An Object-Based Deep Learning Approach for Building Height Estimation from Single SAR Images

TL;DR

This paper presents a deep learning method for estimating building heights from single VHR SAR images, demonstrating high accuracy and cross-continental generalization, especially in European cities, with promising results for urban planning applications.

Contribution

Introduces an object-based deep learning approach for building height estimation from single SAR images, emphasizing cross-continental generalization and out-of-distribution robustness.

Findings

Achieves an MAE of 2.20 m in Munich, outperforming state-of-the-art methods.

Demonstrates strong cross-city transfer learning capabilities.

Highlights challenges in generalizing to Asian urban environments.

Abstract

Accurate estimation of building heights using very high resolution (VHR) synthetic aperture radar (SAR) imagery is crucial for various urban applications. This paper introduces a Deep Learning (DL)-based methodology for automated building height estimation from single VHR COSMO-SkyMed images: an object-based regression approach based on bounding box detection followed by height estimation. This model was trained and evaluated on a unique multi-continental dataset comprising eight geographically diverse cities across Europe, North and South America, and Asia, employing a cross-validation strategy to explicitly assess out-of-distribution (OOD) generalization. The results demonstrate highly promising performance, particularly on European cities where the model achieves a Mean Absolute Error (MAE) of approximately one building story (2.20 m in Munich), significantly outperforming recent state-of-the-art methods in similar OOD scenarios. Despite the increased variability observed when generalizing to cities in other continents, particularly in Asia with its distinct urban typologies and prevalence of high-rise structures, this study underscores the significant potential of DL for robust cross-city and cross-continental transfer learning in building height estimation from single VHR SAR data.