Global Land Surface Data Generation Based On MODIS Data And Mid-infrared Characteristics Analysis And Application

With the rapid development of science and technology,more and more scientific researches are carried out on global large-scale change monitoring and characteristic analysis.Among them,emissivity and reflectivity data are physical quantities that characterize the target’s radiation ability,and are the study of global wide-scale characteristic analysis and radiation transmission.Key parameters in fields such as models.MODIS products have become the main data source for global scale research due to their high time sequence,large width and full spectrum imaging capabilities.However,MODIS data is affected by weather and other related images,and there will be data missing or invalid.Existing research mainly focuses on the application of global-scale data products.Therefore,how to quickly and effectively synthesize and automate global-scale data is also a key issue.problem.At the same time,the frequent occurrence of forest fires around the world in recent years has not only posed a huge threat to the Earth’s ecosystem,but also has a serious impact on human activities.Due to the advantages of high update frequency and wide detection range,satellites Remote sensing monitoring of fire points has also become an indispensable method for real-time monitoring,dynamics and tracking of post-disaster assessment.Among them,the medium and thermal infrared bands are more sensitive to high temperature signals such as forest fires and active volcanoes,which can effectively capture and identify high temperature targets,and have important application value for fire monitoring and prevention.Therefore,this article aims at how to quickly and effectively perform global large-scale data synthesis and fire point extraction and analysis of high-temperature targets,and finally generate global reflectance and emissivity surface data,and successfully extract forest and volcanic fire points.The specific content is as follows:1.Facing the problem of global large-scale data synthesis,carry out the synthesis of global reflectance and emissivity data to solve the invalid pixels or data missing due to sensor failure or the influence of factors such as cloud and deep sea when MODIS data is acquired The problem.2.In order to achieve the problem of rapid batch generation of global large-scale data,this paper takes MODIS’ reflectance and emissivity data as an example,and proposes a method to automatically generate global land surface data.3.Based on the rapid realization of the global large-scale data processing method,study the analysis of the fire spot area by the channel brightness temperature threshold method of the coupling of mid-infrared and thermal infrared.The MOD03 and MOD021KM products in Kilauea and Amazon are preprocessed to generate brightness temperature data,and then the corresponding band and algorithm are selected to complete the extraction of high temperature fire points.Finally,the difference between volcano and forest fire fire points is compared and analyzed.After analyzing the generated global large-scale data,it is found that,on the one hand,the method based on this article can repair the invalid and missing data to a greater extent,and can realize the full-process automatic large-scale data generation,which is a global large-scale.The related research has laid a good data foundation;on the other hand,based on mid-infrared data,this article uses high-temperature target characteristic analysis as a typical application to explore the channel brightness temperature threshold method of coupling mid-infrared and thermal infrared to extract and analyze the fire spot area.So as to provide a scientific basis for monitoring and early warning of volcanoes and forest fires.