Grasshopper Hazard Prediction GIS In The Region Around Qinghai Lake

In this dissertation, a geographic information system (GIS) for grasshopper hazard prediction in the region around Qinghai Lake was constructed. The system can be used to predict the spatial location, intensity and time of grasshopper outbreaks in advance and effectively and, therefore, the measures can be taken timely for mitigating the hazard loss caused by grasshoppers, and the risk of the hazard can be evaluated after the hazard.The geographic information system for grasshopper hazard prediction was established based on an integration of remote sensing and GIS technologies. The method of construction of the system is mainly a combination of those approaches such as RAD, Prototype and OOP, and programming based on GIS software ARCVIEW. This system has varied functions which include data collection, data editing, modeling calculation, spatial analysis, result statistics, data storage, data input and output, data maintenance and update, and map compilation and so one. However, the key function of the system is capable to make the prediction on grasshopper hazard including its intensity, location and area as soon as the parameters required for the models in the system are input.In addition, in order to acquire more accurately the data of grassland vegetation which is essential and indispensable for the running of the models in the system the studies on automatic recognition on TM images were completed. It is the studies which use the method of combining digital elevation model (DEM) with the remotely sensed TM data, and through a combination of quantitative analysis with statistic regressive analysis. The major purpose of the study is to realize the recovering processing of the original TM data, i.e. eliminating the negative impacts of ground topography to spectral radiometer features on the images. Moreover, in order to realize the automatic recognition on grassland vegetation thematic information the method of the recognition was also inveatigated based on the application of GIS data and the expert knowledge.