Study Of Extracting The Crop Biomass Based On The ETM+ Remote Sensing Image

Energy is the basic power of economy and society development, and its consumption would increase continuously with the global economy development and world population growth. Now people are heavily using the traditional mineral energy, at the same time, they are positively finding a kind of replace energy because it is non-renewable. Many countries pay more attention to use renewable energy in the world when we stride in the 21^st century. Our country is a traditional agricultural big country, and the straw stalk which can be used for energy is quite rich. It is important to use the crop biomass energy for exploring the renewable energy and increasingly changing the energy structure in our country. Therefore, it is extremely essential to master the status of crop biomass in time for making reasonable development plan.The first earth resources satellite was launched in 1972, and the remote sensing technology developed quickly. The remote sensing technology has greatly advanced resolving power in recent years and it provides many new methods for the research of crop biomass.Followed the development of remote sensing technology, people are paying more attention to usage of remote sensing images extracting the crop biomass in recent years. In this paper, Pukou county Nanjing city is the study region, and the basic theory and methods of image fusion and classification are adopted. Finish crop biomass extraction from ETM+ image, and study image preprocessing, spectrum character analysis, multi-spectrum transformation in the paper.The primary work and conclusions in the paper as followed:(1)Acquire the raw data and assistance data, and rectify geometrically the raw image of study zone. At last obtain the image with geographical reference.(2)According to image spectrum character, correlation coefficients and so on, expound a method of optimal band choice based on OIF index and the class minimum distance, and ascertain that the optimal band combination of study zone are TM3,TM4,TM5.(3)Different merge methods such as HIS, PCA, Brovey, HPF and Wavelet have been discussed. Based on correlation coefficient quantitative analysis, conclusion was given that wavelet transformation is a kind of fine merge method.(4)Based on the characteristic of TM, combine the advantage of PCA and wavelet transformation, and expound a new image fusion method.(5)Based on the comparison of two unsupervised classification algorithms, choose the ISODATA unsupervised algorithm.(6)In image classification, gain the sample by ISODATA unsupervised classification, and verify the sample in reality. At last choose partial sample as the classification signature data and put others as verification data.(7) In view of the TM database with a normal distribution, choose the method of maximum likelihood as the supervised classification to classify the images.(8) Compute the area of crop based on the number of pixel after classification, and obtain the area and status of crop coverage.(9)Based on the relevant datum statistics and the crop area, obtain the crop biomass quantity of study zone.