The role of remote sensing in process-scaling studies of managed forest ecosystems

Forest Ecology and Management

Volumn 355, Issue , 2015, Pages 109-123

  Masek, Jeffrey G ^a   Hayes, Daniel J ^b,c   Joseph Hughes, M ^c   Healey, Sean P ^d   Turner, David P ^e  

^a NASA GODDARD SPACE FLIGHT CENTER   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

^c UNIVERSITY OF TENNESSEE   (United States)

^d ROCKY MOUNTAIN RESEARCH STATION   (United States)

^e OREGON STATE UNIVERSITY   (United States)

Author keywords

Forest ecology; Remote sensing; Scaling

Indexed keywords

CARBON; CLIMATE CHANGE; ECOLOGY; ECOSYSTEMS; FORESTRY; OPTICAL RADAR; SPECTROSCOPY;

ECOSYSTEM PROCESS; FOREST ECOLOGY; HYPER-SPECTRAL IMAGERIES; INTERFEROMETRIC RADARS; MANAGEMENT DECISIONS; PROCESS UNDERSTANDING; REMOTE SENSING TECHNOLOGY; SCALING;

REMOTE SENSING;

CLIMATE CHANGE; DOWNSCALING; EVAPOTRANSPIRATION; FOREST CANOPY; FOREST ECOSYSTEM; FOREST INVENTORY; FOREST RESOURCE; HYDROLOGICAL CYCLE; INTERFEROMETRY; LIDAR; MODEL VALIDATION; MULTISPECTRAL IMAGE; PARAMETERIZATION; REMOTE SENSING; UPSCALING;

EID: 84953354065     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2015.05.032     Document Type: Review

References (208)

1. Ahmed R., Siqueira P., Hensley S. A study of forest biomass estimates from lidar in the northern temperate forests of New England. Remote Sens. Environ. 2013, 130:121-135.
2. Allen R.G., Tasumi M., Trezza R. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) - model. J. Irrig. Drain. Eng. ASCE 2007, 133:380-394.
3. Anderson M.C., Hain C., Wardlow B., Pimstein A., Mecikalski J.R., Kustas W.P. Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the continental United States. J. Clim. 2010, 24:2025-2044.
4. Anderson M.C., Allen R.G., Morse A., Kustas W.P. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sens. Environ. 2012, 122:50-65.
5. Antonarakis A.S., Saatchi S.S., Chazdon R.L., Moorcroft P. Using lidar and radar measurements to constrain forest ecosystem structure and function. Ecol. Appl. 2011, 21:1120-1137.
6. Antonova, N., Copass, C., Clary, S., 2013, Landsat-Based Monitoring of Landscape Dynamics in the North Cascades National Park Service Complex: 1985-2009. Natural Resource Data Series NPS/NCCN/NRDS-2013/532. National Park Service, Fort Collins, CO.
7. Asner G.P. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens. Environ. 1998, 64:234-253.
8. Asner G.P. Hyperspectral remote sensing of canopy chemistry, physiology and diversity in tropical rainforests. Hyperspectral Remote Sensing of Tropical and Subtropical Forests 2008, 261-288. Taylor and Francis Group, Oxon, UK. M. Kalacska, G.A. Sanchez-Azofeifa (Eds.).
9. Asner G.P., Vitousek P.M. Remote analysis of biological invasion and biogeochemical change. Proc. Natl. Acad. Sci. 2005, 102:4383-4386.
10. Asner G.P., Martin R.E., Anderson C.B., Knapp D.E. Quantifying forest canopy traits: imaging spectroscopy versus field survey. Remote Sens. Environ. 2015, 158:15-27.
11. Ayres M.P., Lombardero M.J. Assessing the consequences of global change for forest disturbance from herbivores and pathogens. Sci. Total Environ. 2000, 26:263-286.
12. Azizi Z., Najafi A., Sadeghian S. Forest road detection using LiDAR data. J. Forest. Res. 2014, 25:975-980.
13. Baccini A., Goetz S.J., Walker W.S., Laporte N.T., Sun M., Sulla-Menashe D., Hackler J., Beck P.S.A., Dubayah R., Friedl M.A., Samanta S., Houghton R.A. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Change 2012, 10.1038/nclimate1354.
14. Baumann M., Ozdogan M., Wolter P.T., Krylov A., Vladimirova N., Radeloff V.C. Landsat remote sensing of forest windfall disturbance. Remote Sens. Environ. 2014, 143:171-179.
15. Bender E.A., Case T.J., Gilpin M.E. Perturbation experiments in community ecology: theory and practice. Ecology 1984, 65:1-13.
16. Bilger W., Schreiber U., Bock M. Determination of the quantum efficiency of photosystem II and of non-photochemical quenching of chlorophyll fluorescence in the field. Oecologia 1995, 102:425-432.
17. Blackard J.A., Finco M.V., Helmer E.H., Holden G.R., Hoppus M.L., Jacobs D.M., Lister A.J., Moisen G.G., Nelson M.D., Riemann R., Ruefenacht B., Salajanu D., Weyermann D.L., Winterberger K.C., Brandeis T.J., Czaplewski R.L., McRoberts R.E., Patterson P.L., Tymcio R.P. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information. Remote Sens. Environ. 2008, 112:1658-1677.
18. Bounoua L., Masek J., Tourre Y.M. Sensitivity of surface climate to land surface parameters: a case study using the simple biosphere model SiB2. J. Geophys. Res. 2006, 111:D22S09. 10.1029/2006JD007309.
19. Chambers J.Q., Fisher J.I., Zeng H., Chapman E.L., Baker D.B., Hurtt G.C. Hurrican Katrina's carbon footprint on U.S. Gulf Coast forests. Science 2007, 318:1107.
20. Chapin F.S., Woodwell G.M., Randerson J.T., Rastetter E.B., Lovett G.M., Baldocchi D.D., et al. Reconciling carbon-cycle concepts, terminology, and methods. Ecosystems 2006, 9:1041-1050.
21. Chen F., Mitchell K., Schaake J., Xue Y., Pan H., Koren V., Duan Q.Y., Ek M., Betts A. Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res. 1996, 101:2896-2916.
22. Clark M.L., Roberts D.A., Clark D.B. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales. Remote Sens. Environ. 2005, 96:375-398.
23. Cohen W.B., Spies T.A. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery. Remote Sens. Environ. 1992, 41:1-17.
24. Cohen W., Harmon M., Wallin D., Fiorella M. Two decades of carbon flux from forests of the Pacific Northwest. Bioscience 1996, 46:836-844.
25. Cook B.D., Corp L.W., Nelson R.F., Middleton E.M., Morton D.C., McCorkel J.T., Masek J.G., Ranson K.J., Ly V., Montesano P.M. NASA Goddard's Lidar, hyperspectral and thermal (G-LiHT) airborne imager. Remote Sens. 2013, 5:4045-4066. 10.3390/rs5084045.
26. Coops N.C., Waring R.H. Estimating forest productivity in the eastern Siskiyou Mountains of southwestern Oregon using a satellite driven process model, 3-PGS. Can. J. For. Res. 2001, 31:143-154.
27. Dale V.H., Joyce L.A., Mcnulty S., Neilson R.P., Ayres M.P., Flannigan M.D., Hanson P.J., Irland L.C., Lugo A.E., Peterson C.J., Simberloff D., Swanson F.J., Stocks B.J., Michael Wotton B. Climate change and forest disturbances. Bioscience 2001, 51:723.
28. de Jong B., Anaya C., Masera O., Olguín M., Paz F., Etchevers J., Martínez R.D., Guerrero G., Balbontín C. Greenhouse gas emissions between 1993 and 2002 from land-use change and forestry in Mexico. For. Ecol. Manage. 2010, 260:1689-1701.
29. Dolan K.A., Masek J.G., Huang C., Sun G. Regional forest growth measured by combining ICESat GLAS and Landsat data. J. Geophys. Res. 2009, 114(G00E05). 10.1029/2008JG000893.
30. Dolan K.A., Hurtt G.C., Chambers J.Q., Dubayah R.O., Frolking S., Masek J.G. Using ICESat's geoscience laser altimeter system (GLAS) to assess large-scale forest disturbance caused by hurricane Katrina. Remote Sens. Environ. 2011, 115:86-96.
31. d'Oliveira M.V.N., Reutebuch S.E., McGaughey R.J., Andersen H. Estimating forest biomass and identifying low-intensity logging areas using airborne scanning lidar in Antimary State Forest, Acre State, Western Brazilian Amazon. Remote Sens. Environ. 2012, 124:479-491.
32. Drolet G.G., Huemmrich K.F., Hall F.G., Middleton E.M., Black T.A., Black T., Barr A., Barr A.A., Margolis H. A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest. Remote Sens. Environ. 2005, 98:212-224. 10.1016/j.rse.2005.07.006.
33. Drusch M., Del Bello U., Carlier S., Colin O., Fernandez V., et al. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services. Remote Sens. Environ. 2012, 120:25-36.
34. Dubayah R.O., Sheldon S.L., Clark D.B., Hofton M.A., Blair J.B., Hurtt G.C., Chazdon R.L. Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica. J. Geophys. Res. 2010, 115. 10.1029/2009JG000933.
35. Eidenshink J., Schwind B., Brewer K., Zhu Z., Quayle B., Howard S. A project for monitoring trends in burn severity. Fire Ecol. 2007, 3:3-21.
36. 2 assimilation in leaves of C3 species. Planta 1980, 149:78-90.
37. Fisher J.B., Tu K.P., Baldocchi D.D. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote Sens. Environ. 2008, 112:901-919.
38. Fisher J.B., Huntzinger D.N., Schwalm C.R., Sitch S. Modeling the terrestrial biosphere. Annu. Rev. Env. Resour. 2014, 39:91-123.
39. Frolking S., Palace M.W., Clark D.B., Chambers J.Q., Shugart H.H., Hurtt G.C. Forest disturbance and recovery: a general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure. J. Geophys. Res. 2009, 114(G2):1-27.
40. Galford G.L., Melillo J.M., Kicklighter D.W., Mustard J.F., Cronin T.W., Cerri C.E.P., Cerri C.C. Historical carbon emissions and uptake from the agricultural frontier of the Brazilian Amazon. Ecol. Appl. 2010, 21:750-763.
41. Garbulsky M.F., Penuelas J., Gamon J., Inoue Y., Filella I. The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: a review and meta-analysis. Remote Sens. Environ. 2011, 115:281-297.
42. Garcia-Haro F.J., Gilabert M.A., Melia J. Monitoring fire-affected areas using Thematic Mapper data. Int. J. Remote Sens. 2001, 22(4):533-549.
43. Garren K.H. Effects of fire on vegetation of the southeastern United States. Bot. Rev. 1943, 9:617-654.
44. Gitay H., Noble I.R. What are functional types and how should we seek them?. Plant Functional Types: Their Relevance to Ecosystem Properties and Global Change 1997, 3-19. Cambridge University Press, Cambridge. T.M. Smith, H.H. Shugart, F.I. Woodward (Eds.).
45. Godron M., Forman R.T.T. Landscape modification and changing ecological characteristics. Disturbance and Ecosystems 1983, 12-28. Springer, Berlin, Heidelberg.
46. Goerner A., Reichstein M., Tomelleri E., Hanan N., Rambal S., Papale D., Dragoni D., Schmullius C. Remote sensing of ecosystem light use efficiency with MODIS-based PRI. Biogeosciences 2011, 8:189-202.
47. Goetz S.J., Bond-Lamberty B., Hicke J.A., Houghton R.A., McNulty S., O'Halloran T., Meddens A.J.H., Pfeifer E.M., Midrexler D., Kasischke E.S. Observations and assessment of forest carbon recovery following disturbance in North America. J. Geophy. Res. 2012, 117:G02022. 10.1029/2011JG001733.
48. Goodwin N.R., Coops N.C., Wulder M.A., Gillanders S., Schroeder T.A., Nelson T. Estimation of insect infestation dynamics using a temporal sequence of Landsat data. Remote Sens. Environ. 2008, 112:3680-3689.
49. Goward S.N., Masek J.G., Cohen W., Moisen G., Collatz G.J., Healey S., Houghton R.A., Huang C., Kennedy R., Law B., Powell S., Turner D., Wulder M.A. Forest disturbance and North American carbon flux. EOS Trans. Am. Geophys. Union 2008, 89:105.
50. Gower S.T., Kucharik C.J., Norman J.M. Direct and indirect estimation of leaf area index, fAPAR and net primary production of terrestrial ecosystems. Remote Sens. Environ. 1999, 70:29-51.
51. Grace J., Nichol C., Disney M., Lewis P., Quaife T., Bowyer P. Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence?. Glob. Change Biol. 2007, 13:1484-1497.
52. Guindon L., Bernier P.Y., Beaudoin A., Pouliot D., Villemaire P., Hall R.J., Latifovic R., St-Amant R. Annual mapping of large forest disturbances across Canada's forests using 250 m MODIS imagery from 2000 to 2011. Can. J. For. Res. 2014, 44:1545-1554. 10.1139/cjfr-2014-0229.
53. Gutiérrez-Vélez V.H., DeFries R. Annual multi-resolution detection of land cover conversion to oil palm in the Peruvian Amazon. Remote Sens. Environ. 2013, 129:154-167.
54. Hall R.J., Skakun R.S., Arsenault E.J., Case B.S. Modeling forest stand structure attributes using Landsat ETM+data: application to mapping of aboveground biomass and stand volume. For. Ecol. Manage. 2006, 225:378-390.
55. Hall F.G., Bergen K., Blair J.B., Dubayah R., Houghton R., Hurtt G., Kellendorfer J., Lefsky M., Ranson J., Saatchi S., Shugart H.H., Wickland D. Characterizing 3D vegetation structure from space: mission requirements. Remote Sens. Environ. 2011, 115:2753-2775.
56. Hansen M.C., Potapov P.V., Moore R., Hancher M., Turubanova S.A., Tyukavina A., Thau D., Stehman S.V., Goetz S.J., Loveland T.R., Komardeey A., Egorov A., Chini L., Justice C.O., Townshend J.R.G. High-resolution global maps of 21st-century forest cover change. Science 2013, 342:850-853.
57. Hansen M.C., Stehman S.V., Potapov P.V. Quantification of global gross forest cover loss. Proc. Nat. Academy Sci. 2010, 107:8650-8655.
58. Hargrove W.W., Hoffman F.M., Law B.E. New analysis reveals representativeness of the AmeriFlux network. Eos Trans. Am. Geophys. Union 2003, 84:529-535.
59. Hargrove W.W., Spruce J.P., Gasser G.E., Hoffman F.M. Toward a national early warning system for forest disturbances using remotely sensed canopy phenology. Photogramm. Eng. Remote Sens. 2009, 75:1150-1156.
60. Hayes D.J., Sader S.A. Change detection techniques for monitoring forest clearing and regrowth in a tropical moist forest. Photogramm. Eng. Remote Sens. 2001, 67:1067-1075.
61. Hayes D., Turner D. The need for "apples-to-apples" comparisons of carbon dioxide source and sink estimates. Eos Trans. AGU 2012, 93.
62. 2 sink weakening?. Global Biogeochem. Cycles 2011, 25:GB3018.
63. Hayes D.J., Turner D.P., Stinson G., McGuire A.D., Wei Y., West T.O., Heath L.S., de Jong B., McConkey B.G., Birdsey R.A., Kurz W.A., Jacobson A.R., Huntzinger D.N., Pan Y., Post W.M., Cook R.B. Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions, and a new approach for estimating net ecosystem exchange from inventory-based data. Glob. Change Biol. 2012, 18:1282-1299.
64. Healey S.P., Cohen W.B., Spies T.A., Moeur M., Pflugmacher D., Whitley M.G., Lefsky M. The relative impact of harvest and fire upon landscape-level dynamics of older forests: lessons from the Northwest Forest Plan. Ecosystems 2008, 11:1106. 10.1007/s10021-008-9182-8.
65. Healey S.P., Patterson P.L., Saatchi S.S., Lefsky M.A., Lister A.J., Freeman E.A. A sample design for globally consistent biomass estimation using lidar data from the geoscience laser altimeter system (GLAS). Carbon Balance Manage. 2012, 7. 10.1186/1750-0680-7-10.
66. Healey S.P., Urbanski S.P., Patterson P.L., Garrard C. A framework for simulating map error in ecosystem models. Remote Sens. Environ. 2014, 150:207-217.
67. Heath L.S., Smith J.E., Skog K.E., Nowak D.J., Woodall C.W. Managed forest carbon estimates for the US greenhouse gas inventory, 1990-2008. J. Forest. 2011, 109:167-173.
68. Heinsch F.A., Zhao M., Running S., Kimball J.S., Nemani R., Davis K., Bolstad P., Cook B., Desai A., Ricciuto D., Law B.E., Oechel W., Kwon H., Luo H., Wofsy S., Dunn A., Munger J.W., Baldocchi D., Xu L., Hollinger D., Richardson A.D., Stoy P., Siqueira M., Monson R., Burns S., Flanagan L.B. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Trans. Geosci. Remote Sens. 2006, 44:1908-1925.
69. Helmer E.H., Lefsky M.A., Roberts D.A. Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the geoscience laser altimeter system. J. Appl. Remote Sens. 2009, 3:033505.
70. Hicke J.A., Allen C.D., Desai A.R., Dietze M.C., Hall R.J., Ted Hogg E.H., Kashian D.M., Moore D., Raffa K.F., Sturrock R.N., Vogelmann J. Effects of biotic disturbances on forest carbon cycling in the United States and Canada. Glob. Change Biol. 2012, 18:7-34.
71. Hilker T., Wulder M.A., Coops N.C., Linke J., McDermid G., Masek J., Gao F., White J.C. A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS. Remote Sens. Environ. 2009, 113:1613-1627.
72. Hilker T., Coops N.C., Hall F.G., Nichol C.J., Lyapustin A., Black T.A., Wulder M.A., Leuning R., Barr A., Hollinger D.Y., Munger J.W., Tucker C.J. Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space. J. Geophys. Res. 2011, 116:G03014.
73. Holmgren P., Thuresson T. Satellite remote sensing for forestry planning - a review. Scand. J. For. Res. 1998, 13:90-110.
74. Houghton R.A. Why are estimates of the terrestrial carbon balance so different?. Glob. Change Biol. 2003, 9:500-509.
75. Houghton R.A., Hobbie J.E., Melillo J.M., Moore B., Peterson B.J., Shaver G.R., Woodwell G.M. Changes in the carbon content of terrestrial biota and soils between 1860 and 1980: a net release of CO"2 to the atmosphere. Ecol. Monogr. 1983, 53:235-262.
76. Huang C.Q., Goward S.N., Masek J.G., Thomas N., Zhu Z.L., Vogelmann J.E. An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sens. Environ. 2010, 114:183-198.
77. Hudiburg T., Law B., Turner D.P., Campbell J., Donato D., Duane M. Carbon dynamics of Oregon and Northern California forests and potential land-based carbon storage. Ecol. Appl. 2009, 19:163-180.
78. Hughes, M.J., 2014, New Remote Sensing Methods for Detecting and Quantifying Forest Disturbance and Regeneration in the Eastern United States. PhD Diss. University of Tennessee.
79. Huntzinger D.N., Post W., Wei Y., Michalak A., West T., Jacobson A., Baker I., Chen J., Davis K., Hayes D., Hoffman F., Jain A., Liu S., McGuire A., Neilson R., Potter C., Poulter B., Price D., Raczka B., Tian H., Thornton P., Tomelleri E., Viovy N., Xiao J., Yuan W., Zeng N., Zhao M., Cook R. North American carbon program (NACP) regional interim synthesis: terrestrial biospheric model intercomparison. Ecol. Model. 2012, 232:144-157.
80. Huntzinger D.N., Schwalm C., Michalak A.M., Schaefer K., King A.W., Wei Y., Jacobson A., Liu S., Cook R.B., Post W.M., Berthier G., Hayes D., Huang M., Ito A., Lei H., Lu C., Mao J., Peng C.H., Peng S., Poulter B., Riccuito D., Shi X., Tian H., Wang W., Zeng N., Zhao F., Zhu Q. The North American carbon program multi-scale synthesis and terrestrial model intercomparison project - Part 1: overview and experimental design. Geosci. Model Dev. Discuss. 2013, 6:3977-4008.
81. Hurtt G.C., Dubayah R., Drake J., Moorcroft P.R., Pacala S.W., Blair J.B., Fearon M.G. Beyond potential vegetation: combining lidar data and a height-structured model for carbon studies. Ecol. Appl. 2004, 14:873-883.
82. Imhoff M. Radar backscatter and biomass saturation: ramifications for global biomass inventory. IEEE Trans. Geosci. Remote Sens. 1995, 33:511-518.
83. 2 and climate change. Global Biogeochem. Cycles 2005, 19:GB2015.
84. Jensen J.R. Remote Sensing of the Environment: An Earth Resource Perspective 2/e 2009, Pearson Education India.
85. Joiner J., Yoshida Y., Vasilkov A.P., Yoshida Y., Corp L.A., Middleton E.M. First observations of global and seasonal terrestrial chlorophyll fluorescence from space. Biogeosciences 2011, 8:637-651. 10.5194/bg-8-637-2011.
86. Jung M., Henkel K., Herold M., Churkina G. Exploiting synergies of global land cover products for carbon cycle modeling. Remote Sens. Environ. 2006, 101:534-553.
87. Jung M., Reichstein M., Margolis H.A., Cescatti A., Richardson A.D., Arain M.A., Arneth A., Bernhofer C., Bonal D., Chen J., Gianelle D., Gobron N., Kiely G., Kutsch W., Lasslop G., Law B.E., Lindroth A., Merbold L., Montagnani L., Moors E.J., Papale D., Sottocornola M., Vaccari F., Williams C. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. 2011, 116:G00J07.
88. Justice C.O., Townshend J.R.G., Holben B.N., Tucker C.J. Analysis of the phenology of global vegetation using meterological satellite data. Int. J. Remote Sens. 1985, 6:1271-1318.
89. Justice C.O., Townshend J.R.G., Vermote E.F., Masuoka E., Wolfe R.E., Saleous N., Roy D.P., Morisette J.T. An overview of MODIS land data processing and product status. Remote Sens. Environ. 2002, 83:3-15.
90. Kasischke E.S., Amiro B.D., Barger N.N., French N.H.F., Goetz S.J., Grosse G., Harmon M.A., Hicke J.A., Liu S., Masek J.G. Impacts of disturbance on the terrestrial carbon budget of North America. J. Geophys. Res. Biogeosci. 2013, 118:303-316.
91. Keeley J.E. Fire intensity, fire severity and burn severity: a brief review and suggested usage. Int. J. Wildland Fire 2009, 18:116-126.
92. Kellndorfer J.M., Walker W.S., Pierce L.E., Dobson M.C., Fites J., Hunsaker C. Vegetation height derivation from shuttle radar topography mission and national elevation data sets. Remote Sens. Environ. 2004, 93:339-358.
93. Kennedy R.E., Cohen W.B., Schroeder T.A. Trajectory-based change detection for automated characterization of forest disturbance dynamics. Remote Sens. Environ. 2007, 110:370-386.
94. Kimball J.S., Keyser A.R., Running S.W., Saatchi S.S. Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps. Tree Physiol. 2000, 20:761-775.
95. King D.A., Turner D.P., Ritts W.D. Parameterization of a diagnostic carbon cycle model for continental scale application. Remote Sens. Environ. 2011, 115:1653-1664.
96. Knyazikhin Y., et al. Hyperspectral remote sensing of foliar nitrogen content. Proc. Natl. Acad. Sci. 2013, 110:E185-E192.
97. Kokaly R.F., Asner G.P., Ollinger S.V., Martin M.E., Wessman C.A. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sens. Environ. 2009, 113. 10.1016/j.rse.2008.10.018.
98. Koster R.D., Suarez M.J. Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res. 1992, 97:2697-2715.
99. Krieger D.J. The Economic Value of Forest Ecosystem Services: A Review 2001, Wilderness Society, Washington, DC, USA.
100. Kurz W.A., Dymond C.C., White T.M., Stinson G., Shaw C.H., Rampley G.J., Smyth C., Simpson B.N., Neilson E.T., Trofymow J.A., Metsaranta J., Apps M.J. CBM-CFS3: a model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol. Model. 2009, 220:480-504.
101. Landsberg J.J., Waring R.H. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. For. Ecol. Manage. 1997, 95:209-228.
102. le Maire G., Dupuy S., Nouvellon Y., Loos R.A., Hakamada R. Mapping short-rotation plantations at regional scale using MODIS time series: case of eucalypt plantations in Brazil. Remote Sens. Environ. 2014, 152:136-149.
103. Lim K.P., Treitz P., Wulder M.A., St-Onge B.A., Flood M. LiDAR remote sensing of forest structure. Prog. Phys. Geogr. 2003, 27:88-106.
104. Liu S.G., Bond-Lamberty B., Hicke J.A., Vargas R., Zhao S.Q., Chen J., Edburg S.L., Hu Y., Liu J., McGuire A.D., Xiao J., Keane R., Yuan W., Tang J., Luo Y., Potter C., Oeding J. Simulating the impacts of disturbances on forest carbon cycling in North America: processes, data, models, and challenges. J. Geophys. Res. Biogeosci. 2011, 116. 10.1029/2010JG001585.
105. Loew A., van Bodegom P.M., Widlowski J.-L., Otto J., Quaife T., Pinty B., Raddatz T. Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts. Biogeosciences 2014, 11:1873-1897. 10.5194/bg-11-1873-2014.
106. Loveland T.R., Reed B.C., Brown J.F., Ohlen D.O., Zhu Z., Yang L., Merchant J.W. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int. J. Remote Sens. 2000, 21:1303-1365.
107. Lu D. The potential and challenge of remote sensing-based biomass estimation. Int. J. Remote Sens. 2006, 27:1297-1328.
108. Luo Y., Ogle K., Tucker C., Fei S., Gao C., LaDeau S., Clark J.S., Schimel D.S. Ecological forecasting and data assimilation in a data-rich era. Ecol. Appl. 2011, 21:1429-1442.
109. Luo Y.Q., Randerson J.T., Abramowitz G., Bacour C., Blyth E., Carvalhais N., Ciais P., Dalmonech D., Fisher J.B., Fisher R., Friedlingstein P., Hibbard K., Hoffman F., Huntzinger D., Jones C.D., Koven C., Lawrence D., Li D.J., Mahecha M., Niu S.L., Norby R., Piao S.L., Qi X., Peylin P., Prentice I.C., Riley W., Reichstein M., Schwalm C., Wang Y.P., Xia J.Y., Zaehle S., Zhou X.H. A framework for benchmarking land models. Biogeosciences 2012, 9:3857-3874.
110. Mao J., Shi X., Thornton P.E., Piao S., Wang X. Causes of spring vegetation growth trends in the northern mid-high latitudes from 1982 to 2004. Environ. Res. Lett. 2012, 7:014010.
111. Mao J., Thornton P.E., Shi X., Zhao M., Post W.M. Remote sensing evaluation of CLM4 GPP for the period 2000-09. J. Clim. 2012, 25:5327-5342.
112. Margono Belinda A., et al. Mapping and monitoring deforestation and forest degradation in Sumatra (Indonesia) using landsat time series data sets from 1990 to 2010. Environ. Res. Lett. 2012, 7. 10.1088/1748-9326/7/3/034010.
113. Marsden C., le Maire G., Stape J.-L., Seen D.L., Roupsard O., Cabral O., Epron D., Lima A.M.N., Nouvellon Y. Relating MODIS vegetation index time series with structure, light absorption, and stem production of fast-growing Eucalyptus plantations. For. Ecol. Manage. 2010, 259:1741-1753.
114. Marshall M., Tu K., Funk C., Michaelsen J., Williams P., Williams C., Ardö J., Boucher M., Cappelaere B., de Grandcourt A., Nickless A., Nouvellon Y., Scholes R., Kutsch W. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach. Hydrol. Earth Syst. Sci. 2013, 17:1079-1091.
115. Masek J.G., Collatz G.J. Estimating forest carbon fluxes in a disturbed southeastern landscape: integration of remote sensing, forest inventory, and biogeochemical modeling. J. Geophys. Res. 2006, 111(G01006). 10.1029/2005JG000062.
116. Masek J.G., Huang C., Wolfe R., Cohen W., Hall F., Kutler J., Nelson P. North American forest disturbance mapped from a decadal Landsat record. Remote Sens. Environ. 2008, 112:2914-2926.
117. Matthews E. Global vegetation and land use: new high-resolution data bases for climate studies. J. Clim. Appl. Meteorol. 1983, 22:474-487.
118. McConnel, T.J., Johnson, E.W., Burns, B., 2000. A Guide to Conducting Aerial Sketchmapping Surveys FHTET 00-01. USDA Forest Service, Fort Collins, Colorodo.
119. McRoberts R.E., Tomppo E.O. Remote sensing support for national forest inventories. Remote Sens. Environ. 2007, 110:412-419.
120. Medvigy D., Wofsy S.C., Munger J.W., Hollinger D.Y., Moorcroft P.R. Mechanistic scaling of ecosystem function and dynamics in space and time: ecosystem demography model version 2. J. Geophys. Res. Biogeosci. 2009, 114:G01002.
121. Meigs G.W., Kennedy R.E., Cohen W.B. A Landsat time series approach to characterize bark beetle and defoliator impacts on tree mortality and surface fuels in conifer forests. Remote Sens. Environ. 2011, 115:3707-3718.
122. Melillo J.M., McGuire A.D., Kicklighter D.W., Moore B., Vorosmarty C.J., Schloss A.L. Global climate change and terrestrial net primary production. Nature 1993, 363:234-240.
123. Melton J.R., Arora V.K. Sub-grid scale representation of vegetation in global land surface schemes: implications for estimation of the terrestrial carbon sink. Biogeosciences 2014, 11:1021-1036.
124. Milesi C., Hashimoto H., Running S.W., Nemani R.R. Climate variability, vegetation productivity and people at risk. Global Planet. Change 2005, 47:221-231.
125. Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-Being: Synthesis. Island Press, Washington. 155pp.
126. Minh D.H.T., Le Toan T., Rocca F., Tebaldini S., d'Alessandro M.M., Villard L. Relating P-band synthetic aperture radar tomography to tropical forest biomass. IEEE Trans. Geosci. Remote Sens. 2014, 52:967-979.
127. Mitchard E.T.A., Feldpausch T.R., Brienen R.J.W., et al. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Glob. Ecol. Biogeogr. 2014, 23:935-946.
128. Mu Q., Zhao M., Running S.W. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ. 2011, 115:1781-1800.
129. Myneni R.B., Hoffman S., Knyazikhin Y., Privette J.L., Glassy J., Tian Y., Wang Y., Song X., Zhang Y., Smith G.R., Lotsch A., Friedl M., Morisette J.T., Votava P., Nemani R.R., Running S.W. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 2002, 83:214-231.
130. Nakaji T., Ide R., Takagi K., Kosugi Y., Ohkubo S., Nasahara K.N., Saigusa N., Oguma H. Utility of spectral vegetation indices for estimation of light conversion efficiency in coniferous forests in Japan. Agric. For. Meteorol. 2008, 148:776-787.
131. Neigh C.S.R., Nelson R.F., Ranson K.J., Margolis H.A., Montesano P.M., Sun G., Kharuk V., Naesset E., Wulder M.A., Anderson H.E. Taking stock of circumboreal forest carbon with ground measurements, airborne, and spaceborne LiDAR. Remote Sens. Environ. 2013, 137:274-287.
132. Nelson R.F., Gobakken T., Naesset E., Gregoire T.G., Stahl G., Holm S., Flewelling J. Lidar sampling - using an airborne profiler to estimate forest biomass in Hedmark County, Norway. Remote Sens. Environ. 2012, 123:563-578.
133. Nemani R.R., Keeling C.D., Hashimoto H., Jolly W.M., Piper S.C., Tucker C.J., Myneni R.B., Running S.W. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 2003, 300:1560-1563.
134. Ohmann J.L., Gregory M.J. Predictive mapping of forest composition and structure with direct gradient analysis and nearest-neighbor imputation in coastal Oregon, USA. Can. J. For. Res. 2002, 32:725-741.
135. Ohmann J.L., Gregory M.J., Roberts H.M., Cohen W.B., Kennedy R.E., Yang Z.Q. Mapping change of older forest with nearest-neighbor imputation and Landsat time-series. For. Ecol. Manage. 2012, 272:13-25.
136. Ohmann J.L., Gregory M.J., Roberts H.M. Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping. Remote Sens. Environ. 2014, 151:3-15.
137. Ollinger S., Smith M.-L. Net primary production and canopy nitrogen in a temperate forest landscape: an analysis using imaging spectroscopy, modeling and field data. Ecosystems 2005, 8:760-778.
138. O'Neill R.V., Krummel J.R., Gardner R.H., Sugihara G., Jackson B., DeAngelis D.L., Milne B.T., Turner M.G., Zygmunt B., Christensen S.W., Dale V.H., Graham R.L. Indices of landscape pattern. Landscape Ecol. 1988, 1:153-162.
139. Orwig D.A., Thompson J.R., Povak N., Manner M., Niebyl D., Foster D.R. A foundation tree at the precipice: Tsuga canadensis health after the arrival of Adelges tsugae in central New England. Ecosphere 2012, 3:1-16.
140. Oumar Z., Mutanga O. The potential of remote sensing technology for the detection and mapping of Thaumastocoris peregrinus in plantation forests. South. For.: J. For. Sci. 2011, 73:23-31.
141. Palmer, W.C., 1965, Meteorological drought. In: Bureau, U.S.W. (Ed.), p. 65.
142. Pan Y., Birdsey R.A., Fang J., et al. A large and persistent carbon sink in the world's forests. Science 2011, 333:988-993.
143. Parazoo N.C., Bowman K., Fisher J.B., Frankenberg C., Jones D.B.A., Cescatti A., Perez-Priego O., Wohlfahrt G., Montagnani L. Terrestrial gross primary production inferred from satellite fluorescence and vegetation models. Glob. Change Biol. 2014, 20:3103-3121.
144. Peres C.A., Barlow J., Laurance W.F. Detecting anthropogenic disturbance in tropical forests. Trends Ecol. Evol. 2006, 21:227-229.
145. Pflugmacher D., Cohen W.B., Kennedy R.E. Using Landsat-derived disturbance history (1972-2010) to predict current forest structure. Remote Sens. Environ. 2012, 122:146-165.
146. Pickett S.T.A., White P.S. The Ecology of Natural Disturbance and Patch Dynamics 1985, Academic Press, Orlando, FL.
147. Potter C.S., Randerson J.T., Field C.B., Matson P.A., Vitousek P.M., Mooney H.A., Klooster S.A. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochem. Cycles 1993, 7:811-841.
148. Powell S.L., Cohen W.B., Healey S.P., Kennedy R.E., Moisen G.G., Pierce K.B., Ohmann J.L. Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: a comparison of empirical modeling approaches. Remote Sens. Environ. 2010, 114:1053-1068.
149. Quaife T., Lewis P., De Kauwe M., Williams M., Law B.E., Disney M., Bowyer P. Assimilating canopy reflectance data into an ecosystem model with an ensemble Kalman filter. Remote Sens. Environ. 2008, 112:1347-1364.
150. Quillet A., Peng C., Garneau M. Toward dynamic global vegetation models for simulating vegetation-climate interactions and feedbacks: recent developments, limitations, and future challenges. Environ. Rev. 2010, 18:333-353.
151. Raymond C.L., Healey S., Peduzzi A., Patterson P. Representative regional models of post-disturbance forest carbon accumulation: integrating inventory data and a growth and yield model. For. Ecol. Manage. 2015, 336:21-34.
152. Rayner P.J., Scholze M., Knorr W., Kaminski T., Giering R., Widmann H. Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS). Global Biogeochem. Cycles 2005, 19. 10.1029/2004GB002254.
153. Richardson A., Jenkins J., Braswell B., Hollinger D., Ollinger S., Smith M.-L. Use of digital webcam images to track spring green-up in a deciduous broadleaf forest. Oecologia 2007, 152:323-334.
154. Richardson A., Williams M., Hollinger D., Moore D.P., Dail D.B., Davidson E., Scott N., Evans R., Hughes H., Lee J., Rodrigues C., Savage K. Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. Oecologia 2010, 164:25-40.
155. Roberts D.A., Gardner M., Church R., Ustin S., Scheer G., Green R.O. Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sens. Environ. 1998, 65:267-279.
156. Rosette J., Cook B., Nelson R., Huang C., Masek J., Tucker C., Sun G., Huang W., Montesano P., Rubio-Gil J., Ranson J. Sensor compatibility for biomass change estimation using remote sensing data sets: part of NASA's carbon monitoring system initiative. IEEE Geosci. Remote Sens. Lett. 2015, 12:1511-1517.
157. Running S.W., Baldocchi D.D., Turner D.P., Gower S.T., Bakwin P.S., Hibbard K.A. A global terrestrial monitoring network integrating tower fluxes, flask sampling, ecosystem modeling and EOS satellite data. Remote Sens. Environ. 1999, 70:108-128.
158. Running S.W., Nemani R.R., Heinsch F.A., Zhao M., Reeves M., Hashimoto H. A continuous satellite-derived measure of global terrestrial primary production. Bioscience 2004, 54:547-560.
159. Ryan C.M., Hill T., Woollen E., Ghee C., Mitchard E., Cassells G., et al. Quantifying small-scale deforestation and forest degradation in African woodlands using radar imagery. Glob. Change Biol. 2012, 18:243-257.
160. Saatchi S.S., Harris N.L., Brown S., Lefsky M., Mitchard E.T.A., Salas W., Zutta B.R., Buermann W., Lewis S.L., Hagen S., Petrova S., White L., Silman M., Morel A. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl. Acad. Sci. 2011, 108:9899-9904.
161. Santos C., Messina J.P. The integration of ground-based digital video and synthetic aperture radar for spatio-temporal modeling of African palm in the Ecuadorian, Amazon. Photogramm. Eng. Remote Sens. 2008, 74:711-723.
162. Schaefer K., Schwalm C.R., Williams C., Arain M.A., Barr A., Chen J.M., Davis K.J., Dimitrov D., Hilton T.W., Hollinger D.Y., Humphreys E., Poulter B., Raczka B.M., Richardson A.D., Sahoo A., Thornton P., Vargas R., Verbeeck H., Anderson R., Baker I., Black T.A., Bolstad P., Chen J., Curtis P.S., Desai A.R., Dietze M., Dragoni D., Gough C., Grant R.F., Gu L., Jain A., Kucharik C., Law B., Liu S., Lokipitiya E., Margolis H.A., Matamala R., McCaughey J.H., Monson R., Munger J.W., Oechel W., Peng C., Price D.T., Ricciuto D., Riley W.J., Roulet N., Tian H., Tonitto C., Torn M., Weng E., Zhou X. A model-data comparison of gross primary productivity: results from the North American carbon program site synthesis. J. Geophys. Res.: Biogeosci. 2012, 117:G03010.
163. Scheffer M., Westley F., Brock W.A., Holmgren M. Dynamic interaction of Societies and ecosystems - linking theories from ecology, economy, and sociology. Panarchy 2002, Island Press, Washington DC. L.H. Gunderson, C.S. Holling (Eds.).
164. 2 on the terrestrial carbon cycle. Proc. Natl. Acad. Sci. 2015, 10.1073/pnas.1407302112.
165. Schroeder T.A., Wulder M.A., Healey S.P., Moisen G.G. Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data. Remote Sens. Environ. 2011, 115:1421-1433.
166. Sonnentag O., Hufkens K., Teshera-Sterne C., Young A.M., Friedl M., Braswell B.H., Milliman T., O'Keefe J., Richardson A.D. Digital repeat photography for phenological research in forest ecosystems. Agric. For. Meteorol. 2012, 152:159-177.
167. Sousa W.P. The role of disturbance in natural communities. Annu. Rev. Ecol. Syst. 1984, 15:535-591.
168. Ståhl G., Holm S., Gregoire T.G., Gobakken T., Naesset E., Nelson R. Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, Norway. Can. J. For. Resour. 2010, 41:96-107.
169. Su Z. The surface energy balance system (SEBS) for estimation of turbulent heat fluxes. Hydrol. Earth Syst. Sci. 2002, 6.
170. Thenkabail P.S., Stucky N., Griscom B.W., Ashton M.S., Diels J., Van Der Meer B., Enclona E. Biomass estimations and carbon stock calculations in the oil palm plantations of African derived savannas using IKONOS data. Int. J. Remote Sens. 2004, 25(23):5447-5472.
171. Thomas R.Q., Hurtt G.C., Dubayah R., Schilz M.H. Using lidar data and a height-structured ecosystem model to estimate forest carbon stocks and fluxes over mountainuous terrain. Can. J. Remote Sens. 2008, 34:S351-S363.
172. Thomas N.E., Huang C., Goward S.N., Powell S., Rishmawi K., Schleeweis K., Hinds A. Validation of North American forest dynamics derived from Landsat time series stacks. Remote Sens. Environ. 2011, 115:19-32.
173. Thornton P.E., Law B.E., Gholz H.L., Clark K.L., Falge E., Ellsworth D.S., Goldstein A.H., Monson R.K., Hollinger D., Falk M., Chen J., Sparks J.P. Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agric. For. Meteorol. 2002, 113:185-222.
174. Thornton P.E., Doney S.C., Lindsay K., Moore J.K., Mahowald N., Randerson J.T., Fung I., Lamarque J.F., Feddema J.J., Lee Y.H. Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: results from an atmosphere-ocean general circulation model. Biogeosciences 2009, 6:2099-2120.
175. Tomppo, E., 1991, Satellite image-based National Forest Inventory of Finland. In: Proceedings of the Symposium on Global and Environmental Monitoring, Techniques and Impacts, Victoria, British Columbia, Canada, 17-21, September 1990. International Archives of Photogrammetry and Remote Sensing, vol. 28, pp. 419-424.
176. Townsend P.A., Singh A., Foster J.R., Rehberg N.J., Kingdon C.C., Eshleman K.N., Seagle S.W. A general Landsat model to predict canopy defoliation in broadleaf deciduous forests. Remote Sens. Environ. 2012, 119:255-265.
177. Treuhaft R.N., Law B.E., Asner G.P. Forest attributes from radar interferometric structure and its fusion with optical remote sensing. Bioscience 2004, 54:561-571.
178. Treuhaft R.N., Goncalves F., dos Santos J.R., Keller M., Palace M., Madsen S.N., Sullivan F., Graca P.M.L.A. Tropical-forest biomass estimation at X-band from the spaceborne TanDEM-X interferometer. IEEE Geosci. Remote Sens. Lett. 2015, 12:239-243.
179. Tucker C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8:127-150.
180. Tucker C.J., Townshend J.R.G., Goff T.E. African land-cover classification using satellite data. Science 1985, 227:369-375.
181. Turner D.P., Ollinger S.V., Kimball J.S. Integrating remote sensing and ecosystem process models for landscape- to regional-scale analysis of the carbon cycle. Bioscience 2004, 54:573-584.
182. Turner D.P., Ritts W.D., Cohen W.B., Gower S.T., Running S.W., Zhao M., Costa M.H., Kirschbaum A.A., Ham J.M., Saleska S.R., Ahl D.E. Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sens. Environ. 2006, 102:282-292.
183. Turner D.P., Ritts W.D., Styles J.M., Yang Z., Cohen W.B., Law B.E., Thornton P.E. A diagnostic carbon flux model to monitor the effects of disturbance and interannual variation in climate on regional NEP. Tellus B 2006, 58:476-490.
184. Turner D.P., Ritts W.D., Yang Z., Kennedy R.E., Cohen W.B., Duane M.V., Thornton P.E., Law B.E. Decadal trends in net ecosystem production and net ecosystem carbon balance for a regional socioecological system. For. Ecol. Manage. 2011, 262:1318-1325.
185. Turner D.P., Jacobson A.R., Ritts W.D., Wang W.L., Nemani R. A large proportion of North American net ecosystem production is offset by emissions from harvested products, river/stream evasion, and biomass burning. Glob. Change Biol. 2013, 19:3516-3528.
186. Ustin S.L., Gitelson A.A., Jacquemoud S., Schaepman M., Asner G.P., Gamon J.A., Zarco-Tejada P. Retrieval of foliar information about plant pigment systems from high resolution spectroscopy. Remote Sens. Environ. 2009, 113:S67-S77.
187. van der Tol C., Berry J.A., Campbell P.K.E., Rascher U. Models of fluorescence and photosynthesis for interpreting measurements of solar-induced chlorophyll fluorescence: open access. J. Geophys. Res. Biogeosci. 2015, 119. 10.1002/2014JG002713.
188. van der Werf G.R., Randerson J.T., Collatz G.J., Giglio L., Kasibhatla P.S., Arellano A.F., Olsen S.C., Kasischke E.S. Continental-scale partitioning of fire emissions during the 1997 to 2001 El Niño/La Niña period. Science 2004, 303:73-76.
189. van der Werf G.R., Morton D.C., DeFries R.S., Giglio L., Randerson J.T., Collatz G.J., Kasibhatla P.S. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling. Biogeosciences 2009, 6. 10.1016/j.atmosenv.2008.09.047.
190. van Wagtendonk J.W., Root R.R., Key C.H. Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sens. Environ. 2004, 92:397-408.
191. Vinukollu R.K., Wood E.F., Ferguson C.R., Fisher J.B. Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: evaluation of three process-based approaches. Remote Sens. Environ. 2011, 115:801-823.
192. Vogelmann J.E., Tolk B., Zhu Z. Monitoring forest changes in the southwestern United States using multitemporal Landsat data. Remote Sens. Environ. 2009, 113:1739-1748.
193. Waring R.H., Law B.E., Goulden M.L., Bassow S.L., McCreight R.W., Wofsy S.C., Bazzaz F.A. Scaling daytime gross ecosystem production at Harvard Forest with remote sensing: a comparison of estimates from a constrained quantum-use efficiency model and eddy correlation. Plant, Cell Environ. 1995, 18:1201-1213.
194. Watts A.C., Ambrosia V.G., Hinkley A.E. Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens. 2012, 4:1671-1692.
195. White J.D., Ryan K.C., Key C.C., Running S.W. Remote sensing of forest fire severity and vegetation recovery. Int. J. Wildland Fire 1996, 6:125-136.
196. Williams C.A., Collatz G.J., Masek J.G., Goward S. Carbon consequences of forest disturbance and recovery across the conterminous United States. Global Biogeochem. Cycles 2012, 26. 10.1029/2010GB003947.
197. Williams C.A., Collatz G.J., Masek J., Huang C., Goward S.N. Impacts of disturbance history on forest carbon stocks and fluxes: merging satellite disturbance mapping with forest inventory data in a carbon cycle model framework. Remote Sens. Environ. 2014, 151:57-71.
198. Wilson E.H., Sader S.A. Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens. Environ. 2002, 80:385-396.
199. Wimberly M.C., Reilly M.J. Assessment of fire severity and species diversity in the southern Appalachians using Landsat TM and ETM+ imagery. Remote Sens. Environ. 2007, 108:189-197.
200. Wulder M.A., White J.C., Nelson R.F., Naesset E., Ørka H.O., Coops N.C., Hilker T., Bater C.W., Gobakken T. Lidar sampling for large-area forest characterization: a review. Remote Sens. Environ. 2012, 121:196-209.
201. Wullschleger S.D., Epstein H.E., Box E.O., Euskirchen E.S., Goswami S., Iversen C.M., Kattge J., Norby R.J., van Bodegom P.M., Xu X. Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems. Ann. Bot. 2014, 114:1-16.
202. Zald H.S.J., Ohmann J.L., Roberts H.M., Gregory M.J., Henderson E.B., McGaughey R.J., Braaten J. Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure. Remote Sens. Environ. 2014, 143:26-38.
203. 2 variability. Global Biogeochem. Cycles 2005, 19:GB1016.
204. Zhang K., Kimball J.S., Zhao M.S., Oechel W.C., Cassano J., Running S.W. Sensitivity of pan-Arctic terrestrial net primary productivity simulations to daily surface meteorology from NCEP-NCAR and ERA-40 reanalyses. J. Geophys. Res. Biogeosci. 2007, 112:14.
205. Zhang F., Chen J.M., Pan Y., Birdsey R.A., Shen S., Ju W., He L. Attributing carbon changes in conterminous U.S. forests to disturbance and non-disturbance factors from 1901 to 2010. J. Geophys. Res.: Biogeosci. 2012, 117(G2).
206. Zhao M.S., Running S.W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 2010, 329:940-943.
207. Zhu Z., Woodcock C.E., Olofsson P. Continuous monitoring of forest disturbance using all available landsat imagery. Remote Sens. Environ. 2012, 122:75-91.
208. Zolkos S., Goetz S.J., Dubayah R.O. A meta-analysis of terrestrial above-ground biomass estimation using lidar remote sensing. Remote Sens. Environ. 2013, 128:289-298.