Geospatial ML with Amazon SageMaker

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

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 smart decisions across a wide variety of use cases and industries.

Why Geospatial ML?

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?

How it works

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to 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.

How it works

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to 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.

Benefits of SageMaker geospatial capabilities

Access readily available geospatial data sources, including satellite imagery, maps, and location data
Efficiently transform or enrich large-scale geospatial datasets with open-source libraries or purpose-built operations such as 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.

Use Cases

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

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

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

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

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


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