Three Exciting Ways to Protect Forests With Remote Sensing

Forests cover one third of the Earth’s land mass and are home to more than 80% of the terrestrial species of animals, plants and insects. However, 13 million hectares of forest are destroyed each year. The United Nations International Day of Forests took place recently, on 21st March, to raise awareness of this vital resource.

Three remote sensing applications to help protect forests caught our eye recently:

Two scans show the difference between infected, on the right, and uninfected, on the left, patches of forest. Image Courtesy of University of Leiceste

Identifying Diseased Trees
In the March issue of Remote Sensing, researchers from the University of Leicester, (Barnes et al, 2017), published a paper entitled ‘Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands’. It describes how the researchers were able to identify individual trees affected by larch tree disease, also known as phytophthora ramorum.

This fungus-like disease can cause extensive damage, including the death, and diseased trees can be identified by defoliation and dieback. Airborne LiDAR surveys were undertaken by the company Bluesky at an average altitude of 1500 m, with a scan frequency of 66 Hz that gave a sensor range precision within 8 mm and elevation accuracy around 3–10 cm.

Remote sensing has been used to monitor forests for many years, but using it to identify individual trees is uncommon. The researchers in this project were able to successfully identify larch canopies partially or wholly defoliated by the disease in greater than 70% of cases. Whilst further development of the methodology will be needed, it is hoped that this will offer forest owners a better way of identifying diseased trees and enable them to respond more effectively to such outbreaks.

Monitoring Trees From Space
An interesting counterpoint to work of Barnes et al (2017) was published by the journal Forestry last month. The paper ‘Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications‘ written by Fassnacht et al (2017).

It describes work undertaken to compare the results of very high resolution optical satellite data with that of airborne LiDAR and hyperspectral data to provide support for forestry management. The team used WorldView-2 images, of a temperate mixed forest in Germany, with a 2m pixel size, alongside a LiDAR DTM with a 1 m pixel size. This data was then used to estimate tree species, forest stand density and biomass.

They found  good results for both forest stand density and biomass compared to other methods, and although the tree classification work did achieve over eighty percent, this was less than achieved by hyperspectral data over the same site; although differentiation of broadleaved and coniferous trees was almost perfect.

This work shows that whilst further work is needed, optical data has the potential to offer a number of benefits for forestry management.

Monitoring Illegal Logging
Through the International Partnership Programme the UK Space Agency is funding a consortium, led by Stevenson Astrosat Ltd, who will be using Earth Observation (EO) data to monitor, and reduce, illegal logging in Guatemala.

The issue has significant environmental and socioeconomic impacts to the country through deforestation and change of land use. The Guatemalan government have made significant efforts to combat the problem, however the area to be monitored is vast. This project will provide a centralised system using EO satellite data and Global Navigation Satellite Systems (GNSS) technology accessed via mobile phones or tablets to enable Guatemala’s National Institute of Forestry (INAB) to better track land management and identify cases of illegal logging.

Overall
The protection of our forests is critical to the future of the planet, and it’s clear that satellite remote sensing can play a much greater role in that work.