AI/ML Building Footprints Extraction and Rooftop Classification
By leveraging satellite and aerial/drone imagery Artificial Intelligence (AI), and Machine Learning (ML) algorithms, it becomes possible to automate the extraction of building footprints and perform rooftop assessments roofs over large areas, saving time and resources compared to manual ground surveys. Image segmentation separates the different components in an image, distinguishing the roofs from other objects and background elements that include roof shape, size, color, texture, presence of solar panels and spatial relationships with other objects. This technology can support decision-making processes and enable efficient analysis of buildings on a global scale. The detected roofs can be utilized for various purposes, such as urban planning, disaster management, assessing solar panel potential, estimating building density, or identifying vulnerable areas.





