35 results about "Satellite precipitation" patented technology

A spatial autocorrelation machine learning-based downscaling method of satellite precipitation data includes obtaining the TRMM precipitation data and the land surface parameters; preprocessing the land surface parameters to obtain DEM, day land surface temperature, night surface land temperature, day-and-night land surface temperature difference and NDVI with spatial resolutions of 1 km and 25 km; performing a spatial autocorrelation analysis of the TRMM precipitation data to obtain an estimated spatial autocorrelation value of the precipitation data with a spatial resolution of 25 km; downscaling the spatial resolution of the spatial autocorrelation value of the precipitation data from 25 km to 1 km; establishing a nonlinear regression model; obtaining a precipitation downscaling data with a spatial resolution of 1 km based on the nonlinear regression model. A system and a terminal are also provided.

The invention discloses a CMORPH satellite precipitation data downscaling method based on Fuzzy-OLS (Ordinary Least Squares) and a multi-environment factor variable. The method comprises the following steps: firstly, aggregation calculation is carried out on 1km environment factor variables, i.e., eight pieces of data including a vegetation index, a digital elevation model, daytime surface temperature, night surface temperature, a topographic wetness index, a gradient, a slope direction and a slope length gradient to 25km to serve as independent variables, and the CMORPH data of a corresponding 25km resolution is used as a dependent variable. On the basis of a fuzzy aggregation idea, the optimal aggregation number and aggregation center of the environment variable under the scale of 25km can be calculated so as to divide a whole sample set into subsample sets with most prominent difference, so that samples in each subsample set have a maximum similarity, and a least square regression model is independently established for each subsample set so as to predict the downscaling precipitation data of 1km. A downscaling result based on the Fuzzy-OLS model is obviously superior to the downscaling result of a conventional regression model.

The invention discloses a self-adaptive dynamic fusion method of satellite-earth multi-source precipitation. and roughness; time-varying factors include: NDVI, wind speed, surface temperature, scattering index, and microwave polarization index; downscale each satellite to obtain fine-resolution precipitation for each satellite; construct an adaptive dynamic Bayesian framework , through the distribution conversion of precipitation error and the optimization of precipitation probability density function parameters to calculate the optimal weight of each satellite in the grid where the measured site is located; to calculate the optimal weight of each satellite’s fine-resolution grid, each satellite’s fine-resolution The weighted sum of the grid precipitation is used to obtain the fused precipitation. The invention fuses station precipitation and multi-satellite precipitation through an adaptive dynamic fusion method to obtain a fine-resolution fusion precipitation product, and provides data support for the input of a refined hydrological model.