Regional yield forecasts of malting barley (Hordeum vulgare L.) by NOAA-AVHRR remote sensing data and ancillary data

Journal of Agronomy and Crop Science

Volumn 191, Issue 4, 2005, Pages 308-320

  Weissteiner, C J ^a   Kuhbauch W ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

Malting barley; NDVI; NOAA AVHRR; Remote sensing; Yield forecast; Yield prediction

Indexed keywords

AVHRR; BARLEY; NDVI; NOAA SATELLITE; PREDICTION; YIELD;

HORDEUM VULGARE; HORDEUM VULGARE SUBSP. VULGARE;

EID: 23744485821     PISSN: 09312250     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1439-037X.2005.00154.x     Document Type: Article

References (39)

1. Atzberger, C., 1997: Estimates of Winter Wheat Production Through Remote Sensing and Crop Growth Modelling - A Case Study in the Camargue Region. Akademische Abhandlungen zu den Geowissenschaften, VWF Verlag für Wissenschaft und Forschung, Berlin.
2. Bochenek, Z., 2000: Operation use of NOAA data for crop condition assessment in Poland. In: J. L. Casanova, ed. Remote Sensing in the 21st Century: Economic and Environmental Applications, pp. 387-392. Balkema, Rotterdam.
3. Chmielewski, F.-M., 1998: Der Einfluß der Witterung auf die Ertragsbildung von Sommergerste. Mitt. Ges. Pflanzenbauwiss. 11, 97-98.
4. Chowdhury, S. I., and I. F. Wardlaw, 1978: The effect of temperature on kernel development in cereals. Aust. J. Agric. Res. 29, 205-223.
5. Coleman, V. R., 1995: The use of NOAA-AVHRR in the development of a cereal yield prediction model for England and Wales. PhD Thesis/Dissertation, Silsoe College, Cranfield University.
6. Daughtry, C. S. T., K. P. Gallo, and M. E. Bauer, 1983: Spectral estimates of solar radiation intercepted by corn canopies. Agron. J. 75, 527-531.
7. De Koeijer, K. J., M. D. Steven, and J. J. Colls, 2000: Integration of earth observation data with a crop model for yield forecasting. Aspects Appl. Biol. 60, 91-98.
8. Dech, S., P. Tungalagsaikhan, C. Preusser, and R. Meisner, 1998: Operational value-adding to AVHRR data over Europe: methods, results and prospects. Aerospace Sci. Technol. 5, 335-346.
9. Delécolle, R., S. J. Maas, M. Guérif, and F. Baret, 1992: Remote Sensing and crop production models: present trends. ISPRS J. Photogramm. Remote Sens. 47, 145-161.
10. Doorenbos, J., and A. H. Kassam, 1979: Yield Response to Water, FAO Irrigation and Drainage, paper, 33. FAO publications, Rome.
11. Eagles, H. A., A. G. Bedggood, J. F. Panozzo, and P. J. Martin, 1996: Cultivar and environmental effects on malting quality in barley. Aust. J. Agric. Res. 46, 831-844.
12. EEA, 2003: CORINE land cover. 12/2000. European Environment Agency, http://dataservice.eea.eu.int/ [accessed on 12 November 2004].
13. EU, 2004: Introduction to the NUTS and the Statistical regions of Europe. Europäische Union, http://europa. eu.int/comm/eurostat/ramon/nuts/ home_regions_de. html [accessed on 12 November 2004].
14. Evans, L. T., I. F. Wardlaw, and R. A. Fischer, 1978: Wheat. University Press, Cambridge.
15. Geisler, G., 1983: Ertragsphysiologie von Kulturarten des gemäßigten Klimas. P. Parey, Berlin.
16. Genovese, G., C. Vignolles, T. Nègre, and G. Passera, 2001: A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study in Spain. Agronomie 21, 91-111.
17. Goward, S. N., B. Markham, D. G. Dye, W. Dulaney, and J. Yang, 1991: Normalized difference vegetation index measurements from AVHRR. Remote Sens. Environ. 35, 257-277.
18. Hatfield, J. L., 1983: Remote sensing estimators of potential and actual crop yield. Remote Sens. Environ. 13, 301-311.
19. Holben, B. N., 1986: Characteristics of maximum value composite images from temporal AVHRR data. Int. J. Remote Sens. 11, 1511-1520.
20. Hünting, K., C. J. Weissteiner, and W. Kühbauch, 2003: Yield prediction of malting barley based on meteorological data. Proc. 2003 IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), 21-25 July 2003, pp. 383-385, Toulouse/France.
21. Illera, P., J. A. Delgado, A. Fernández Unzueta, and A.A. Fernández Manso, 2000: Integration of NOAA-AVHRR and meteorological data in a GIS - application for vegetation monitoring in Castilla y León, Spain. In: J. L. Casanova, ed. Remote Sensing in the 21st Century: Economic and Environmental Applications, pp. 47-54. Balkema, Rotterdam.
22. Jaggard, K. W., and C. J. Clark, 1990: Remote Sensing to Predict the Yield of Sugar Beet in England. Butterworths, London.
23. Jones, P. G., P. K. Thornton, and P. Hill, 1997: Agrometeorological models: crop growth and stress indices. Proceedings of crop yield forecasts methods, Villefranche-sur-Mer, 24-27 October 1994, pp. 53-65. Office for Official Publications of the European Communities, Luxembourg.
24. Kogan, F. N., 2001: Operational space technology for global vegetation assessment. Bull. Am. Meteorol. Soc. 82, 1950-1964.
25. Kühbauch, W., G. Kupfer, F. Boochs, C. Büker, K. Dockter, J. Schellberg, C. von Rüsten and U. Tempelmann, 1991: Abschlußbericht zum Forschungsvorhaben Ertragsschätzung an landwirtschaftlichen Kulturpflanzenbeständen mit Hilfe der Fernerkundungstechnik. Lehrstuhl f. Allg. Pflanzenbau und Inst. f. Photogrammetrie der Univ. Bonn, Bonn.
26. Li, Y., 1990: Estimating production of winter wheat by remote sensing and unified ground network. II Nationwide estimation of wheat yields. In: M. D. Steven, and J. A. Clark, eds. Applications of Remote Sensing, pp. 149-158. Butterworths, London.
27. Maselli, F., S. Romanelli, L. Bottai, and G. Maracchi, 2000: Processing of GAC NDVI data for yield forecasting in the Sahelian region. Int. J. Remote Sens. 21, 3509-3523.
28. Moulin, S., A. Bondeau, and R. Delécolle, 1998: Combining agricultural crop models and satellite observations: from field to regional scales. Int. J. Remote Sens. 19, 1021-1036.
29. Nelder, J. A., and R. Mead, 1965: A simplex method for function minimization. Comput. J. 7, 307-313.
30. Pinter, P. J., Jr, R. D. Jackson, S. B. Idso, and R. J. Reginato, 1981: Multidate spectral reflectance as predictors of yield in water stressed wheat and barley. Int. J. Remote Sens. 2, 43-48.
31. Qi, J., F. Cabot, M. S. Moran, and G. Dedieu, 1995: Biophysical parameter estimation using multidirectional spectral measurements. Remote Sens. Environ. 54, 71-83.
32. Quarmby, N. A., M. Milnes, T. L. Hindle, and N. Silleos, 1993: The use of mulit-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction. Int. J. Remote Sens. 14, 199-210.
33. Rouse, J. W., R. H. Haas, J. A. Schell, D. W. Deering, and J. C. Harlan, 1974: Monitoring the Vernal Advancement of Retrogradation of Natural Vegetation. NASA/GSFC, Greenbelt, MD.
34. Schelling, K., K. Born, C. J. Weissteiner, and W. Kühbauch, 2003: Relationships between yield and quality parameters of malting barley (Hordeum vulgare L.) and phenological and meteorological data. J. Agron. Crop Sci. 189, 113-122.
35. Seiler, R. A., F. N. Kogan, and G. Wei, 2000: Monitoring weather impact and crop yield from NOAA AVHRR data in Argentina. Adv. Space Res. 26, 1177-1185.
36. Steven, M. D., and K. W. Jaggard, 1995: Advances in crop monitoring by remote sensing. In: S. E. Plummer, and Danson F. M. (eds), Advances in Environmental Remote Sensing, pp. 143-156. John Wiley & Sons Ltd, Chichester.
37. Unganai, L. S., and F. N. Kogan, 1998: Drought monitoring and corn yield estimation in southern Africa from AVHRR data. Remote Sens. Environ. 63, 219-232.
38. Wardlaw, I. F., I. A. Dawson, P. Munibi, and R. Fewster, 1989: The tolerance of wheat to high temperatures during reproductive growth. 1. Survey procedures and general response patterns. Aust. J. Agric. Res. 40, 1-13.
39. 2. J. Exp. Bot. 47, 623-630.