Vegetation index prediction method, system and device based on classification and regression tree algorithm

Abstract

The invention relates to a vegetation index prediction method, a system and a device based on a classification and regression tree algorithm. The method comprises the steps of through using vegetationindexes as dependent variables; and constructing a classification and regression tree model by taking the global land data assimilation system basin surface model data set and the elevation data as independent variables, classifying the sample data by utilizing the classification and regression tree model, predicting a vegetation index of a target time period according to a classification result,and obtaining a vegetation index prediction result. Compared with the prior art, the problem of lack of vegetation indexes in the prior art is solved, a user can use the method to realize vegetationindex prediction in any time period, and vegetation index data are perfected.

Description

Technical field [0001] The present invention relates to the technical field of geographic information, in particular to a vegetation index prediction method, system and equipment based on classification and regression tree algorithms. Background technique [0002] The vegetation index is a numerical value extracted from multi-spectral remote sensing data that can effectively measure the condition of surface vegetation, and has a good correlation with vegetation coverage and biomass. However, the existing vegetation index data involves a relatively short period of time. Due to the huge amount of vegetation index data, the calculation process is complicated, and there is no method to extract the long-term vegetation index. The long-term vegetation index reflects the surface vegetation conditions and cycles of the area. It plays an important role in the study of the regional ecological environment carrying capacity. Summary of the invention [0003] The purpose of the present invent...

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Problems solved by technology

However, the time period involved in the existing vegetation index data is relatively short. Due to the huge amount of vegetation index data, the calculation process is complicated, and there is no method to extract the long-term vegetation index. It plays an important role in the change of nature and the carrying capacity of the ecological environment in the research area.

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