Processing System Development Of Winter Wheat Growing Hyperspectral Data Based On C#

Crop growth monitoring is an important field in agricultural remote sensing, which based on the green vegetation spectral theory. Absorption bands in visible region, reflection peaks in near infrared region and portfolios reflected crop growth condition, soil fertility and plant nutrition timely for taking reasonable and effective measures to ensure the normal growth. The application of hyperspectral remote sensing could record the observable ground objects in the form of spectral curves, resulting in continuous spectrum with rich information. The number of hyperspectral bands has reached to several thousands. Data transformation such as the derivative transformation, logarithmic transformation, calculating the correlation coefficient and various vegetation indices lead to the information increasing nearly hundredfold. In addition, the field trials of winter wheat were the basis of the study. A series of experiments could get numerous valid physiological and biochemical data of winter wheat. Faced with so much experimental data, it consume a lot of time to input and output tedious data, calculate and analysis complex data in traditional methods. With the development of experimental techniques and larger data, it could not satisfy the necessary of researchers to analysis the data efficiently and effectively..With the winter wheat canopy spectra, physiological and ecological data and the conclusion of data analysis methods, a winter wheat growing hyperspectral data processing system based on the C # language run successfully. The following major results:1. The spectrum, physiological and biochemical data obtained in winter wheat field trials could be analyzed.2. The design of winter wheat hyperspectral data processing system was completed according to the function needed in analysis processing and the design principles. The system is divided into three functional modules such as data entry, data analysis and data output. Data analysis was the core function including spectral transform, correlation coefficient, vegetation index, spectral feature extraction, extraction and optimal growing vegetation index grading, vegetation index inversion of physiological and biochemical functions.3. The system used C/S software construction techniques and based on the object-oriented programming language C# on Microsoft’s .NET platform,, which developed a practical winter wheat growing data processing system with simple and friendly user interface,. The system provided a fast and efficient data processing platform for winter wheat research. Through analyzing and processing the hyperspectral data and leaf area index (LAI) data obtained in field trials, the system reached to the design requirements. The system achieved the monitoring on the winter wheat rapidly and nondestructively and for hyperspectral study provided important infrastructure and technical supports to winter wheat growing data processing.