All-weather surface temperature generation method integrating thermal infrared and reanalysis data

Abstract

The invention provides an all-weather surface temperature generation method integrating thermal infrared and reanalysis data, which is realized on the basis of random forest integrated thermal infrared remote sensing and reanalysis data. The method specifically comprises the following steps: performing data preprocessing and space-time matching; implementing a time algorithm; implementing a spacealgorithm; and generating the final 1km all-weather surface temperature. According to the invention, reanalysis data is introduced, a long surface temperature and related observation data can be provided, the data is integrated with thermal infrared satellite remote sensing to obtain all-weather surface temperature with long time sequence and high temporal-spatial resolution. The obtained surfacetemperature has good consistency with a traditional thermal infrared satellite remote sensing surface temperature product, and through the inspection of the actually measured surface temperature, theprecision is within an acceptable range, the image quality is higher, more space detail information of the surface temperature can be displayed, and the overall quality and precision are superior to those of a method for integrating thermal infrared satellite remote sensing data and passive microwave data.

Description

technical field [0001] The invention relates to the field of satellite remote sensing surface temperature product generation, in particular to a 1km all-weather surface temperature generation method based on random forest integration of thermal infrared remote sensing and reanalysis data. Background technique [0002] Land surface temperature (LST) is a very important physical quantity in the material circulation and energy exchange at the interface between the earth's surface and the atmosphere. Accurate estimation of surface temperature can promote energy cycle, climate forecast, agricultural production and so on. It is of great significance to grasp the temporal and spatial distribution of surface temperature on regional and global scales in time, especially the comprehensive, complete and continuous temporal and spatial distribution information of surface temperature, which is of great significance to the energy balance of the earth-atmosphere system and the study of eco...

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Problems solved by technology

However, in areas with frequent cloud cover like the Qinghai-Tibet Plateau, traditional surface temperature products cannot meet the application requirements of all-weather monitoring

The method of integrating thermal infrared and passive microwave data can generate all-weather surface temperature with higher resolution and effectively fill in the missing part of the data, but because the time span of the data source involved in this method is short, the time resolution is not enough to meet the Long time series, high spatial and temporal resolution surface temperature data production needs

Reanalysis data, such as the Global Land Data Assimilation System (GLDAS), can also provide temporal and spatial continuous all-weather surface temperature. Compared with traditional surface temperature products, reanalysis data can provide higher temporal resolution of surface temperature and its related parameters, but limited by its low spatial resolution, it cannot provide LST with sufficient spatial variation details in specific regional studies

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