The early explanatory power of NDVI in crop yield modelling

References

• AAFC. 1999. Market information: Cereals sector profile. Available online at: http://sea.agr.ca/can/e2207.htm (accessed 8 March 2006)
   Google Scholar
• Allen R, Hanuscak G, Craig M. 2002. Limited use of remotely sensed data for crop condition monitoring and crop yield forecasting in NASS. Available online at: http://www.usda.gov/nass/nassinfo/remoteuse.htm (accessed 8 March 2006)
   Google Scholar
• Anonymous. 2004. Landforms and climate of the prairies ecozone. Available online at: http://www.ec.gc.ca/soer‐ree/English/vignettes/Terrestrial/pr/land.cfm (http://www.ec.gc.ca/soer-ree/English/vignettes/Terrestrial/pr/land.cfm) (accessed 8 March 2006)
   Google Scholar
• Báez‐González , A. D. , Chen , P. Y. , Tiscareno‐Lopez , M. and Srinivasan , R. 2002 . Using satellite and field data with crop growth modeling to monitor and estimate corn yield in Mexico. . Crop Science , 42 : 1943 – 1949 .
   Web of Science ®Google Scholar
• Basnyat , P. , McConkey , B. , Lafond , G. R. , Moulin , A. and Pelcat , Y. 2004 . Optimal time for remote sensing to relate to crop grain yield on the Canadian prairies. . Canadian Journal of Plant Science , 84 : 97 – 103 .
   Web of Science ®Google Scholar
• Boken , V. K. and Shaykewich , C. F. 2002 . Improving an operational wheat model using phenological phase‐based Normalized Difference Vegetation Index. . International Journal of Remote Sensing , 23 : 4155 – 4168 .
   Web of Science ®Google Scholar
• Das , D. K. , Mishra , K. K. and Kalra , N. 1993 . Assessing growth and yield of wheat using remotely‐sensed canopy, temperature, and spectral indices. . International Journal of Remote Sensing , 14 : 3081 – 3092 .
   Web of Science ®Google Scholar
• Domenikiotis , C. , Spiliotopoulos , M. , Tsiros , E. and Dalezios , N. R. 2004 . Early cotton yield assessment by the use of NOAA/AVHRR derived from Vegetation Condition Index (VCI) in Greece. . International Journal of Remote Sensing , 25 : 2807 – 2819 .
   Web of Science ®Google Scholar
• Ferencz , C. , Bognar , P. , Lichtenberger , J. , Hamar , D. , Tarcsai , G. , Timar , G. , Molnar , G. , Pasztor , S. , Steinbach , P. , Szekely , B. and Ferencz , O. E. 2004 . Crop yield estimation by satellite remote sensing. . International Journal of Remote Sensing , 25 : 4133 – 4149 .
   Web of Science ®Google Scholar
• Fitzmaurice , G. M. , Laird , Nan M. Ware. and James , H. 2004 . Applied Longitudinal Analysis , Hoboken, NJ : Wiley .
   Google Scholar
• Groten , S. M. E. 1993 . NDVI—crop monitoring and early yield assessment of Burkina‐Faso. . International Journal of Remote Sensing , 14 : 1495 – 1515 .
   Web of Science ®Google Scholar
• Hassan , Z. A. and Huff , H. B. 1978 . Commodity Forecasting Models for Canadian , Ottawa : Canadian Department of Agriculture (Information Division) .
   Google Scholar
• Kastens , J. H. , Kastens , T. L. , Kastens , D. L. A. , Price , K. P. , Martinko , E. A. and Lee , R.‐Y. 2005 . Image masking for crop yield forecasting using AVHRR NDVI timeseries imagery. . Remote Sensing of Environment , 99 : 341 – 356 .
   Web of Science ®Google Scholar
• Kogan , F. , Yang , B. J. , Wei , G. , Pei , Z. Y. and Jiao , X. F. 2005 . Modelling corn production in China using AVHRR‐based vegetation health indices. . International Journal of Remote Sensing , 26 : 2325 – 2336 .
   Web of Science ®Google Scholar
• Kogan , F. N. 1990 . Remote sensing of weather impacts on vegetation in non‐homogeneous areas. . International Journal of Remote Sensing , 11 : 1405 – 1419 .
   Web of Science ®Google Scholar
• Kogan , F. N. , Gitelson , A. , Zakarin , E. , Spivak , L. and Lebed , L. 2003 . AVHRR‐based spectral vegetation index for quantitative assessment of vegetation and productivity: calibration and validation. . Photogrammatic Engineering and Remote Sensing , 69 : 899 – 906 .
   Web of Science ®Google Scholar
• Koller , M. and Upadhyaya , S. K. 2005 . Prediction of processing tomato yield using a crop growth model and remotely sensed aerial images. . Transaction of the ASAE , 48 : 2335 – 2341 .
   Google Scholar
• Labus , M. P. , Nielsen , G. A. , Lawrence , R. L. , Engel , R. and Long , D. S. 2002 . Wheat yield estimates using multi‐temporal NDVI satellite imagery. . International Journal of Remote Sensing , 23 : 4169 – 4180 .
   Web of Science ®Google Scholar
• Littell , R. C. , Milliken , G. A. , Stroup , W. W. and Wolfinger , R. D. 1996 . SAS System for Mixed Models , Cary, NC : SAS Institute .
   Google Scholar
• Liu , W. T. and Kogan , F. 2002 . Monitoring Brazilian soybean production using NOAA/AVHRR based vegetation condition indices. . International Journal of Remote Sensing , 23 : 1161 – 1179 .
   Web of Science ®Google Scholar
• Ma , B. L. , Dwyer , L. M. , Costa , C. , Cober , E. R. and Morrison , M. J. 2001 . Early prediction of soybean yield from canopy reflectance measurements. . Agronomy Journal , 93 : 1227 – 1234 .
   Web of Science ®Google Scholar
• Manjunath , K. R. and Potdar , M. B. 2002 . Large area operational wheat yield model development and validation based on spectral and meteorological data. . International Journal of Remote Sensing , 23 : 3023 – 3038 .
   Web of Science ®Google Scholar
• Maselli , F. , Conese , C. , Petrkov , L. and Gilabert , M. A. 1993 . Environmental monitoring and crop forecasting in the Sahel through the use of NOAA NDVI data—a case‐study—Niger 1986–89. . International Journal of Remote Sensing , 14 : 3471 – 3487 .
   Web of Science ®Google Scholar
• Mkhabela , M. S. , Mkhabela , M. S. and Mashinini , N. N. 2005 . Early maize yield forecasting in the four agro‐ecological regions of Swaziland using NDVI data derived from NOAAs‐AVHRR. . Agricultural and Forest Meteorology , 129 : 1 – 9 .
   Web of Science ®Google Scholar
• Nivens , H. , Kastens , T. and Dhuyvetter , K. Using satellite imagery in Kansas crop yield and net farm income forecasts. NCR‐134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management ,
   Google Scholar
• PFRA. 2001. Prairie Land and Water: The Last 100 Years. Available online at: http://collections.ic.gc.ca/ (accessed 8 March 2006)
   Google Scholar
• Potdar , M. B. , Manjunath , K. R. and Purohit , N. L. 1999 . Multi‐season atmospheric normalization of NOAA AVHRR derived NDVI for crop yield modeling. . Geocarto International , 14 : 51 – 56 .
   Google Scholar
• Prasad , A. K. , Chai , L. , Singh , R. P. and Kafatos , M. 2006 . Crop yield estimation model for Iowa using remote sensing and surface parameters. . Internationational Journal of Applied Earth Observation and Geoinformatin , 8 : 26 – 33 .
   Web of Science ®Google Scholar
• Quarmby , N. A. , Milnes , M. , Hindle , T. L. and Silleos , N. 1993 . The use of multitemporal NDVI measurements from AVHRR data for crop yield estimation and prediction. . International Journal of Remote Sensing , 14 : 199 – 210 .
   Web of Science ®Google Scholar
• Rasmussen , M. S. 1992 . Assessment of millet yields and production in northern Burkina‐Faso using integrated NDVI from the AVHRR. . International Journal of Remote Sensing , 13 : 3431 – 3442 .
   Web of Science ®Google Scholar
• Rasmussen , M. S. 1997 . Operational yield forecast using AVHRR NDVI data: Reduction of environmental and inter‐annual variability. . International Journal of Remote Sensing , 18 : 1059 – 1077 .
   Web of Science ®Google Scholar
• Rasmussen , M. S. 1998 . Developing simple, operational, consistent NDVI‐vegetation models by applying environmental and climatic information. Part II: Crop yield assessment. . International Journal of Remote Sensing , 19 : 119 – 139 .
   Web of Science ®Google Scholar
• Reichert , G. C. and Caissy , D. 2002 . A Reliable Crop Condition Assessment Program (CCAP) Incorporating NOAA AVHRR Data, a Geographical Information System, and the Internet
   Google Scholar
• Reichert , G. C. , Nixon , P. R. and Dobbins , R. N. 1998 . Statistics Canada's near real‐time Crop Condition Assessment Program (CCAP) utilizing NOAA AVHRR data, remote sensing, GIS and the Internet. . Agricultural Statistics 2000 , : 142 – 148 .
   Google Scholar
• Robertson , B. , Ericson , A. , Friedel , J. , Guindon , B. , Fisher , T. , Brown , R. , Teillet , P. , D'Iorio , M. , Cihlar , J. and Sanz , A. 1992 . “ GEOCOMP—A NOAA AVHRR Geocoding and Geocompositioning system. ” . In Proceedings of the International Society of Photogrammetry and Remote Sensing Washington, DC
   Google Scholar
• Royo , C. , Aparicio , N., D., V. , Casadesus , J. , Monneveux , P. and Araus , J. L. 2003 . Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions. . International Journal of Remote Sensing , 24 : 4403 – 4419 .
   Web of Science ®Google Scholar
• Schwarz , G. 1978 . Estimating the dimension of a model. . Annals of Statistics , 6 : 461 – 464 .
   Web of Science ®Google Scholar
• Seiler , R. A. , Kogan , F. and Wei , G. 2000 . Monitoring weather impact and crop yield from NOAA AVHRR data in Argentina. . Remote Sensing for Land Surface Characterisation Advances in Space Research , 14 : 199 – 210 .
   Google Scholar
• Smith , R. C. G. , Adams , J. , Stephens , D. J. and Hick , P. T. 1995 . Forecasting wheat yield in a Mediterranean‐type environment from the NOAA satellite. . Australian Journal of Agricultural Research , 46 : 113 – 125 .
   Google Scholar
• Tucker , C. J. , Holben , B. N. , Elgin , J. H. and McMurtrey , J. E. 1980 . Relationship of spatial data to grain yield variation. . Photogrammetric Engineering and Remote Sensing , 46 : 657 – 666 .
   Web of Science ®Google Scholar
• Unganai , L. S. and Kogan , F. N. 1998 . Drought monitoring and corn yield estimation in Southern Africa from AVHRR data. . Remote Sensing of Environment , 63 : 219 – 232 .
   Web of Science ®Google Scholar
• Vicente‐Serrano , S. M. , Cuadrat‐Prats , J. M. and Romo , A. 2006 . Early prediction of crop using drought indices at different time‐scales and remote sensing data: application in the Ebro Valley (north‐east Spain). . International Journal of Remote Sensing , 27 : 511 – 518 .
   Web of Science ®Google Scholar
• Walker , G. K. 1989 . Model for operational forecasting of Western Canada wheat yield. . Agricultural and Forest Meterology , 44 : 339 – 351 .
   Web of Science ®Google Scholar
• Wang , J. , Price , K. P. and Rich , P. M. 2001 . Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains. . International Journal of Remote Sensing , 22 : 3827 – 3844 .
   Web of Science ®Google Scholar
• Wang , J. , Rich , P. M. and Price , K. P. 2003 . Temporal responses tof NDVI to precipitation and temperature in the central Great Plains, USA. . International Journal of Remote Sensing , 24 : 2345 – 2364 .
   Web of Science ®Google Scholar
• Weissteiner , C. J. and Kuhbauch , W. 2005 . Regional yield forecasts of malting barley (Hordeum vulgare L.) by NOAA‐AVHRR remote sensing data and ancillary data. . Journal of Agronomy and Crop Science , 191 : 308 – 320 .
   Web of Science ®Google Scholar