4 Recommended softwares and tools
I will be using the following to collect data, perform analysis and visualize the results:
OpenStreetMaps (OSM): OSM is a crowdsourced mapping tool that is used to collect and update geographic data. It is a free and open-source mapping tool that provides map data and related services to users worldwide. You might compare this to Google Maps, but it is even better because we will be able to pull data from the OSM database and perform analyses
QGIS: QGIS is a free and open-source geographic information system (GIS) software that is used for creating, editing, visualizing, and analyzing geospatial data. QGIS is a powerful tool that supports a wide range of vector, raster, and database formats.
Figma: Figma is a cloud-based design tool that makes it a breeze to layout and create infographics. You could use Photoshop or Illustrator do the the same thing but I like it for the convenience. We’ll need a vector editing tool to handle SVG formats.
Python: Python is a popular language for geospatial data analysis and visualization due to its large ecosystem of libraries and tools. We’ll be using this rarely if we need to process some data for analysis.
R: R is a programming language that is widely used for statistical analysis and data visualization. R has a large number of libraries and packages for geospatial analysis and visualization.
DepthmapX: DepthmapX is a free and open-source software tool used for spatial network analysis. It was developed by researchers at the Bartlett School of Architecture, University College London. One of the key features of DepthmapX is its ability to perform space syntax analysis. Space syntax is a theory that links the spatial configuration of a built environment to the social, cultural, and economic activities that take place within it. DepthmapX provides a range of tools to analyze spatial configurations, such as isovist and visibility analysis, axial analysis, and integration analysis.
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