Mapping & Monitoring
Pan-tropical Forest Carbon Mapped with Satellite and Field Observations
Tropical deforestation and forest degradation account for up to 20% of the world's annual anthropogenic emissions of carbon dioxide, a significant greenhouse gas contributor. Despite the important services that tropical forests provide, there is incomplete data and knowledge of their condition and coverage, and thus no accurate baseline for evaluating and monitoring future changes. As international initiatives develop under the UNFCCC to provide a policy mechanism for slowing tropical deforestation, a baseline for evaluating and monitoring forest cover and associated biomass changes needs to be established across the forested tropics of Central Africa, Latin America and Southeast Asia.
The Woods Hole Research Center has initiated a three-year project focused on pan-tropical mapping of forest cover and carbon stocks stored in tropical forests. The project encompasses two approaches (See sidebar for link to ALOS approach as well as capacity building component.) The approach detailed below employs the fusion of medium-resolution optical (MODIS) and lidar (GLAS) data. It is a first pan-tropical map of forest carbon derived using this approach, informed with extensive satellite canopy structure sampling calibrated with co-located field measurements.
A series of forest canopy structure metrics were derived using data from the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat), launched in January 2003. GLAS is a light detection and ranging (lidar) instrument that, like any lidar, has the capability of measuring the three-dimensional vertical structure of vegetation in great detail, sometimes with hundreds of measurements in the vertical dimension (creating a “waveform”) (Figure 1) for many locations across the pan-tropical region. Additional such instruments are being designed by NASA for launch in the near future (Houghton and Goetz 2009). The quality of each GLAS lidar “shot” varies depending on several factors, including atmospheric conditions and the ground surface slope and roughness (Lefsky 2005). Center researchers removed shots that did not produce adequate waveforms for characterizing vegetation structure from this analysis. The screening procedure was intentionally conservative in regards to quality, while still retaining as many data points as possible.
Field measurements are an essential part of any effort to link vegetation carbon stocks to satellite observations. Center scientists initiated an effort to collect field data co-located with the GLAS shot (footprint) over a broad range of conditions across the pan-tropical region. This effort was facilitated by cooperative agreements with host institutions in many tropical countries, which to date include Brazil, Colombia, Ecuador, Bolivia, Democratic Republic of the Congo, Tanzania, Uganda, Laos, Vietnam and Indonesia. A protocol was established to standardize collection in field campaigns focused primarily on the measurement of stem diameters (diameter at breast height; DBH) occurring within and centered on the GLAS shots, using a satellite geographic positioning system (GPS). Allometric relationships that allowed the estimation of tree biomass density from field measured properties were used (after Chave et al. 2005). A statistical relationship between the field biomass estimates and the GLAS metrics was then established, effectively allowing extension of the field measurements to thousands of locations across the tropics.
Satellite imagery of the Pan-tropical Region
To extend the large sample of GLAS biomass values to map form, continuous “wall to wall” data sets are required. Canopy reflectance maps produced from the Moderate resolution Imaging Spectrometer (MODIS) sensors onboard NASA’s TERRA and AQUA satellites were used. The 500m spatial resolution MODIS reflectance measurements were screened for cloud cover, normalized for viewing and solar conditions, and composited to an 8-day time interval (Schaaf et al. 2002). This MODIS product assures the largest number of observations of the highest possible data quality. The reflectance data set was screened to include only those solutions that made use of at least 3 observations within two 8-day time periods. This approach of using only the best quality data results in image map products with a substantial number of data gaps (spatially). Center scientists then further composited the images over two full calendar years (2005-2006) to compile the final best-quality image product.
Pan-tropical woody vegetation carbon stock
A robust statistical model was developed to relate the MODIS corrected reflectance data at the GLAS shot locations to the GLAS estimated biomass, and then applied to the MODIS image product to produce the first consistent map of pan-tropical carbon stored in aboveground woody biomass (Figures 2 and 3). The map will have wide utility for a range of applications, not least the establishment of a baseline against which future stock changes (whether deforestation, degradation or regrowth) can be assessed, but also the basis for determining which regions have the greatest potential for preserving carbon in tropical forests, the wildlife and human communities within them, and the extensive ecosystem services these forests provide. The carbon stock map can also inform mechanisms for distributing incentive payments that account for carbon stocks, whether national or subnational, thereby helping to ensure that effective, efficient and equitable mechanisms are in place for reducing carbon emissions from deforestation and forest degradation.
We acknowledge support from the Gordon and Betty Moore Foundation, Google.org, the David and Lucile Packard Foundation, and the NASA Applied Sciences, Terrestrial Ecology, and Land Cover Land Use Change Programs. We thank Mark Friedl and Damien Sulla-Menashe at Boston University for extensive assistance with the MODIS image processing.
Baccini, A., N. T. Laporte, S. J. Goetz, M. Sun, and H. Dong. 2008. A first map of tropical Africa’s above-ground biomass derived from satellite imagery. Environmental Research Letters 045011 Open access online: http://stacks.iop.org/1748-9326/1743/045011.
Cattaneo, A. in press. Incentives to reduce emissions from deforestation: a stock-flow approach with target reductions, in V. Bosetti and R. Lubowski., editors. Deforestation and Climate Change: Reducing Carbon Emissions from Deforestation and Forest Degradation (in press).
Chave, J., C. Andalo, S. Brown, M. Cairns, J. Chambers, D. Eamus, H. Fölster, F. Fromard, N. Higuchi, T. Kira, J. P. Lescure, B. Nelson, H. Ogawa, H. Puig, B. Riéra, and T. Yamakura. 2005. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145:87-99.
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Goetz, S. J., A. Baccini, N. Laporte, T. Johns, W. S. Walker, J. M. Kellndorfer, R. A. Houghton, and M. Sun. 2009. Mapping & monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance and Management, Open access online: www.cbmjournal.com/content/4/1/2:doi:10.1186/1750-0680-1184-1182.
Houghton, R. A., F. G. Hall, and S. J. Goetz. 2009. The importance of biomass in the global carbon cycle. Journal of Geophysical Research - Biogeosciences 114.
Houghton, R. A. and S. J. Goetz. 2008. New satellites help quantify carbon sources and sinks. Eos Transactions AGU 89:417-418.
Lefsky, M. A., D. J. Harding, M. Keller, W. B. Cohen, C. C. Carabajal, F. Del Bom Espirito-Santo, M. O. Hunter, and R. de Oliveira Jr. 2005. Estimates of forest canopy height and aboveground biomass using ICESat. Geophysical Research Letters 32:doi:10.1029/2005GL023971.
Schaaf, C. B., F. Gao, A. H. Strahler, W. Lucht, X. Li, T. Tsang, and Strugnell. 2002. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment 83:135-148.
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Funding and support:
Gordon and Betty Moore Foundation, Google.org, the David & Lucile Packard Foundation, and NASA.
Key Project Partners:
Japan Aerospace Exploration Agency (JAXA), JAXA Kyoto and Carbon Inititiative, Alaska Satellite Facility (ASF), NASA, SARMAP, Boston University.