Research On Monitoring Main Regulation Cultivation Indices For Wheat And Rice By Remote Sensing Technology

Wheat and rice are the two most important food crops in our country and Jiangsu province. The optimized cultivation techniques have played an important role in the actual production of wheat and rice. However, the technology of monitoring and forecasting wheat and rice production status on large areas is the more lag so far. The growth status and environment of wheat and rice can be monitored and forecasted synchronizely at a large-scale and in real-time by remote sensing technology. It achieved to provide the technical support for large-scale, low-cost monitoring and forecasting of early quality and yield of wheat and rice.The study is in connection with the practical problems that the currently rice-wheat cultivation techniques imperfect which needed further development and solved, at the same time,it need grasping information on the regional rice-wheat crop fastly and without damage and meeting the demand of rice and wheat production management practice, and ultimately making the target of high-quality, high yield, efficient, safe, ecological cultivation of this rice-wheat production come out, Around the variables relationship between the growth of rice-wheat crop, wheat yield and the main grain quality parameters and remote sensing quantitative, this study depends on the remote sensing technology to study of tuning the mechanism and methods of integration between remote sensing technology and rice-wheat cultivating management measures. We also explore the application of remote sensing techniques to monitor the growth of rice-wheat crop, prediction of wheat grain quality and the feasibility estimating of wheat production. The main research content covers the following aspects:(1) The study on monitoring the growth situation of winter wheat by remote sensing based on Landsat TM dataWe analysisd the correlation between physical and chemical parameters different growth stages of wheat.The results showed that leaf nitrogen content and grain protein, wet gluten and starch significantly or very significantly correlated. But the correlation of flowering is most closely.It shows that flowering can be used as the desirable period of time for grain quality forecasted by remote sensing.By analysising of remote sensing variables and are the growth of wheat, the relationship between parameters showed that when monitoring wheat SPAD, biomass, LAI, leaf nitrogen content and leaf water content,in the jointing stage, we selected to B5, NDVI, DSW5, B2 and the RVI as sensitive remote-sensing variables.In the flowering period, we selected NRI, B4, NDVI, and NDWI2 as sensitive remote-sensing variables. After evaluation, the remote sensing monitoring model about the jointing stage of wheat crop is growing and flowering stages has been determined.With the use of the above model, we enter by the spectrum of remote sensing to map that is generated target image and solver variables, and then overlay maps of wheat and administrative boundary vector data, by taking into account parameters of grading standards are growing, generate the matic remote sensing monitoring of map of LAI, SPAD, biomass and leaf nitrogen content.It generated graded map of jointing stage and the flowering period of practical significance of the regional agricultural crop mainly with LAI.(2) The study on monitoring and forecasting wihter wheat grain quality and yield by Remote Sensing based on Landsat TM dataBy Analysising of leaf nitrogen content of wheat grain quality indicators of the main, the grain protein content, yield and remote sensing variables, the correlation between variables, results showed that in the flowering period by the using of NDVI predicted crude protein content and yield of grain is the most appropriate.With the Indirect model, the use of remote sensing to monitor flowering leaf nitrogen content,combined with leaf nitrogen content and grain crude protein content of the quantitative relationship .We constructed and validated the prediction model of remote sensing the direct mode and indirect mode about grain crude protein content and yield, which was high precision. Bsed on grain protein content and yield grading standards, forcasting maps and the zoning map of wheat quality in Jiangsu Province has been generated about different levels of grain protein content and yield,in order to provide wheat grain quality and yield informaition to relevant departments to help enterprises to an abriged version efficiency.(3) Diagnosing leaf nutrition concentration and leaf area index in rice through leaf spectra dataThe research analysised spectral characteristics of rice leaves showed that the rice leaf reflectance spectra and transmission spectra of the waveform characteristics and trends were very similar, while contrary with absorption spectra, due to the impact of the visible light absorpted by the pigment.It resulted in spectral reflectance and transmittance are comparatively low ; near-infrared bands due to being blade platform, the internal effects of multiple light scattering, resulting in spectral reflectance and transmittance have tended to be 50%, while the low absorption rate.Through analysising the correlaition between remote sensing spectral variable physical and chemical parameters in rice. The results showed thatwe can make use of leaf spectral reflectance diagnosis LAI, SPAD and the CHL in the 400-1250nm band, diagnosis, LWC, and LNC in the 1350-1550nm band; It is feasible to use NDVI, NDWI, GreenNDVI and the NRI and other spectral vegetation index in diagnosis of the corresponding leaf nutrition and LAI.We have constructed and validated model of remote sensing variables that using these remote sensing parameters for self-diagnosis.In particular, the use of NDWI (860, 1240) diagnosis of LWC, GreenNDVI diagnosis of SPAD is desirable to construct the diagnostic model, respectively: y = 74.39x + 71.702 and y = 64.737x + 25.221.(4) Hyperspectral remote sensing diagnosis models for nitrogen nutrition status in rice The purpose of study was to analysis the correlation of remote sensing spectral variables and nitrogen content of rice .The results showed that it is feasible. We use the spectral reflectance near to 796nm as independent variables of nitrogen content in the linear model to diagnose rice nitrogen nutrition. And then, near to 738nm Department's first-order differential spectral reflectance as the independent variable nitrogen content of rice nitrogen nutrition index of model-based diagnosis is also feasible and superior to the spectral reflectance the linear model built which based on at 796.7nm. After forecasting evaluation , the final proposed to adopt a vegetation index, normalized variables (SDr-SDb) / (SDr + SDb) as independent variables built Hyperspectral remote sensing of rice nitrogen nutrition diagnosis model (y = 365.871 + 639.323 (SDr-SDb) / ( SDr + SDb)) diagnosis of nitrogen nutrition of rice is the best.(5) The study on integrating the optimized cultivation techniquesBy the analysis of jointing stage of wheat leaf SPAD values and the quantitative relationship between the amount of nitrogen, we have found the amount of nitrogen fertilizer in a targeted manner of a certain region according to wheat leaf SPAD value of the remote sensing monitoring results. Then according to the different plots within a region Wheat leaf SPAD value, we put forward a single block of nitrogen fertilizer. The above analysis has been initially achieved tuning of satellite remote sensing and wheat cultivation techniques of integration.Then we formed a set of satellite-based remote sensing and leaf SPAD value of the real-time diagnosis and variable fertilization of wheat technology, which can be used for real-time diagnosis of wheat crop is growing and the regulation of variable rate fertilization.Through integrating the satellite remote sensing images and rice cultivation techniques, we generated a long-heading stage of rice crop growth status of remote sensing classification map that based on LAI grading standards.And based on a long-heading stage of rice crop growth status of satellite remote sensing monitoring results, a rice tune excellent cultivation techniques was integrated.Long-heading stage of rice abnormal growth of the specific control measures have been figured out. The establishment of rice tuning cultivation techniques which was satellite remote sensing -based and LAI, the technology can be used for remote monitoring of bloom conditions proposed by supporting cultivation management measures.