Based On Modis Data And Meteorological Data, Vegetation Water Monitoring Study

Forest fire is a universal natural disaster with high frequency. It has random, sudden and regulary features. When forest fire has a certain forest vegetation, weather and terrain conditions, it can occur.Vegetation water content has an important role on the burning of forest. Deepen the study of vegetation water will contribute to a better understanding of forest vegetation growth and predict forest fire situation, and benefiting effective measures to prevent forest fires.In this paper, the research and work include:1. Elaborate the concept of vegetation water content, and make a brief description for the significance of vegetation water content monitoring, monitoring methods and techniques.2. Make a brief introduction of the EOS program involved in the research. The introduction explains the characteristics, technical indicators and band distribution of the MODIS instruments which are both on the Terra and Aqua satellites. It is also to the application of MODIS data products at different levels and fields as well as the relationship between various types of products. It makes a good foundation for the application of MODIS data in the study.3. The introduction summarizes the principles and methods of vegetation water content monitoring, including traditional manual method of sampling and monitoring and method of vegetation water content based on RS.4:In this study area, it uses remote sensing data and meteorological data to monitor vegetation water content, analysis methods and results.The innovation in this article:1.It makes a comprehensive and systematic summary of the characteristics of MODIS data and related applications.2. It summarizes the principles and methods of vegetation water content monitoring, including traditional manual method of sampling and monitoring and method of vegetation water content based on RS.3. On the experimental area, in accordance with the principles of hierarchical classification, it uses remote sensing data for vegetation water content monitoring. Meanwhile long series of meteorological data are used for secondary analysis. Finally, it validates the results.