Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

Remote Sensing

Volumn 6, Issue 3, 2014, Pages 2108-2133

  Wang, Junbang ^a   Dong, Jingwei ^b   Liu, Jiyuan ^a   Huang, Mei ^a   Li, Guicai ^c   Running, Steven W ^d   Kolby Smith, W ^d   Harris, Warwick ^e   Saigusa, Nobuko ^f   Kondo, Hiroaki ^g   Liu, Yunfen ^a   Hirano, Takashi ^h   Xiao, Xiangming ^b  

^a INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

^b UNIVERSITY OF OKLAHOMA   (United States)

^c NATIONAL SATELLITE METEOROLOGICAL CENTER   (China)

^d UNIVERSITY OF MONTANA   (United States)

^e LANDCARE RESEARCH   (New Zealand)

^f NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES   (Japan)

^g NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^h HOKKAIDO UNIVERSITY   (Japan)

Author keywords

GIMMS NDVI1g; GIMMS NDVI3g; GLOPEM CEVSA; Gross Primary Productivity (GPP); MOD15A2; MOD17A2; Southeast Asia

Indexed keywords

CARBON DIOXIDE; DATA PROCESSING; DEFORESTATION; ESTIMATION; RADIOMETERS; SATELLITE IMAGERY;

GIMMS NDVI1G; GIMMS NDVI3G; GLOPEM-CEVSA; GROSS PRIMARY PRODUCTIVITY; MOD15A2; MOD17A2; SOUTHEAST ASIA;

ECOSYSTEMS;

CARBON DIOXIDE; DATA PROCESSING; DEFORESTATION; ECOSYSTEMS; IMAGE ANALYSIS; PRODUCTIVITY; RADIOMETRY; SATELLITES; SOUTHEAST ASIA;

EID: 84896973495     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs6032108     Document Type: Article

References (90)

1. Xiao, X.; Hollinger, D.; Aber, J.; Goltz, M.; Davidson, E.A.; Zhang, Q.; Moore, B. Satellite-based modeling of gross primary production in an evergreen needleleaf forest. Remote Sens. Environ. 2004, 89, 519-534.
2. Gao, Q.; Li, Y.; Wan, Y.; Qin, X.; Wang, J.; Liu, Y. Dynamics of alpine grassland NPP and its response to climate change in Northern Tibet. Clim. Chang. 2009, 97, 515-528.
3. Beer, C.; Reichstein, M.; Tomelleri, E.; Ciais, P.; Jung, M.; Carvalhais, N.; Rodenbeck, C.; Arain, M.A.; Baldocchi, D.; Bonan, G.B.; et al. Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate. Science 2010, 329, 834-838.
4. Falge, E.; Baldocchi, D.; Tenhunen, J.; Aubinet, M.; Bakwin, P.; Berbigier, P.; Bernhofer, C.; Burba, G.; Clement, R.; Davis, K.J.; et al. Seasonality of ecosystem respiration and gross primary production as derived from FLUXNET measurements. Agric. For. Meteorol. 2002, 113, 53-74.
5. Luo, T.; Li, W.; Zhu, H. Estimated biomass and productivity of natural vegetation on the Tibetan Plateau. Ecol. Appl. 2002, 12, 980-997.
6. Piao, S.; Fang, J.; He, J. Variations in vegetation net primary production in the Qinghai-Xizang Plateau, China, from 1982 to 1999. Clim. Chang. 2006, 74, 253-267.
7. Baldocchi, D.D. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: Past, present and future. Glob. Chang. Biol. 2003, 9, 479-492.
8. Running, S.W.; Baldocchi, D.; Turner, D.; Gower, S.; Bakwin, P.; Hibbard, K. A global terrestrial monitoring network integrating tower fluxes, flask sampling, ecosystem modeling and EOS satellite data. Remote Sens. Environ. 1999, 70, 108-127.
9. Wang, J.; Liu, J.; Cao, M.; Liu, Y.; Yu, G.; Li, G.; Qi, S.; Li, K. Modelling carbon fluxes of different forests by coupling a remote-sensing model with an ecosystem process model. Int. J. Remote Sens. 2011, 32, 6539-6567.
10. Cao, M.; Yu, G.; Liu, J.; Li, K. Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle. Sci. China Ser. D 2005, 48, 17-32.
11. Liu, J.; Chen, J.; Cihlar, J.; Park, W. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 1997, 62, 158-175.
12. Churkina, G.; Tenhunen, J.; Thornton, P.; Falge, E.M.; Elbers, J.A.; Erhard, M.; Grunwald, T.; Kowalski, A.S.; Rannik, U.; Sprinz, D. Analyzing the ecosystem carbon dynamics of four European coniferous forests using a biogeochemistry model. Ecosystems 2003, 6, 168-184.
13. Law, B.E.; Waring, R.H.; Anthoni, P.M.; Aber, J.D. Measurements of gross and net ecosystem productivity and water vapour exchange of a Pinus ponderosa ecosystem, and an evaluation of two generalized models. Glob. Chang. Biol. 2000, 6, 155-168.
14. Churkina, G.; Running, S.W. Contrasting climatic controls on the estimated productivity of global terrestrial biomes. Ecosystems 1998, 1, 206-215.
15. Turner, D.P.; Urbanski, S.; Bremer, D.; Wofsy, S.C.; Meyers, T.; Gower, S.T.; Gregory, M. A cross-biome comparison of daily light use efficiency for gross primary production. Glob. Chang. Biol. 2003, 9, 383-395.
16. Turner, D.P.; Ritts, W.D.; Cohen, W.B.; Gower, S.T.; Zhao, M.; Running, S.W.; Wofsy, S.C.; Urbanski, S.; Dunn, A.L.; Munger, J.W. Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation. Remote Sens. Environ. 2003, 88, 256-270.
17. Xiao, X.; Zhang, Q.; Braswell, B.; Urbanski, S.; Boles, S.; Wofsy, S.; Moore, B., III; Ojima, D. Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data. Remote Sens. Environ. 2004, 91, 256-270.
18. Xiao, X.M.; Zhang, Q.Y.; Hollinger, D.; Aber, J.; Moore, B. Modeling gross primary production of an evergreen needleleaf forest using modis and climate data. Ecol. Appl. 2005, 15, 954-969.
19. Behrenfeld, M.J.; Randerson, J.T.; McClain, C.R.; Feldman, G.C.; Los, S.O.; Tucker, C.J.; Falkowski, P.G.; Field, C.B.; Frouin, R.; Esaias, W.E. Biospheric primary production during an ENSO transition. Science 2001, 291, 2594-2597.
20. Field, C.B.; Randerson, J.T.; Malmstrom, C.M. Global net primary production: Combining ecology and remote sensing. Remote Sens. Environ. 1995, 51, 74-88.
21. 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. Glob. Biogeochem. Cycle 1993, 7, 811-841.
22. Prince, S.D.; Goward, S.N. Global primary production: A remote sensing approach. J. Biogeog. 1995, 2, 815-835.
23. Ruimy, A.; Saugier, B.; Dedieu, G. Methodology for the estimation of terrestrial net primary production from remotely sensed data. J. Geophys. Res.-Atmos. 1994, 99, 5263-5283.
24. Alton, P.; Bodin, P. A comparative study of a multilayer and a productivity (light-use) efficiency land-surface model over different temporal scales. Agric. For. Meteorol. 2010, 150, 182-195.
25. Zhao, M.S.; Heinsch, F.A.; Nemani, R.R.; Running, S.W. Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens. Environ. 2005, 95, 164-176.
26. Yuan, W.; Liu, S.; Zhou, G.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, A.H.; Goulden, M.L.; et al. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes. Agr. For. Meteorol. 2007, 143, 189-207.
27. Wu, C.; Munger, J.W.; Niu, Z.; Kuang, D. Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. Remote Sens. Environ. 2010, 114, 2925-2939.
28. Ryu, Y.; Baldocchi, D.D.; Kobayashi, H.; Ingen, C.; Li, J.; Black, T.A.; Beringer, J.; Gorsel, E.; Knohl, A.; Law, B.E. Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales. Glob. Biogeochem. Cycle 2011, 25, doi:10.1029/2011GB004053.
29. Wu, C.; Chen, J.M.; Desai, A.R.; Hollinger, D.Y.; Arain, M.A.; Margolis, H.A.; Gough, C.M.; Staebler, R.M. Remote sensing of canopy light use efficiency in temperate and boreal forests of North America using MODIS imagery. Remote Sens. Environ. 2012, 118, 60-72.
30. Cramer, W.; Kicklighter, D.; Bondeau, A.; Iii, B.M.; Churkina, G.; Nemry, B.; Ruimy, A.; Schloss, A. Comparing global models of terrestrial net primary productivity (NPP): Overview and key results. Glob. Chang. Biol. 1999, 5, 1-15.
31. Zhao, G.; Wang, J.; Fan, W.; Ying, T. Vegetation net primary productivity in Northeast China in 2000-2008: Simulation and seasonal change. Chin. J. Appl. Ecol. 2011, 22, 621-630.
32. Wang, J.; Liu, J.; Shao, Q.; Liu, R.; Fan, J.; Chen, Z. Spatial-temporal patterns of net primary productivity for 1988-2004 based on GLOPEM-CEVSA model in the ?Three-river Headwaters? region of Qinghai province, China. Chin. J. Plant Ecol. 2009, 33, 254-269.
33. Tucker, C.J.; Pinzon, J.E.; Brown, M.E.; Slayback, D.A.; Pak, E.W.; Mahoney, R.; Vermote, E.F.; El Saleous, N. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int. J. Remote Sens. 2005, 26, 4485-4498.
34. Sellers, P.J. Canopy reflectance, photosynthesis and transpiration. Int. J. Remote Sens. 1985, 6, 1335-1372.
35. Sellers, P.J.; Tucker, C.J.; Collatz, G.J.; Los, S.O.; Justice, C.O.; Dazlich, D.A.; Randall, D.A. A revised land surface parameterization (SiB2) for atmospheric GCMS. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data. J. Clim. 1996, 9, 706-737.
36. Myneni, R.B. ?Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011)?. Available online: http://www.mdpi.com/journal/remotesensing/special_issues/ monitoring_global (accessed on 20 March 2013).
37. Zeng, F.-W.; Collatz, G.J.; Pinzon, J.E.; Ivanoff, A. Evaluating and quantifying the climate-driven interannual variability in global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) at global scales. Remote Sens. 2013, 5, 3918-3950.
38. Monteith, J.; Moss, C. Climate and the efficiency of crop production in Britain [and discussion]. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 1977, 281, 277-294.
39. Monteith, J. Solar radiation and productivity in tropical ecosystems. J. Appl. Ecol. 1972, 747-766.
40. Goetz, S.J.; Prince, S.D. Modelling terrestrial carbon exchange and storage: Evidence and implications of functional convergence in light-use efficiency. Adv. Ecol. Res. 1999, 28, 57-92.
41. Goetz, S.J.; Prince, S.D.; Small, J.; Gleason, A.C.R. Interannual variability of global terrestrial primary production: Results of a model driven with satellite observations. J. Geophys. Res. 2000, 105, 20077-20091.
42. Goetz, S.J.; Prince, S.D.; Goward, S.N.; Thawley, M.M.; Small, J. Satellite remote sensing of primary production: An improved production efficiency modeling approach. Ecol. Model. 1999, 122, 239-255.
43. Cao, M.K.; Prince, S.D.; Small, J.; Goetz, S.J. Remotely sensed interannual variations and trends in terestrial net primary productivity 1981-2000. Ecosystems 2004, 7, 233-242.
44. Cao, M.; Woodward, F.I. Dynamic responses of terrestrial ecosystem carbon cycling to global climate change. Nature 1998, 393, 249-252.
45. Cao, M.; Woodward, F.I. Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their response to climate change. Glob. Chang. Biol. 1998, 4, 185-198.
46. 2. Tellus B 2005, 57, 210-217.
47. Collatz, G.; Ball, J.; Grivet, C.; Berry, J. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: A model that includes a laminar boundary layer. Agric. For. Meteorol. 1991, 54, 107-136.
48. Raich, J.W.; Rastetter, E.B.; Melillo, J.M.; Kicklighter, D.W.; Steudler, P.A.; Peterson, B.J.; Grace, A.L.; Moore, B.; Vorosmarty, C.J. Potential net primary productivity in South America: Application of a global model. Ecol. Appl. 1991, 1, 399-429.
49. Zhao, M.; Running, S.W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 2010, 329, 940-943.
50. Zhao, M.; Running, S.W.; Nemani, R.R. Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses. J. Geophys. Res. Biogeosci. 2006, 111, doi:10.1029/2004JG000004.
51. Kanamitsu, M.; Ebisuzaki, W.; Woollen, J.; Yang, S.-K.; Hnilo, J.J.; Fiorino, M.; Potter, G.L. NCEP-DOE AMIP-II Reanalysis (R-2). Bull. Am. Meteorol. Soc. 2002, 83, 1631-1643.
52. Allen, R.G.; Food and Agriculture Organization of the United Nations. Chapter 3: Meteorological Data. In Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; Food and Agriculture Organization of the United Nations: Rome, Italy, 1998; pp. 33-36.
53. Hutchinson, M. ANUSPLIN Version 4.2; Centre for Resource and Environmental Studies, Australian National University: Canberra, Australia, 2001.
54. Yatagai, A.; Kamiguchi, K.; Arakawa, O.; Hamada, A.; Yasutomi, N.; Kitoh, A. APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull. Am. Meteorol. Soc. 2012, 93, 1401-1415.
55. Los, S.O. Linkages between Global Vegetation and Climate: An Analysis Based on NOAA Advanced very High Resolution Radiometer Data; 016049527X; National Aeronautics and Space Administration, Goodard Space Flight Center: Greenbelt, MD, USA, 1998.
56. Matlab, R.V. R2011b; The Mathworks Inc.: Natick, MA, USA.
57. Myneni, R.; Hoffman, S.; Knyazikhin, Y.; Privette, J.; Glassy, J.; Tian, Y.; Wang, Y.; Song, X.; Zhang, Y.; Smith, G. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 2002, 83, 214-231.
58. Myneni, R.; Ramakrishna, R.; Nemani, R.; Running, S. Estimation of global leaf area index and absorbed PAR using radiative transfer models. IEEE Trans. Geosci. Remote Sens. 1997, 35, 1380-1393.
59. Knyazikhin, Y.; Martonchik, J.; Myneni, R.; Diner, D.; Running, S. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. J. Geophys. Res. 1998, 103, 32257-32276.
60. Privette, J.L.; Myneni, R.B.; Knyazikhin, Y.; Mukelabai, M.; Roberts, G.; Tian, Y.; Wang, Y.; Leblanc, S.G. Early spatial and temporal validation of MODIS LAI product in the Southern Africa Kalahari. Remote Sens. Environ. 2002, 83, 232-243.
61. Tian, Y.; Wang, Y.; Zhang, Y.; Knyazikhin, Y.; Bogaert, J.; Myneni, R. Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions. Remote Sens. Environ. 2003, 84, 143-159.
62. Jönsson, P.; Eklundh, L. TIMESAT-A program for analyzing time-series of satellite sensor data. Comput. Geosci. 2004, 30, 833-845.
63. Eklundha, L.; Jönssonb, P. TIMESAT 3.1 Software Manual; Lund University: Lund, Sweden, 2012.
64. Friedl, M.A.; McIver, D.K.; Hodges, J.C.; Zhang, X.; Muchoney, D.; Strahler, A.H.; Woodcock, C.E.; Gopal, S.; Schneider, A.; Cooper, A. Global land cover mapping from MODIS: Algorithms and early results. Remote Sens. Environ. 2002, 83, 287-302.
65. 2 flux and its environmental factors in evergreen coniferous plantation. Sci. China Ser. D 2005, 48, 123-132.
66. Wen, X.; Yu, G.; Sun, X.; Liu, Y. Turbulence flux measurement above the overstory of a subtropical Pinus plantation over the hilly region in Southeastern China. Sci. China Ser. D 2005, 48, 63-73.
67. Yan, J.; Liu, X.; Tang, X.; Yu, G.; Zhang, L.; Chen, Q.; Li, K. Substantial amounts of carbon are sequestered during dry periods in an old-growth subtropical forest in South China. J. For. Res. 2013, 18, 21-30.
68. Yan, J.; Zhang, Y.; Yu, G.; Zhou, G.; Zhang, L.; Li, K.; Tan, Z.; Sha, L. Seasonal and inter-annual variations in net ecosystem exchange of two old-growth forests in Southern China. Agric. For. Meteorol. 2013.
69. Zhang, Y.; Tan, Z.; Song, Q.; Yu, G.; Sun, X. Respiration controls the unexpected seasonal pattern of carbon flux in an Asian tropical rain forest. Atmos. Environ. 2010, 44, 3886-3893.
70. Hirata, R.; Saigusa, N.; Yamamoto, S.; Ohtani, Y.; Ide, R.; Asanuma, J.; Gamo, M.; Hirano, T.; Kondo, H.; Kosugi, Y. Spatial distribution of carbon balance in forest ecosystems across East Asia. Agric. For. Meteorol. 2008, 148, 761-775.
71. 2 flux in boreal, temperate, and tropical forests in East Asia. Agric. For. Meteorol. 2008, 148, 700-713.
72. 2 Fluxes at Various Forests in East Asia. In Plant Responses to Air Pollution and Global Change; Omasa, K., Nouchi, I., Kok, L., Eds.; Springer: Tokyo, Japan, 2005; pp. 215-225.
73. Hirano, T.; Segah, H.; Kusin, K.; Limin, S.; Takahashi, H.; Osaki, M. Effects of disturbances on the carbon balance of tropical peat swamp forests. Glob. Chang. Biol. 2012, 18, 3410-3422.
74. Hirano, T.; Kusin, K.; Limin, S.; Osaki, M. Carbon dioxide emissions through oxidative peat decomposition on a burnt tropical peatland. Glob. Chang. Biol. 2013, 20, 555-565.
75. Song, X.; Yu, G.; Liu, Y.; Sun, X.; Ren, C.; Wen, X. Comparison of flux measurement by open-path and close-path eddy covariance systems. Sci. China Ser. D 2005, 48, 174-184.
76. Song, X.; Liu, Y.; Xu, X.; Yu, G.; Wen, X. Comparison study on carbon dioxide, water and heat fluxes of the forest ecosystem in red earth hilly zone over winter and spring. Resour. Sci. 2004, 26, 96-104.
77. Yang, F. Influences of Land Use on Terrestrial Carbon Cycles in Red Soil Hilly Area of South China: Case Research at Qianyanzhou Experimental Station; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences: Beijing, China, 2005.
78. Li, Z.Q.; Yu, G.R.; Wen, X.F.; Zhang, L.M.; Ren, C.Y.; Fu, Y.L. Energy balance closure at ChinaFlux sites. Sci. China Ser. D 2005, 48, 151-162.
79. Yu, G.R.; Wen, X.F.; Li, Q.K.; Zhang, L.M.; Ren, C.Y.; Liu, Y.F.; Guan, D.X. Season pattern and response character to environment of sub-tropic and temperature forest ecosystem respiration in China. Sci. China Ser. D 2005, 48, 93-105.
80. Hirano, T.; Segah, H.; Harada, T.; Limin, S.; June, T.; Hirata, R.; Osaki, M. Carbon dioxide balance of a tropical peat swamp forest in Kalimantan, Indonesia. Glob. Chang. Biol. 2007, 13, 412-425.
81. Fensholt, R.; Proud, S.R. Evaluation of Earth Observation based global long term vegetation trends-Comparing GIMMS and MODIS global NDVI time series. Remote Sens. Environ. 2012, 119, 131-147.
82. Gibson, L.; Lynam, A.J.; Bradshaw, C.J.A.; He, F.; Bickford, D.P.; Woodruff, D.S.; Bumrungsri, S.; Laurance, W.F. Near-complete extinction of native small mammal fauna 25 years after forest fragmentation. Science 2013, 341, 1508-1510.
83. Chen, J.M.; Mo, G.; Pisek, J.; Liu, J.; Deng, F.; Ishizawa, M.; Chan, D. Effects of foliage clumping on the estimation of global terrestrial gross primary productivity. Glob. Biogeochem. Cycle 2012, 26, doi:10.1029/2010GB003996.
84. Zhu, Z.; Bi, J.; Pan, Y.; Ganguly, S.; Anav, A.; Xu, L.; Samanta, A.; Piao, S.; Nemani, R.; Myneni, R. Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2011. Remote Sens. 2013, 5, 927-948.
85. Turner, D.P.; Ritts, W.D.; Cohen, W.B.; Gower, S.T.; Running, S.W.; Zhao, M.S.; Costa, M.H.; Kirschbaum, A.A.; Ham, J.M.; Saleska, S.R.; et al. Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sens. Environ. 2006, 102, 282-292.
86. Serbin, S.P.; Ahl, D.E.; Gower, S.T. Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence. Remote Sens. Environ. 2013, 133, 71-84.
87. Eklundha, L.; Jönssonb, P. Timesat 3.0 Software Manual; Lund University: Lund, Sweden, 2010.
88. Hird, J.N.; McDermid, G.J. Noise reduction of NDVI time series: An empirical comparison of selected techniques. Remote Sens. Environ. 2009, 113, 248-258.
89. Schubert, P.; Lagergren, F.; Aurela, M.; Christensen, T.; Grelle, A.; Heliasz, M.; Klemedtsson, L.; Lindroth, A.; Pilegaard, K.; Vesala, T.; et al. Modeling GPP in the Nordic forest landscape with MODIS time series data-Comparison with the MODIS GPP product. Remote Sens. Environ. 2012, 126, 136-147.
90. Huete, A.R.; Restrepo-Coupe, N.; Ratana, P.; Didan, K.; Saleska, S.R.; Ichii, K.; Panuthai, S.; Gamo, M. Multiple site tower flux and remote sensing comparisons of tropical forest dynamics in Monsoon Asia. Agric. For. Meteorol. 2008, 148, 748-760.