Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Agricultural and Forest Meteorology

Volumn 201, Issue , 2015, Pages 111-119

  Xin, Qinchuan ^a   Broich, Mark ^b   Suyker, Andrew E ^c   Yu, Le ^a   Gong, Peng ^a,d  

^a TSINGHUA UNIVERSITY   (China)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Crop yield; Flux tower; National inventory; Net primary production; Remote sensing

Indexed keywords

AGRICULTURAL LAND; FLUX MEASUREMENT; IN SITU MEASUREMENT; LIGHT USE EFFICIENCY; MAIZE; MODIS; NET PRIMARY PRODUCTION; REMOTE SENSING; SOYBEAN;

MIDWEST; UNITED STATES;

EID: 84911424621     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2014.11.004     Document Type: Article

References (50)

1. Bandaru V., West T.O., Ricciuto D.M., César Izaurralde R. Estimating crop net primary production using national inventory data and MODIS-derived parameters. ISPRS J. Photogramm. Remote Sens. 2013, 80:61-71.
2. Beer C., et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 2010, 329(5993):834-838.
3. Boryan C., Yang Z., Mueller R., Craig M. Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, cropland data layer program. Geocarto Int. 2011, 26(5):341-358.
4. Bradford J., Hicke J., Lauenroth W. The relative importance of light-use efficiency modifications from environmental conditions and cultivation for estimation of large-scale net primary productivity. Remote Sens. Environ. 2005, 96(2):246-255.
5. Chen T., van der Werf G.R., Dolman A.J., Groenendijk M. Evaluation of cropland maximum light use efficiency using eddy flux measurements in North America and Europe. Geophys. Res. Lett. 2011, 38.
6. Choudhury B.J. Carbon use efficiency, and net primary productivity of terrestrial vegetation. Adv. Space Res. 2000, 26(7):1105-1108.
7. Cramer W., et al. Comparing global models of terrestrial net primary productivity (NPP): overview and key results. Global Change Biol. 1999, 5(S1):1-15.
8. Field C.B., Randerson J.T., Malmstrom C.M. Global net primary production: combining ecology and remote sensing. Remote Sens. Environ. 1995, 51(1):74-88.
9. Garbulsky M.F., et al. Patterns and controls of the variability of radiation use efficiency and primary productivity across terrestrial ecosystems. Global Ecol. Biogeogr. 2010, 19(2):253-267.
10. Gelybó G., Barcza Z., Kern A., Kljun N. Effect of spatial heterogeneity on the validation of remote sensing based GPP estimations. Agric. For. Meteorol. 2013, 174:43-53.
11. 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(3):239-255.
12. Gower S., et al. Net primary production and carbon allocation patterns of boreal forest ecosystems. Ecol. Appl. 2001, 11(5):1395-1411.
13. 2 fluxes with tunable diode laser absorption spectroscopy and micrometeorological techniques. Agric. For. Meteorol. 2004, 124(1):15-29.
14. Guanter L., et al. Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc. Natl. Acad. Sci. U. S. A. 2014, 111(14):E1327-E1333.
15. Heinsch F.A., et al. User's Guide: GPP and NPP (MOD17A2/A3) Products, NASA MODIS Land Algorithm, Version 2.0 2003, 1-57.
16. Hilker T., Coops N.C., Wulder M.A., Black T.A., Guy R.D. The use of remote sensing in light use efficiency based models of gross primary production: a review of current status and future requirements. Sci. Total Environ. 2008, 404(2):411-423.
17. Hilker T., et al. Remote sensing of photosynthetic light-use efficiency across two forested biomes: spatial scaling. Remote Sens. Environ. 2010, 114(12):2863-2874.
18. Huete A., et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 2002, 83(1-2):195-213.
19. 2 flux tower data. Agric. For. Meteorol. 2011, 151(12):1514-1528.
20. Lindquist J.L., Arkebauer T.J., Walters D.T., Cassman K.G., Dobermann A. Maize radiation use efficiency under optimal growth conditions. Agron. J. 2005, 97(1):72-78.
21. Lobell D.B., et al. Satellite estimates of productivity and light use efficiency in United States Agriculture, 1982-98. Global Change Biol. 2002, 8(8):722-735.
22. Matamala R., Jastrow J.D., Miller R.M., Garten C. Temporal changes in C and N stocks of restored prairie: implications for C sequestration strategies. Ecol. Appl. 2008, 18(6):1470-1488.
23. Meyers T.P., Hollinger S.E. An assessment of storage terms in the surface energy balance of maize and soybean. Agric. For. Meteorol. 2004, 125(1):105-115.
24. Myneni R.B., et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 2002, 83(1-2):214-231.
25. Potter C.S., et al. Terrestrial ecosystem production - a process model-based on global satellite and surface data. Global Biogeochem. Cycles 1993, 7(4):811-841.
26. Prince S.D., Goward S.N. Global primary production: a remote sensing approach. J. Biogeogr. 1995, 22(4-5):815-835.
27. Prince S.D., Haskett J., Steininger M., Strand H., Wright R. Net primary production of US Midwest croplands from agricultural harvest yield data. Ecol. Appl. 2001, 11(4):1194-1205.
28. Reeves M.C., Zhao M., Running S.W. Usefulness and limits of MODIS GPP for estimating wheat yield. Int. J. Remote Sens. 2005, 26(7):1403-1421.
29. Reichstein M., et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biol. 2005, 11(9):1424-1439.
30. 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(D3):5263-5283.
31. Running S.W., et al. A continuous satellite-derived measure of global terrestrial primary production. Bioscience 2004, 54(6):547-560.
32. Running S.W., Thornton P.E., Nemani R., Glassy J.M. Global terrestrial gross and net primary productivity from the earth observing system. Methods Ecosyst. Sci. 2000, 44-57.
33. Schlesinger W.H., Bernhardt E.S. Biogeochemistry: An Analysis of Global Change 2013, Elsevier.
34. Sinclair T.R., Muchow R.C. Radiation use efficiency. Advances in Agronomy 1999, 65:215-265.
35. Singer J.W., Meek D.W., Sauer T.J., Prueger J.H., Hatfield J.L. Variability of light interception and radiation use efficiency in maize and soybean. Field Crops Res. 2011, 121(1):147-152.
36. Sjöström M., et al. Evaluation of MODIS gross primary productivity for Africa using eddy covariance data. Remote Sens. Environ. 2013, 131:275-286.
37. Suyker A.E., Verma S.B. Gross primary production and ecosystem respiration of irrigated and rainfed maize-soybean cropping systems over 8 years. Agric. For. Meteorol. 2012, 165:12-24.
38. Taylor K.E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. Atmos. (1984-2012) 2001, 106(D7):7183-7192.
39. Turner D.P., Gower S.T., Cohen W.B., Gregory M., Maiersperger T.K. Effects of spatial variability in light use efficiency on satellite-based NPP monitoring. Remote Sens. Environ. 2002, 80(3):397-405.
40. Turner D.P., et al. Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sens. Environ. 2006, 102(3):282-292.
41. 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(12):2925-2939.
42. Xiao X.M., et al. Satellite-based modeling of gross primary production in an evergreen needleleaf forest. Remote Sens. Environ. 2004, 89(4):519-534.
43. Xin Q., et al. A production efficiency model-based method for satellite estimates of corn and soybean yields in the midwestern US. Remote Sens. 2013, 5(11):5926-5943.
44. Yang Y., Shang S., Guan H., Jiang L. A novel algorithm to assess gross primary production for terrestrial ecosystems from MODIS imagery. J. Geophys. Res.: Biogeosci. 2013, 118(2):590-605.
45. Yu L., et al. FROM-GC: 30m global cropland extent derived through multi-source data integration. Int. J. Digit. Earth 2013, 6:521-533.
46. Zhang Q., et al. Estimation of crop gross primary production (GPP): I. Impact of MODIS observation footprint and impact of vegetation BRDF characteristics. Agric. For. Meteorol. 2014, 191:51-63.
47. Zhang Y., Yu Q., Jiang J., Tang Y. Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau. Global Change Biol. 2008, 14(4):757-767.
48. Zhao M., 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(2):164-176.
49. Zhao M., Running S.W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 2010, 329(5994):940-943.
50. Zhong L., Hawkins T., Biging G., Gong P. A phenology-based approach to map crop types in the San Joaquin Valley, California. Int. J. Remote Sens. 2011, 32(22):7777-7804.