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Forests play a crucial part in the climate system of the Earth. They provide unique habitats for fauna and flora, prevent soil erosion and mitigate climate change. Forests are threatened by anthropogenic activities such as farming and logging, with an estimated 46 to 58 thousand square miles of forest loss each year. Unfortunately, at present there is no reliable method of measuring forest biomass and deforestation because of inherent limitations of existing satellite systems (e.g. global heterogeneity in terms of accuracy & resolution) and the rate of illegal activities in remote areas.

This project aims to develop a multi-receiver Synthetic Aperture Radar (SAR) system able to accurately quantify the amount of biomass loss on a worldwide scale by using radar tomography from space. The European Space Agency (ESA) is particularly interested in measuring biomass and has commissioned a P-band radar satellite, Biomass (Figure 1), that will be launched in 2021 [1]. Biomass will have a single receiver, as previous satellites have had. In response to this, this project will study the possibility of using small and less expensive passive radar receivers (e.g. nanosats) as companions of the Biomass satellite. 

The project will address two scientific questions: a) a) what is the quality reduction in tomographic imaging when using small satellites as passive receivers? b) how accurately we can estimate above-ground woody biomass, forest structure and degradation using P-band tomography?

We will use a ground radar system developed by the lead supervisor to perform forest fieldworks in the UK and acquire data that will emulate the future Biomass and companion system.

 Measuring biomass is characterised by a number of difficulties. It has been shown that airborne SAR tomography (SARTom) can potentially offer an elegant solution [2]. SARTom allows to obtain three-dimensional estimates of forests by observing the forest with slightly different look angles. When applied from space, current techniques would take several months to perform the different passes, which means that inevitable changes in forest would impede focusing. Small passive receivers, on the other hand, can potentially allow all the necessary images to be acquired in one single pass. Existing and novel tomographic algorithms will be tested in order to overcome difficulties arising from the use of small receivers (e.g. inaccurate pointing, higher noise level, etc).

ESA Biomass satellite. Credits: Airbus.


In this project, available data from ESA third party airborne campaigns and the Open University ground radar will be used for developing tomographic algorithms for future companion satellites.

The project consists of two main stages:

1) Emulating data from companion satellites by degrading the quality of airborne or ground data. Known radar tomographic algorithms (e.g. Fourier, Beamforming, Capon, MUSIC, and filtered back-projection) will be tested to assess the performance of forest structure and biomass retrieval using companion satellite acquisitions.

2) Modifying the known algorithms and developing novel tomographic techniques for overcoming the weaknesses of traditional algorithms when used on data acquired by companion satellites.

Training and Skills

NERC CENTA students are required to complete 45 days training throughout their PhD including a 10 day work placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes.

This is a multi-disciplinary project including topics related to (a) Earth Observation; (b) radar; (c) forestry; (d) data handling and programming.

The successful candidate will gain valuable skills in the context of: (a) analysing and processing satellite data using computational software; (b) developing mathematical methodology; (c) using Geographical Information Systems (GIS) software.


Year 1: Literature review on the topics of microwave scattering from forests, tomographic techniques and nanosats. Applying known tomographic techniques to airborne radar data. Acquiring tomographic data with the ground radar.

Year 2: Developing new tomographic techniques for companion satellites.

Year 3: Analysing the results of the new techniques and estimating the quality of biomass retrievals when using companion satellites.

Partners and collaboration (including CASE)

This project will consider a collaboration with the University of Edinburgh.


Further Details

Students are expected to have a strong background in Engineering and Physical Sciences or related subjects, combined with enthusiasm for research, data processing and associated travelling. Experience of programming (e.g. Matlab, Python, etc) is desirable. The student will join an established team researching Earth Observation at the Open University.

Please contact Dr Armando Marino for further information (e-mail: armando.marino@open.ac.uk).

Applications should include:

Applications should be sent to


by 5 pm on Monday 22nd January 2018