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You're tasked with working with geospatial databases. What's the best way to get started?

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Geospatial databases are specialized systems that store and manage spatial data, such as locations, shapes, and attributes of geographic features. They are essential tools for many Geographic Information Systems (GIS) applications, such as mapping, analysis, and visualization. If you're tasked with working with geospatial databases, you might wonder what's the best way to get started. Here are some tips to help you learn and master this skill.

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1 Know the basics

Before you dive into the details of geospatial databases, you should have a solid understanding of the basic concepts and principles of spatial data. For example, you should know the difference between vector and raster data, the types of spatial data models, the common spatial data formats, and the methods of spatial data quality and accuracy assessment. You should also be familiar with the concepts of coordinate systems, projections, and transformations, as they are crucial for ensuring the consistency and compatibility of spatial data across different sources and platforms.

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Shelley Jeltema

Assistant Professor at Lansing Community College
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I came to work in the geospatial field from a vastly different starting point. I was a long time IT Solutions Architect. My solutions were data centric so knowing about databases and how applications connected to databases was critical. I was very familiar with data structures, data formats, controlled access, data relationships before I ever knew what GIS was. In my years of teaching GIS, I have learned that students do better when they have a solid foundation in Databases, data architecture, and SQL before they start learning about geospatial databases. It makes the transition easier.

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2 Choose the right software

There are many software options for working with geospatial databases, ranging from desktop applications to web-based platforms. Some of the most popular and widely used ones include PostgreSQL with PostGIS, Oracle Spatial and Graph, Microsoft SQL Server Spatial, Esri ArcGIS, QGIS, and Google Earth Engine. Each software has its own advantages and disadvantages, depending on your needs, preferences, and budget. You should compare and evaluate the features, functions, and performance of different software, and choose the one that best suits your project and workflow.

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3 Learn the SQL language

SQL, or Structured Query Language, is the standard language for interacting with relational databases, including geospatial databases. SQL allows you to create, manipulate, query, and analyze spatial data in a geospatial database. You should learn the basic syntax and commands of SQL, as well as the spatial extensions and functions that are specific to each geospatial database software. For example, PostGIS provides a set of spatial functions that follow the Open Geospatial Consortium (OGC) standards, such as ST_Intersects, ST_Contains, ST_Buffer, and ST_Distance. You should also learn how to use SQL in combination with other programming languages, such as Python or R, to automate and enhance your spatial data processing and analysis.

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Shelley Jeltema

Assistant Professor at Lansing Community College
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Learning how to Extract, Transform, and Load (ETL) data is an absolute necessity. SQL is a major tool when it comes to data manipulation. I would also consider SQL to be a foundational requirement for working with any type of database. I would also suggest learning about stored procedures that will help reduce development time and increase accuracy and repeatability. It can also help with reducing processing time since you would not be reliant upon slower scripting languages. Learning programming language syntax and structure are important as well. R has statistic specific syntax but it is slow as is Python that has not been compiled. These work great for smaller tasks. Larger more complex analysis can take hours when coded in Python or R.

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4 Practice with real data

The best way to improve your skills and confidence in working with geospatial databases is to practice with real data. You can find many sources of free and open spatial data online, such as Natural Earth, OpenStreetMap, USGS, NASA, and FAO. You can also use your own spatial data, if you have any, or create some using GIS software or tools. You should try to perform different tasks and operations on the spatial data using geospatial databases, such as importing, exporting, indexing, joining, filtering, aggregating, and visualizing. You should also check the results and outputs of your queries and analysis for accuracy and validity.

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5 Seek feedback and support

Working with geospatial databases can be challenging and complex, especially if you encounter errors, bugs, or issues that you don't know how to solve. You should not hesitate to seek feedback and support from others who have more experience and expertise in this field. You can join online communities and forums, such as Stack Overflow, GIS Stack Exchange, Reddit, and LinkedIn, where you can ask questions, share your problems, and learn from other users' solutions and suggestions. You can also take online courses, workshops, or tutorials that teach you the fundamentals and best practices of working with geospatial databases, such as those offered by Udemy, Coursera, or Esri.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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You're tasked with working with geospatial databases. What's the best way to get started?

1

2

3

4

5

6

1 Know the basics

2 Choose the right software

3 Learn the SQL language

4 Practice with real data

5 Seek feedback and support

6 Here’s what else to consider

Geographic Information Systems (GIS)

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You're tasked with working with geospatial databases. What's the best way to get started?

1

2

3

4

5

6

1 Know the basics

2 Choose the right software

3 Learn the SQL language

4 Practice with real data

5 Seek feedback and support

6 Here’s what else to consider

Geographic Information Systems (GIS)

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