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How MapInfo Pro Leverages AI for Smarter Geospatial Analysis.

Writer: Howard KrinitzskyHoward Krinitzsky

Updated: Feb 12

MapInfo Pro lacks inherent AI features, but it can utilize AI via different integrations, plugins, and scripting. Here's how AI can be incorporated into MapInfo Pro:


AI-Powered Data Analysis

  • Machine Learning with Python: MapInfo Pro supports Python scripting, allowing integration with AI/ML libraries like Scikit-learn, TensorFlow, and PyTorch for predictive modeling and pattern recognition.

  • Geospatial AI (GeoAI): AI models possess the capability to analyze spatial data for applications including land use classification, anomaly detection, and predictive analytics.


Image Recognition & Processing

  • Satellite & Aerial Imagery Analysis: Integrating AI-driven tools such as Google Earth Engine allows for Deep Learning-based object detection to be utilized in land cover classification, feature extraction, and urban planning.

  • Integration with Cloud AI Services: Connect MapInfo Pro with platforms like Microsoft Azure AI, Google AI, or AWS SageMaker for image processing and spatial data insights.


Automation & Smart Mapping

  • AI-Assisted Data Cleansing: AI algorithms can streamline geocoding, extract features, and fix data errors automatically.

  • Predictive Heatmaps & Spatial Trends: AI can help analyze movement patterns, detect hotspots, and predict future trends using historical spatial data.


Natural Language Processing (NLP) & AI Chatbots

  • MapInfo Pro can incorporate AI-driven chatbots or NLP tools to facilitate voice-based or text-based queries for spatial analysis, eliminating the need for complex queries.


Advanced GIS & AI Interoperability

  • Using AI Models in GIS Platforms: AI models developed in Python, R, or cloud-based platforms can be integrated with MapInfo Pro using APIs or database connections.

  • Esri & QGIS AI Integration: Data processed with AI in platforms like ArcGIS or QGIS can be imported into MapInfo Pro for further spatial analysis.


MapInfo Pro: Transforming Geospatial Analysis with AI
MapInfo Pro: Transforming Geospatial Analysis with AI


Sample MapBasic script to interact with external Python Object Detection Model

Option Explicit

' Define file paths


Dim sImagePath As String

Dim sPythonScript As String

Dim sOutputCSV As String


sImagePath = "C:\MapInfo\input_image.jpg" ' Image to be processed

sPythonScript = "C:\MapInfo\detect_objects.py" ' Python script location

sOutputCSV = "C:\MapInfo\detected_objects.csv" ' Output from Python




' Export raster layer (if needed)

Run Command "Export Raster """ + sImagePath + """"

' Run the Python script using ShellExecute


Declare Function ShellExecuteA Lib "shell32.dll" _

(ByVal hwnd As Integer, ByVal lpOperation As String, _

ByVal lpFile As String, ByVal lpParameters As String, _

ByVal lpDirectory As String, ByVal nShowCmd As Integer) As Integer


Dim sCommand As String

sCommand = "python """ + sPythonScript + """ """ + sImagePath + """ """ + sOutputCSV + """"

Call ShellExecuteA(0, "open", "cmd.exe", "/c " + sCommand, "", 1)


' Wait for Python script execution (optional: add a delay)

Pause 5 ' Wait for 5 seconds

' Import CSV results as a point layer in MapInfo

Dim sTableName As String

sTableName = "Detected_Objects"


' Check if table exists, then drop it

If TableInfo(1, TAB_INFO_NAME) = sTableName Then

Close Table sTableName

Kill File sTableName + ".TAB"

End If

' Import detected objects from CSV

Open Table sOutputCSV As sTableName

Commit Table sTableName

Map From sTableName


Please reach out to us if you want to apply a particular AI use case in MapInfo Pro.



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