Geospatial ML with Amazon SageMaker (Preview)

Build, train, and deploy ML models faster using geospatial data

Up to 10 GB of free storage

for 30 days with the AWS Free Tier

Access readily available geospatial data sources, including satellite imagery, maps, and location data.

Efficiently process or enrich large-scale geospatial datasets with purpose-built operations such as resampling, mosaicking, and reverse geocoding.

Accelerate model building by using built-in, pretrained deep neural network models such as land cover segmentation and cloud masking.

Analyze geospatial data and explore model predictions on an interactive map using 3D accelerated graphics with built-in visualization tools.

How it works

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to easily build, train, and deploy ML models using geospatial data. Access geospatial data sources, purpose-built processing operations, pretrained ML models, and built-in visualization tools to run geospatial ML faster and at scale.
Diagram shows how to use Amazon SageMaker geospatial ML capabilities to access data resources, transform and enrich your data, select or train your models, deploy a model, and visualize your model predictions on a map.
Why geospatial ML? (1:46)
Why geospatial ML?
The video shows how geospatial data, such as satellite imagery, maps, and location data, can be used to innovate faster and make smarter decisions across a wide variety of use cases and industries.
Why geospatial ML?
The video shows how geospatial data, such as satellite imagery, maps, and location data, can be used to innovate faster and make smarter decisions across a wide variety of use cases and industries.

Use cases

Assess risk and insurance claims

Measure risk, validate claims and prevent fraud, analyze damage impact from natural disasters on local economies, and track construction projects.

Inform trading strategies

Monitor financial assets globally, forecast market commodity prices, enhance your hedging or trading strategies, and mitigate the impact of price volatility.

Monitor climate change

Track deforestation and biodiversity, measure methane gas emissions, create climate resiliency plans, and improve power grid reliability.

Support sustainable urban development

Design more sustainable and livable urban environments, identify areas for land development, track traffic trends, or evaluate the feasibility of energy projects.

Maximize harvest yield and food security

View satellite images to diagnose plant health, insure and classify crops, predict harvest yield, forecast demand for agriculture produce, or detect farm boundaries.

Predict retail demand

Track high-growth city areas to improve sales or supply distribution channels, or combine location data with competitive intelligence to choose new store locations.

How to get started

AWS News Blog

Use Amazon SageMaker to build, train, and deploy ML models using geospatial data.

Read the blog »

Developer Guide

Learn more about Amazon SageMaker geospatial capabilities in this step-by-step guide.

Read the guide »

Example notebook

Learn how farmers can optimize crop production through advanced analytics and ML.

View the example »

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