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Agriculture & Soil
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The method and practice of macro Remote Sensing Monitoring of winter wheat
Xu Xiru, Zhu Xiaohong
(The Institute of remote Sensing Technology
and Applications of Peking University)
Zhang Xuding
The Department of Mathematics of peking university
Beijing, 100871, China
Summary
China is developing country with large population and less arable land. It is strategically important to have a bumper ha vest for Chinese economic development. It is necessary step for scientific and democratic administrative management to apply remote sensing technique for realizing timely monitoring of crop yield. The most models were directly established between spectral parameters and yield of winter wheat by statistical method. (1) (2) (3) in fact, the yield of winter whet id determined by three factors (ear number (S), grain number (L) and grain weight (Z), they are formed in different stage and are controlled by different, main factors, so the method of estimation of winter wheat yield should be based on the relationship between spectral parameters and the three basic factors which form the winter wheat yield. Authors had utilized the synchronized spectral parameters and necessary agronomic data gained form controllable sample fields to analyze the relationship between three basic factors and remote sensing data adding non-remote sensing parameters.
The forming of yield depends on slow accumulation of photosynthetic products, but any kind remote sensing images only offer an instant information of spatial distribution of spectral reflectance. The contradiction between spatial and temporal continuity is always the core of problem, for this reason non-remote sensing data and GIS are necessary for yield estimation of winter wheat. The theory of decomposition of mixed pixel had made it possible to realize macro monitoring of winter wheat using low resolution AVHHR data.
Model of estimation Of winter wheat
It is well known photosynthesis is the basic course for vegetative growing :
The chloroplasts catch photos to offer necessary energy for dark reaction of photosynthesis, so the amount of chloroplasts are directly related to the most possible biomass. K.P. Gallo and C.J. Tucker (4) (5) had proven the close relationship between spectral parameters and effective photosynthetic energy of crop from experiments and theory respectively. So, people can get correct information of spatial distribution of chlorophyll density from remote sensing data. If we measured the spectral parameters for whole life to winter wheat, then the total biomass, the ratio between them have been called economic coefficient. Many models treated it as constant. As a matter of fact we can easily find many samples, their total biomass are similar but their yield are quite different. The key problem is that the three basic factors are formed in different stage and their decisive factors are not the same. At one side they are related to each other, on the other side they are distinguished from each other. Therefore the correct method of yield estimation by remote sensing technology hast o explain the relationship between spectral parameters and three basic factors.
We intent to find out the relationship between them through control able sample fields. We planted winter wheat into a cement pool with bottom sealed. The irrigation water and fertilizer are controlled in order to enlarge the span of yield among different sample fields. We measured spectral reflectance of winter wheat, leaves area (LAI) for whole life, the amount of irrigation water were recorded. After harvest we measured ear number(s), grain number (L) and grain weight (Z) for every sample field. Because spectral reflectance of soil background with different irrigation water is different, so we adopted PVI as a basic spectral parameter in order to filter the influence of soil background better.
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