Table Joins are a way to join 2 separate layers based on a common attribute value. QGIS has a Join Attributes By Field Value algorithm that allows you to table joins. A limitation of this algorithm is that the field values must match exactly. If the values differ slightly – the join will fail. There are many times where you are trying to join 2 layers from different sources and they contain values which are similar but may not match exactly. Fortunately QGIS now has built-in fuzzy string matching functions that can be used – along with Aggregate function – to do table join based on fuzzy matches.

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Mapshaper is a free and open-source software for spatial data processing. It is written in javascript and runs in your browser without any extra plugins and can perform a range of analysis. It started out as a tool for topologically-aware simplification, but has evolved into a swiss army knife of spatial data processing tools. All processing is done in the browser locally, and I have found that it can handle large volumes of data easily and processing is usually much faster than desktop based GIS software.

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When you want to buffer features that are spread across a large area (such as global layers), there is no suitable projection that can give you accurate results. This is the classic case for needing Geodesic Buffers – where the distances are measured on an ellipsoid or spherical globe. This post explains the basics of geodesic vs. planar buffers well.

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