Building Height Estimation Using Shadow Length in Satellite Imagery

TL;DR

This work proposed a novel method that first localized a building and its shadow in the given satellite image, and then estimated the associated building height using solar elevation with shadow length through analytical formulation.

Abstract

Estimating building height from satellite imagery poses significant challenges, especially when monocular images are employed, resulting in a loss of essential 3D information during imaging. This loss of spatial depth further complicates the height estimation process. We addressed this issue by using shadow length as an additional cue to compensate for the loss of building height estimation using single-view imagery. We proposed a novel method that first localized a building and its shadow in the given satellite image. After localization, the shadow length is estimated using a regression model. To estimate the final height of each building, we utilize the principles of photogrammetry, specifically considering the relationship between the solar elevation angle, the vertical edge length of the building, and the length of the building's shadow. For the localization of buildings in our model, we utilized a modified YOLOv7 detector, and to regress the shadow length for each building we utilized the ResNet18 as backbone architecture. Finally, we estimated the associated building height using solar elevation with shadow length through analytical formulation. We evaluated our method on 42 different cities and the results showed that the proposed framework surpasses the state-of-the-art methods with a suitable margin.

Figures (5)

• Figure 1: Overview of the proposed framework for building height estimation using shadow length.
• Figure 2: Sample image showing the screenshot of annotation tools. Bounding boxes along with the annotations for vertical edge and shadow length for the encompassing building are shown for each bounding box.
• Figure 3: (a) Box plots of Root Mean Square Error on the dataset, plotted across values of ground truth height. (b) Bar plot representing the average (mean) Root Mean Square Error plotted against values of ground truth height. We can observe that the range of values that RMSE takes is small for buildings lying in the $12$-$30$m range. The range of RMSE for buildings in the height range of $3$-$9$m is pretty large which suggests noise. Moreover, buildings with a height $>30$m show very large RMSE.
• Figure 4: (a) YOLOv7 Predictions (b) Bounding box ground truth.
• Figure 5: Jin Mao Tower in Shanghai. Actual height $420$ meters. The height computed from our annotated shadow length is $430$ meters.