Dynamic filtering modeling downscaling method of environment variable on the basis of low-resolution satellite remote sensing data

Abstract

The invention discloses a dynamic filtering modeling downscaling method of an environment variable on the basis of low-resolution satellite remote sensing data. The dynamic filtering modeling downscaling method comprises the following steps: firstly, carrying out aggregation calculation on 1km environment variable factors including eight pieces of data i.e., a vegetation index, a digital evaluation model, daytime surface temperature, night surface temperature, a topographic wetness index, a gradient, a slope aspect and a slope length gradient, into 25km to serve as independent variables, and taking corresponding 25Km resolution TRMM (Tropical Rainfall Measuring Mission) 3B43 v7 precipitation data as a dependent variable. An M5 method divides data sets formed by each environment variable into different vector spaces according to geographical similarity, then, the most effect environment variable is independently dynamically filtered in different vector spaces, and a divisional multiple regression model is independently established in the corresponding vector space; and the model is finally applied to the 1km environment variable to finally obtain a precipitation product of the 1km resolution. A downscaling result obtained by partitioning and dynamic factor filtering is obviously superior to a downscaling result based on a conventional regression model.

Description

technical field [0001] The invention relates to a downscaling method for dynamic screening and modeling of environmental variables based on low-resolution satellite remote sensing data, in particular to a downscaling method for dynamic screening and modeling of regional environmental factors of TRMM 3B43 v7 precipitation data. technical background [0002] Precipitation plays an important role in the fields of hydrology, meteorology, ecology, and agricultural research, especially an important part of the conservation of matter-energy exchange. Surface observation station is a widely used means of precipitation measurement, and has the characteristics of high precision and mature technology. However, the precipitation monitored by surface observation stations only represents the precipitation at a certain distance from the surface observation stations and surrounding areas, so it is difficult to express the characteristics of precipitation distribution over a large area, espe...

AI Technical Summary

Problems solved by technology

However, the original resolution of the TRMM satellite is relatively low (spatial resolution is 0.25°, about 25km), and it has certain limitations and deviations in predicting regional-scale precipitation. Therefore, it is necessary to perform spatial scale conversion on the TRMM data to obtain Higher resolution precipitation measurements

However, there is still no method that can accurately predict precipitation in complex areas.

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