A short tour of Open Geospatial Tools of the scientific Python ecosystem

One of my favorite statistics is that about 80% of data in the world, contain some element that is spatial. For instance, take the list of gas stations in a city or restaurants in a city, revenue from medical industry, there is always some element of this data that can be categorized as being spatial - be it locations, routes the products take, cost variations in gas prices etc.

This spatial relationship is of significant interest to me and I have been analyzing them for over a decade and have been building software to analyze them for more than half of the past decade. While majority of what I built were proprietary, this blog is a look at what is available in the open-source ecosystem and when to use which tool.

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Imagery in ArcGIS ecosystem

ArcGIS apps give you access to work imagery data from a variety of file formats. The goal is to unify the differences in image characteristics (spatial, spectral, temportal resolutions), file formats (local - different types of image formats, mosaic and web). However, it is useful to understand the basics. This page does not teach you remote sensing or spatial analysis, it just gives you a roadmap to navigate the software.

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A few tutorials I authored for ArcGIS

Below is a non-exhaustive list of tutorials that I authored for ArcGIS. The objective of these tutorials is to demonstrate spatial data analysis using the scientific computing ecosystem of Python and the ArcGIS stack.