Based On Remote Sensing Of The Crop Diseases And Pest Monitoring Method Study

It has important significance to improve monitoring the diseases and pest level and to maintain food security and ecological environment protection in China. As a large, fast, no damage, no pollution monitoring technology, remote sensing monitoring can realize the unity of the economy, society and environment. In this paper, we take Xiangfan district in Hubei province as a case, the method of the application of satellite remote sensing technology in pest monitoring was studied.1. Hyperspectral monitoringThere is a distinct difference on the chlorophyll content between the disease and health leaves after analyzing. Therefore the following bands, 470nm, 550nm, 635nm, 680nm, 800nm, sensitive to chlorophyll are used to monitoring the disease leaves. Combined with the measured chlorophyll content, the model for estimating chlorophyll content is constructed.The model can be used evaluating the extent of the wheat rust.The research of the canopy scale is based on the quantitative analysis on the first-order differential spectrum characteristics of the disease and health canopy. The following parameters, Db, Dy, Dr, Dinr, Rg, Ro, SDr/ SDb and SDinr/ SDb, are selected as hyperspectral characteristic parameters to diagnose the wheat yellow rust disease.2. Habitat factor monitoringThrough the correlation analysis between the average temperature, average maximum temperature, average minimum temperature and the rate of the winter-wheat yellow rust, the results indicate that:The main habitat factor influence the winter-wheat yellow rust occurrence is the month average maximum temperature in January, February, June and July, while the influence of the precipitation is less. Also causes a brief analysis. A forecasting model of the winter-wheat yellow rust occurrence is established according to the historical material, which can as the assistance method to monitoring the winter-wheat yellow rust.3. Remote sensing monitoring on the vegetation indexThe vegetation index NDVI was adopted for monitoring by comparison on various vegetation indexes. The TM image was selected on April 8th 2004 in Xiangfan Hubei province. First, winter-wheat is divided into three types using supervised classification method. Then the NDVI value is calculated. Finally the winter-wheat health status can be determined. The results showed that NDVI can be used to identified the health and disease region. It is in accord with the occurrence area.