GeoPython2019
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Auditorium / other
Room 1
Room 2
08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
Registration
()
Coffee Break (Workshop Day)
()
Lunch
()
Coffee Break (Workshop Day)
()
Ice Breaker Party (12th floor, or outside building if nice weather)
()
Bridging Earth Observation data and Machine Learning in Python
(Matej Aleksandrov)
Deep Learning using Airborne Imagery
(Adrian Meyer, Daniel Rettenmund, Denis Jordan)
Wikidata - a new source for geospatial data
(Knut Hühne)
Python from “Hello World” to “Fit for GeoPython” in 180 Minutes
(Miroslav Šedivý)
Introduction to geospatial data analysis with GeoPandas and the PyData stack
(Joris Van den Bossche)
Introduction to Spatial Data Processing using FME and Python
(Régis Longchamp)
Auditorium / other
Room 1
Room 2
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
Opening / Annoucements
(Martin Christen)
Coffee Break
()
Lunch
()
Coffee Break Afternoon
()
Lightning Talks
()
Conference Dinner (in Basel "Restaurant Rebhaus")
()
Machine Learning for Land Use / Land Cover Statistics of Switzerland
(Adrian Meyer)
How to structure EO data for ML workflows
(Matic Lubej)
Terrain segmentation with label bootstrapping for lidar datasets, case of doline detection
(Rok Mihevc)
Detect and Remediate Bias in Machines Learning Datasets and Models
(Ilja Rasin)
Using Tensorflow for Infrared UAV-based Wildlife Detection
(Adrian Meyer)
Spotting Sharks with the TensorFlow Object Detection API
(Andrew Carter)
Building a Secure and Transparent ML Pipeline Using Open Source Technologies
(Ilja Rasin)
Bayesian modeling with spatial data using PyMC3
(Shreya Khurana)
Understanding and Implementing Generative Adversarial Networks (GANs): One of the BIGGEST Breakthroughs in the Deep Learning Revolution
(Anmol Krishan Sachdeva)
Messaging with Satellites from Anywhere on the Planet
(Andrew Carter)
Automating the definition and optimization of census sampling areas
(Freja Hunt)
Coastline mapping with python, satellite imagery and computer vision.
(Rachel Keay)
Using Python to build a scalable realtime information system for a railway service
(Stanis Trendelenburg)
GeoHealthCheck: QoS Monitor for Geospatial Web Services
(Tom Kralidis, Just van den Broecke)
pyramid_georest
(Clemens Rudert)
A Day Has Only 24±1 Hours
(Miroslav Šedivý)
Geodata Processing and Webservices with Python and Azure
(André Zehnder)
Geoprocessing for Agricultural Analysis using Python: Case study of the Baixio do Irecê Irrigation Perimeter
(Vinícius Cruvinel Rêgo)
Simulation and Visualization of Gully Erosion – a Work-in-Progress Report
(Dietrich Schröder)
Modeling of Subsurface Flow and Transport with Dynamic Boundary Conditions
(Mike Müller)
Building a bus rapid transport system simulator with SimPy and GeoPandas
(Michael Gfeller, Ture Friese)
Scientific Geo-Computing using Python. How we teach it at ITC
(Luis Calisto)
Python in a Geologist’s Backpack
(Kristiaan Joseph)
Python and QGIS - a powerful and lovely partnership
(Stark, Hans-Jörg Prof.)
PyQGIS the comfortable way - tricks to efficiently work with Python and QGIS
(Marco Bernasocchi)
Python as an integrator of technologies to support modernization of land administration in Colombia
(Germán Carrillo)
The Integrated Risk Modelling Toolkit: a QGIS plugin driving the OpenQuake Engine
(Paolo Tormene)
HyBridge: an open-source framework for QGIS desktop - Web Application interoperability.
(Matteo Nastasi)
Auditorium / other
Room 1
Room 2
09:00
10:00
11:00
12:00
13:00
14:00
15:00
Coffee Break
()
Lunch
()
Lightning Talks
()
Closing Session & Raffle
(Martin Christen)
Data Location Enrichment. Get valuable results from spatial data analysis
(Artem Kryvonis)
Spatial data in real-time apps with Python
(Dmitry Karpov)
Automated and reproducible object creation from swisstopo 3D geo data for a VR app with Python and FME
(Michael Zwick)
Working with 3D city models in Python
(Balázs Dukai)
Site planning with Geopandas and CARTO
(Giulia Carella)
Open source web-based tool for quality control of large spatial datasets
(Jiří Kadlec)
The Mission Support System
(Reimar Bauer)
Digital Farming: Fertilise Variably Based on Satellite Data
(Aragats)
Getting Data out of CAD and into Python
(Martin Pike, Joseph Kaelin)
Geomapping with Pyecharts(Echarts.js)
(Chenfu Wang)
PyViz for Mapping Global Shipping
(Andrew Smith)
Analyzing geospatial data using GeoPandas
(Marvin Bensch)
ipyleaflet - A Jupyter-Leaflet bridge enabling interactive maps in Jupyter
(Martin Renou, Sylvain Corlay)
Sporty Python
(Stark, Hans-Jörg Prof.)
Accelerating distances calculations using GPU
(Serhii Hulko)
Geodata processing using Python and JupyterHub
(Martin Christen)