GeoPython 2021
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- GeoPython Track
- Machine Learning Track
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Track 1
Track 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 Opens
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Opening Session Day 1
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Geopythonic processing of massive high resolution Copernicus Sentinel data streams on cloud infrastructure
(ANASTASAKIS Konstantinos, Guido Lemoine)
Interpolating Elevation Data inside Tunnel and Bridge Networks
(Alexander Held)
How to Use Spatial Data to Identify CPG Demand Hotspots
(Argyrios Kyrgiazos)
Break
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Mapquadlib - A Python library that supports multi-level tiled representations of the map of the earth.
(Christian Stade-Schuldt)
30 Maps in 30 days with Python
(Topi Tjukanov, Alexander Kmoch)
Python in QGIS
(Zoltan Siki)
Predicting Traffic Accident Hotspots with Spatial Data Science
(Miguel Alvarez)
Building custom web administrators for geographic data driven websites with Django
(Marc Compte)
Break
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Interactive mapping and analysis of geospatial big data using geemap and Google Earth Engine
(Kel Markert, Qiusheng Wu)
Break
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How I Used Python and Big Data to Measure Seismic Silences during the COVID19 Lockdown?
(Artash Nath)
SaferPLACES platform: a GeoPython-based climate service addressing urban flooding hazard and risk.
(stefano bagli)
ML-Enabler: Enabling Rapid Machine Learning Inference of School Mapping in Asia, Africa and South America
(Martha Morrissey)
[TALK CANCELLED] Estimating the economic impact of COVID-19 using real-time images from space
(Nataraj Dasgupta)
Break
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Crop yield prognosis using ML and EO data
(Peter Fogh)
Mapping, Monitoring and Forecasting Groundwater Floods in Ireland
(Joan Campanyà i Llovet)
The power of "Where" - Location data in Moovit
(Yehuda Horn)
Universal geospatial data storage with TileDB: No more file formats
(Norman Barker)
Break
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Break
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3D Geological Modelling using GemPy
(Kristiaan Joseph)
The Open Data Cube (ODC): a very intuitive tool to store, manage and analyse satellite images data
(Aurelio Vivas)
eemont: A Python Package that extends Google Earth Engine
(David Montero Loaiza)
Deep learning-based remote sensing for disaster relief with Python
(Thomas Chen)
Track 1
Track 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 Session Day 2
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Geospatial analysis using python 101
(krishna lodha)
Break
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Predicting dissolved oxygen in a lagoon using interpretable machine learning
(Dimitris Politikos)
Curie Point Depth Mapping using PyCurious from Aeromagnetic Data
(izzul)
Understanding Qiskit: Quantum by Quantum
(Anmol Krishan Sachdeva)
Improved Crop Yield Prediction through Spatio-Temporal Analysis of Agricultural Data
(Arjumand Younus)
The Bavarian Open Data Cube
(Steven Hill, Sebastian Foertsch)
Break
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Trackintel: An open-source python library for human mobility modeling and analysis
(Ye Hong)
Break
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On the role of packaging in GIS, or: How to drive computer clusters and GPUs from within desktop GUI applications for non-technical users
(Sebastian M. Ernst)
Pyinterpolate - Python package for spatial interpolation and deconvolution of areal data
(Szymon Moliński)
Bins! An easy path to make them using Fast API, PostGIS and JavaScript
(Vinícius Cruvinel Rêgo)
Spatial SQL? ...can you say that in Python, please?
(César Ariel Pérez Mercado)
Audio Signal Processing for Feature Building and Machine Learning
(Jyotika Singh)
Cal ToxTrack: A Web GIS for Pollution Mapping in California
(Megan Luisa White)
Closing Session
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Break
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Travel Time Prediction for Urban Travel using Uber Movement and OpenStreetMap
(Vishnu Prasad J S, Ujaval Gandhi)
Spatial analysis of Covid-19 relation with weather parameters
(Abouzar Ramezani)
Break
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Maps with Django
(Paolo Melchiorre)
Creating 3D Terrain Models of Switzerland using Open Data
(Martin Christen)
Break
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Exploratory Movement Data Analysis
(Anita Graser)
Should We Return to Python 2?
(Miroslav Šedivý)