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The progress on remote sensing technology in identifying tropical forest degradation: a synthesis of the present knowledge and future perspectives

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Abstract

Since the launch of the first satellite in 1972, ecologists have been equipped with new tools to address the degradation of tropical forests, previously limited by field-based methods. This article is a review of the state of remote sensing technology in characterizing the degradation of tropical forest. The factors responsible for the structural and functional degradation of the tropical forest and its likely impacts are described in view of generating remote sensing based inputs. In order to assess the degradation and utility of geo-informatics tools, 32 parameters are identified. The research developments at different levels of information extraction from the historic to recent periods are elaborated, and future challenges are predicted. The article concludes that an additional momentum of research is required to answer many unresolved questions of tropical forest degradation.

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References

  • Anaya JA, Chuvieco E, Palacios-Orueta A (2009) Aboveground biomass assessment in Colombia: a remote sensing approach. For Ecol Manag 257(4):1237–1246

    Google Scholar 

  • Anitha K, Balasubramanian P, Prasad SN (2007) Tree Community structure and regeneration in Anaikatty hills, Western Ghats. Indian J For 30:315–324

    Google Scholar 

  • Anitha K, Joseph S, Ramasamy EV, Prasad SN (2009) Changes in structural attributes of plant communities along disturbance gradients in a dry deciduous forest of Southern India. Environ Monit Assess 155(1):393–405

    Article  Google Scholar 

  • Anitha K, Joseph S, Chandran RJ, Ramasamy EV, Prasad SN (2010) Tree species diversity and community composition in a human-dominated tropical forest of Western Ghats biodiversity hotspot, India. Ecol Complex 7(2):217–224

    Google Scholar 

  • Asner GP (1998) Biophysical and biochemical sources of variability in canopy reflectance—the SAIL model. Rem Sen Environ 64(3):234–253

    Article  Google Scholar 

  • Asner GP, Martin RE (2008) Spectral and chemical analysis of tropical forests: Scaling from leaf to canopy levels. Rem Sen Environ 112:3958–3970

    Article  Google Scholar 

  • Asner GP, Martin RE (2009) Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests. Front Ecol Environ 7:269–276

    Article  Google Scholar 

  • Asner GP, Vitousek PM (2005) Remote analysis of biological invasion and biogeochemical change. Proc Natl Acad Sci USA 102:4383–4386

    Article  Google Scholar 

  • Asner GP, Michael P, Michael K, Rodrigo P Jr, Jose NMS, Johan CZ (2002) Estimating canopy structure in an Amazon forest from laser range finder and IKONOS satellite observations. Biotropica 34:483–492

    Google Scholar 

  • Asner GP, Jones MO, Martin RE et al (2008) Remote sensing of native and invasive species in Hawaiian forests. Rem Sen Environ 112:1912–1926

    Article  Google Scholar 

  • Baccini A et al (2008) A first map of tropical Africa’s above-ground biomass derived from satellite imagery. Environ Res Lett 3:045011

    Article  Google Scholar 

  • Baret F, Hagolle O, Geiger B, Bicheron P, Miras B, Huc M, Berthelot B, Nino F, Weiss M, Samain O, Roujean JL, Leroy M (2007) LAI, FAPAR and FCOVER CYCLOPES global products derived from VEGETATION. Rem Sen Environ 110:275–286

    Article  Google Scholar 

  • Bawa KS, Dayanandan S (1997) Socioeconomic factors and tropical deforestation. Nature 386:562–563

    Article  Google Scholar 

  • Biesmeijer JC, Roberts SPM, Reemer M, Ohlemüller R, Edwards M, Peeters T (2006) Parallel declines in pollinators and insect-pollinated in Britain and the Netherlands. Science 313:351–354

    Article  Google Scholar 

  • Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449

    Article  Google Scholar 

  • Bourgeau-Chavez LL, Kasischke ES, Brunzell S, Mudd JP, Tukman M (2002) Mapping fire scars in global boreal forests using imaging radar data. Int J Remote Sens 23:4211–4234

    Article  Google Scholar 

  • Braswell BH, Hagen SC, Frolking SE et al (2003) A multivariable approach for mapping sub-pixel land cover distributions using MISR and MODIS: application in the Brazilian Amazon region. Rem Sen Environ 87:243–256

    Article  Google Scholar 

  • Broadbent EN, Asner GP, Keller M et al (2008) Forest fragmentation and edge effects from deforestation and selective logging in the Brazilian Amazon. Biol Conserv 141:1745–1757

    Article  Google Scholar 

  • Brook BW, Sodhi NS, Ng PKL (2003) Catastrophic extinctions follow deforestation in Singapore. Nature 424:420–426

    Article  Google Scholar 

  • Carreiras JMB, Pereira JMC, Campagnolo ML et al (2006) Assessing the extent of agriculture/pasture and secondary succession forest in the Brazilian Legal Amazon using SPOT VEGETATION data. Rem Sen Environ 101:283–298

    Article  Google Scholar 

  • Chambers JQ, Asner GP, Morton DC, Anderson LO, Saatchi SS, Espírito-Santo FDB (2007) Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests. Trends Ecol Evol 22:414–423

    Article  Google Scholar 

  • Chapin FS III, Zavaleta ES, Eviner VT (2000) Consequences of changing biodiversity. Nature 405:234–243

    Article  Google Scholar 

  • Clark DB, Read JM, Clark ML, Cruz AM, Dotti MF, Clark DA (2004) Application of 1-m and 4-m resolution satellite data to ecological studies of tropical rain forests. Ecol Appl 14:61–74

    Article  Google Scholar 

  • Clark ML, Roberts DA, Clark DB (2005) Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales. Rem Sen Environ 96:375–398

    Article  Google Scholar 

  • Cochrane MA (2000) Using vegetation reflectance variability for species level classification of hyperspectral data. Int J Remote Sens 21:2075–2087

    Article  Google Scholar 

  • Cochrane MA (2003) Fire science for rainforests. Nature 421:913–919

    Article  Google Scholar 

  • Convention on Biological Diversity (2002) Harmonization of forest-related definitions for use by various Stakeholders. In: Conference of the parties to the Convention on Biological Diversity—6th meeting, The Hague, p 16

  • Couturier S, Taylor D, Siegert F, Hoffmann A, Bao MQ (2001) ERS SAR backscatter: a potential real-time indicator of the proneness of modified rainforests to fire. Rem Sen Environ 76:410–417

    Article  Google Scholar 

  • Crutzen PJ, Andreae MO (1990) Biomass burning in the tropics: impact on atmospheric chemistry and biogeochemical cycles. Science 250:1669–1678

    Article  Google Scholar 

  • Curran PJ (2001) Imaging spectrometry for ecological applications. Int J Appl Earth Observ Geoinf 3(4):305–312

    Article  Google Scholar 

  • Daily GC (1997) Nature’s services. Island Press, Washington

    Google Scholar 

  • Dale MRT (1999) Spatial pattern analysis in plant ecology. Cambridge University Press, New York

    Book  Google Scholar 

  • Darvishzadeh R, Skidmore A, Schlerf M, Atzberger C (2008) Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland. Rem Sen Environ 112:2592–2604

    Article  Google Scholar 

  • Defries RS (1999) Combining satellite data and biogeochemical models to estimate global effects of human-induced land cover change on carbon emissions and primary productivity. Global Biogeochem Cycles 13:803–815

    Article  Google Scholar 

  • Dennis RA, Colfer CP (2006) Impacts of land use and fire on the loss and degradation of lowland forest in 1983–2000 in East Kutai District, East Kalimantan, Indonesia. Singap J Trop Geogr 27:30–48

    Article  Google Scholar 

  • Diaz S, Fargione J, Chapin FS, Tilman D (2006) Biodiversity loss threatens human well-being. PLoS Biol 4:e277

    Article  Google Scholar 

  • Drolet GG, Huemmrich KF, Hall FG, Middleton EM, Black TA, Barr AG, Margolis HA (2005) A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest. Rem Sen Environ 98(2–3):212–224

    Google Scholar 

  • Ewers RM, Laurence WF (2006) Scale-dependent patterns of deforestation in the Brazilian Amazon. Environ Conserv 33:203–211

    Article  Google Scholar 

  • Fensholt R, Sandholt I (2003) Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment. Rem Sen Environ 87(1):111–121

    Google Scholar 

  • Food and Agricultural Organization (2002) Evaluation of world forestry resources 2000. Main Report. FAO, Rome, p 466

    Google Scholar 

  • Fraser RH, Fernandes R, Latifovic R (2003) Multi-temporal mapping of burned forest over Canada using satellite-based change metrics. Geocarto Int 18:37–47

    Article  Google Scholar 

  • French NHF, Bourgeau-Chavez LL, Wang Y, Kasischke ES (1999) Initial observations of Radarsat imagery at fire-disturbed sites in interior Alaska. Rem Sen Environ 68:89–94

    Article  Google Scholar 

  • Friedl MA, McIver DK, Hodges JCF, Zhang XY, Muchoney D, Strahler AH (2002) Global land cover mapping from MODIS: algorithms and early results. Rem Sen Environ 83:287–302

    Article  Google Scholar 

  • Fuller DO (2000) Satellite remote sensing of biomass burning with optical and thermal sensors. Prog Phys Geogr 24:543–561

    Google Scholar 

  • Geist HJ, Lambin EF (2002) Proximate causes and underlying driving forces of tropical deforestation. Bioscience 52:143–150

    Article  Google Scholar 

  • Ghiyamat A, Shafri HZM (2010) A review on hyperspectral remote sensing for homogeneous and heterogeneous forest biodiversity assessment. Int J Remote Sens 31:1837–1857

    Article  Google Scholar 

  • Goetz SJ, Prince SD (1996) Remote sensing of net primary production in boreal forest stands. Agric For Meteorol 78(3–4):149–179

    Article  Google Scholar 

  • Goetz S, Baccini A, Laporte N et al (2009) Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance Manag 4:2

    Article  Google Scholar 

  • Grace J, Nichol C, Disney M, Lewis P, Quaife T, Bowyer P (2007) Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence? Global Change Biol 13:1484–1497

    Google Scholar 

  • Groombridge B, Martin J (2000) Global biodiversity: earth’s living resources in the 21st century. World Conservation Monitoring Centre, UK

    Google Scholar 

  • Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecological Modelling 135:147–186

    Article  Google Scholar 

  • Gutman G, Ignatov A (1995) Global land monitoring from AVHRR: potential and limitations. Int J Remote Sens 16:2301–2309

    Article  Google Scholar 

  • Hansen MC, Stehman SV, Potapov PV, Loveland TR, Townshend JRG, DeFries RS, Pittman KW, Arunarwati B, Stolle F, Steininger MK, Carroll M, DiMiceli C (2008) Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data. Proceedings of the National Academy of Sciences 105(27):9439–9444

    Google Scholar 

  • Hubbell SP, He F, Condit R, Borda-de-Agua L, Kellner J, ter Steege H (2008) How many tree species are there in the Amazon and how many of them will go extinct? Proc Natl Acad Sci 105:11498–11504

    Article  Google Scholar 

  • Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira G (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Rem Sen Environ 83(1-2):195–213

    Google Scholar 

  • Ingram JC, Dawson TP, Whittaker RJ (2005) Mapping tropical forest structure in southeastern Madagascar using remote sensing and artificial neural networks. Rem Sen Environ 94:491–507

    Article  Google Scholar 

  • International Tropical Timber Organization (2002) Guidelines for the restoration. Management and Rehabilitation of Degraded and Secondary Tropical Forests, Yokohama, Japan

    Google Scholar 

  • Jacquemoud S, Verhoef W, Baret F, Bacour C, Zarco-Tejada PJ, Asner GP, Francois C, Ustin SL (2009) PROSPECT + SAIL models: a review of use for vegetation characterization. Rem Sen Environ 113:S56–S66

    Article  Google Scholar 

  • Jia GJ, Burke IC, Goetz AFH, Kaufmann MR, Kindel BC (2006) Assessing spatial patterns of forest fuel using AVIRIS data. Rem Sen Environ 102:318–327

    Article  Google Scholar 

  • Jin S, Sader SA (2005) MODIS time-series imagery for forest disturbance detection and quantification of patch size effects. Rem Sen Environ 99:462–470

    Article  Google Scholar 

  • Joseph S (2008) Assessment of landcover dynamics and its conservation implications in tropical forests of Western Ghats. In: India student conference on conservation science, Cambridge University, UK

  • Joseph S, Anitha K, Murthy M (2009a) Forest fire in India: a review of the knowledge base. J Forest Res 14(3):127–134

    Article  Google Scholar 

  • Joseph S, Blackburn GA, Gharai B, Sudhakar S, Thomas AP, Murthy MSR (2009b) Monitoring conservation effectiveness in a global biodiversity hotspot: the contribution of land cover change assessment. Environ Monit Assess 158:169–179

    Article  Google Scholar 

  • Justice CO, Townshend JRG, Vermote EF, Masuoka E, Wolfe RE, Saleous N et al (2002) An overview of MODIS land data processing and product status. Rem Sen Environ 83:3–15

    Article  Google Scholar 

  • Kalluri S, Desch A, Curry T, Altstatt A, Devers D, Townshend JRG, Tucker CJ (2001) Historical satellite data used to map Pan-Amazon forest cover. EOS Transact 82:201

    Article  Google Scholar 

  • Kiran Chand TR, Badarinath KVS, Krishna Prasad V, Murthy MSR, Elvidge CD, Tuttle BT (2006) Monitoring forest fires over the Indian region using defense meteorological satellite program-operational Linescan system night time satellite data. Rem Sen Environ 103:165–178

    Article  Google Scholar 

  • Kokaly RF, Rockwell BW, Haire SL, King TVV (2007) Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing. Rem Sen Environ 106:305–325

    Article  Google Scholar 

  • Lamb D, Erskine PD, Parrotta JA (2005) Restoration of degraded tropical forest landscapes. Science 310:1628–1632

    Article  Google Scholar 

  • Lambin EF (1999) Monitoring forest degradation in tropical regions by remote sensing: some methodological issues. Glob Ecol Biogeogr 8:191–198

    Article  Google Scholar 

  • Lambin EF, Geist HJ, Lepers E (2003) Dynamics of land-use and cover change. Ann Rev Environ Resour 28:205–241

    Article  Google Scholar 

  • Lewis SL, Phillips OL, Baker TR, Lloyd J, Malhi Y, Almeida S et al (2004) Concerted changes in tropical forest structure and dynamics: evidence from 50 South American long-term plots. Philosoph Transact: Biol Sci 359:421–436

    Article  Google Scholar 

  • Luyssaert S, Inglima I, Jung M, Richardson AD, Reichstein M, Papale D, Piao SL, Schulze ED, Wingate L, Matteucci G, Aragao L, Aubinet M, Beer C, Bernhofer C, Black KG, Bonal D, Bonnefond JM, Chambers J, Ciais P, Cook B, Davis KJ, Dolman AJ, Gielen B, Goulden M, Grace J, Granier A, Grelle A, Griffis T, Grunwald T, Guidolotti G, Hanson PJ, Harding R, Hollinger DY, Hutyra LR, Kolari P, Kruijt B, Kutsch W, Lagergren F, Laurila T, Law BE, Le Maire G, Lindroth A, Loustau D, Malhi Y, Mateus J, Migliavacca M, Misson L, Montagnani L, Moncrieff J, Moors E, Munger JW, Nikinmaa E, Ollinger SV, Pita G, Rebmann C, Roupsard O, Saigusa N, Sanz MJ, Seufert G, Sierra C, Smith ML, Tang J, Valentini R, Vesala T, Janssens IA (2007) CO2 balance of boreal, temperate, and tropical forests derived from a global database. Global Change Biol 13:2509–2537

    Article  Google Scholar 

  • Malhi Y, Román-Cuesta RM (2008) Analysis of lacunarity and scales of spatial homogeneity in IKONOS images of Amazonian tropical forest canopies. Rem Sen Environ 112:2074–2087

    Article  Google Scholar 

  • Miles L, Newton AC, DeFries RS (2006) A global overview of the conservation status of tropical dry forests. J Biogeogr 33:491–506

    Article  Google Scholar 

  • Moya I, Camenen L, Evain S, Goulas Y, Cerovic ZG, Latouche G, Flexas J, Ounis A (2004) A new instrument for passive remote sensing - 1. Measurements of sunlight-induced chlorophyll fluorescence. Rem Sen Environ 91(2):186–197

    Google Scholar 

  • Murthy MSR, Giriraj A, Dutt CBS (2003) Geoinformatics for biodiversity assessment. Biol Lett 40:75–100

    Google Scholar 

  • Murthy MSR, Pujar GS, Giriraj A (2006) Geoinformatics-based management of biodiversity from landscape to species scale—an Indian perspective. Curr Sci 91:1477–1485

    Google Scholar 

  • Mutlu M, Popescu SC, Stripling C, Spencer T (2008) Mapping surface fuel models using lidar and multispectral data fusion for fire behavior. Rem Sen Environ 112:274–285

    Article  Google Scholar 

  • Myers N, Mittermeier RA, Mittermeier CG, de Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858

    Article  Google Scholar 

  • Nagendra H, Rocchini D (2008) High resolution satellite imagery for tropical biodiversity studies: the devil is in the detail. Biodivers Conserv 17:3431–3442

    Article  Google Scholar 

  • Nagendra H, Rocchini D, Ghate R et al (2010) Assessing plant diversity in a dry tropical forest: comparing the utility of Landsat and Ikonos satellite images. Remote Sens 2:478–496

    Article  Google Scholar 

  • Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ et al (2003) Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300:1560–1563

    Article  Google Scholar 

  • Newton AC, Hill Ross A, EcheverrÃa C et al (2009) Remote sensing and the future of landscape ecology. Prog Phys Geogr 33:528–546

    Article  Google Scholar 

  • Ouma YO, Tetuko J, Tateishi R (2008) Analysis of co-occurrence and discrete wavelet transform textures for differentiation of forest and non-forest vegetation in very-high-resolution optical-sensor imagery. Int J Remote Sens 29:3417–3457

    Article  Google Scholar 

  • Penner JE, Dickinson RE, O’Neill CA (1992) Effects of aerosol from biomass burning on the global radiation budget. Science 256:1432–1434

    Article  Google Scholar 

  • Peres CA, Barlow J, Laurance WF (2006) Detecting anthropogenic disturbance in tropical forests. Trends Ecol Evol 21:227–229

    Article  Google Scholar 

  • Podest E, Saatchi S (2002) Application of multiscale texture in classifying JERS-1 radar data over tropical vegetation. Int J Remote Sens 23:1487–1506

    Article  Google Scholar 

  • Puissant A, Hirsch J, Weber C (2005) The utility of texture analysis to improve per-pixel classification for high to very high spatial resolution imagery. Int J Remote Sens 26:733–745

    Article  Google Scholar 

  • Read JM, Marcelo PM, Eduardo MV, Marcelo PM (2003) Application of merged 1-m and 4-m resolution satellite data to research and management in tropical forests. J Appl Ecol 40:592–600

    Article  Google Scholar 

  • Robinson JM (1991) Fire from space: global evaluation using infrared remote sensing. Int J Remote Sens 12:3–24

    Article  Google Scholar 

  • Rudel TK (2006) Shrinking tropical forests, human agents of change, and conservation policy. Conserv Biol 20:1604–1609

    Article  Google Scholar 

  • Saatchi SS, Houghton RA, Dos Santos Alvala RC et al (2007) Distribution of aboveground live biomass in the Amazon basin. Global Change Biol 13:816–837

    Article  Google Scholar 

  • Sabine CL, Heimann M, Artaxo P, Bakker DCE, Chen CTA, Field CB, Gruber N, Quéré Cl, Prinn RG, Richey JE, Lankao PR, Sathaye JA, Valentini R (2004) Current status and past trends of the global carbon cycle. In: Field CB, Raupach MR (eds) The global carbon cycle: integrating humans, climate and the natural world. Island Press, Washington, DC, pp 17–44

    Google Scholar 

  • Schmerbeck J, Seeland K (2007) Fire supported forest utilisation of a degraded dry forest as a means of sustainable local forest management in Tamil Nadu/South India. Land Use Policy 24:62–71

    Article  Google Scholar 

  • Sgrenzaroli M, De Grandi GF, Eva H, Achard F (2002) Tropical forest cover monitoring: estimates from the GRFM JERS-1 radar mosaics using wavelet zooming techniques and validation. Int J Remote Sens 23:1329–1355

    Article  Google Scholar 

  • Siegert F, Boehm H-D (2001) Land use change and (Il)-legal logging in central Kalimantan, Indonesia. Int Peat J 11:51–57

    Google Scholar 

  • Sims DA, Gamon JA (2002) Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Rem Sen Environ 81(2–3):337–354

    Article  Google Scholar 

  • Stibig H-J, Achard F (2003) Assessment of tropical forest cover from satellite images at different geographical scales: case studies from Southeast Asia. In: Roy PS (ed) Geoinformatics for tropical ecosystems. Bishen Singh Mahendra Pal Singh, Dehradun, India, pp 33–48

    Google Scholar 

  • Thenkabail PS, Enclona EA, Ashton MS, Legg C, De Dieu MJ (2004) Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests. Rem Sen Environ 90:23–43

    Article  Google Scholar 

  • Townsend AR, Asner GP, Cleveland CC (2008) The biogeochemical heterogeneity of tropical forests. Trends Ecol Evol 23:424–431

    Article  Google Scholar 

  • Townshend JRG, Bell V, Desch A, Havlicek C, Justice C (1995) The NASA landsat pathfinder humid tropical deforestation project. In: ASPRS conference—proceedings of land satellite information in the next decade, Vienna, pp 76–87

  • Trigg SN, Curran LM, McDonald AK (2006) Utility of landsat 7 satellite data for continued monitoring of forest cover change in protected areas in Southeast Asia. Singap J Trop Geogr 27:49–66

    Article  Google Scholar 

  • Turner DP, Ritts WD, Cohen WB, Maeirsperger TK, Gower ST, Kirschbaum AA, Running SW, Zhao M, Wofsy SC, Dunn AL, Law BE, Campbell JL, Oechel WC, Kwon HJ, Meyers TP, Small EE, Kurc SA, Gamon JA (2005) Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring. Global Change Biol 11(4):666–684

    Google Scholar 

  • Ustin SL, Roberts DA, Gamon JA, Asner GP, Green RO (2004) Using imaging spectroscopy to study ecosystem processes and properties. Bioscience 54(6):523–534

    Article  Google Scholar 

  • van Wagtendonk JW, Root RR, Key CH (2004) Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Rem Sen Environ 92:397–408

    Article  Google Scholar 

  • Varghese AO, Murthy YVNK (2006) Application of geoinformatics for conservation and management of rare and threatened plant species. Curr Sci 91:762–769

    Google Scholar 

  • Vina A, Henebry GM (2005) Spatio-temporal change analysis to identify anomalous variation in the vegetated land surface: ENSO effects in tropical South America. Geophys Res Lett 32: L21402

  • Wardle DA, Walker LR, Bardgett RD (2004) Ecosystem properties and forest decline in contrasting long-term chronosequences. Science 305:509–513

    Article  Google Scholar 

  • White MA, Thornton PE, Running SW, Nemani RR (2000) Parameterization and Sensitivity Analysis of the BIOME-BGC Terrestrial Ecosystem Model: net primary production controls. Earth Interactions 4(3):1–85

    Google Scholar 

  • Williams C, Hanan N, Neff J et al (2007) Africa and the global carbon cycle. Carbon Balance Manag 2:3

    Article  Google Scholar 

  • Yu Q, Gong P, Clinton N, Biging G, Kelly M, Schirokauer D (2006) Object-based detailed vegetation classification with airborne high spatial resolution remotesensing imagery. Photogramm Eng Remote Sens 72:799–811

    Google Scholar 

  • Zaremba MB, Gougeon FA (2006) Fusion of high-resolution satellite and lidar data for individual tree recognition. In: 2006 Canadian conference on electrical and computer engineering, pp 1112–1115

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Acknowledgments

The authors are sincerely thankful to P. S. Roy, Edward J Milton, Ben Smith, Shivam Trivedi, and George Alan Blackburn for their encouragement and beneficial discussions, and Kathryn Sund for editing the manuscript, and two anonymous reviewers for their constructive comments on the previous version of the manuscript.

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Joseph, S., Murthy, M.S.R. & Thomas, A.P. The progress on remote sensing technology in identifying tropical forest degradation: a synthesis of the present knowledge and future perspectives. Environ Earth Sci 64, 731–741 (2011). https://doi.org/10.1007/s12665-010-0893-8

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