I have been asked many times on possible ways one can get started in building geospatial-based applications and analysis software. Few resources are available online to explain these approaches, and also Geoinformatics, Geomatics, and GIS.
This article is an approach to explain Geoinformatics, Geomatics, and GIS, and how to begin a programming approach towards the fields.
What is Geoinformatics?
It is the science and technology dealing with the structure and character of spatial information, capture, classification, and qualification, storage, processing, portrayal, and dissemination, including the infrastructure necessary to secure optimal use of this information.
Geoinformatics is a combination of two words, Geo which refers to Geospatial, and Informatics which refers to Information Science a multidisciplinary science (e.g., computer science, software engineering, computer vision, mobile and game technology, intelligent system, internet of things).
What is Geomatics?
It is a discipline concerned with the collection, distribution, storage, analysis, processing, presentation of geographic data or geographic information. It deals more with surveying and includes geomatics engineering (and surveying engineering) with geospatial science (geospatial engineering and geospatial technology).
What is GIS?
A geographic information system (GIS) is a framework for gathering, managing, and analyzing data. Rooted in the science of geography, GIS integrates many types of data. It analyzes spatial location and organizes layers of information into visualizations using maps and 3D scenes.
GIS Programming Languages
We have numerous programming languages out there, and it is hard to choose which one is best for GIS applications. Python is a multipurpose programming language, and so far, it is the language I advise people to learn when starting with GIS programming. You should also learn JavaScript because this will be useful when dealing with some mapping libraries like Leaflet and Google map APIs.
Languages such as C and C++ also make use of advanced application development. R and Julia are well recognized when dealing with Geospatial Analysis and Big data. Other programming languages used are depending on the task at hand and companies specific requirements.
Conclusion
You can now begin your journey into building GIS applications with a better understanding and a clear pathway. You sure don't want to miss the coming articles. Stay tuned.
Feel free to reach out to me via Twitter: @MustaphaMoshoo8
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