Based On Remote Sensing Image Fusion Technology In Rice Acreage Extraction And Rice Smut Estimation

Jiangsu Province is one of the major rice producing areas, and its rice acreage and production is among the domestic front. Now, with the high yield rice harvest, the occurrence of rice false smut has been increasing in recent years. So that, it is necessary to make effective estimates about rice acreage and smut disease, but remote sensing monitoring of crop diseases and insect pests usually faced with two problems, "same specture with different crops", "different specture with same crops", and model applicability inadequate. Based on the above, this article made some different exposition as follows:1. In order to improve rice acreage observation accuracy of Jiangsu Province, and solve the problem as, "same specture with different crops", "different specture with same crops", we choose four methods (PCA, Brovey, HPF, and Wavelet) to do image fusion by ENVI and ERDAS software, and the images came from GF-1/PMS Panchromatic Portrait and HJ-1B/CCD multispectral images. Then we evaluated the spectral information, texture feature, fidelity, etc of fusion image by visual and fusion effect, and we compared the spectral characteristics of fusion image and the measured data to select the best fusion image by RVI and NDVI. Moreover, we made the rice planting distribution map by unsupervised classification, and we took three experimental plots to vivificate accuracy of fusion images. The results showed that, fusion image with richest spectral information, most clear spatial texture features, and best fidelity were come from by HPF. What’s more, its value was nearest to the RVI and NDVI values, and the approximate rate was 87.71% and 98.63%, respectively. Do some quadrat verifications on the HPF fusion merge, and the mean verification accuracy was 94.55%.2. To increase the applicability of the model, we departed from the pathogenesis of false smut bacteria and occurrence, conbined meterological, agricultural and remote sensing elements, consided the meteorological factors conducive to false smut pathogen infection and dissemination, field management, rice varieties, nitrogen fertilizer, etc, from the view of the bacteria pathogenesis and occurrence of false smut, for the main rice varieties in Jiangsu Procince Huaidao 5 and Lianjing 7, finally we selected five indicators, such as temperature, precipitation, leaf area index, biomass, and nitrogen content of leaf, to simulate forecast model of rice false smut index by 50 sample points data of Xinghua, Shuyang, Jianhu, Lianshui, and Guannan from 2012-2013, and verified the model by data of Xinghua in 2014. The results showed that the model was basically consistent with the actual situation, and the verification accuracy of the model was 83.32%.What’s more, we used the remote sensing image retrieval agricultural condition parameters, and produced a rice false smut disease distribution map of the study area combined with the meteorological data.