There is an urgent need for a remote sensing system that can provide timely and accurate information on the clearance and degradation of tropical forests. This information is required by organisations around the world with a stake in tropical forest management. Governments require this information to manage their forests, whilst under a new climate change mitigation strategy called REDD+, large polluting countries will pay countries with large forest resources to reduce the carbon emissions arising from deforestation and forest degradation, and to support the conservation of forests. Rich countries have promised $100bn for REDD+ to be available by 2020. These financial commitments have been made based upon the assumption that there is readily-available and accurate information on both deforestation (clearance of trees from the land) and forest degradation (the removal of biomass and other damage to the forest). Yet unfortunately this is not the case.

Whilst deforestation has a long heritage of being measured using optical remote sensing data (e.g. using Landsat imagery), there is a major gap in the detection and measurement of forest degradation using the same approach. This is because forest degradation can occur without optical data being able to see it. The most widely available type of remote sensing data, optical (e.g. using satellites like Landsat, ASTER, SPOT, DMCii), is largely unsuitable for mapping small-scale deforestation or forest degradation in the tropics (Baldauf et al., 2009; GOFC-GOLD, 2012), due to cloud cover, lack of canopy penetration, and inconsistent spectral responses between different vegetation types and seasons. Yet this more ‘cryptic’ loss of biomass has been shown to result in huge carbon emissions in Brazil (Asner et al., 2005), and across Africa. Here, emissions from forest degradation are estimated to be as much as 50% of the total emissions from deforestation (Lambin et al., 2003; Murdiyarso et al., 2008). Failure to measure these emissions therefore will have a huge impact on the efficacy and operationalization of the REDD+ programme and other initiatives designed to improve the management of tropical forests. Consequently, filling this gap, it will have major implications by providing the reliable estimates of forest degradation that are required for improved forest management.

One potential solution is provided by the use of radar data, which has the advantage of not only being able to ‘see through’ cloud but also being correlated with forest biomass, though it is not a direct measure (Woodhouse, 2012). Researchers at the School of Geosciences at the University of Edinburgh have been at the forefront of demonstrating this applicability of radar data to the measurement of deforestation and forest degradation (e.g. Ryan et al., 2012, Mitchard et al., 2013). The SAREDD project brings together the School of GeoScience’s expertise in analysing radar data to measure ecological change, with Airbus Defence and Space who have the capacity to provide advanced processing, storage and dissemination facilities for bulk volumes of radar data. This provides us with a means of apply the techniques pioneer by the School of GeoSciences to new large volumes of data, in order to estimate forest degradation and deforestation across the world’s forests. The ultimate objective is to develop a product that will provide users with accurate and timely information on deforestation and forest degradation in their areas of interest.

The Project Team

The work forms an exciting link between UK academia and industry, and is funded by the UK Technology Strategy Board and NERC. Dr Murray Collins is a Royal Society of Edinburgh Enterprise Fellow at the University of Edinburgh, focusing on the commercialisation of the mapping products, as well as core algorithm development for the detection of deforestation and forest degradation from radar data. Dr Edward Mitchard is the Principal Investigator. At Airbus Defence and Space, a number of analysts are supporting project development by providing expertise in radar data processing, storage and dissemination.

References

Asner, G.P., Knapp, D.E., Broadbent, E.N., Oliveira, O.J.C, Keller, M. and Silva, J.N. (2005) Selective logging in the Brazilian Amazon. Science 310: 480-482.

Baldauf, T., Plugge, D., Rquibate, A., & Kohl, M. 2009. Case studies on measuring and assessing forest degradation. Forest Resources Assessment Working Paper 162, FAO, Rome.

Collins, M. B. and Mitchard, E. T. A.: Integrated radar and lidar analysis reveals extensive loss of remaining intact forest on Sumatra 2007–2010, Biogeosciences Discuss., 12, 8573-8614, doi:10.5194/bgd-12-8573-2015, 2015.

GOFC-GOLD. 2012. A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals associated with deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation. Report version COP18, Version 1. GOFC-GOLD Land Cover Project Office, Wageningen University, The Netherlands.

Mitchard, E.T.A., P. Meir, C.M. Ryan, E.S. Woolen, M. Williams, L.E. Goodman, J.A. Mucavele, P. Watts, I.H. Woodhouse, & S.S. Saatchi. 2013. A novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique. Plant Ecology & Biodiversity, 6, 159-170

Murdiyarso, D., Skutsch,M., Guariguata,M., Kanninen,M., Luttrell,C., Verweij,P. and Stella, O. (2008). Measuring and monitoring forest degradation for REDD. Implications of country circumstances. Info Brief No. 16. CIFOR. Bogor, Indonesia.

Ryan, C.M., Hill, T., Woollen, E., Ghee, C., Mitchard, E.T.A., Cassells, G., Grace, J., Woodhouse, I.H., & Williams, M. 2012. Quantifying small-scale deforestation and forest degradation in African woodlands using radar imagery. Global Change Biology, 18, 243-257.

Woodhouse, I.H., Mitchard, E.T.A., Brolly, M., Maniatis, D., & Ryan, C.M. 2012. Radar backscatter is not a ‘direct measure’ of forest biomass. Nature Climate Change, 2, 556-557.doi:10.1038/nclimate1601