Infrared radiation normalization modeling method of different sensors applied to forest fire hotspot discrimination

Abstract

The invention relates to a multi-temporal infrared radiation normalization modeling method of different sensors applied to forest fire discrimination, including analyzing the infrared radiation characteristics of MODIS, AVHRR, and VIRR sensors; obtaining sensor MODIS brightness temperature values, AVHRR surface temperature, and VIRR brightness Temperature value; preprocessing; set the threshold through reflectivity, identify cloud and water bodies, and eliminate the identified cloud and water pixels, and calculate the NDVI value; standardize the infrared radiation data of MODIS, AVHRR, and VIRR sensors, Set the MODIS sensor as the standard sensor, normalize the infrared radiation data of the AVHRR and VIRR sensors, select the reference infrared image data and the infrared image data to be normalized for curve fitting and regression analysis, and determine the normalization of the infrared radiation of different sensors Parameters, establish a normalized model of infrared radiation of different sensors, and form a normalized image map of infrared radiation. The model established by the invention can better eliminate the influence of radiation difference, equally divide the atmospheric radiation error, and reduce the radiation difference from different time phases in the infrared band of the same sensor.

Description

Technical field [0001] The present invention relates to the technical field of forest fire monitoring, in particular to a method for normalizing infrared radiation of different sensors applied to forest fire hot spot discrimination. Background technique [0002] Remote sensing earth observation has decades of observation history. Due to different sensors used on spaceborne or airborne platforms, the acquired image data have different geometric, radiation and image characteristics. The existing remote sensing satellites are used in various applications such as meteorology, resources, oceans, and environmental disaster reduction, and have achieved industrial development in related fields. At the same time, they have accumulated many years of remote sensing data to record changes in the surface and atmosphere. Making full use of these precious historical resources is of great historical significance for global climate research, economic and social development and the progress of hum...

AI Technical Summary

Problems solved by technology

Although there are some methods that can achieve better results, there are still many shortcomings. Therefore, a method that can further improve the radiation normalization effect is needed

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