Skip to content
Machine Learning

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Machine Learning in ArcGIS

ArcGIS includes regression and interpolation techniques that can be used for performing prediction analysis e.g. Bayesian kriging (EBK), areal interpolation, EBK regression prediction, ordinary least squares (OLS) regression, OLS exploratory regression, and geographically weighted regression (GWR).

  • Financial Services
  • Retail
  • Transportation
  • Government
  • Health care
  • Oil and Gas
  • Urban Development
  • Conservation

Machine Learning & AI

AI GIS is combination of AI technology with various GIS functions, including spatial data processing and analysis algorithms (GeoAI) that incorporates AI technology.

Two of the most widely adopted machine learning methods are supervised learning and unsupervised learning

  1. SUPERVISED LEARNING is just fitting data to a function for prediction
  2. UNSUPERVISED LEARNING recognizes what the data is using patterns from unlabelled data.

We apply AI in areas such as classification, prediction, and segmentation for GIS

  • Image Classification (Support Vector Machine)
  • Image Segmentation and Clustering with K-means
  • Prediction Using Empirical Bayesian Kriging (EBK)

we also deplo the use tools such as Picteria

Example Use Cases:
  1. Land classification (vegetation monitoring, growth, decline, change)
  2. Impervious surface
  3. Change detection/anomaly
  4. Geosptatial attribute trending (census, twitter)
  5. Agriculture
  6. Road networks
  7. Object identification & tracking (ships, cars)
  8. Imagery mosaicing, stitching, pre-processing
  9. Resolution enhancement
  10. 3D modeling & Digital Elevation/Surface Mapping
  11. Coastal vegetation monitoring
  12. Kriging