Learning SQL: Exploring Geospatial Data Analysis and GIS Applications

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Welcome to this guide on exploring geospatial data analysis with SQL and understanding the various applications of Geographic Information Systems (GIS). SQL, which stands for Structured Query Language, is a powerful tool for managing and analyzing large data sets stored in relational databases. When combined with an understanding of GIS, it is possible to conduct powerful spatial and geographic analyses directly within the database.

Understanding GeoSpatial Data

Geospatial data, or spatial data, are data points that are associated with a specific geographical location. These could be coordinates, addresses, or even just a city name. Geospatial data analysis is the collection, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

SQL and GIS Applications

SQL procedures enable you to perform advanced analysis and optimization on data within the database without additional coding. These analyses can yield meaningful insights that can be used across various sectors - urban planning, hazard assessments, disease tracking, population growth, and crime pattern analysis being to name a few.

Example SQL Code for GIS applications

Using GIS in SQL

PostgreSQL, an open-source advanced SQL platform, offers PostGIS, a spatial database extender, which allows for geographic objects support. It also lets you run location queries in SQL. For example:

Analysing geospatial data with SQL is a powerful tool to produce data-driven decision-based solutions. By honing these skills, you’ll open doors to solving real-world problems of a diverse range.

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