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Widespread subsidence and carbon emissions across Southeast Asian peatlands

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Over the last three decades, most of the 25 million hectares of tropical peatlands in Southeast Asia have been deforested and drained. As a consequence, declining water tables are exposing peat to oxidation, converting plant material accumulated over millennia to carbon dioxide, and causing land subsidence. Here, we quantify the widespread peat carbon loss by using InSAR remote sensing to map subsidence at 90-m resolution across 2.7 Mha of peatland area from 2007 to 2011. Over 90% of the surveyed area is subsiding, with a mean rate of 2.2 cm yr−1. Consequently, the region now faces loss of productive land and flooding because many peatlands are near sea level. Our measurements reveal that smallholder agricultural areas and degraded peatlands are subsiding at rates comparable to those of plantations, and that subsidence rates increase away from rivers and decrease over time following drainage. Because of its detailed spatial resolution, InSAR provides a valuable tool to identify emissions by land use and geography and to target hotspots for better management. Finally, we use remotely sensed maps to update IPCC emissions factors and calculate regional CO2 emissions from peat oxidation of 155 ± 30 MtC yr−1 in 2015, similar in magnitude to both regional fossil-fuel emissions and peat fires.

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Fig. 1: Subsidence rates and time series in peat and non-peatland areas in ALOS frame 1 of 8.
Fig. 2: Subsidence and land-use maps.
Fig. 3: Subsidence rates over time since oil palm plantation establishment.

Data availability

The calculated mean subsidence rates that support the findings of this study are archived on Zenodo at The raw SAR data that support the findings of this study are publicly available through the Alaska Satellite Facility data portal at

Change history

  • 25 June 2020

    The ‘Editor recognition’ statement has been amended to additionally include the contribution of Xujia Jiang; the sentence now reads ‘Primary Handling Editors: Clare Davis; Xujia Jiang.’


  1. 1.

    Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Glob. Ecol. Conserv. 6, 67–78 (2016).

    Article  Google Scholar 

  2. 2.

    Hooijer, A. et al. Subsidence and carbon loss in drained tropical peatlands. Biogeosciences 9, 1053–1071 (2012).

    Article  Google Scholar 

  3. 3.

    Page, S. E., Rieley, J. O. & Banks, C. J. Global and regional importance of the tropical peatland carbon pool. Glob. Change Biol. 17, 798–818 (2011).

  4. 4.

    Miettinen, J., Hooijer, A., Vernimmen, R., Liew, S. C. & Page, S. E. From carbon sink to carbon source: extensive peat oxidation in insular Southeast Asia since 1990. Environ. Res. Lett. 12, 024014 (2017).

    Article  Google Scholar 

  5. 5.

    Evans, C. D. et al. Rates and spatial variability of peat subsidence in Acacia plantation and forest landscapes in Sumatra, Indonesia. Geoderma 338, 410–421 (2019).

    Article  Google Scholar 

  6. 6.

    Western Johore Integrated Agricultural Development Project, Peat Soil Management Study (Department of Irrigation and Drainage (DID), Kuala Lumpur, Malaysia and Land and Water Research Group (LAWOO), 1996).

  7. 7.

    Taylor, D. & Ali, M. Biogeochemical Responses to Land Cover Changes in Coastal Peatland Catchments: Spatial and Temporal Fluxes in Greenhouse Gas Emissions and Peat Subsidence, Jambi Province, Sumatra (SARCS/UNOP, 2001).

  8. 8.

    Othman, H., Mohammed, A. T., Darus, F. M., Harun, M. H. & Zambri, M. P. Best management practices for oil palm cultivation peat: ground water-table maintenance in relation to peat subsidence and estimation of CO2 emissions at Sessang, Sarawak. J. Oil Palm Res. 23, 1078–1086 (2011).

    Google Scholar 

  9. 9.

    Couwenberg, J. & Hooijer, A. Towards robust subsidence-based soil carbon emission factors for peat soils in south-east Asia, with special reference to oil palm plantations. Mires Peat 12, 1 (2013).

    Google Scholar 

  10. 10.

    Nagano, T. et al. Subsidence and soil CO2 efflux in tropical peatland in southern Thailand under various water table and management conditions. Mires Peat 11, 6 (2013).

  11. 11.

    Wösten, J., Ismail, A. & van Wijk, A. Peat subsidence and its practical implications: a case study in Malaysia. Geoderma 78, 25–36 (1997).

    Article  Google Scholar 

  12. 12.

    Ritzema, H., Limin, S., Kusin, K., Jauhiainen, J. & Wösten, H. Canal blocking strategies for hydrological restoration of degraded tropical peatlands in Central Kalimantan, Indonesia. Catena 114, 11–20 (2014).

  13. 13.

    Whittle, A. & Gallego-Sala, A. V. Vulnerability of the peatland carbon sink to sea-level rise. Sci. Rep. 6, 28758 (2016).

    Article  Google Scholar 

  14. 14.

    Wijedasa, L. S. et al. Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences. Glob. Change Biol. 23, 977–982 (2017).

  15. 15.

    Carlson, K. M., Goodman, L. K. & May-Tobin, C. C. Modeling relationships between water table depth and peat soil carbon loss in Southeast Asian plantations. Environ. Res. Lett. 10, 074006 (2015).

    Article  Google Scholar 

  16. 16.

    Bürgmann, R., Rosen, P. A. & Fielding, E. J. Synthetic aperture radar interferometry to measure Earth’s surface topography and its deformation. Annu. Rev. Earth Planet. Sci. 28, 169–209 (2000).

    Article  Google Scholar 

  17. 17.

    Chaussard, E., Amelung, F., Abidin, H. & Hong, S.-H. Sinking cities in Indonesia: ALOS PALSAR detects rapid subsidence due to groundwater and gas extraction. Remote Sens. Environ. 128, 150–161 (2013).

    Article  Google Scholar 

  18. 18.

    Chaussard, E. et al. Interseismic coupling and refined earthquake potential on the Hayward-Calaveras fault zone. J. Geophys. Res. Solid Earth 120, 8570–8590 (2015).

    Article  Google Scholar 

  19. 19.

    Massonnet, D. et al. The displacement field of the Landers earthquake mapped by radar interferometry. Nature 364, 138–142 (1993).

    Article  Google Scholar 

  20. 20.

    Fialko, Y. Interseismic strain accumulation and the earthquake potential on the southern San Andreas fault system. Nature 441, 968–971 (2006).

    Article  Google Scholar 

  21. 21.

    Pritchard, M. E. & Simons, M. An InSAR-based survey of volcanic deformation in the southern Andes. Geochem. Geophys. Geosyst. 5, L15610 (2004).

  22. 22.

    Cuenca, M. C. & Hanssen, R. Subsidence due to peat decomposition in the Netherlands: kinematic observations from radar interferometry. In Fifth International Workshop on ERS/Envisat SAR Interferometry, ‘FRINGE07’ 1–6 (2008).

  23. 23.

    Cigna, F., Sowter, A., Jordan, C. J. & Rawlins, B. G. Intermittent Small Baseline Subset (ISBAS) monitoring of land covers unfavourable for conventional C-band InSAR: proof-of-concept for peatland environments in North Wales, UK. Proc. SPIE 9243, 924305 (2014).

    Article  Google Scholar 

  24. 24.

    Marshall, C. et al. Monitoring tropical peat related settlement using ISBAS InSAR, Kuala Lumpur International Airport (KLIA). Eng. Geol. 244, 57–65 (2018).

    Article  Google Scholar 

  25. 25.

    Zhou, Z. The Applications of InSAR Time Series Analysis for Monitoring Long-Term Surface Change in Peatlands. PhD thesis, Univ. Glasgow (2013).

  26. 26.

    Chaussard, E. et al. Potential for larger earthquakes in the East San Francisco Bay Area due to the direct connection between the Hayward and Calaveras Faults. Geophys. Res. Lett. 42, 2734–2741 (2015).

    Article  Google Scholar 

  27. 27.

    Berardino, P., Fornaro, G., Lanari, R. & Sansosti, E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 40, 2375–2383 (2002).

  28. 28.

    Khasanah, N. & van Noordwijk, M. Subsidence and carbon dioxide emissions in a smallholder peatland mosaic in Sumatra, Indonesia. Mitig. Adapt. Strateg. Glob. Change 24, 147–163 (2019).

  29. 29.

    Ishikura, K. et al. Soil carbon dioxide emissions due to oxidative peat decomposition in an oil palm plantation on tropical peat. Agric. Ecosyst. Environ. 254, 202–212 (2018).

    Article  Google Scholar 

  30. 30.

    Maswar, M. Kajian Cadangan Karbon pada Lahan Gambut Tropika Yang Didrainase Untuk Tanaman Tahunan (Carbon Stock in the Drained Tropical Peat Used for Perennial Plantation Crops). PhD dissertation, Bogor Agricultural Univ. (2011).

  31. 31.

    Hooijer, A. et al. Current and future CO2 emissions from drained peatlands in Southeast Asia. Biogeosciences 7, 1505–1514 (2010).

    Article  Google Scholar 

  32. 32.

    Hirano, T., Jauhiainen, J., Inoue, T. & Takahashi, H. Controls on the carbon balance of tropical peatlands. Ecosystems 12, 873–887 (2009).

    Article  Google Scholar 

  33. 33.

    Jauhiainen, J., Kerojoki, O., Silvennoinen, H., Limin, S. & Vasander, H. Heterotrophic respiration in drained tropical peat is greatly affected by temperature—a passive ecosystem cooling experiment. Environ. Res. Lett. 9, 105013 (2014).

  34. 34.

    Hoyt, A. M. et al. CO2 emissions from an undrained tropical peatland: interacting influences of temperature, shading and water table depth. Glob. Change Biol. 25, 2885–2899 (2019).

  35. 35.

    Cobb, A. R. et al. How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands. Proc. Natl Acad. Sci. USA 114, E5187–E5196 (2017).

    Google Scholar 

  36. 36.

    Moore, S. et al. Deep instability of deforested tropical peatlands revealed by fluvial organic carbon fluxes. Nature 493, 660–663 (2013).

    Article  Google Scholar 

  37. 37.

    Chaussard, E. & Amelung, F. C. Characterization of geological hazards using globally observing spaceborne SAR. Photogramm. Eng. Remote Sens. 79, 982–986 (2013).

    Google Scholar 

  38. 38.

    Chen, C. W. & Zebker, H. A. Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models. IEEE Trans. Geosci. Remote Sens. 40, 1709–1719 (2002).

    Article  Google Scholar 

  39. 39.

    Elliott, J. R., Biggs, J., Parsons, B. & Wright, T. J. InSAR slip rate determination on the Altyn Tagh Fault, northern Tibet, in the presence of topographically correlated atmospheric delays. Geophys. Res. Lett. 35, L12309 (2008).

  40. 40.

    Chaussard, E., Johnson, C. W., Fattahi, H. & Burgmann, R. Potential and limits of InSAR to characterize interseismic deformation independently of GPS data: application to the southern San Andreas Fault system. Geochem. Geophys. Geosyst. 17, 1214–1229 (2016).

  41. 41.

    Fattahi, H. & Amelung, F. DEM error correction in InSAR time series. IEEE Trans. Geosci. Remote Sens. 51, 4249–4259 (2013).

    Article  Google Scholar 

  42. 42.

    Chaussard, E., Amelung, F. & Aoki, Y. Characterization of open and closed volcanic systems in Indonesia and Mexico using InSAR time series. J. Geophys. Res. Solid Earth 118, 3957–3969 (2013).

    Article  Google Scholar 

  43. 43.

    Zwieback, S., Hensley, S. & Hajnsek, I. Assessment of soil moisture effects on L-band radar interferometry. Remote Sens. Environ. 164, 77–89 (2015).

    Article  Google Scholar 

  44. 44.

    Scott, C. P., Lohman, R. B. & Jordan, T. E. InSAR constraints on soil moisture evolution after the March 2015 extreme precipitation event in Chile. Sci. Rep. 7, 4903 (2017).

  45. 45.

    De Zan, F., Zonno, M. & Lopez-Dekker, P. Phase inconsistencies and multiple scattering in SAR interferometry. IEEE Trans. Geosci. Remote Sens. 53, 6608–6616 (2015).

    Article  Google Scholar 

  46. 46.

    Page, S. E. et al. The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420, 61–65 (2002).

    Article  Google Scholar 

  47. 47.

    Miettinen, J., Shi, C., Tan, W. J. & Liew, S. C. 2010 land cover map of insular Southeast Asia in 250-m spatial resolution. Remote Sens. Lett. 3, 11–20 (2012).

    Article  Google Scholar 

  48. 48.

    Miettinen, J. et al. Historical Analysis and Projection of Oil Palm Plantation Expansion on Peatland in Southeast Asia (International Council on Clean Transportation, 2012).

  49. 49.

    van den Akker, J. J. H. et al. Emission of CO2 from agricultural peat soils in the Netherlands and ways to limit this emission. In Proc. 13th International Peat Congress ‘After Wise Use—the Future of Peatlands, Vol. 1 Oral Presentations (eds Farrell, C. & Feehan, J.) 645–648 (International Peat Society, 2008).

  50. 50.

    van den Wyngaert, I. J. I., Kramer, H., Kuikman, P. & Lesschen, J. P. Greenhouse Gas Reporting of the LULUCF Sector, Revisions and Updates Related to the Dutch NIR 2009 Alterra Report 1035-7 (Alterra, 2009).

  51. 51.

    Leifeld, J., Müller, M. & Fuhrer, J. Peatland subsidence and carbon loss from drained temperate fens. Soil Use Manag. 27, 170–176 (2011).

    Article  Google Scholar 

  52. 52.

    Driessen, P. M. & Rochimah, L. The Physical Properties of Lowland Peats from Kalimantan (Indonesia) 56–73 (Soil Research Institute, 1976).

  53. 53.

    Diemont, W. H. & Supardi, M. N. N. Accumulation of organic matter and inorganic constituents in a peat dome in Sumatra, Indonesia. In International Peat Society Symposium on Tropical Peat and Peatlands for Development 698–708 (1987).

  54. 54.

    Cameron, C. C., Esterle, J. S. & Palmer, C. A. The geology, botany and chemistry of selected peat-forming environments from temperate and tropical latitudes. Int. J. Coal Geol. 12, 105–156 (1989).

  55. 55.

    Neuzil, S. G. Onset and rate of peat and carbon accumulation in four domed ombrogenous peat deposits, Indonesia. In Biodiversity and Sustainability of Tropical Peatlands (eds Rieley, J. O. & Page, S. E.) 55–72 (Samara, 1997).

  56. 56.

    Page, S. E. et al. A record of Late Pleistocene and Holocene carbon accumulation and climate change from an equatorial peat bog (Kalimantan, Indonesia): implications for past, present and future carbon dynamics. J. Quat. Sci. 19, 625–635 (2004).

    Article  Google Scholar 

  57. 57.

    Sumawinata, B., Mulyanto, B., Djajakirana, G. & Pulunggono, H. B. Some considerations of tropical peat for energy. In Carbon-Climate-Human Interaction on Tropical Peatland: Proc. International Symposium and Workshop on Tropical Peatland (2007).

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We thank D. Sheehan, A. Graham, M. Wrable and J. Murack of the MIT Libraries’ GIS and Data Lab for sharing their time, expertise and the computing resources of the Lab. The ALOS‐PALSAR data are copyrighted by the Japanese Aerospace Exploration Agency and Ministry of Economy, Trade and Industry and were made available by the US Government Research Consortium through the Alaska Satellite Facility. ISCE is an InSAR processing software package developed at NASA JPL, Caltech and Stanford, which was made available through the Western North America InSAR Consortium. Peatland land-use maps1 were made available by the Centre for Remote Imaging, Sensing and Processing at the National University of Singapore. This work benefited from access to the University of Oregon high performance computer, Talapas. This research was supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme, the Singapore–MIT Alliance for Research and Technology, the US National Science Foundation (grants 1114155, 1114161 and 1923491 to C.F.H.) and the Environmental Solutions Initiative at MIT.

Author information




A.M.H., E.C. and C.F.H. conceived of the study. E.C. and A.M.H. completed InSAR data processing and time-series analysis. A.M.H. and S.S.S. performed land-use and spatial analysis, as well as regional upscaling. A.M.H. wrote the manuscript with contributions from E.C., S.S.S. and C.F.H.

Corresponding author

Correspondence to Alison M. Hoyt.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editors: Clare Davis; Xujia Jiang.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Industrial Plantations and Non-Peatland Areas at all Sites.

Density plot of subsidence rates for industrial plantations (2007) and non-peatland areas for each ALOS frame. Non-peatland areas are shown for pixels >15 km from the edge of the peat to exclude transition zones between peatland and mineral soils. Positive values indicate subsidence and negative values indicate uplift.

Extended Data Fig. 2 Subsidence Rate by Land Use.

Mean subsidence rates (positive values) for each 2007 land use category on peat within each ALOS frame, where available. Numbers indicate number of InSAR measurements averaged for each bar. Dashed lines indicate the mean subsidence rate of 2.24 cm/yr across all peatland measurements. Non-peatland areas (light blue) are shown for pixels >15 km from the edge of the peat to exclude transition zones between peatland and mineral soils. Error bars represent the standard deviation of the data (not the standard error of the mean).

Extended Data Fig. 3 Example of Upscaled Subsidence Map and Regression Tree.

(a) Map of upscaled subsidence. (b) Regression tree schematic. Mean regional subsidence and associated uncertainties were calculated based on a bootstrapping analysis of 1,000 regression trees and corresponding upscaled subsidence maps (Methods). To generate a single regression tree, 2007 land use was used as the Current Land Use, concurrent with ALOS measurements from 2007–2011. For regional upscaling, 2015 land use was used as the Current Land Use, as the most recently available regional mapping. All land use maps were generated by Miettinen et al.1. Total regional CO2 emissions and emissions factors were based on the mean of eight regression trees (each removing data from one ALOS frame). The displayed regression tree, for example purposes only, is based on all data and was used to generate the example regional subsidence map above. The upscaling map is provided as an illustration of the method. It is not our intent to make site-specific predictions due to the wide variability in drainage practices.

Extended Data Fig. 4 InSAR Validation with Ground-Based Subsidence Data.

(a) ALOS frame 6 measurements of industrial plantations which overlap in space and time with measurements on oil palm plantations in Sarawak, Malaysia by Othman et al.8 This is the only area of direct overlap in the region. (b) InSAR data from all other industrial plantations compared to ground-based pole measurements also made on plantations, but at different times and/or places. (c) InSAR data from all non-plantation land uses on peat (excluding pristine peat swamp forest) compared to ground-based pole measurements made on non-plantation land uses in the region, but at different times and/or places. In all panels, where multiple points are shown from a single study, they represent plantation areas established at different times or distinct land uses with distinct subsidence rates. Error bars indicate the standard deviation of the ground-based measurements within these study groups.

Extended Data Fig. 5 Schematic explanation of two methods for calculating carbon loss from bulk density profiles in a subsiding peatland with water table decline.

Method #1: The approach first applied to tropical peat by Couwenberg and Hooijier9. Bulk density profiles are plotted relative to the land surface, which has subsided. It is evident from these bulk density profiles, before and after subsidence, that the carbon loss can be calculated from the change in thickness of the anoxic peat, the small yellow rectangle on the far right. Method #2: Bulk density profiles are plotted relative to elevation. The net carbon lost must be the same regardless of how the plot is constructed, but the calculation is more complex for Method #2. Here the net carbon lost is shown as loss in carbon due to the drop in the land surface, minus the apparent gain in carbon from the increased bulk density below the elevation that is now the land surface. The carbon lost is the difference between the gain and loss shown by the yellow regions on the far right. Our results rely on Method #1. However, calculations of CO2 emissions from Method #2 yield similar results with higher uncertainties. Assuming a dry bulk density of 0.11 ± .03 g/cm3 and carbon content of 55 ± 2 % in the compacted oxic peat, a mean subsidence rate of 2.24 ± 0.23 cm/yr, a peat area of 15.7 Mha, and the fraction of subsidence due to compaction of 75 ± 15 % as found by Hooijer et al.2, we calculate CO2 emissions equivalent to 160 ± 61 MtC/yr (compared to 155 ± 30 MtC/yr using Method #1).

Extended Data Fig. 6 Frame 1 Subsidence and Land Use Map.

ALOS Frame 1 mean subsidence rates (top), 1990 land use (left) and 2007 land use (right). Positive values indicate subsidence and negative values indicate uplift. Peatland extent and land-use maps adapted with permission from ref. 1, Elsevier.

Extended Data Fig. 7 Frame 3 Subsidence and Land Use Map.

ALOS Frame 3 mean subsidence rates (top), 1990 land use (left) and 2007 land use (right). Positive values indicate subsidence and negative values indicate uplift. Peatland extent and land-use maps adapted with permission from ref. 1, Elsevier.

Extended Data Fig. 8 Frame 4 Subsidence and Land Use Map.

ALOS Frame 4 mean subsidence rates (top), 1990 land use (left) and 2007 land use (right). Positive values indicate subsidence and negative values indicate uplift. Peatland extent and land-use maps adapted with permission from ref. 1, Elsevier.

Extended Data Fig. 9 Frame 6 Subsidence and Land Use Map.

ALOS Frame 6 mean subsidence rates (top), 1990 land use (left) and 2007 land use (right). Positive values indicate subsidence and negative values indicate uplift. Peatland extent and land-use maps adapted with permission from ref. 1, Elsevier.

Extended Data Table 1 Study sites (ALOS frames) listed from north to south, first in Sumatra, then in Borneo

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Hoyt, A.M., Chaussard, E., Seppalainen, S.S. et al. Widespread subsidence and carbon emissions across Southeast Asian peatlands. Nat. Geosci. 13, 435–440 (2020).

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