PyVideo.org - Anders Lehmann

Using iPython Notebook in the Classroom

Anders Lehmann — Thu, 04 Jul 2013 00:00:00 +0000

Online Education: challenges and opportunities for Staff and Students

Anders Lehmann — Thu, 06 Aug 2015 00:00:00 +0000

Description

Anders Lehmann - Online Education: challenges and opportunities for Staff and Students [EuroPython 2015] [23 July 2015] [Bilbao, Euskadi, Spain] [Education Summit]

From september 2015 Aarhus School of Engineering will offer the education Bachelor of Electronic Engineering, as a combined online and on campus education. In the talk I will describe the technical and pedagogical setup, we are working at to meet the challenges of having both on-site and remote students.

I will also touch on how IPython Notebook, will be part of the technical setup, and how it can be incorporated into the teaching.

How to GIS with Python

Anders Lehmann — Wed, 05 Aug 2015 00:00:00 +0000

Description

Anders Lehmann - How to GIS with Python [EuroPython 2015] [24 July 2015] [Bilbao, Euskadi, Spain]

In this talk I will present some tools for working with Geographic Information Systems in Python.

Geographic information Systems are widely used for managing geographic (map) data. As an example I will present how to use Open Street Map data (http://openstreetmap.org/), in routing, traffic planning and estimation of pollution emission.

For the purpose of the project EcoSense (http://ecosense.au.dk), GPS data from users smartphones are mapped to OSM roads. The map matching algorithm is written in Python and uses data from the database PostgreSQL, with the PostGIS extension.

One of the goals of the EcoSense project is to devise methods to improve the estimation of air quality in urban environments.

Modelling pollution from traffic, using Smartphone data and Python

Anders Lehmann — Fri, 14 Jul 2017 00:00:00 +0000

Description

The talk presents results from my PhD project on models for transportation related pollution.

Pollution from personal transport in Cities is a big and growing problem. By monitoring the flow, and congestion in the transport system two goals can be achieved. First, the adherence to agreed limit values (or breaking said limits) can be followed and used to decrease health effects of local pollution hotspots. Secondly, monitoring of the total emission of climate forcing gases from transportation, is important for designing climate mitigation actions.

Python is used in combination with other tools to convert sensor data from smartphones, into pollution concentrations in urban settings. To mitigate the lack of complete data coverage, the missing data is simulated by a traffic model, to locate congestion and model the traffic related pollution concentration.