic using an agent-based approach and assess the emission produced by the model’s scenario. Taking Novi Sad as a case study, we simulated the traffic composition at 1-s resolution using the GAMA platform and calculated its emission at 1-h resolution. We used telecom data together with population and GIS data to calculate spatial-temporal movement and imported it to the ABM. Traffic flow was calibrated and validated with data from automatic vehicle counters, while air quality data was used to validate emissions. The results demonstrate the value of using diverse data sets for the creation of decision-making tools. We believe that this study is a positive endeavor toward combining big data and ABM in urban studies.

Path Of Building Download 3.4 - Colaboratory

PDF) Role of Remote Sensing and GIS in Natural- Disaster Management Cycle

Frontiers Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine

IJGI Free Full-Text UAV Photogrammetry-Based 3D Road Distress Detection

Route 66 Chicago 6000 Software Update - Colaboratory

IJGI, Free Full-Text

MDPI Article Template - Overleaf, Online LaTeX Editor

Hartford Ct Gis Data Download - Colaboratory

Cryengine-Levels Zum Download - Colaboratory

IJGI, Free Full-Text

Driver And Vehicle Computer Services Division Shannon - Colaboratory

PDF) GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

Full article: Rainfall induced landslide susceptibility mapping using novel hybrid soft computing methods based on multi-layer perceptron neural network classifier

Full article: Landslide susceptibility mapping in three Upazilas of Rangamati hill district Bangladesh: application and comparison of GIS-based machine learning methods

Polycom Cloud Relay Download - Colaboratory