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Spatial Thinking with Python Sangarshanan

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{{ ME_IRL }} 2 sangarshanan sangarshanan Sangarshanan Recently graduated from VIT Vellore Working at Grofers Makes memes hanging upside down

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The geostory begins

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When you realize that John Snow was basically the first person to effectively make use of geospatial data everything

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Location Intelligence 7 Intelligence you acquire from spatial thinking

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When you realize that spatial data doesn’t get the attention it deserves

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WHAT IS GEOSPATIAL DATA ?

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Geospatial data is any data with a geographic component that can be layered onto a map 10

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Types of these geographic components ?

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12 Vector Points / Geometries /Shapes eg: Shapefiles, GEOJSON Raster Pixels with or without spatial metadata eg: GEOTIFF, TIFF

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Raster Data

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We can get our Raster’s degree now

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We can get our Raster’s degree now - Monitoring and predicting natural phenomena like Hurricanes, Forest fires etc - Do tons of cool analysis over time like calculating the Affluence of the area, Extent of vegetation, Types of buildings, Road network, Population, Nightlights.

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Well Known text Well known binary

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Spatial Reference System Geographic coordinate systems Projected coordinate systems

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SHP KML Carto KMZ Geojson GML KML Geotiff CSV GPX ESRI GeoRSS GSC SHP Sentinel 2

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Read/ Write/ Analyze

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GDAL / OGR Geospatial Data Abstraction Library YEAR 1998 154 raster and 93 vector geospatial data formats

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ogr2ogr can convert data in PostGIS to KML ogrinfo lists information about the data

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Vector Data OGR's neat and nimble API for Python programmers Geographic data to pandas objects Geometry Engine – Open Source

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OSR Projections / Rtree Pythonic cartographic projections and coordinate transformations library Advanced spatial indexing features Fiona ,Shapely, Geopandas

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Indexing Geospatial Data Suppose you want to find all the geospatial points in a given radius Are you gonna iterate ? HELL NAHHH Use Spatial indices provided by the spatial extensions of traditional databases like postgres ( Postgis uses Rtrees )

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Hexagonal grid indexing (Uber H3)

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Raster Data Rasterio reads and writes raster formats and provides a Python API based on N-D arrays.

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There are also packages than combine these existing packages that are actually wrappers on already existing packages

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Vector data Raster data

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OSMNX (0SM + Networkx) Work with road network data from osm using networkx Analyze and visualize street networks, routing , travel times etc

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Visualize

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When you plot and visualize all your spatial layers on a basemap

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You need to know javascript to create such cool maps

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Just Plot em Matplotlib (for everything) Leaflet / Openlayers / Mapbox Plotly + Mapbox / Mapboxgl

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Geometry + Matplotlib = Descartes Enables plotting of shapely geometries as matplotlib paths/ patches.

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Me after running import tensorflow as tf

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PySAL: Python Spatial Analysis Library Spatially constrained Clustering Spatio-temporal data analysis Spatial regression and Statistical modeling

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It’s Code Time https://github.com/Sangarshanan/talks/blob/master/spatial-thinking- with-python/spatial_thinking.ipynb

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https://github.com/Sangarshanan/talks/tree/master/spatial-thinking-with-python

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What’s the POINT(12.22,73.32) ?

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Marketing

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GEO - Marketing

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PennyWISE Decision Making

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GEO - Surge

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That was UnUbercool

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Blogs I stole from - https://blog.mapbox.com/a-dive-into-spatial-search-algorithms-ebd0c5e39d2a - https://github.com/pcjericks/py-gdalogr-cookbook - https://medium.com/locale-ai - https://geoffboeing.com/ - https://towardsdatascience.com/geospatial-indexing-with-ubers-h3-766399b690c - https://medium.com/@chrieke/essential-geospatial-python-libraries-5d82fcc38731 - https://pysal.readthedocs.io/en/latest/

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Hey You…. Yes you :) You’re Breathtaking