PhD Research Project

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Quantifying forest state and degradation: exploiting new lidar measurements

Institution:

University College London

Dept/School/Faculty:

Department of Geography

PhD Supervisor:

Dr M Disney

Co-Supervisor:

Dr S Lewis

Application Deadline:

No more applications being accepted

Funding Availability:

Funded PhD Project (European/UK Students Only)

PhD Research Project

Subject areas: environmental remote sensing; biomass; lidar; tropical ecology; deforestation; monitoring; conservation.

Quantifying forest biomass is increasingly important for forestry, terrestrial C-cycle responses to climate change and disturbance as well as and resource management, particularly in the tropics. Degradation and disturbance monitoring require low-cost, rapid, repeatable estimates of biomass. While satellite optical and radar remote sensing can provide large-scale coverage they can be limited by cloud cover (optical), lack of sensitivity to high biomass (both) and perhaps most importantly, the difficulty of relating biomass to rather indirect measurements.

Lidar (light detection and ranging) is an extremely promising alternative technology, providing much more direct measurement of vegetation canopy properties. This project will develop methods to exploit new airborne and terrestrial lidar measurements for quantifying forest biomass (state and change). The project aims to establish how well airborne laser scanning (ALS) can estimate biomass via measurement of key canopy structural properties (height, cover, structure) over contrasting forest biomes (temperate, tropical). The project will use a combination of simulation models and lidar data to test the hypotheses that: biomass can be estimated from canopy height and cover via ALS; canopy cover can be derived from ALS independent of structural assumptions, reducing the need for empirical calibration of height/biomass relationships; ALS-derived biomass estimates can be tested using stem density and diameter measurements obtained from terrestrial laser scanning (TLS).

The candidate should ideally have a strong background in a numerate discipline (including but not limited to physics, engineering, computing, environmental science, ecology etc.). The project will involve fieldwork in the UK and Africa, and additional training from the CASE partner.

For more information please contact Dr. Mat Disney: mathias.disney@ucl.ac.uk

Candidates will be informed if they are to be interviewed by the 19th April, and interviews will be carried out on the 26th April.

Application details: www.geog.ucl.ac.uk/admissions-and-teaching/postgraduates/phd-research/phd-applications-and-funding/

See NERC website for eligibility: www.nerc.ac.uk/funding/available/postgrad/eligibility.asp