Grassland drought monitoring method comprehensively considering temperature and water stress

Abstract

The invention discloses a grassland drought monitoring method comprehensively considering temperature and water stress. The method comprises the following steps: S1, acquiring and processing large-scale remote sensing data; s2, constructing a drought monitoring model VDI; s3, dividing drought basic units of the research area; s4, based on the drought regionalization units, estimating a VDI weight coefficient in each regionalization unit; s5, determining a VDI drought level threshold value; and S6, obtaining a drought distribution result. According to the method, the defect that a drought index model only adopting the vegetation index and the land surface temperature cannot reflect the spatial distribution and change state of the drought in time is overcome, and the problem that the drought monitoring precision is influenced under the condition that the correlation between the temperature index and the vegetation index is not significant is solved; in addition, the defects of a single coefficient model are overcome, and the accuracy of large-scale grassland drought monitoring is effectively improved.

Description

technical field [0001] The invention relates to a drought monitoring method, in particular to a grassland drought monitoring method which comprehensively considers temperature and water stress. Background technique [0002] Drought lasts for a long time, affects a wide range, and occurs repeatedly in a short period of time. It is one of the most serious natural disasters that cause losses to human society, especially agricultural production, and has a significant impact on the development of the national economy. With the warming of the global climate, the frequency of drought has a clear upward trend. There are 2 billion people and 41% of the world are affected by drought in varying degrees. It is of great practical significance to accurately grasp the degree and distribution of drought, take effective measures for drought prevention and relief in time, and scientifically guide agricultural production. [0003] The traditional drought monitoring method is mainly based on t...

AI Technical Summary

Problems solved by technology

At present, most of the existing large-scale drought monitoring indexes are based on the negative correlation between surface temperature and vegetation index, and there are obvious deviations in the accuracy of drought monitoring in areas where surface temperature and vegetation index are positively correlated or not, and the vegetation index has a significant impact on soil The response of water and drought has a hysteresis, which is affected by factors such as surface atmospheric circulation in different regions, underlying surface conditions, and different growth periods. Accuracy cannot be effectively guaranteed

[0004] In summary, the existing grassland drought monitoring methods mainly have the following three major technical defects: First, the monitoring of drought requires real-time and rapid response, and the existing technology cannot obtain the dynamics of drought in time only by relying on vegetation index and temperature factors, resulting in The response to drought monitoring is not timely enough; second, it does not consider the case where the correlation between the vegetation index and the temperature index is not significant, resulting in a decrease in the accuracy of drought monitoring under the condition of no temperature stress; third, the existing technology only relies on a single coefficient model, The specificity of different underlying surface types is not considered, resulting in a very limited area and scope of application of the model

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