NORTHAMPTON-based remote sensing technology provider, 2Excel Geo, has signed up to the national SPRINT business support programme to undertake an innovative remote sensing project on urban trees.

SPRINT (SPace Research and Innovation Network for Technology), which helps businesses through the commercial exploitation of space data and technologies, will support 2Excel Geo with funded access to expertise from the Open University (OU) to identify the species, size and condition of trees reliably and accurately in urban settings from fine resolution, remotely sensed imagery.

2Excel Geo will collaborate with OU academics to develop ground-validation datasets for the mapping, monitoring and species identification of trees in urban environments from airborne platforms.

The study will use different scales of hyperspectral Earth observation data such as that from a commercial airborne imaging spectrometer and from a cutting-edge drone-mounted non-imaging system. It will also incorporate the UK’s largest urban tree map, from the Treezilla citizen science platform, providing unprecedented ground-validation of tree species and location.

Gary Llewellyn, remote sensing consultant at 2Excel Geo, said: “Analysis of terrestrial vegetation is a key focus area for 2Excel Geo and we’re looking to use our experience of looking at trees from the air to change the way that we look at trees in the future when appropriate satellite systems become available. The SPRINT project with the Open University will investigate stress and the effects of diseases on trees present in their natural habitat. The university’s expertise will enable us to better identify these trees using airborne, satellite and ground-level remote sensing data.

“There are exciting satellite platforms in the launch stage, and we want to be ready to develop tools to source and validate the data that they capture. One of key things about Earth observation systems is that we will get significantly more detail from the combined ground and airborne approaches, which is fundamental in helping to build our datasets. Nothing can compete with the expertise of the university’s dedicated academic unit so we’re confident that the SPRINT project will enhance our level of domain expertise and improve our data, procedures and software.”

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