Data mining-based drought monitoring method

Abstract

The invention discloses a data mining-based drought monitoring method. The method comprises the following steps: 1, data reconstruction is carried out on an MODIS vegetation index product, a land surface temperature product and an evapotranspiration product; 2, according to the vegetation index obtained in the first step and DEM data, downscaling is carried out on a TRMM rainfall product; 3, a vegetation anomaly index, a temperature anomaly index, an evapotranspiration anomaly index and a rainfall anomaly index are extracted again; and 4, a classification and regression tree model is used for building a statistical regression rule and a linear fitting model to obtain a drought monitoring model. Compared with the prior art, the method of the invention comprehensively considers multi-source remote sensing spatial information, such as the rainfall, the evapotranspiration, the vegetation growth state, the land using type, the altitude and other factors, in the case of drought monitoring, spatial data mining is adopted, the drought monitoring model is built, and the drought monitoring precision is improved.

Description

technical field [0001] The invention relates to the field of environmental monitoring, in particular to a drought monitoring method based on data mining. Background technique [0002] Traditional drought monitoring is limited to using soil water content data distributed on relatively sparse points on the ground to monitor drought conditions and distribution range. Due to the small amount of ground monitoring data and poor representation, dynamic monitoring of large-scale drought disasters cannot be realized. Satellite remote sensing information provides an efficient and convenient technical platform for large-scale drought disaster monitoring because of its macroscopic, dynamic, objective, and time-sensitive characteristics. [0003] Remote sensing technology is a necessary means to obtain distributed information on the land surface. Since remote sensing technology turned to civilian use, using remote sensing technology to monitor regional drought has become one of the mai...

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Problems solved by technology

[0009] Remote sensing drought monitoring methods are widely used because of their high spatio-temporal resolution and the ability to obtain regional continuous spatial drought conditions. However, previous remote sensing drought monitoring methods focused on considering single factors such as soil and vegetation, especially most It cannot reflect the precipitation profit and loss information in the drought-causing factors, and the single monitoring index generated from the vegetation index or surface temperature and their combination has great uncertainty in drought monitoring

With the development of microwave radar remote sensing technology, it is possible to obtain real-time atmospheric precipitation from a continuous space plane, especially the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite, which provides a new remote sensing data source for comprehensive drought monitoring. However, its spatial resolution is too coarse to reflect the finer surface coverage, and it is necessary to downscale the spatial precipitation before it can be used in drought monitoring.

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