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Machine Learning and GIS

Category: Technology
Author: David Kitavi
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Machine Learning is a field that has been in existence for decades. For years, it has been used by scientists to explore and analyse millions of data. Today, with the advent of huge chunks of data, machine learning is playing crucial roles in extracting information from millions of dataset.

GIS, on the other hand, is a field that has been in existence for centuries. John Snow, a health worker, is accredited to be the pioneer of GIS. He mapped the spread of cholera.

Although GIS has experienced radical technological growth, such as introduction of both commercial and free open source software and scripting tools. Machine learning has however not been fully integrated into many of these platforms.

Classification, segmentation and clustering are some of the ways in which machine learning can be used with spatial data. Companies such as ESRI and Google have invested hugely on artificial intelligence products governing GIS.

Typical example is the Google Earth engine that allows individuals to analyze satellite data using machine learning models. ESRI have python API's such as arcgis.learn which allows developers to utilize their resources.

Therefore, although both fields have been in existence for long, good measures need to be taken to ensure that individuals can use the two skills with ease. As an example, web-accessible and user friendly interfaces could provide a basis for knowledge sharing and actualizing machine learning in the geospatial field.

Comments

*** DevOPs ,says: A fantastic field of exploration