Implementing urban canopy height derived from a TanDEM-X-DEM: An expert survey and case study

Schreyer, Johannes; Walker, Blake Byron; Lakes, Tobia

doi:10.1016/j.isprsjprs.2022.02.015

Cited by 2 publications

(1 citation statement)

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“…The DEM generated from the Sentinel-1 InSAR picked the variations in large scale features however because of the spatial resolution, small scale features such as trees, budlings and other features could not be identified. A high spatial resolution (i.e., an order of centimetres to few meters) SAR images with relatively larger perpendicular baseline between two acquisitions of an InSAR observations is needed to at least identify small scale features such as urban trees 17 .…”

Section: Resultsmentioning

confidence: 99%

Estimation of tree height using radar remote sensing in urban settings: a preliminary result

Tessema,

Uzor,

Mortimer

et al. 2023

Earth Resources and Environmental Remote Sensing/Gis Applications XIV

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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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Section: Resultsmentioning

confidence: 99%