HYPERSPECTRAL DATA ANALYSIS OF N-FERTILISATION EFFECTS ON WINTER WHEAT : A CASE STUDY OF HUIMIN COUNTY , NORTH CHINA PLAIN

High nitrogen fertiliser applications are very common in many densely populated areas as in the North China Plain (NCP). A still growing population and an ongoing economic progress enforce that process. Remote sensing methods can help to optimize the N-management for diagnosing crop N status on a field and regional level. For that purpose, spectral and agronomic data were collected during the vegetation period of winter wheat (Triticum aestivum L.) in 2006 and in 2007 in the study area of Huimin County. In a post-processing step, a hyperspectral and agronomic data library was established which enables the analysis of spectra in dependence of agronomic data. The investigated parameters include biomass, N-uptake, LAI (Leaf Area Index), plant height and others. Finally, a model was developed which could be applied for extrapolation of the regional knowledge by using hyperspectral air or satellite borne remote sensing data. This paper shows that the collection and postprocessing of spectral and agronomic data of winter wheat in combination with GIS (Geographic Information Systems) and RS (Remote Sensing) analysis help to identify over-fertilised and undersupplied managements for different phenological stages from shooting to heading. * Corresponding author.

[1]  P. Wang,et al.  Synchronizing N Supply from Soil and Fertilizer and N Demand of Winter Wheat by an Improved Nmin Method , 2006, Nutrient Cycling in Agroecosystems.

[2]  LOW ALTITUDE AERIAL PHOTOGRAPHY , 2006 .

[3]  Rainer Laudien,et al.  Entwicklung eines GIS-gestützten schlagbezogenen Führungsinformationssystems für die Zuckerwirtschaft , 2005 .

[4]  Jürgen Schellberg,et al.  Die Spektrale Reflexion von Weizen : ein Beitrag zur Zustandsbeschreibung landwirtschaftlicher Kulturpflanzenbestände durch Fernerkundung , 1990 .

[5]  John R. Miller,et al.  Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .

[6]  E. C. Large.  GROWTH STAGES IN CEREALS ILLUSTRATION OF THE FEEKES SCALE , 1954 .

[7]  R. D. Ramsey,et al.  Canopy Reflectance Estimation of Wheat Nitrogen Content for Grain Protein Management , 2004 .

[8]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[9]  Jorge A. Delgado,et al.  Increased nitrogen use efficiencies as a key mitigation alternative to reduce nitrate leaching in north china plain , 2007 .

[10]  R. Colwell.  Remote sensing of the environment , 1980, Nature.

[11]  M. Flowers,et al.  Remote Sensing of Winter Wheat Tiller Density for Early Nitrogen Application Decisions , 2001 .

[12]  J. Peñuelas,et al.  Remote sensing of biomass and yield of winter wheat under different nitrogen supplies , 2000 .

[13]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[14]  N. Oppelt,et al.  Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data , 2004 .

[15]  W. Cao,et al.  The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII-4/C7 CLASSIFICATION OF HIGH RESOLUTION OPTICAL AND SAR FUSION IMAGE USING FUZZY KNOWLEDGE AND OBJECT-ORIENTED PARADIGM , 2010 .

[16]  M. Norman.  Field crops research , 1978 .

[17]  Böning Zilkens.  Comparative appraisal of different agronomic strategies in a winter wheat-summer maize double cropping system in the North China Plain with regard to their contribution to sustainability. , 2004 .