How do you apply machine learning and AI techniques in ArcGIS?

1 ArcGIS Pro and Python

ArcGIS Pro is the desktop application for creating and managing GIS projects. It supports Python scripting, which allows you to access a rich set of libraries and frameworks for machine learning and AI, such as TensorFlow, PyTorch, scikit-learn, and more. You can use Python to create custom geoprocessing tools, automate tasks, perform advanced analysis, and build models and applications. You can also use the ArcGIS API for Python, which is a Python library that integrates with ArcGIS Online and ArcGIS Enterprise, to manage your data, maps, layers, and services, and to perform spatial analysis, data science, and deep learning.

2 ArcGIS Image Analyst

ArcGIS Image Analyst is an extension for ArcGIS Pro that provides advanced tools and capabilities for image analysis and exploitation. It enables you to apply machine learning and AI techniques to imagery and raster data, such as object detection, classification, segmentation, change detection, and feature extraction. You can use the Image Classification Wizard to train and apply supervised or unsupervised classification models, or use the deep learning tools to train and apply deep learning models using TensorFlow, PyTorch, or Keras. You can also use the raster functions to apply pre-trained models or custom Python scripts to process imagery on the fly.

3 ArcGIS GeoAnalytics Server

ArcGIS GeoAnalytics Server is a component of ArcGIS Enterprise that provides distributed processing and analysis of large and complex spatial data. It leverages the power of big data frameworks, such as Spark and Hadoop, to perform scalable and parallel analysis using machine learning and AI techniques. You can use the GeoAnalytics tools to perform spatial aggregation, summarization, clustering, regression, prediction, and outlier detection. You can also use the GeoAnalytics Python API to access the GeoAnalytics tools and functions from Python scripts or notebooks.

4 ArcGIS Insights

ArcGIS Insights is a web-based application for exploratory data analysis and visualization. It allows you to connect to various data sources, such as ArcGIS Online, ArcGIS Enterprise, databases, spreadsheets, and files, and to perform interactive analysis using charts, maps, tables, and diagrams. You can use the machine learning tools in ArcGIS Insights to apply machine learning and AI techniques to your data, such as classification, regression, clustering, forecasting, and association. You can also use the R and Python integration to run custom scripts or models from R or Python libraries and frameworks.

5 ArcGIS Notebooks

ArcGIS Notebooks are web-based notebooks that allow you to create and share documents that contain code, text, maps, and outputs. They are powered by Jupyter, which is a popular platform for data science and machine learning. You can use ArcGIS Notebooks to access and analyze your data from ArcGIS Online or ArcGIS Enterprise, and to use Python libraries and frameworks for machine learning and AI, such as TensorFlow, PyTorch, scikit-learn, and more. You can also use the ArcGIS API for Python, the GeoAnalytics Python API, and the ArcGIS Learn module to perform spatial analysis, data science, and deep learning.

6 ArcGIS Hub

ArcGIS Hub is a cloud-based platform that enables you to create and share interactive web pages and apps that showcase your data, analysis, and stories. It helps you to engage with your audience, collaborators, and stakeholders, and to foster data-driven decision making. You can use ArcGIS Hub to integrate and display your machine learning and AI outputs, such as maps, charts, tables, diagrams, dashboards, and stories. You can also use ArcGIS Hub to collect feedback, input, and data from your users, and to incorporate them into your machine learning and AI workflows.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?