Estimation Of Winter Wheat Residue Cover Of Yucheng Area, Shandong

The research content of this paper is an important part of the project "Monitoring Carbon sequestration parameters of East China"(Grant No. XDA05050106) under the project "Strategic Priority Research Program-Climate Change:Carbon Budget and Relevant Issues" of the Chinese Academy of Sciences and the project "Remote sensing Monitoring Land Cover and Land surface parameters of East China"(Grant No.STSN-01-05) under the project National ecological environment change in decade (2000-2010).Crop residues are the portions of a crop that are left in the field after harvest, which is an important part of the farmland ecosystem. Crop residues can influence the course of carbon, water, nitrogen and other substances cycling, greenhouse gas mitigation and cropland protection.HJ-1CCD remote sensing imagery and synchronous field measurements are used to do this research based on the two projects. First, the sensitive band is selected after analyzing the field measurements of winter wheat residues spectral data. The reflectance of winter wheat residue is simulated using SAIL model. Then, a look-up table between the simulated reflectance and remote sensing imagery is built. Finally, the winter wheat cover in Yucheng area of Shandong province is estimated. The main contents and results of the research are presented as follows: (1) Winter wheat residue spectrum and their derivatives of different cover are analyzed. The results show the most sensitive bands that distinguish winter wheat residue from the green wheat and bare soil are2100nm-2300nm. Crop residues have strong absorption in the bands, and different coverage makes different absorption depth, which is mainly due to the lignin and cellulose in crop residues.(2) The correlations between winter wheat residues cover and spectral reflectance, its first order derivative, as well as normalized difference and ratio index are evaluated using regression analysis. The results indicate that winter wheat residue cover is positively correlated with its reflectance. And the maximum value of the correlation coefficient is0.98. For first order derivative, correlations are fluctuated. And for normalized difference index and ratio index, maximum value of the correlation coefficient is in the combination of2100nm-2300nm. Also, band combinations (between1450nm and2100nm-2300nm) show high correlation, which can be used to build index to estimate crop residue cover.(3) The correlations between field measured winter wheat residues cover and satellite-based crop residues index, as well as band reflectance of HJ-1are evaluated using regression analysis. The index CAI (cellulose absorption index) performs best of all crop residues index. NDSVI (Normalized Differential Senescent Vegetation Index) based on HJ performs best of the wide band based index. And the index using short-wave infrared band seems performing better. Among the band reflectance of HJ-1, winter wheat residue cover is highly correlated with near-infrared band, which can be used to estimate winter wheat residue cover.(4) The reflectance of winter wheat residue is simulated using SAIL (Scattering by Arbitrary Inclined Leaves) model, in which the original parameter leaf area index is replaced by crop residue area index. And the results are compared with the filed-measured data; showing that near infrared band can describe winter wheat residue cover best and can be used to estimate the cover. Then according to the selected sensitive band, a look-up table is built between the simulated reflectance and HJ-CCD near-infrared band in the winter wheat planting area. Finally, the winter wheat cover of Yucheng area Shandong province is estimated. The model is validated using field-measured data. The maximum relative error of the21plots is19.15%, and the average relative error is5.71%, indicating an acceptable accuracy of the model estimation.Focusing on the Yucheng area Shandong Province, winter wheat residue cover is estimated with domestic HJ-1CCD remotely sensed data through spectrum analysis, sensitive band selection, and winter wheat residue cover estimation. This is beneficial for winter wheat residue cover research of the study area and Huang-huai-hai Plain, and can provide dataset for climate change research and related models.