Machine learning

How can Machine Learning be applied with GIS?

Having lots of different GIS geographic data is not enough to know the reality of a business or market. You need a tool capable of extracting the last drop of its value. Fortunately, these solutions are already well established in different business environments and Machine Learning technology is a key ingredient. We tell you why it is essential to “listen” in detail to everything that geodata tells us. 

What is Machine Learning?

Machine Learning is a field within Artificial Intelligence consisting of a group of algorithms and techniques that work with data to solve a given problem as optimally as possible.

The main quality of Machine Learning is that these algorithms are able to learn by themselves and improve their results with experience, i.e. as they are fed with more and more data.

Machine Learning has the advantage of working with huge amounts of information and detecting patterns and trends that would be impossible to identify using other more “traditional” techniques. In this way, they can make accurate predictions, as well as classify and group different types of data (qualitative, quantitative and images).

How solutions based on Machine Learning and GIS data work

Artificial intelligence

Among all the types of data that can be useful for Machine Learning solutions are those that have a geographic component, such as geolocated information, satellite images or orthophotos, among others. These data are presented in different formats and scales and come from many different sources.

This heterogeneity means that in order to achieve the full value they bring, it is necessary to apply an effective working procedure. An example of such a procedure is roughly summarised in the following steps:

  1. Collection of geolocalized data from datasets, sensors or any other capture system.
  2. Transformation and homogenisation of data.
  3. Training of artificial intelligence algorithms to generate a data model.
  4. Identification of trends and patterns.
  5. Obtaining the desired result: prediction, explanation of a phenomenon, grouping of data, etc.
  6. Decision-making on the basis of the results.

What are the applications and benefits of Machine Learning solutions that work with GIS?

There are many ways in which GIS data analysis with Machine Learning can offer benefits of great interest to different types of industries. In this article we cannot address all of them, but we can give a glimpse of some of the most important ones.

If we move to sectors such as retail, catering, banking or similar, these solutions are very useful when it comes to knowing in detail the behaviour of potential customers. For this, they can count on datasets related to aspects such as:

  • Pedestrian and vehicle mobility: average number of people and vehicles in the vicinity of the establishments, days and hours of highest density, parking data, etc.
  • Consumption habits: average expenditure, most and least sold products, time distribution of sales, etc.
  • Socio-demographic data: income levels, ages, types of families, educational levels, etc.

With proper processing of this data, Machine Learning algorithms can make accurate predictions about which areas will be ideal for opening new establishments, which ones will have to be closed, which product catalogue will have more sales in each store, the busiest times to better manage their human and material assets, better understand the competition, the reality of the market and many other opportunities for improvement.

From a logistics perspective, Machine Learning and GIS also have the ability to study and recommend the best routes for either procurement or home delivery in an omni-channel scenario.

In addition, Machine Learning processing of maps and satellite images has proven its usefulness in recognising the environments of a specific location and searching for areas that are similar to them. For example, the proximity of public transport stops, work, leisure or educational centres can influence the success or failure of a business.

Another type of companies that have great growth potential thanks to Machine Learning and GIS are those in the telco sector. They will be able to analyse and predict by areas the evolution of network performance, user demand and other very useful information to design the deployment of infrastructure and the allocation of resources with the highest possible profitability and offering a quality service tailored to the demands of their customers.

The arrival and standardisation of Machine Learning in business has completely changed the way of understanding reality in many industries and, for this, the participation of GIS information is also fundamental. With this cocktail, improvements can be seen in a short time thanks to more accurate decisions that are correctly documented.

Do you need to have them now? Locatium offers you the data and the appropriate technology for your project in an innovative platform that will show, in a clear and understandable way, the conclusions you need to know to lay the foundations for a successful project. We invite you to get to know it by means of a free demo. Ask for it now!



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