Study On Remote Sensing Extraction Method Of Winter Wheat Irrigation Information

China is a country with severe water shortage,which is one of the thirteen water-deficient countries in the world.Per capita water consumption is one fourth of the world's per capita level.At the same time,China is also a large agricultural country,with a cultivated area of 2,024 million mu of cultivated land,ranking third in the world.Irrigation agriculture is the main direction of agricultural development in China.Irrigation area is an important base for agricultural development and a basic guarantee for national food security.At present,one of the most important problems of irrigated agriculture in China is that the domestic water resources are unevenly distributed,the water and soil resources are unbalanced,the groundwater resources are seriously over-exploited and the waste of irrigation water is very serious.The rapid expansion of large-scale irrigation has led to land salinization and lower groundwater levels.These problems have increased dramatically in the past few decades.Lack of awareness of agricultural water management may lead to unsustainable agriculture production because of the growing shortage of water resources in the future.So the development of efficient and water-saving irrigation agriculture is imminent.Mastering the accurate information of irrigation districts is an important basis for the development of high-efficiency water-saving irrigation.The basic data such as the planting structure and irrigated area of the main crops in the irrigated agricultural areas are the important prerequisites for rational allocation of water resources and the implementation of fine irrigation water planning.This thesis took Dingxing county as study area,based on long-term sequence Sentinel-2 satellite image data and SMAP Soil Moisture data,combined with field survey and measured data,using vegetation index analysis and decision tree classification method to extract winter wheat planting area in Dingxing County.Based on the perpendicular drought index PDI,an irrigation area monitoring model was established,which can extract the irrigated area of the study area.And the technical methods and applications of extraction winter wheat area irrigation information by remote sensing were studied.The main results of the thesis are as follows:(1)Winter wheat planting areas in Dingxing county was extract by remote sensing methodsm,Compared this results with local statistical results,the remote sensing results are well improved,and the consistency can reach 90.2%.(2)The irrigation areas in Dingxing county were extracted by the perpendicular drought index PDI during mid-November to early December of 2017 and late March to mid-April of 2018.It's found wintering water is mainly concentrated in the western,central and southern regions of the study area,while there are few in the southeastern region.The distribution of the latter is basically consistent with the former.Compared the remote sensing results of irrigated areas with the local statistical results,the extraction accuracy of soil moisture in pre-wintering is 75.6%,and the extraction accuracy of soil moisture in jointing is 81%.(3)A nonlinear model of irrigation information monitoring based on SMAP data was constructed and its feasibility was evaluated.SMAP soil moisture product data was suitable for extracting irrigation information from the intensive planting of winter wheat,the concentration of irrigation,and the daily minimum temperature above 0 degrees.In Dingxing County,the overall proportion of winter wheat planting is not high,and the irrigation behavior is more dispersed.The area has a lower temperature during the winter irrigation period.The SMAP data is not suitable for extracting winter wheat irrigation information during this period.However this data has a certain response to the irrigation during the winter wheat jointing stage.