Geopython 2021
April 22nd - April 23rd 2021
website - https://event.geopython.net/#/room/#announce:event.geopython.net
schedule - https://2021.geopython.net/schedule.html
Room 1 videos - https://vimeo.com/user/137335150/folder/4121205
Room 2 videos - https://vimeo.com/user/137335150/folder/4250501
Tutorials
Interactive mapping and analysis of geospatial big data using geemap and Google Earth Engine, Qiusheng Wu
https://geemap.org/workshops/GeoPython_2021/
Geopsatial analysis using python 2021, Krishna Lodha, SEGES
https://github.com/krishnaglodha/geopython2021-Geospatial-analysis-101
Talks
Day 1 room 1
Geopythonic processing of massive high resolution Copernicus Sentinel data streams on cloud infrastructure. Konstantinos Anastasiakos, Guido Lemoine, JRC D5 - GTCAP Team
https://jrc-cbm.readthedocs.io/en/latest/
Confirm or reject farmer declares practice (markers)
Sentinal-2 is optical, Sentinal-1 is microwave
Used rasterstats previously (mean, std, min, max, p25, p50, p75) for the bands of the images. Expensive as does raster -> vector. Now speed up as a look up using numba.
https://creodias.eu/price-list has pricing of services
Interpolating Elevation Data inside Tunnel and Bridge Networks, Alexander Held, geops
NetworkX, numpy solution
Q. asked more high resolution terrain data: https://geoservice.dlr.de/web/dataguide/tdm90/
How to use geosocial data to identify CGP Demand Hotspots, Argyrios Kyrgiazos, carto
Carto offer geospatial data https://carto.com/spatial-data-catalog/browser/
Mapquadlib, Christian Stade-Schuldt, here
https://res.cloudinary.com/here/image/upload/v1619085466/maps/HereQuadWorldLvl5_mzsg7x.png
https://res.cloudinary.com/here/image/upload/v1619085466/maps/MercatorQuadWorldLvl5_wjwbds.png
to be released
comparisons to https://h3geo.org/
30 maps in 30 days, Alexander Kmoch
https://github.com/allixender/30MapChallenge2020
https://allixender.github.io/30MapChallenge2020/geopython2021/index.html
https://allixender.github.io/30MapChallenge2020/
idea from https://tjukanov.org/
geospatial data catalog - https://data.world/
https://hackmd.io/9QHsCvq9SeyhUlrFW0fspA - conference chat on open geospatial datasets
Python in QGIS, Zoltan Siki
Predicting Traffic Accident Hotspots with spatial data science, Miguel Alvarez, CARTO
https://github.com/CartoDB/cartoframes
https://carto.com/blog/predicting-traffic-accident-hotspots-with-spatial-data-science/
https://public.carto.com/kuviz/3672c7a5-2e83-45a0-9727-ebab9596ecc5
Data: Accidents; Traffic signs. OSM: street inspections, building footprints; AEMET - daily weather
Premium data: TomTom (road network, traffic density). POIs (points of interset) from Pitney Bowes, 13 categories
Human mobility: Vodafone. 250 x 250 m grid. Working population: Unica360
https://carto.com/spatial-data-catalog/
Moran I for classification of areas hot vs cold.
used https://pysal.org/libpysal/ for weights https://pysal.org/libpysal/api.html https://pysal.org/libpysal/generated/libpysal.weights.lag_spatial.html#libpysal-weights-lag-spatial -
https://pysal.org/libpysal/api.html#sphere
Feature engineering: spatial lags (distance from city center; how close intersections are)
indices: types of roads
https://pysal.org/tobler/api.html for some interpolation
https://mmaelicke.github.io/scikit-gstat/index.html for ?
https://github.com/GeoStat-Framework/PyKrige used for regression kriging (krigging on the residuals of RF)
Django, Marc Compte
QGIS Bridge, Metadata & Geostyler, Paul van Genuchten, geocat
Seismic silences during the COVID19 lockdown, Artash Nath
https://github.com/Artash-N/Monitor-My-Lockdown-Using-Seismic-Vibrations
SaferPLACES platform: a Geopython-based climate service addressing urban flooding hazard and risk, Stefano Bagli
http://platform.saferplaces.co/
https://earthengine.google.com/timelapse/ - for motivation of sprawling cities
Flood hazard model. pluvial - extreme rainfall event. safer_rain - hierarchical filling and spilling
Coastal extreme sea levels. safer_coast
Riverine flood. fluvial.
Damage assessment bayesian network model
Mitigation measures
https://samapriya.github.io/awesome-gee-community-datasets/projects/global_power/
ML-Enabler: Enabling Rapid Machine Learning Inference of School Mapping in Asia, Africa and South America, Martha Morrissey, Development seed
https://github.com/developmentseed/ml-enabler
Image classification of tiles (1 = school. 0 = no school).
TT-SNE shows mix of images.
Use https://www.tensorflow.org/api_docs/python/tf/data/TFRecordDataset for effective TF training. Use Kubeflow.
Day 1 room 2
Crop yield prognosis using ML and EO data, Peter Fogh, SEGES
https://vimeo.com/geopython/review/539850665/a5a1e8d8d7?sort=lastUserActionEventDate&direction=desc
https://www.seges.dk/software/plante/cropmanager
Used gradient boosting from sklearn
Interpolate to daily data and resample to 14 day data
Mapping, Monitoring and Forecasting Groundwater Floods in Ireland, Joan Campanyà i Llovet, IT Carlow / Geological Survey Ireland
https://vimeo.com/geopython/review/539470731/ef072137e0?sort=lastUserActionEventDate&direction=desc
The power of "Where" - Location data in Moovit, Yehuda Horn
https://vimeo.com/geopython/review/539470769/566a70124c?sort=lastUserActionEventDate&direction=desc
https://github.com/mrcagney/gtfs_kit
Universal geospatial data storage with TileDB: No more file formats, Norman Barker, TileDB Inc
https://vimeo.com/geopython/review/539850335/470f80d8bc?sort=lastUserActionEventDate&direction=desc
https://github.com/TileDB-Inc/TileDB-Py
https://github.com/TileDB-Inc/TileDB-Examples
https://www.capellaspace.com/community/ - SAR data
3D Geological Modelling using GemPy, Kristiaan Joseph
https://vimeo.com/geopython/review/539073526/bfb74ae414?sort=lastUserActionEventDate&direction=desc
The Open Data Cube (ODC): a very intuitive tool to store, manage and analyze satellite images data, Aurelio Vivas
https://vimeo.com/geopython/review/539470798/d7a8664c57?sort=lastUserActionEventDate&direction=desc
https://github.com/DonAurelio/geopython-2021
https://github.com/DonAurelio/geopython-2021/blob/main/Presentation.pdf
https://datacube-core.readthedocs.io/en/latest/index.html
eemont: A Python Package that extends Google Earth Engine, David Montero Loaiza
https://vimeo.com/geopython/review/539470855/1d71f86f58?sort=lastUserActionEventDate&direction=desc
https://github.com/davemlz/eemont
https://eemont.readthedocs.io/en/0.1.9/
Nice methods e.g. ee.ImageCollection().maskClouds().filterBounds().scale().index()
https://github.com/davemlz/awesome-ee-spectral-indices
https://earthengine-stac.storage.googleapis.com/catalog/catalog.json
Deep learning-based remote sensing for disaster relief with Python, Thomas Chen
https://vimeo.com/geopython/review/540097666/ff29681003?sort=lastUserActionEventDate&direction=desc
ResNet18 - petrained on image net.
Cross-entropy loss
ADAM
LR = 0.001
100 epochs
K80 GPU
Gradient class activation map
Day 2 room 1
Predicting dissolved oxygen in a lagoon using interpretable machine learning, Dimitris Politikos
Extremely Randomized Trees (ERT)
The Mission Support System, Reimar Bauer
A QT application, a OGC web map server, a collaboration server to plan atmospheric research flights
https://github.com/Open-MSS/MSS
https://gmd.copernicus.org/articles/5/55/2012/gmd-5-55-2012.pdf
Curie Point Depth Mapping using PyCurious from Aeromagnetic Data, Izzul Qudsi
https://brmather.github.io/pycurious/
Understanding Qiskit: Quantum by Quantum, Anmol Krishan Sachdeva
https://github.com/greatdevaks/geopython-qiskit
Improved Crop Yield Prediction through Spatio-Temporal Analysis of Agricultural Data, Arjumand Younus
https://docs.google.com/presentation/d/1gqobnB-nDUmych2isMhEjq1caZEpIub5YX9Z8krPXdQ/edit#slide=id.p
https://github.com/phanein/deepwalk
The Bavarian Open Data Cube. Sebastian Foertsch
https://github.com/opendatacube?type=source
The Participatory Terrain model (ParTerra) in Python, Arjen Haag, Deltares
https://drive.google.com/file/d/1dD62ygkgrW4NrYou_I8o4X90YQiQl2Qa/view?usp=sharing
https://gitlab.com/deltares/parterra/parterra-python
OSM - https://www.youtube.com/watch?v=7sC83j6vzjo&t=27s
Over-Simplified Modeling - The case of the Global Warming Potential. Mike Müller
FaIR: Finite Amplitude Impulse Response simple climate model
https://github.com/OMS-NetZero/FAIR
https://github.com/hydrocomputing/igwp/tree/master/
https://www.nature.com/articles/s41612-019-0086-4
https://gitlab.ouce.ox.ac.uk/OMP_climate_pollutants/co2-warming-equivalence/
Trackintel: An open-source python library for human mobility modeling and analysis, Ye Hong
https://github.com/mie-lab/trackintel other packages in this space https://github.com/anitagraser/movingpandas https://github.com/scikit-mobility/scikit-mobility
this focusses on human mobility
https://blog.mapbox.com/9-years-of-openstreetmap-gps-tracks-available-for-mapping-47f6074c0688
https://www.microsoft.com/en-us/download/details.aspx?id=52367
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
https://github.com/qgis/QGIS-Enhancement-Proposals/issues/179
Pyinterpolate - Python package for spatial interpolation and deconvolution of areal data, Szymon Moliński
https://github.com/szymon-datalions/pyinterpolate
https://pyinterpolate.readthedocs.io/en/latest/tutorials.html
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
https://drive.google.com/file/d/1xdUbVbzrVcaKXu1CMIk4I5whFk3gD8s1/view
https://github.com/jsingh811/pyAudioProcessing
Cal ToxTrack: A Web GIS for Pollution Mapping in California, Megan Luisa White
https://docs.djangoproject.com/en/3.2/ref/contrib/gis/#module-django.contrib.gis
use PostgreSQL db with PostGIS
Day 2 room 2
Travel Time Prediction for Urban Travel using Uber Movement and OpenStreetMap, Vishnu Prasad
https://spatialthoughts.com/2020/02/22/snap-to-roads-qgis-and-osrm/
https://travel-time-prediction-app.herokuapp.com/
Spatial analysis of Covid-19 relation with weather parameters, Abouzar Ramezani
Maps with Django, Paolo Melchiorre
https://www.paulox.net/2021/04/23/geopython-2021/
Exploratory Movement Data Analysis, Anita Graser
https://vimeo.com/geopython/review/539472075/d68aff3d10?sort=lastUserActionEventDate&direction=desc
https://anitagraser.github.io/movingpandas/
https://github.com/anitagraser/EDA-protocol-movement-data
https://fosdem.org/2021/schedule/event/geopandasholoviews/
https://www.youtube.com/watch?v=dRE9Zl7jpUA
https://github.com/anitagraser/movingpandas-examples