Scottish Alliance for Geoscience, Environment and Society

Prof. Iain Woodhouse

Department / group: School of Geosciences, Geography and the Lived Environment / Environment and Society

Research interests:

Radar Remote Sensing; Polar Decomposition Methods for Visualising SAR Data; Novel Visualisation Techniques for the Analysis of Multichannel Remote Sensing Data; DEM Generation and Regional Scale Geomorphology; Synergistic Remote Sensing of Vegetation; Macroecology and Telemacroscopics.

Career history:

Present: Professor of Applied Earth Observation; Head of Geography and the Lived Environment Research Institute

Active research projects:

Currently, I am working on four research projects:

(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.

(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.

Recent publications:

De Grandi, E.C., Mitchard, E., Woodhouse, I.H. and De Grandi, G.D., 2015. Spatial Wavelet Statistics of SAR Backscatter for Characterizing Degraded Forest: A Case Study From Cameroon. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(7), pp.3572-3584.

Muirhead, F., Halcrow, G., Woodhouse, I.H., Mulgrew, B. and Greig, D., 2015, July. Compact, low cost, airborne SAR interferometry for environmental monitoring. In Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International (pp. 802-805). IEEE.

Muirhead, F., Mulgrew, B., Woodhouse, I.H. and Greig, D., 2015, October. Sparsity-driven autofocus for multipass SAR tomography. In SPIE Remote Sensing (pp. 96420G-96420G). International Society for Optics and Photonics.

Michelakis, D., Stuart, N., Brolly, M., Woodhouse, I.H., Lopez, G. and Linares, V., 2015. Estimation of Woody Biomass of Pine Savanna Woodlands From ALOS PALSAR Imagery. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(1), pp.244-254.

Ryan, C.M., Williams, M., Hill, T.C., Grace, J. and Woodhouse, I.H., 2014. Assessing the phenology of southern tropical Africa: a comparison of hemispherical photography, scatterometry, and optical/NIR remote sensing. Geoscience and Remote Sensing, IEEE Transactions on, 52(1), pp.519-528.

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