A Drought Event Recognition Method Based on 3D Drought Body Structure

Abstract

The invention discloses a drought event identification method based on a three-dimensional drought body structure, which includes calculating the drought index and determining the threshold value of the drought index; preprocessing the drought index data, and importing the preprocessed drought index data into the Voxler platform; the drought index Data gridding; 3D drought volume structure extraction; obtaining the start and end time of drought events; optimizing the visual expression effect. The method of the present invention starts from the perspective of three-dimensional space-time, and based on the idea of ​​space-time clustering, proposes a method for completely extracting drought events, constructing a three-dimensional drought body structure, and simulating the development and evolution process of drought, which avoids the minimum drought area in the identification process of drought three-dimensional clustering algorithm The subjectivity of A0 parameter selection overcomes the defect of missing some mild drought events in the past drought identification, provides a new method and technology for the complete and accurate identification of the whole process of drought events, and also provides a comprehensive analysis and evaluation of drought time and space in the next step. The characteristics of evolution have laid a good foundation.

Description

technical field [0001] The invention relates to a drought recognition technology, in particular to a drought event recognition method based on a three-dimensional drought body structure. Background technique [0002] At present, most of the identification of drought events at home and abroad adopts a one-dimensional time identification method, that is, the Run Theory proposed by Yevjevich et al. (1967). A threshold is set for the time series of drought indicators. is a negative run, from which features such as drought duration, drought intensity, and drought intensity are extracted. There are also some studies that identify drought in two-dimensional space, and grasp the evolution trend and law of drought through the spatial distribution of drought index in different periods. For example, Andreadis (2005) used multiple consecutive spatially correlated soil moisture images to analyze the spatiotemporal development process of regional drought in the United States, searched an...

AI Technical Summary

Problems solved by technology

In previous drought identification methods, from one-dimensional run theory, two-dimensional space search to three-dimensional clustering algorithm, the identification results of drought events are usually compared with historical drought records or previous research results. The identification and statistical analysis of major drought events often filter out small drought events, so there is inevitably the defect of missing some mild drought events

Therefore, it is impossible to accurately analyze the evolution and development of the whole process of drought events under the coupling of different temporal and spatial scales

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