Estimating tropical deforestation from Earth observation data

Carbon Management

Volumn 1, Issue 2, 2010, Pages 271-287

  Achard, Frédéric ^a   Stibig, Hans Jürgen ^a   Eva, Hugh D ^a   Lindquist, Erik J ^b   Bouvet, Alexandre ^a   Arino, Olivier ^c   Mayaux, Philippe ^a  

^a JOINT RESEARCH CENTRE   (Italy)

^b FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS   (Italy)

^c ESA ESRIN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CARBON EMISSIONS; CONSENSUS PROTOCOLS; DATA SOURCE; EARTH OBSERVATION DATA; EARTH OBSERVATIONS; GHG EMISSION; GLOBAL MONITORING; LEVEL OF DETAIL; MONITORING PROGRAMS; REGIONAL SCALE; SATELLITE REMOTE SENSING; SPATIAL RESOLUTION; TROPICAL DEFORESTATION; TROPICAL FOREST; UNITED NATIONS FRAMEWORK CONVENTION ON CLIMATE CHANGES;

DEFORESTATION; DEVELOPING COUNTRIES; ESTIMATION; GLOBAL WARMING; OBSERVATORIES; REMOTE SENSING; SATELLITE IMAGERY; TROPICS;

UNCERTAINTY ANALYSIS;

DEFORESTATION; DEVELOPING COUNTRIES; IMAGE ANALYSIS; REMOTE SENSING; SATELLITES;

EID: 79955011049     PISSN: 17583004     EISSN: 17583012     Source Type: Journal    
DOI: 10.4155/cmt.10.30     Document Type: Review

References (96)

1. Global Forest Assessment 2010: Main Report. Food and Agriculture Organization of the UN, Rome, Italy (2010). • • Report with the most consistent global database of national estimates of forest area change for the period 1990-2010.
2. DeFries RS, Rudel T, Uriarte M, Hansen M. Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nature Geosci 3, 178-181 (2010).
3. Gibbs K, Ruesch AS, Achard F et al. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proc. Natl Acad. Sci. USA 107(38), 16732-16737 (2010).
4. Rudel TK, Defries R, Asner GP, Laurance WF. Changing drivers of deforestation and new opportunities for conservation. Conserv. Biol. 23(6), 1396-1406 (2009).
5. Penman J, Gytarsky M, Hiraishi T et al. Good Practice Guidance for Land Use, Land-Use Change and Forestry. IPCC National Greenhouse Gas Inventories Programme and Institute for Global Environmental Strategies. Kanagawa, Japan (2003).
6. Denman KL, Brasseur G, Chidthaisong A et al. Couplings between changes in the climate system and biogeochemistry. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon S, Qin D, Manning M et al. (Eds). Cambridge University Press, Cambridge, UK (2007).
7. Asner GP, Powell GVN, Mascaro J et al. High-resolution forest carbon stocks and emissions in the Amazon. Proc. Natl Acad. Sci. USA 107(38), 16738-16742 (2010).
8. 2 emissions from forest loss. Nature Geosci. 2, 737-738 (2009).
9. Lewis SL, Lopez-Gonzalez G, Sonké B et al. Increasing carbon storage in intact African tropical forests. Nature 457, 1003-1006 (2009).
10. 2. Science 316, 1732-1735 (2007). (Pubitemid 46988545)
11. Solomon S, Qin D, Manning M et al. Technical summary. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon S, Qin D, Manning M et al. (Eds). Cambridge University Press, Cambridge, UK (2007).
12. Houghton RA. Aboveground forest biomass and the global carbon balance. Glob. Chang. Biol. 11, 945-958 (2005). (Pubitemid 40865258)
13. Ramankutty N, Gibbs H, Achard F, DeFries RS, Foley J, Houghton RA. Challenges to estimating carbon emissions from tropical deforestation. Glob. Chang. Biol. 13, 51-66 (2007). (Pubitemid 46092182)
14. Baker DJ, Richards G, Grainger A et al. Achieving forest carbon information with higher certainty: a five-part plan. Environ. Sci. Policy. 13, 249-260 (2010).
15. Global Forest Resources Assessment 2000. Food and Agriculture Organization of the UN. Rome, Italy, 140(2001).
16. Achard F, Eva HD, Mayaux P, Stibig H-J, Belward A. Improved estimates of net carbon emissions from land cover change in the tropics for the 1990s. Global Biogeochem. Cycles 18 (GB2008) (2004). Estimates of emissions from tropical deforestation based on a sample of moderate-resolution satellite imagery for estimation of deforestation.
17. DeFries RS, Houghton RA, Hansen M, Field C, Skole DL, Townshend J. Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 90s. Proc. Natl Acad. Sci. USA 99(22), 14256-14261 (2002). • use of co arse-resolution satellite imagery for estimation of tropical deforestation. (Pubitemid 35257659)
18. Keith H, Mackey BG, Lindenmayer DB. Re-evaluation of forest biomass carbon stocks and lessons from the world's most carbon-dense forests. Proc. Natl Acad. Sci. USA 106(28), 11635-11640 (2009).
19. McRoberts RE, Cohen WB, Næsset E, Stehman SV, Tomppo EO. Using remotely sensed data to construct and assess forest attribute maps and related spatial products. Scand. J. For. Res. 25(4) 340-367 (2010).
20. Baccini A, Laporte N, Goetz SJ, Sun M, Dong H. A first map of tropical Africa's above-ground biomass derived from satellite imagery. Environ. Res. Lett. 3, 045011(2008).
21. Gibbs HK, Brown S, Niles JO, Foley JA. Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ. Res. Lett. 2(4), 045023(2007).
22. Saatchi SS, Houghton RA, Dos Santos Alvala RC, Soares JV, Yu Y. Distribution of aboveground live biomass in the Amazon basin. Glob. Chang. Biol. 13, 816-837 (2007). (Pubitemid 46638550)
23. Houghton RA, Hall FG, Goetz SJ. The importance of biomass in the global carbon cycle. J. Geophys. Res. Biogeosci. 114, G00E03 (2009).
24. Methodological Guidance for Activities Relating to Reducing Emissions from Deforestation and Forest Degradation and the Role of Conservation, Sustainable Managemen of Forests and Enhancement of Forest Carbon Stocks in Developing Countries. UNFCCC Secretariat, Bonn, Germany (2009).
25. Seventh Conference of Parties: The Marrakech Accords. UNFCCC Secretariat, Bonn, Germany (2002).
26. Mollicone D, Achard F, Federici et al. An incentive mechanism for reducing emissions from conversion of intact and non-intact forests. Clim. Change 83, 477-493 (2007). (Pubitemid 47030195)
27. Moving Ahead with REDD: Issues, Options and Implications. Angelsen A (Ed.). Center for International Forestry Research, Bogor, Indonesia (2008).
28. Grainger A. Difficulties in tracking the long-term trend in tropical forest area. Proc. Natl Acad. Sci. USA 105(2), 818-823 (2008). (Pubitemid 351171793)
29. McRoberts RE, Tomppo EO. Remote sensing support for national forest inventories. Remote Sens. Environ. 110(4), 412-419 (2007). (Pubitemid 47361231)
30. DeFries RS, Achard F, Brown S et al. Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. Environ. Sci. Policy 10, 385-394 (2007). (Pubitemid 46830335)
31. Achard F, DeFries R, Eva HD, Hansen M, Mayaux P, Stibig H-J. Pan-tropical monitoring of deforestation. Environ. Res. Lett. 2, 045022(2007).
32. A Sourcebook of Methods and Procedures for Monitoring and Reporting Anthropogenic Greenhouse Gas Emissions and Removals Caused by Deforestation, Gains and Losses of Carbon Stocks in Forests Remaining Forests, and Forestation. Achard F, Brown S, De Fries R et al. (Eds). Global Observation of Forest and Land Cover Dynamics, Alberta, Canada (2009).
33. Good Practice Guidance for Land Use, Land-Use Change and Forestry (GPG-LULUCF). Intergovernmental Panel on Climate Change. Institute for Global Environmental Strategies, Kanagawa, Japan (2003).
34. Coppin P, Jonckheere I, Nackaerts K, Muys B. Digital change detection methods in ecosystem monitoring: a review. Int. J. Remote Sens. 25(9), 1565-1596 (2004). (Pubitemid 38516797)
35. Fritz S, McCallum I, Schill C et al. Geo-wiki.org: the use of crowdsourcing to improve global land cover. Remote Sens. 1, 345-354 (2009).
36. Bartholomé E, Belward AS. GLC2000: a new approach to global land cover mapping from Earth observation data. Int. J. Remote Sens. 26(9), 1959-1197 (2005).
37. Friedl MA, McIver DK, Hodges JCF et al. Global land cover mapping from MODIS: algorithms and early results. Remote Sens. Environ. xs 83 (1-2), 287-302 (2002). (Pubitemid 35307474)
38. Herold M, Woodcock C, Di Gregorio A et al. A joint initiative for harmonization and validation of land cover datasets. IEEE Trans. Geosci. Remote Sens. 44, 1719-1727 (2006). (Pubitemid 44109493)
39. Hansen MC, Townshend J, DeFries RS, Carroll M. Estimation of tree cover using MODIS data at global, continental and regional/local scales. Int. J. Remote Sens. 26(19), 4359-4380 (2005). (Pubitemid 43064740)
40. Friedl MA, Sulla-Menashe D, Tan B et al. MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens. Environ. 114(1), 168-182 (2010).
41. Arino O, Bicheron P, Achard F, Latham J, Witt R, Weber JL. The most detailed portrait of Earth. European Space Agency Bulletin 136, 24-31 (2008).
42. Eva HD, Belward AS, De Miranda E et al. A land cover map of South America. Global Change Biol. 10, 732-745 (2004).
43. Mayaux P, Bartholomé E, Fritz S, Belward AS. A new landcover map of Africa for the year 2000 J. Biogeogr. 31, 1-17 (2004).
44. Stibig HJ, Belward AS, Roy PS et al. A land cover map for South and Southeast Asia derived from SPOT-VEGETATION data. J. Biogeogr. 34, 625-637 (2007). (Pubitemid 46493420)
45. Vancutsem C, Pekel J-F, Evrard C, Malaisse F, Defourny P. Mapping and characterizing the vegetation types of the Democratic Republic of Congo using SPOT-VEGETATION time series. Int. J. Appl. Earth Obs. Geoinf. 11, 62-76 (2009).
46. Strahler AH, Boschetti L, Foody GM et al. Global Land Cover Validation: Recommendations for Evaluation and Accuracy Assessment of Global Land Cover Maps. EUR 22156 EN. Office for Official Publications of the European Communities, Luxembourg (2006).
47. Lepers E, Lambin EF, Janetos AC et al. A synthesis of information on rapid land-cover change for the period 1981-2000. Bioscience 55, 115-124 (2005). (Pubitemid 40218457)
48. Hansen MC, Stehman SV, Potapov PV et al. Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data. Proc. Natl Acad. Sci. USA 105(27), 9439-9444 (2008). • • New method combing the identification of areas of forest loss from time series of coarse resolution (500m) satellite imagery calibrated with a sample of reference blocks derived from moderate resolution satellite imagery.
49. Monitoramento da Floresta Amazônica Brasileira por Satelite, Projeto PRODES. Instituto de Pesquisas Espaciais, São Jose dos Campos, Brazil (2010). • • Operational yearly wall-to-wall forest monitoring system covering Brazilian Amazonia using moderate resolution satellite imagery.
50. Tucker CJ, Grant DM, Dykstra JD. NASA's Global Orthorectified Landsat Data Set. Photogramm. Eng. Remote Sens. 70, 313-322 (2004).
51. Gutman G, Byrnes R, Masek J et al. Towards monitoring land-cover and land-use changes at a global scale: the Global Land Survey 2005. Photogramm. Eng. Remote Sens. 74(1), 6-10 (2008).
52. Franks S, Masek J, Headley R, Gasch J, Arvidson T. Large area scene selection interface (LASSI) methodology of selecting landsat imagery for the Global Land Survey 2005. Photogramm. Eng. Remote Sens. 75, 1287-1296 (2009).
53. Böttcher H, Eisbrenner K, Fritz S et al. An assessment of monitoring requirements and costs of 'Reduced Emissions from Deforestation and Degradation'. Carbon Balance Manag 4(7) DOI: 10.1186/1750-0680-4-7 (2009) (Epub).
54. Morton D, DeFries RS, Shimabukuro y et al. Rapid assessment of annual deforestation in the Brazilian Amazon using MODIS data. Earth Interact. 9, 1-22 (2005).
55. Bontemps S, Langner A, Defourny P. Monitoring forest changes in Borneo on a yearly basis by an object-based change detection algorithm using Spot-VEGETATION time series. Int. J. Remote Sens. (2010) (In Press).
56. Czaplewski RL. Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation? Int. J. Remote Sens. 24(6), 1409-1412 (2003). (Pubitemid 36440277)
57. Stehman SV. Comparing estimators of gross change derived from complete coverage mapping versus statistical sampling of remotely sensed data. Remote Sens. Environ. 96 (3-4), 466-474 (2005). • Key paper on the use of sampling strategy versus the wall-to-wall approach. (Pubitemid 40912444)
58. Mayaux P, Holmgren P, Achard F, Eva HD, Stibig HJ, Branthomme A. Tropical forest cover change in the 1990s and options for future monitoring. Philos. Trans. R. Soc. B Biol. Sci. 360, 373-384 (2005). (Pubitemid 41529631)
59. Gallego FJ. Stratified sampling of satellite images with a systematic grid of points. ISPRS J. Photogramm. Remote Sens. 59, 369-376 (2005). (Pubitemid 41728961)
60. Drigo R, Lasserre B, Marchetti M. Patterns and trends in tropical forest cover. Plant Biosystems 143(2) 311-327 (2009).
61. Broich M, Stehman SV, Hansen MC, Potapov P, Shimabukuro YE. A comparison of sampling designs for estimating deforestation from Landsat imagery: a case study of the Brazilian legal Amazon. Remote Sens. Environ. 113(11), 2448-2454 (2009).
62. Eva HD, Carboni S, Achard F et al. Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery. ISPRS J. Photogramm. Remote Sens. 65, 191-197 (2010).
63. Potapov P, Hansen MC, Gerrand AM et al. The global Landsat imagery database for the FAO FRA remote sensing survey. Int. J. Digital Earth 1, 1753-8955 (2010).
64. Ridder RM. Options and Recommendations for a Global Remote Sensing Survey of Forests. Food and Agriculture Organization of the UN, Rome, Italy (2007).
65. The 2010 Global Forest Resources Assessment Remote Sensing Survey: An Outline of the Objectives, Data, Methods and Approach. Food and Agriculture Organization of the UN, Rome, Italy (2009).
66. Bodart C, Beuchle R, Raši R et al. Pre-processing and segmentation of a global sample of multi-scene Landsat imagery used to monitor forest cover changes over the tropics. ISPRS-J. Photogramm. Remote Sens. (2010) (In Press).
67. Duveiller G, Defourny P, Desclée B, Mayaux P. Deforestation in Central Africa: estimates at regional, national and landscape levels by advanced processing of systematicallydistributed Landsat extracts. Remote Sens. Environ. 112(5), 1969-1981 (2008).
68. Desclée B, Bogaert P, Defourny P. Forest change detection by statistical object-based method. Remote Sens. Environ. 102 (1-2), 1-11 (2006).
69. Stach N, Salvado A, Petit M et al. Land use monitoring by remote sensing in tropical forest areas in support of the Kyoto Protocol: the case of French Guiana. Int. J. Remote Sens. 30(19), 5133-5149 (2009).
70. Steininger MK, Godoy F, Harper G. Effects of systematic sampling on satellite estimates of deforestation rates. Environ. Res. Lett. 4, 034015(2009).
71. State of Forest Report 2009. Ministry of Environment and Forest, Dehra Dun, India (2009). • Operational biannual wall-to-wall forest monitoring system over India combined with national forest field inventory.
72. Hansen MC, Roy DP, Lindquist e et al. A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo Basin. Remote Sens. Environ. 112(5), 2495-2513 (2008).
73. Lindquist EJ, Hansen MC, Roy DP, Justice CO. The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the global land survey. Int. J. Remote Sens. 29, 7269-7275 (2008).
74. Asner GP, Knapp DE, Balaji A, Paez-Acosta G. Automated mapping of tropical deforestation and forest degradation: CLASlite. J. Appl. Remote Sens. 3, 033543(2009).
75. Le Toan T, Quegan S, Woodward I, Lomas M, Delbart N, Picard G. Relating radar remote sensing of biomass to modelling of forest carbon budgets. Clim. Change 67, 379-402 (2004). (Pubitemid 40390655)
76. Rosenqvist A, Finlayson CM, Lowry J, Taylor D. The potential of long-wavelength satellite-borne radar to support implementation of the Ramsar Wetlands Convention. Aquatic Conservation: Marine and Freshwater Ecosystems 17, 229-244 (2007). (Pubitemid 46953481)
77. Almeida-Filho R, Shimabukuro YE, Rosenqvist A, Sanchez GA. Using dualpolarized ALOS PALSAR data for detecting new fronts of deforestation in the Brazilian Amazônia. Int. J. Remote Sens. 30(14) 3735-3743 (2009).
78. Navarro de Mesquita H Jr, Crislei Silva M, Freitas de Moraes D et al. Law enforcement deforestation assessment. In: K&C Science report - Phase 1. Japanese Aerospace Exploration Agency, EORC report NDX-100003(2009).
79. Hoekman D, Vissers M, Wielaard N. PALSAR wide-area mapping of Borneo: methodology and map validation. IEEE JSTARS DOI: 10.1109/JSTARS.2010. 2070059(2010) (Epub ahead of print).
80. Walker WS, Stickler CM, Kellndorfer JM, Kirsch KM, Nepstad DC. Land cover in the Brazilian Amazon: a comparative analysis of ALOS/PALSAR and Landsat data sources. IEEE JSTARS. DOI: 10.1109/JSTARS.2010.2076398 (2010) (Epub ahead of print).
81. Mayaux P, De Grandi GF, Rauste Y, Simard M, Saatchi S. Large Scale vegetation maps derived from the combined L-band GRFM and C-band CAMP wide area radar mosaics of Central Africa. Int. J. Remote Sens. 23(7), 1261-1282 (2002). (Pubitemid 34416263)
82. Sgrenzaroli M, De Grandi GF, Eva HD, Achard F. Tropical forest cover monitoring: estimates from the GRFM JERS-1 radar mosaics using wavelets zooming techniques and Validation. Int. J. Remote Sens. 23(7), 1329-1355 (2002). (Pubitemid 34439786)
83. Stehman S. Sampling designs for accuracy assessment of land cover. Int. J. Remote Sens. 30(20), 5243-5272 (2009).
84. Grassi G, Monni S, Federici S, Achard F, Mollicone D. Applying the conservativeness principle to REDD to deal with the uncertainties of the estimate. Environ. Res. Lett. 3, 035005(2008)
85. Foody GM. Assessing the accuracy of land cover change with imperfect ground reference data. Remote Sens. Environ. 114(10), 2271-2285 (2010).
86. Martimort P, Berger M, Carnicero B et al. Sentinel-2 the optical high-resolution mission for GMES operational services. European Space Agency Bulletin 131, 19-23 (2007).
87. Attema E, Bargellini P, Edwards P et al. Sentinel-1 the radar mission for GMES operational land and sea services. European Space Agency Bulletin 131, 11-17 (2007).
88. Le Toan T, Quegan S, Davidson MWJ et al. The BIOMASS Mission: mapping global forest biomass to better understand the terrestrial carbon cycle. Remote Sens. Environ. (2010) (In Press).
89. Goetz SJ, Baccini A, Laporte NT et al. Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance and Manag. 4, 2(2009).
90. Lefsky MA. A global forest canopy height map from the moderate resolution imaging spectroradiometer and the geoscience laser altimeter system. Geophys. Res. Lett. 37, L15401 (2010).
91. Asner GP, Rudel TK, Aide TM, Defries R, Emerson R. A contemporary assessment of change in humid tropical forests. Conserv. Biol. 23(6), 1386-1395 (2009).
92. Kintish E. Improved monitoring of rainforests helps pierce haze of deforestation. Science 316, 536-537 (2007).
93. Report on the Concept Phase for developing a Global Forest Observations Initiative. Planning Group under the GEO Forest Carbon Tracking Task (GEO Task CL-09-03b). The Group on Earth Observations, Geneva, Switzerland (2010).
94. Loveland TR, Zhu Z, Ohlen DO, Brown JF, Reed C, Yang L. An analysis of the IGBP global land-cover characterization process. Photogramm. Eng. Remote Sens. 1021-1032 (1999). (Pubitemid 29432604)
95. Hansen MC, DeFries RS, Townshend JRG, Sohlberg R. Global land cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens. 21, 1331-1364 (2000). (Pubitemid 30242138)
96. Achard F, Eva HD, Mayaux P. Tropical forest mapping from coarse spatial resolution satellite data: production and accuracy assessment issues. Int. J. Remote Sens. 22(14), 2741-2762 (2001). (Pubitemid 32863569)