[ Skip to content]

Science and Engineering at The University of Edinburgh

School of GeoSciences

Personal Home Pages

View Iain Woodhouse's profile on LinkedIn

Iain H Woodhouse

I love forests.

I love them because they are aesthetically beautiful (to look at and to be in). But I also love them for their regulating role on the world's climate (they take CO2 out of the atmosphere) and their role in supporting people's livelihoods (about 1.4 billion people, almost one quarter of the world's population, rely on forests for a major part of their livelihood).

The challenge we face right now is that the world's forest are under threat. Deforestation accounts for 17% of the global greenhouse gas budget. An area of forest the size of a football pitch is destroyed every few seconds.

[Iain Naturalist]

My contribution to addressing this challenge is through remote sensing, the use of airborne and satellite measurements to help us map, monitor and understand forests and forest use. My research is aimed at developing new and effective ways of measuring structural properties of a forest -- how to measure forest height, forest biomass (and therefore the amount of carbon is stored there) or structural complexity (which has some relationship to biodiversity). Through my teaching, capacity building and knowledge exchange activities, I aim to build the expertise of current and future scientists and decision makers so that they are better equipped to protect the world's forests.


Currently, I am working on four research projects:

[tree stumps]

(1) REDD Horizon. This is a project with the University of Mzuzu and the Forest Department to prepare Malawi for REDD (Reduced Emissions from Deforestation and Degradation). This involves developing new MRV protocols (Monitoring, Reporting and Verification) for community managed forests, determining the best satellite data products to use for forest carbon inventory and building sufficient indigenous capacity to fully utilise the satellite products available. This team includes Gemma Cassells (a PhD student), Mavuto Tembo (Mzuzu University), Steve Makungwa (University of Malawi, who will be in Edinburgh for the whole of 2010 as part of a Commonwealth Split Award). This work also overlaps with Edward Mitchard's work in mapping the forest resource of Africa.

(2) The Influence of Forest Structure. Using the generic structure models from macroecology, I am working with Matthew Brolly, Maurizio Mencuccini and Shane Cloude on ways to link forest process models with observational models through a more effective representation of the forest structure. The structural parameters that are relevant in radar and lidar remote sensing include the vertical distribution of material, canopy height, stem density and stem size. Results so far suggest that, contrary to expectation, the backscatter-biomass saturation in SAR is not related to the opacity of the canopy but the stem size.

(3) Multispectral Canopy Lidar. As part of the Carbomap team we have developed a new multispectral LiDAR that is optimised for detailed structure and physiology measurements in forest ecosystems. The basic principle is to utilise, in a single instrument, both the capacity of multispectral sensing to measure plant physiology (through NDVI and PRI indices) with the ability of LiDAR to measure vertical structure information and generate "hot spot" (specular) reflectance data independent of solar illumination. Laboratory-based measurement were conducted for live trees, demonstrating that realistic values of the indices can be measured. Model-based analysis demonstrates that the LiDAR waveforms can not only capture the tree height information, but also picks up the seasonal and vertical variation of NDVI inside the tree canopy. We are currently developing this concept for both an airborne instrument and a satellite concept.


Morsdorf F., Nichol C., Malthus T., Woodhouse I. (2009), 'Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling', Remote Sensing of Environment 113, 2152-2163.

(4) M-POL. In collaboration with eOsphere and DLR I am also involved with an ESA project evaluating a new algorithm for sea ice detection. This uses synthetic aperture radar using developed by one of my PhD students, Armando Marino, for sea ice detection. Not a forest application per se, but a project that spun out of some work looking at objects under forest canopies.

Additionally, since 2009 I am the Director of the NERC Field Spectroscopy Facility, the top rated NERC facility in the UK.

Capacity Building and Knowledge Exchange

[Group of REDDH]

(1) Open Access Eduction. Educating students is my primary capacity building activity. I currently deliver courses on Remote Sensing of Global Change (see video below), and an Introduction to Radar Remote Sensing. I am also developing a portfolio of video lectures, some of which are already available on-line: What is Remote Sensing?, Introduction to Orbits, Atmospheric Absorption.

(2) Capacity Building. Whenever possible I contribute to the GEO Capacity Building Committee. As highlighted above, my research projects like REDD Horizon have a large capacity building element included.

(3) LIN Fellowship. Until 2012 I am a NERC LIN (Linking Innovation with NERC) Knowledge Exchange Fellow. My role is to increase the economic and social impact of NERC-funded research at Edinburgh.  The challenge is in both translating the University research (covering carbon modelling, remote sensing and ecology) into something that can be used by the range of service companies within the network (LTSI, Envirotrade and Ecometrica, a carbon assessment/management company that I co-founded in 2008) and also linking the University research and service companies to the technology companies (AELc, Clyde Space, eOsphere, Selex-Galileo). This last link is vital in driving the development of new environmental sensing technologies that meet the relevant science and societal needs.

© School of GeoSciences --- Privacy & Cookies --- Last modified: 23 Mar, 2011 --- Page contact: