Anthropogenic Risk


As of 2015, forests were estimated to cover around 31% of the global land area or 3999 M ha. This represents a decline of around 3% since 1990 due to anthropogenic and natural causes, although this rate has halved in the last 25 years (Keenan et al., 2015). Anthropogenic factors are a primary cause of this deforestation. For example, deliberate policy to clear land for agriculture or other purposes, and logging concessions can create large-scale deforestation. Even within sustainably managed concessions and protected areas, illegal logging still has the potential to cause wide-scale forest loss.

Approaches to assessing risk

There are a number of approaches to predicting the risk of deforestation. However, these typically focus on identifying the variables closely associated with deforestation. Such variables tend to relate to accessability to the forest, such as the presence of nearby roads, and also to the value of the forests themselves. Application of these approaches to looking at the risks to commercial timber and carbon forestry projects is however problematic. By definition, commercial timber and carbon projects must be accessible and timber projects must be of value. Furthermore, some variables such as political and regulatory risk do not lend themselves to a probability type approach required for risk assessment e.g. it is unlikely to be possible to identify the annual probability of a reversal of support for e.g. sustainable forest management or carbon offsets. Finally, forest carbon projects, particularly those such as REDD+ projects, which are aimed at reducing deforestation and degradation, are often located in areas known to be at high risk. Approaches to assessing risk are therefore not of high relevance to this audience.

In this section we therefore focus primarily on presenting approaches to assessing and quantifying deforestation, and changes to biomass/carbon stocks, rather than approaches to predicting the risks of deforestation.

Remote sensing of canopy height and biomass to track deforestation

Prof. Balzter has developed Synthetic Aperture Radar (SAR) and LIDAR techniques for mapping forest canopy height and forest biomass, which can be used to track deforestation (Lynch et al., 2013). He is the principal investigator in a range of satellite programmes including TerraSAR-X, Disaster Monitoring Constellation, ENVISAT, ERS-1/2, JERS-1 and ALOS PALSAR. He is also scientist-in-charge of the European Centre of Excellence for Earth Observation Research Training “GIONET” and has had a long involvement with the European Copernicus initiative (formerly GMES), which delivers operational data services from remote sensing and ancillary observing networks. This was through the land-monitoring projects GEOLAND and GEOLAND-2 and in 2014 his group completed the delivery of the UK CORINE 2012 land cover map under the GIO-Land programme to the European Environment Agency and DEFRA. The ESA project GLOBBIOMASS, is aiming to improve forest aboveground biomass estimates by developing innovative synergistic mapping approaches in five regional sites for the epochs 2005, 2010 and 2015 and for one global map for the year 2010, and includes the leading Earth Observation experts of Europe. Prof. Balzter is leading the task on Regional Case Studies, with the aim to produce 3 global forest biomass maps. He is an advocate of using satellite information to monitor deforestation (Lynch et al., 2013). Contact: Prof. Heiko Balzter

Deforestation and degradation detection algorithm – Congo

Dr Mitchard has current grants from the UK’s Natural Environment Research Council (NERC) and Innovate UK to develop a deforestation and degradation detection algorithm using C-band radar data; from the US Forest Service to work on the relations between fire return period and carbon storage in Congo. Contact: Dr Ed Mitchard

Remote sensing of deforestation – general

As Director of Forestry at DMCii Prof. Lynch had responsibility for developing partnerships and tools. DMCii, primarily focuses on disasters and has used its Disaster Monitoring Constellation (DMC) to provide wide-scale mapping of tropical forests such as the Amazon Basin and sub-Saharan Africa since 2005. He is a strong advocate of using satellite technology to monitor deforestation, REDD delivery and illegal logging (Lynch et al., 2013). He believes current monitoring is too infrequent e.g. annual observation does not provide seasonal variability in carbon stock, and ideally optical measurements should be every 1-2 weeks. To act as an early warning system to stop illegal logging they need to be daily. Both optical and radar sensors are needed: radar can scan down to 5-20m resolution regardless of the weather as it can penetrate cloud cover – a particular issue in equatorial rainforest – which optical imaging can not. Optical satellites can detect changes in chlorophyll to detect pest and disease impact and can provide resolution down to 20m of vegetation greenness and density, tree cover and forest type. At DMCii he led a multi-disciplinary consortium of universities, companies and public sector organisations inFORm which supports UK efforts to be involved in REDD+. He is continuing to develop this led from the Universities of Surrey and Leicester, but also engaging a consortium ASTROTROP led from Edinburgh and Leeds Universities to create a virtual forestry observatory. In a NERC funded SCENARIO project at Surrey and Reading Universities he is working with the University of Sao Paulo and the Brazilian Space Agency INPE to generate indicators for the monitoring and management of forests in a sustainable land use context. Contact: Prof. Jim Lynch

Landcover, landcover change and forestry classes

Prof Balzter led the creation of the new Corine land cover map for 2012 for the European Environment Agency and Defra, an Open Access dataset. It shows land cover and forestry classes at 25 ha minimum mapping unit, and land cover change over a 6-year time frame at 5 ha minimum mapping unit including forest to non-forest and regrowth and replanting. It will be available from the NERC Environmental Information Centre (Link). Contact: Prof. Heiko Balzter

Monitoring forest inventory via remote sensing – general

Prof Juan Suárez  has been working with airborne LiDAR for 15 years. He has developed techniques for analysing the point clouds generated by the sensor to produce stand and tree level estimates. At stand level, it is possible to calculate biomass, volume, fractional cover, canopy height, site index and yield class. At tree level, he has developed an algorithm over eCognition to delineate individual tree canopies. Canopy area and height is used to estimate diameter at breast height (DBH) and stem volume (Suárez, 2014). The location of individual trees and its characteristics is used in combination with timber quality models and competition indices to estimate stem density and straightness (Suárez, 2009). Stand level predictions have been calculated for the Cowal and Trossachs Forest District to update the Sub-compartment Database (SCDB) and to run the Production Forecast more accurately.  Juan was the Principal Investigator for  projects to: use airborne LiDAR for British forest inventory (2014-16);  to update the National Forest Inventory (GB) using satellite imagery (2016 DEFRA project); and to develop new methods for biomass assessment and forest inventory using airborne LiDAR and Hyperspectral imagery in China (Newton Grant 2015-16). He was also part of a NERC-funded Partnership Research Grant with University of Swansea to use satellite LiDAR to enhance Forest Inventory and Production Forecast Capabilities (2008-14). Whilst working at the NASA Goddard Space Flight Centre (Maryland, US) he worked on the application of small footprint LiDAR systems to support  the Carbon Monitoring System project (2011-12). Contact: Prof. Juan Suárez-Minguez

Our Ecosystem: Web-based Pan-Tropic GIS maps of forest carbon stocks

Dr  Mitchard is an expert in using GIS to provide benchmarks of carbon stock information. Two medium resolution (500m-1,000m) maps have recently been generated that both use the same spaceborne LIDAR dataset to calculate pan-tropical carbon stocks but different algorithms. Dr Mitchard was involved in one of these (Saatchi et al., 2011) but not the other (Baccini et al., 2012). In conjunction with the company Ecometrica, he has produced a freely available web-based interactive map which displays the two maps and compares the difference in measurements (Mitchard et al., 2013) (Open access (free): link). A higher resolution (100m) biomass map has been generated for part of the Columbian Amazon using forest information from the FAO. The maps are widely used by REDD+ stakeholders at national and sub-national level. Users can select an area to view the carbon stock information (link).  Contact: Dr Ed Mitchard.

Distinguishing land degradation caused by climatic vs anthropogenic factors

Prof. Balzter has also worked on an approach that uses remote sensing to distinguish vegetation change due to climatic factors from that caused by anthropogenic factors on the basis of vegetation greenness and rainfall trends and anomalies (Hoscilo et al., 2015). If over a 10 year period conditions become wetter and greener or drier and browner then the approach assumes that the cause was climatic, however, if areas become wetter and browner then the cause is likely to be non-climatic i.e. due to anthropogenic causes. He was involved in developing a method for land degradation mapping using Normalised Difference Vegetation Index data from satellite data and soil moisture trends (Ibrahim et al., 2015). Contact: Prof. Heiko Balzter

Illegally logged timber (FLEGT)

Prof. Lynch is an expert in FLEGT (Forest Law Enforcement, Governance and Trade), which aims to reduce the import of illegal logging to the EU. He was the lead Board Member in setting up the FLEGT facility in the European Forest Institute. Contact: Prof. Jim Lynch

REDD+: Advice on minimising risk in sustainable community forestry

Prof. Lynch has spent 17 years working for OECD in relation to sustainable agriculture and forestry. He is therefore able to offer expertise on optimising productive community forest projects and minimising risks. He believes community involvement is essential to preventing deforestation which cannot be solved by Governments alone. This includes appropriate species selection to minimise risks such as pest and disease risk, and to maximise community benefits e.g. he advised on planting Jatropha in Ghana as a productive crop but which also solved the problem of a lack of lighting in local schools as they could burn Jatropha. oil. He has also has experience in other parts of Africa; he is a Member of the Board of the Council for the Frontiers of Knowledge in Africa, based at Makere University, Uganda. This experience includes bioenergy generation and horticulture specific to Africa (Lynch and Harvey, 2011; Lynch and Von Lampe, 2011). Contact: Prof. Jim Lynch


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HOSCILO, A., BALZTER, H., BARTHOLOME, E., BOSCHETTI, M., BRIVIO, P. A., BRINK, A., CLERICI, M. & PEKEL, J. F. 2015. A conceptual model for assessing rainfall and vegetation trends in sub-Saharan Africa from satellite data. International Journal of Climatology, 35, 3582-3592.
IBRAHIM, Y. Z., BALZTER, H., KADUK, J. & TUCKER, C. J. 2015. Land Degradation Assessment Using Residual Trend Analysis of GIMMS NDVI3g, Soil Moisture and Rainfall in Sub-Saharan West Africa from 1982 to 2012. Remote Sensing, 7, 5471-5494.
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LYNCH, J., MASLIN, M., BALZTER, H. & SWEETING, M. 2013. Choose satellites to monitor deforestation. Nature, 496, 293-294.
MITCHARD, E., SAATCHI, S., BACCINI, A., ASNER, G., GOETZ, S., HARRIS, N. & BROWN, S. 2013. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps. Carbon Balance and Management, 8, 10. Open access: link
SAATCHI, S. S., HARRIS, N. L., BROWN, S., LEFSKY, M., MITCHARD, E. T. A., SALAS, W., ZUTTA, B. R., BUERMANN, W., LEWIS, S. L., HAGEN, S., PETROVA, S., WHITE, L., SILMAN, M. & MOREL, A. 2011. Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences of the United States of America, 108, 9899-9904.
SUÁREZ, J.C. 2009. ‘An analysis of the consequences of stand variability in Sitka spruce plantations in Britain using a combination of airborne LiDAR analysis and models’. PhD thesis. University of Sheffield.
SUÁREZ, J.C. 2014. ‘An individual canopy delineation algorithm based on Object-Oriented segmentation and classification’. Book chapter in ‘Challenges and opportunities for the world’s forests in the 21st century’. Springer.