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ELEV-VISION-SAM: Integrated Vision Language and Foundation Model for Automated Estimation of Building Lowest Floor Elevation
By evaluating various vision language models, integration methods, and text prompts, we identify the most suitable model for street view image analytics and LFE estimation tasks, thereby improving the availability of the current LFE estimation model based on image segmentation from 33% to 56% of properties.
ML4EJ: Decoding the Role of Urban Features in Shaping Environmental Injustice Using Interpretable Machine Learning
The insights gleaned from this study offer fresh perspectives on the relationship among urban features and their interplay with environmental hazard exposure disparities, informing the development of more integrated urban design policies to enhance social equity and environmental injustice issues.
ELEV-VISION: Automated Lowest Floor Elevation Estimation from Segmenting Street View Images
The depth from the camera to the door bottom was obtained from the depthmap paired with the Google Street View image.
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