Green infrastructure directly impacts our daily life and promotes the mitigation of climate change at large. Urban woodlands are one of the green infrastructures that need regular monitoring. Existing urban tree inventories and monitoring schemes are based on spatial sampling assessment techniques. Urban tree health monitoring using remote sensing techniques such as LiDAR is used for inventory but needs a regular revisit. However, radar remote sensing has the potential to investigate the estimation of tree height, an important parameter towards tree health monitoring. Here we use Digital Elevation Model (DEM) differential interference based on Synthetic Aperture Radar (SAR) satellite data. We use Sentinel-1 (C-band) data to estimate the three heights in urban setting. In addition, we use exiting LiDAR data to estimate the tree height and ground-based smartphone Augmented Reality (AR) based height estimation for comparison and validation purposes. The result can be integrated with the available forest database and contribute towards regular monitoring of green infrastructure. As a case study to demonstrate the methodology, we investigate sample trees in Ealing, one of the boroughs of London with good coverage of urban trees and woodlands.
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