Spatial thinking with Python and QGIS
Sangarshanan (~Sangarshanan) |
Data scientists work with all kinds of data, It could be a text an image or maybe it is a bunch of coordinates. Though computer vision and natural language processing have hit it off spatial data science doesn’t get the attention it deserves. Spatial data has both social and industrial impact. Spatial data is useful in agriculture and for observing weather patterns to predict natural disasters. It is also very important for industries that deal with logistics and supply chain management.
In this talk I would talk about spatial data it’s importance and elaborate on how to store, manipulate and visualize such data. I would talk about the use of Python and several related modules (GDAL, Shapely, Fiona etc) in processing geospatial data. I would also like to discuss QGIS, a desktop based open source GIS platform and a variety of useful operations that can be done with it. I would also like to talk about building geospatial dashboards and servers to serve spatial layers and discuss the geospatial support provided by the latest elastic stack V7.0
Here is how the talk would be structured
- What is GIS data and it’s importance
- Discuss the various spatial databases to store spatial data of any size (from Postgis to Geomesa)
- Using Python to access and manipulate spatial and spatiotemporal data
- QGIS to plot and perform operations on the data manipulated for visualization using python
- Overview of geospatial servers (Geoserver, QGIS server) and dashboards (Cartodb, Kibana) to store and share geospatial layers
The talk with begin with a quick introduction followed by an interesting problem statement that would be solved as a demo using a simple geospatial pipeline with Postgres ,python and QGIS. The talk ends with a discussion on how to publish the result of the problem statement followed by a small demo on how geospatial dashboards that can be built using kibana and cartodb .
This is a beginner friendly talk. Basic Python knowledge would be more than necessary
Basic knowledge on GIS data would be nice (A simple google search would be sufficient)
I am attaching some useful links for interested folks
My name is Sangarshanan and I am currently an intern at Grofers.
I am in my final year of Undergraduation and will graduate from VIT Vellore this July.
I am interested in data science and data engineering. I love working with text data and GIS data. I have been working on geospatial data in supply chain for the past few months.
I also love to talk about space, tennis , pop culture and memes