Ecological Applications, 22(3), 2012, pp. 993–1003 Ó 2012 by the Ecological Society of America Assessing aboveground tropical forest biomass using Google Earth canopy images PIERRE PLOTON, 1,2 RAPHAE ¨ L PE ´ LISSIER, 1,3,5 CHRISTOPHE PROISY, 3 THE ´ O FLAVENOT, 1 NICOLAS BARBIER, 3 S. N. RAI, 4,6 AND PIERRE COUTERON 3 1 De ´partement d’Ecologie, Institut Franc ¸ ais de Pondiche ´ry, UMIFRE MAEE-CNRS 21, Puducherry 605 001 India 2 IRD, Institut de Recherche pour le De ´veloppement, UMR AMAP, University of Yaounde I, Yaounde, Cameroon 3 IRD, UMR AMAP, F-34000 Montpellier, France 4 101 Maha Gauri Aptt., MLA Layout, RMV II Stage, Bangalore 560 094 India Abstract. Reducing Emissions from Deforestation and Forest Degradation (REDD) in efforts to combat climate change requires participating countries to periodically assess their forest resources on a national scale. Such a process is particularly challenging in the tropics because of technical difficulties related to large aboveground forest biomass stocks, restricted availability of affordable, appropriate remote-sensing images, and a lack of accurate forest inventory data. In this paper, we apply the Fourier-based FOTO method of canopy texture analysis to Google Earth’s very-high-resolution images of the wet evergreen forests in the Western Ghats of India in order to (1) assess the predictive power of the method on aboveground biomass of tropical forests, (2) test the merits of free Google Earth images relative to their native commercial IKONOS counterparts and (3) highlight further research needs for affordable, accurate regional aboveground biomass estimations. We used the FOTO method to ordinate Fourier spectra of 1436 square canopy images (125 3 125 m) with respect to a canopy grain texture gradient (i.e., a combination of size distribution and spatial pattern of tree crowns), benchmarked against virtual canopy scenes simulated from a set of known forest structure parameters and a 3-D light interception model. We then used 15 1-ha ground plots to demonstrate that both texture gradients provided by Google Earth and IKONOS images strongly correlated with field-observed stand structure parameters such as the density of large trees, total basal area, and aboveground biomass estimated from a regional allometric model. Our results highlight the great potential of the FOTO method applied to Google Earth data for biomass retrieval because the texture–biomass relationship is only subject to 15% relative error, on average, and does not show obvious saturation trends at large biomass values. We also provide the first reliable map of tropical forest aboveground biomass predicted from free Google Earth images. Key words: aboveground biomass; canopy texture; forest structure; Fourier spectra; Google Earth; tree biomass allometry; very-high-resolution images; Western Ghats of India. INTRODUCTION Deforestation and forest degradation have been shown to be the second most important source of anthropogenic carbon emissions, accounting for 20– 25% of the total (IPCC 2007), although this figure has recently been revised downward to 10–15% (van der Werf et al. 2009). It is nevertheless a consensus that reducing carbon emissions from forest ecosystems (the UNFCCC REDD program: Reducing Emissions from Deforestation and Forest Degradation), particularly in the tropics where almost all of the emissions occur (Houghton 2005), would be a cost-effective means to mitigate climate change. Although REDD is likely to be part of the future post-Kyoto protocol (UNFCCC 2009), its implementation still faces a host of technical challenges. One basic requirement for practical application of the REDD mechanism is our technical ability to accurately assess forest carbon stock variations induced by deforestation and degradation processes. Such an assessment is typically achieved by combining spatially limited ground measurements of forest stand structure (e.g., trunk diameter distribution) with forest cover types extensively mapped from remote-sensing data (Maniatis and Mollicone 2010). Although deforestation stricto sensu (i.e., loss of forest cover) is fairly easy to measure and map using a variety of image types and methods (e.g., Hansen et al. 2008), forest degradation is far more difficult to monitor and is still hindered by technical limits in the tropics (DeFries et al. 2007). In particular, space-borne optical and radar signals of medium to high Manuscript received 2 September 2011; revised 1 November 2011; accepted 7 December 2011. Corresponding Editor: V. C. Radeloff. 5 Corresponding author. Present address: IRD, UMR AMAP, TA A51/PS2, Montpellier Cedex 05, 34398 France. E-mail: Raphael.Pelissier@ird.fr 6 Formerly Principal Chief Conservator of Forest, Karna- taka Forest Department, Bangalore, India (now retired). 993