IDL-oriented projection transformation algorithm

Abstract

The invention relates to an IDL-oriented projection transformation algorithm. Arctic region data of global temperature data of UTM projection is transformed into polar region normal projection. Longitude and latitude (hereinafter referred to as global longitude and latitude) of the global temperature data of the UTM projection, longitude and latitude (hereinafter referred to as arctic longitude and latitude) of an arctic region of the polar region normal projection, and the global temperature data are read by adopting an IDL; variables are defined for storing arctic temperature data after transformation; and a distance from each grid of the arctic longitude and latitude to each grid of the global longitude and latitude is calculated, the temperature data pointed by a global longitude and latitude index corresponding to a minimum distance is assigned to a variable grid pointed by an arctic longitude and latitude index, and all grids are circularly calculated in sequence to finally obtain arctic region temperature data of the polar region normal projection. According to the IDL-oriented projection conversion algorithm, a polar region part can be cut directly from data of global UTM projection and transformed into the polar region normal projection, so that the problem of difficulty in transforming original data of a global parameter into polar region data is solved.

Description

technical field [0001] The invention relates to an IDL-oriented projection conversion algorithm. It belongs to the technical field of remote sensing data processing. Background technique [0002] The IDL programming language is powerful and widely used in aerospace, remote sensing and geo-information fields. When many researchers study polar-related parameters such as temperature, sea temperature, wind, etc., they will encounter a problem. Data such as temperature, sea temperature, and wind are mostly global data projected by UTM, such as Figure 4 Shown is a map of global temperature distribution rather than regional data for the polar regions. Researchers cannot simply cut out part of the data in the polar regions, because the projection of the global data is different from the projection dedicated to the study of the polar regions, which brings more difficulties to researchers. However, there is currently no method to directly crop and convert data from global UTM proje...

AI Technical Summary

Problems solved by technology

Researchers cannot simply cut out part of the data in polar regions, because the projection of global data is different from the projection dedicated to studying polar regions, which brings more difficulties to researchers

However, there is currently no method to directly crop and convert data from global UTM projections to polar positive axis projections

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