Good news folks! MySQL has quietly become a very good spatial database that is widely available on almost all web-hosting platforms. If you are looking for an affordable spatial database solution its worth giving MySQL a look.
PostGIS has long been the gold standard for open source geospatial databases. MySQL had some spatial capabilities but were pretty limited for real GIS applications. That changed a few years ago with MySQL version 5.6 and even more with version 8 but it seems that MySQL has still not been given a solid look by most geospatial professionals. This is unfortunate in my opinion because MySQL has one BIG advantage over PostGIS. It is available on almost every webhosting platform in existence and you can host your geospatial data in a MySQL database that is accessible from anywhere in the world for only a few dollars per month. Inexpensive hosting options for PostGIS on the other hand have gone the way of the dinosaur and are essentially non-existent today. It was this lack of affordable options for PostGIS hosting that caused me to take a second look at MySQL and I liked what I found and wanted to spread the good news.
If you are interested in learning more you can sign up for my new course MySQL for Geospatial Applications today for $9.99 using the coupon code MYSQLGEO, This offer is good through Dec 1. All of my other courses are also available during this time period for the same price using the same coupon code.
This course will teach you
What a spatial database is and why you shoud use one
Review of SQL for non-spatial data
SQL functions for spatial data and analysis
How to load your GIS data into MySQL
How to access your MySQL data from a variety of clients
How to set up user accounts and control access to your data
How to deploy your MySQL database to a web-hosting platform
How to customize MySQL to automate your business logic with stored procedures, custom functions, and triggers
February is here and there are a lot of new students from the Black friday and New Years sales. But I’d like to give everyone the chance to buy another course or two at $9.99 before spring arrives to motivate them to keep the learning going until spring arrives As a bonus its beneficial to the instructors, like me, if you buy now. So if you are looking for ways to continue your professional development during the winter, please consider an Udemy course on open source geospatial technologies. You can buy them TODAY and watch them when you are ready.
All of my courses on open source geospatial technology will be available through February 9 using the coupon code FEB2023.
I am pleased to announce a new course titled “Google Tools for GIS Applications“. This course is an overview of Google Cloud Platform tools, analytical tools, and mapping API’s that may be of interest to geospatial professionals. The course is broad rather than deep. My goal is to show you how to get started with many different products with an emphasis on geospatial applications. In many cases there are existing courses that cover the details but with little information on geospatial applications and this course is intended to fill in those gaps.
I am pleased to announce the availability of a new course “Geospatial Data Science with Python: Data Visualizations“. This course will focus on visualizing data in the Jupyter Notebook environment. I start with the basics of Matplotlib, and then move on to higher level API’s of Panda’s and Seaborn. You will learn how to make beautiful charts that clearly show important patterns in your data in a number of different ways. And since this course is about Geospatial Data Science, we will also focus on geospatial visualizations. Geopanda’s provides core geospatial plotting capabilities and I also demonstrate how those visualizations can be modified in many ways using Matplotlib to control the placement and styling of legends, labels, annotations and more. I also demonstrate how to work with and display raster data using the Rasterio package and online background maps like OpenStreetMaps and OpenTopoMaps with the Contextily package.
I am pleased to announce the availability of a new course “Geospatial Data Science with Python: Statistics and Machine Learning I“. This course is about statistical analysis of vector data and machine learning using vector data. Statistical inference and machine learning are closely related and use a similar set of methods but ultimately have different goals. Statistical inference is used to make inference from a sample to a population and its goal is generally to improve understanding of the underlying processes of interest, while the goal of machine learning is to use a set of training data to “teach the machine” to make predictions about new observations where the truth is not known.
Get started with the latest Geospatial Data Science tools and learn what all the hype is about. This approach provides a stark contrast to traditional desktop GIS analysis methods. In this course we use Jupyter Notebooks to provide an interactive python coding environment, and GeoPandas to read, store, analyze, and visualize our data. Continue reading “New Course: Geospatial Data Science with Python: GeoPandas”
QGIS plugins allow you to extend the QGIS toolset to fit your own specific needs, or to develop general purpose tools that solve common problems that others may be facing. Although you can do quite a lot with Python in QGIS without developing a plugin (see Automating QGIS 3.xx with Python), plugins allow you to develop beautiful graphical user interfaces using PyQt5, and make your solutions easily available to other people.
PyQt5 from A-ZTo register simply click on the links above and the discount will be applied automatically.This sale is in preparation for the release of a new course “QGIS plugin development with Python”. This is not a beginner class and I will expect students to be familiar with the content of the above three courses so if you are interested in QGIS plugin development and feel you need to brush up on your Python skills, you can purchase one or all of these courses now and be ready when the QGIS plugin course is realized (probably the first week of November).