Method of predicting satisfaction degree of massive satellite observation requirements

Abstract

The invention relates to a method for predicting the satisfaction degree of massive satellite observation requirements. In the invention, by setting a user annual observation requirement format, the method is designed which includes automatically reading user observation requirements, performing regional division of the whole world in accordance with satellite orbit characteristics and satellite conventional operating characteristics, carrying out automatic matching with requirements in massive regions and different time periods, calculating the satisfaction degree and giving the calculation method of the effective satisfaction degree of the specified region, and the basis for the satisfaction degree and validity of the future acquisition of the user requirements is provided. According to the invention, the user satellite observation requirement format is formulated, an observational requirement library is established, a foundation is laid for automatically reading mass user requirements, decomposing according to the time period, the observation frequency and the satellite requirements and automatically calculating the satisfaction degree, the working efficiency and calculation accuracy are greatly improved, and the defects of low efficiency and long time consumption of a manual mode are overcome.

Description

technical field [0001] The invention belongs to the field of remote sensing satellite orbit forecasting, and relates to a method for predicting the satisfaction degree of massive satellite observation demands, in particular to a method for predicting the satisfaction degree of annual observation demands of massive users by using satellite orbit regression characteristics. Background technique [0002] Most of my country's remote sensing satellites adopt the characteristics of sun-synchronous return orbit, and the data have been widely used in land, forestry, water conservancy, environmental protection, agriculture and other fields, playing an important role. With the continuous deepening of the application of remote sensing data by users, the number of user observation needs continues to increase. The main users of land observation satellites put forward their observation needs for one year at the beginning of each year. Many, large area, high frequency, long time span and s...

AI Technical Summary

Problems solved by technology

However, the user's annual observation demand areas include large areas and small areas, as well as domestic and foreign areas. The number is large, and the time span is one year, and the observation frequency is high. For the observation needs of tens of thousands of large areas with a long time span, there is no To form a unified observation demand format and automatic, fast and effective algorithms, relying on manual participation in statistics, it is necessary to analyze user demand distribution, satellite orbit characteristics, observation frequency, and weather forecast calculations. The calculation workload is heavy, the work efficiency is low, and the cost is high.

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