Remote Sensing Classification Of Forest Types

Forest was one of the most important resources. The capacity of the state forest resources could direct the conditions of forest production,the capacity of forest resources and the production of forest and so on. The forest resources in our country was wide distribution, with a the most plantation area in the world. Forest resource information was an important foundation for national information resources and an important basis for the decision of forestry building. The management and monitoring of forest resources was important for forest work. It was an important work that how to obtain forest resources information economically and efficiently.The traditional method of update forest information in the operation and management of forest resources was the forest investigation, which need great human resources and material resources, with an inaccurate result for the reality. A new research method was provided by Remote sensing, Geographic Information System technology and Global Positioning System technology. Remote Sensing technology was more macroscopic, more comprehensive, more repeatable, quicker and more economic than the traditional method. So Remote Sensing technology could obtain forest resources information economically and efficiently to provide an ideal tool for the research of forest resource and dynamic research. In this paper, the study area was TaHe Country, which was located in Daxing munitions. The forest cover type of the study area was extracted from the fore times remote sensing data, which was multi-spectral remote sensing data from 1970's to now, with the classification system of forest which was formulated according to reference, with the ideal to combine multiple methods of classification together. The results demonstrate that the application of the decision level fusion techniques could improve the accuracy of remote sensing classification efficiently to obtain the forest cover type of study area accurately, which provided a new ideal for the application of remote sensing for forest and had great theoretical and practical significance.