Agriculture: Solutions Based on Satellite Imagery

Through information solutions based on the use of satellite photos, the application of classification models and the implementation of machine learning algorithms, it is possible to optimize the management of large plantations and minimize the risks faced by crops that affect profitability per hectare planted.

Friday, May 28, 2021

The growing availability of data that exists today is leading companies to seek new ways and tools to take advantage of this huge wave of information that is being generated in different business sectors.

Agricultural activity is not exempt from these problems. Until now, through the use of drones and the analysis of low resolution satellite images it was possible to solve some typical problems of the sector: observation and general analysis of plantations, detection of large weed outbreaks, among others. But now, the tools used until now are beginning to be limited in their capacity to manage the "new wave" of information, for which not only other tools are needed, but also other scientific skills and another technological infrastructure for processing all this data.

The work teams of agricultural companies that work with a "data driven" approach have found in Business Intelligence solutions based on the analysis of satellite photographs, a tool of great value to reduce the risks in the investments they make in their crop fields. The following is a real case in which CentralAmericaData had the opportunity to provide its services.

Problem to be solved

A corporation in the agricultural sector, dedicated to the cultivation of pineapple, needed to improve its process of identifying the threats faced by its plantations through the analysis of high-resolution satellite images.

Our Business Intelligence Solution

In order to solve this problem, CentralAmericaData developed a model that has the capacity to classify satellite images, a tool that helps to detect different types of threats faced by the company's plantations, from illegal invasions of the land and theft of seeds or bulbs, to the identification of weed outbreaks, among others.

For the start-up and implementation of this solution, various methodologies were used, combining the use and analysis of high-resolution images with the application of machine learning algorithms.

Methodology and data sources used

The methodology used for the development of this solution consisted of the application of image classification models. These models focus on detecting and characterizing, in the satellite photographs, all the elements that are of interest to the user, regardless of their size. Once this process is done, the data is introduced into a classification model that, as it processes more information, is "trained" more and more, increasing the degree of accuracy of the results.

With the implementation of this model and combined with the application of machine learning algorithms, a solution was generated that allowed the business group to identify, practically in real time, the specific areas of the plantations that face the greatest threats.

What added value is generated by this type of solution?

The company immediately identified the areas where its crops faced risks and focused on optimizing its control processes, thus reducing losses caused by these factors and optimizing profitability.

¿Busca soluciones de inteligencia comercial para su empresa?

Do you need more information about your business sector?

Request more information:

this site is protected by reCAPTCHA and Google's privacy policy and terms of service.
Need assistance? Contact us
(506) 4001-6423

More on this topic

New Trends in Predictive Modeling and AI in Construction

August 2021

Many decision makers in the construction industry don't know what to do with the vast amount of data they have available, as they don't have the right tools to analyze it in a way that will have a meaningful impact on their projects.

Predictive modeling, Big Data analytics, machine learning and artificial intelligence unlock the ability to leverage the data coming from projects to organize and interpret it and thereby discover patterns more quickly. These tools reduce problems, lower costs and mitigate the risk of different processes in construction projects by making the work more predictable and efficient.

Benefits of Geolocation and Big Data in the Agricultural Sector

August 2021

Geolocation systems and Big Data turn data into information that farmers and land managers can use to make more informed and timely decisions to increase productivity.

Sensors located in fields, tractors and on satellites high above farms are constantly collecting data.

Geolocation systems and Big Data are able to convert this data into information that agricultural companies can use to make more informed and timely decisions, increasing productivity, allowing to collect information on soil and plant needs to apply treatments that increase agricultural production, managing costly resources such as fertilizers, pesticides and herbicides.

Geospatial Data for Real Estate Market

June 2021

Through solutions based on the analysis of satellite photos and machine learning models, it is possible to optimize the process of identifying the best land uses and analyze the areas where a construction project will be developed with a high level of detail, in order to find the optimal location and minimize investment risks.

The accelerated growth in the availability of data and the solutions and technologies being developed to take advantage of it is directly impacting all industries, and the real estate and construction industry is no exception.

Satellite Images for Decision Making

May 2021

With the technologies available it is possible to use satellite photos to detect types of surfaces and roofs, objects, land use and variance in farmland, and then analyze the results and transform them into useful data for business decision making.

In the past, it was possible to establish whether an area was industrial, commercial, residential or agricultural by analyzing aerial images, but today, with the use of high-resolution satellite images, more information can be obtained.