The Estimation Of The Available Quantity Of Crop Biomass And Space Distribution Resaerch Based On Remote Sensing Information

Science accuracy estimating the Crop biomass is prerequisite for the strategy of developing and utilizing bio-energy. With the development of remote sensing technology, the temporal resolution, spatial resolution and spectral resolution of remote sensing data are constantly improving. And that provides strong support for estimating the biomass of Crop in the big time span and large spatial scale. In the present paper, the principle and typical application of crop biomass estimation based on remote sensing information is analyzed and summarized, summarized and conclude the method of wheat biomass estimation based on Vegetation Index.In the present paper, the wheat biomass of LuAn was regarded by using May l,and April 25 2015 Landsat8 image data. At the same time,the wheat biomass utilization potential was calculated and analyzed. First of all, the row images of the study area were preprocessed and classificated by land use, then the result of unsupervised and supervised classification algorithm(Parallepiped, Minimum-distance ,Mahalanobis-Distance, Likelihood-Classicification, Neural Net Classification, Support Vector Machine Classification) were contrast analysis. Finally, the the Minium-distance classification was selected to regarding LuAn supervised classficrtion of land use, and the classification results for reprocessing and precision analysis, the wheat planting area of LuAn was extracted. Then the correlation analysis of the measured wheat biomass with the Difference vegetation index(DVI), Green normalized difference vegetation index(NDGI), normalized difference vegetation index (NDVI), Green vegetation index (RI) and the Ratio vegetation index (RVI) were calculated, the results show that the NDVI is highest correlation with wheat biomass and the correlation coefficient r is 0.760, followed by RVI, correlation coefficient r is 0.655. On the basis of above five further cultivation were separately measured wheat biomass by exponential, linear, logarithms, quadratic polynomial, power function fitting of five modes,the vegetation index and fitting type which have the highest correlation coefficient were picked to build model-based on NDVI vegetation index estimating model. The estimation by above-mentioned model and Straw/Grain Ratio models was compared, the results show that the error is only 101150 tons, the percentage error is 6.89%. At the same time, regarding LuAn to each district and county wheat biomass spatial analysis and the unit of wheat biomass density is calculated, the results show that the biomass and biomass density of ShouXian were the highest, respectively 637900 tons and 213.6 tons per square kilometers. Finally, based on the predecessors’ research in wheat collection coefficible and folding Standard coal coefficient weighted averaging in this article collectible wheat coefficient and folding Standard coal coefficient was 0.766 and 0.766 respectively. The wheat biomass utilization potential were calculated and analyzed by using the coefficient. The results showed that wheat biomass utilization potential of LuAn of 2015 was about 551400 tons Standard coal, which could provided 13.85% of the total energy consumption of LuAn of 2015.It bases on the above research found that wheat biomass and biomass estimation method based on remote sensing has certain validity and practicability, which can estimate the wheat biomass of the study area for a certain accuracy requirement, provide the necessary technical support for the biomass energy strategy.