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Property Analysis from Imagery

Identify Property Risk Factors with AI-based computer vision and Geospatial Imagery. Examples: skylights, solar panels, pools and trampolines. Detect Structure attributes including roof footprint, roof material, roof type, roof condition and vegetation overhang. Track changes on many property features to take into consideration upon policy renewal (e.g. deterioration of roof condition, additional structures, and more)

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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

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3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

Awesome Satellite Imagery Datasets

List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datasets at the top of each category (Instance segmentation, object detection, semantic segmentation, scene classification, other).

Maxar Open Data Program

Maxar’s data for selected sudden onset major crisis events. 16 events, Data from 14 countries, 1,834,152 sq km of imagery released since 2017, and 92 events activated since 2017

Deep Satellite Resources

List of labeled datasets, projects, and papers relevant to classifying satellite imagery using deep learning


Off-the-Shelf Products using AI for Property Inspection

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