Vegetation resistance and resilience evaluation system and method under drought stress

Abstract

The invention discloses a vegetation resistance and resilience evaluation system and method under drought stress, and belongs to the field of global change ecology research. Comprising the following steps: collecting related data of vegetation resistance and restoring force by using a data collection module, and inputting the related data of vegetation resistance and restoring force into a data storage module for storage, a vegetation physiological index processing sub-module, a vegetation structure index processing sub-module and a vegetation function index processing sub-module in the data processing module are called to process the collected and stored data; and calling a lag accumulation correlation coefficient calculation sub-module, a vegetation resistance index and restoring force index evaluation model sub-module and a vegetation resistance and restoring force grade division sub-module in the analysis and evaluation module, and finally outputting vegetation resistance and restoring force evaluation grades. According to the method, comprehensive, systematic and accurate evaluation and grading can be carried out on the resistance and the restoring force of the vegetation under drought stress, the vegetation which is difficult to resist drought or is restored after drought stress in the evaluation area is effectively identified, and the method is simple to operate and easy to realize.

Description

Technical Field

[0001] The invention relates to the field of global change ecology, and in particular to a system and method for evaluating vegetation resistance and resilience under drought stress based on hysteresis and cumulative effects. Background Art

[0002] Under the background of global change, the trend of warming and drying is obvious. Warming accelerates the evaporation process, leading to an increase in the frequency, intensity and duration of drought. Climate change, especially drought, affects the physiological and biochemical processes of vegetation, such as stomatal regulation, transpiration, chlorophyll recovery, etc., and further affects the ecosystem structure, such as the phenomenon of dry leaves or death in the canopy structure of trees. When the degree of drought exceeds the maximum adaptation range of vegetation, vegetation growth is inhibited, resulting in damage to ecosystem functions, reduced productivity, and reverse succession. Whether vegetation can maintain normal life activities after experiencing stress depends on resistance and resilience. Resistance is the ability of vegetation to resist stress and maintain its original state; resilience is the ability of vegetation to adjust its survival strategy and restore itself to its original state after the original state of stress is destroyed. Therefore, evaluating the resistance and resilience of vegetation to drought is of great scientific significance for in-depth research on the physiological and biochemical mechanisms of vegetation to drought and predicting the response laws of vegetation under the background of global warming in the future. However, since the growth and development process of vegetation is indirectly affected by drought stress at a previous point in time or time period, the time lag effect and cumulative effect of this indirect impact and the complex response process of vegetation to drought stress make accurate assessment of vegetation's resistance and resilience to drought stress a difficult and hot topic in current research.

[0003] Most of the existing models and methods for evaluating vegetation resistance and resilience under drought stress (such as the "ball-cup" model, the CENTURY model, the controlled experiment method, and the multi-index comprehensive evaluation method) focus on the resistance and resilience of vegetation to a certain response level (such as physiology, structure, function, etc.) to drought stress. They focus on a single response level of vegetation as the research object, lack comprehensive evaluation of vegetation resistance and resilience at all response levels, and are difficult to identify vegetation with low resistance and resilience in the evaluation area from the source. They are less scientific and comprehensive in the actual business scenarios of regional ecological restoration and management. In addition, the existing methods for evaluating vegetation resistance and resilience are relatively inaccurate, and it is easy to irrationally divide the levels of vegetation resistance and resilience, making it difficult to scientifically and accurately evaluate vegetation resistance and resilience. Moreover, the evaluation of vegetation resistance and resilience mainly relies on manual statistics and calculations, resulting in low accuracy of the evaluation and the inability to intuitively understand the accurate evaluation situation. Summary of the invention

[0004] Technical problem: The present invention aims to provide a system and method for evaluating vegetation resistance and resilience under drought stress based on hysteresis and cumulative effects. The system and method take vegetation under drought stress as the evaluation object and are based on the physiological, structural and functional response levels of vegetation to comprehensively, systematically and accurately evaluate vegetation resistance and resilience under drought stress, laying a foundation for future studies on ecosystem stability evaluation and dynamic prediction of ecosystem stability under future climate change. Therefore, the invention of a system and method for evaluating vegetation resistance and resilience under drought stress based on hysteresis and cumulative effects is of great value.

[0005] The present invention adopts the following technical scheme: a method for evaluating vegetation resistance and resilience under drought stress, comprising the following steps:

[0006] Taking the vegetation under drought stress in the assessment area as the assessment object, obtaining and storing the data on the resistance and resilience of the vegetation in the assessment area;

[0007] According to the different response levels of vegetation under drought stress, the lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales was established. Then, the vegetation resistance index and resilience index evaluation model were established according to the vegetation index and lagged cumulative correlation coefficient corresponding to each response level of vegetation under drought stress, and the vegetation resistance index and resilience index of all response levels were integrated.

[0008] According to the vegetation resistance and resilience classification method, the vegetation resistance index and resilience index are divided into several levels. According to the divided levels, the resistance and resilience of vegetation to drought stress are evaluated.

[0009] The vegetation resistance and resilience data include: remote sensing image data, vegetation index data, and drought index data.

[0010] The lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales is as follows:

[0011]

[0012] In the formula, E s represents the time series of vegetation index; is the time series of drought index; i is the lag time of vegetation index relative to drought index, N is the longest lag time of vegetation index relative to drought index; f is the cumulative impact time of drought index on vegetation index, in months, f = 1, 2, 3…48; t n For time; and are respectively the average values ​​of the vegetation index and the drought index; the vegetation index is one of the vegetation physiological index, the vegetation structural index and the vegetation functional index;

[0013] When the lagged cumulative correlation coefficient LCCC reaches its maximum value, the lag time i value of the corresponding vegetation index relative to the drought index and the cumulative impact time f value of the drought index on the vegetation index are recorded.

[0014] The vegetation resistance index and resilience index evaluation model is established according to the vegetation index and the lagged cumulative correlation coefficient corresponding to each response level of the vegetation under drought stress, and is obtained by the following formula:

[0015]

[0016] Where V k represents the vegetation index corresponding to the kth response level; is the standardized precipitation evapotranspiration index at time ti, f is the time scale of the SPEI index, i and f are obtained by establishing the lagged cumulative correlation coefficient LCCC between the vegetation index and the SPEI index at different time scales; ε t is the model residual.

[0017] The vegetation resistance index and resilience index of all response levels are as follows:

[0018]

[0019] Where, VS represents the vegetation resistance index; α k represents the resistance index corresponding to the kth response level of vegetation under drought stress; VL represents the vegetation resilience index; β k represents the resilience index corresponding to the kth response level of vegetation under drought stress; w k represents the weight corresponding to the kth response level of vegetation under drought stress; m represents the type of response level;

[0020] Among them, α k , β k Obtained by evaluating model fit.

[0021] According to the vegetation resistance and resilience classification method, the vegetation resistance index and the resilience index are classified into several levels, and the resistance and resilience of vegetation to drought stress are evaluated according to the classified levels, including the following steps:

[0022] The vegetation resistance index and resilience index are normalized, compared with the set threshold range, and divided into multiple levels; the vegetation resistance index and resilience index are visualized based on regional display;

[0023] The larger the resistance index and resilience index, the smaller the resistance and resilience of the vegetation.

[0024] A system for assessing vegetation resistance and resilience under drought stress, comprising:

[0025] The data collection module is used to obtain vegetation resistance and resilience data;

[0026] The data storage module is used to store the vegetation resistance and resilience data;

[0027] The data processing module is used to process the vegetation index corresponding to each response level according to the response level of vegetation to drought stress;

[0028] The analysis and evaluation module is used to analyze and evaluate the resistance and resilience of vegetation.

[0029] The data processing module comprises:

[0030] The vegetation physiological index processing submodule is used to obtain the vegetation physiological index according to the vegetation index data;

[0031] The vegetation structure index processing submodule is used to obtain the vegetation structure index based on remote sensing image data;

[0032] The vegetation function index processing submodule is used to obtain the vegetation function index according to the vegetation index data.

[0033] The analysis and evaluation module comprises:

[0034] The lagged cumulative correlation coefficient calculation submodule is used to establish the lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales according to the different response levels of vegetation under drought stress;

[0035] The vegetation resistance index and resilience index evaluation model submodule is used to establish the vegetation resistance index and resilience index evaluation model according to the vegetation index and lagged cumulative correlation coefficient corresponding to each response level of vegetation under drought stress, and integrate the vegetation resistance index and resilience index of all response levels;

[0036] The vegetation resistance and resilience grading submodule is used to divide the vegetation resistance index and resilience index into several grades according to the vegetation resistance and resilience grading method, and evaluate the resistance and resilience of vegetation to drought stress according to the divided grades.

[0037] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the method for evaluating vegetation resistance and resilience based on hysteresis and cumulative effects under drought stress is implemented.

[0038] The present invention produces the following beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0039] (1) The vegetation resistance and resilience assessment system under drought stress based on hysteresis and cumulative effects of the present invention comprises a data collection module, a data storage module, a data processing module and an analysis and assessment module; the system can complete data collection, data storage, and vegetation resistance and resilience assessment, automatically complete the entire assessment process of vegetation resistance and resilience, and visualize it, so that environmental protection departments can more quickly and conveniently carry out scientific and systematic protection and restoration of vegetation under drought stress.

[0040] (2) The present invention provides a system and method for evaluating the resistance and resilience of vegetation under drought stress. Based on the hysteresis and cumulative effects, the system and method take the vegetation under drought stress as the object, and construct a vegetation resistance index and resilience index evaluation model according to the vegetation index corresponding to each response level of the vegetation under drought stress and the hysteresis cumulative correlation coefficient. The vegetation index corresponding to each response level of the vegetation under drought stress is used to characterize the degree of influence of drought stress on different levels of vegetation. When calculating the index, the different levels of vegetation response to drought stress are considered, rather than being limited to a single level, so that the method of the present invention is more accurate and comprehensive, and the comprehensive evaluation of vegetation resistance and resilience is more scientific and systematic.

[0041] (3) The vegetation resistance index and resilience index evaluation model constructed by the method of the present invention can individually evaluate the resistance and resilience of vegetation at each response level under drought stress, as well as the comprehensive resistance and resilience of all response levels. By evaluating the resistance and resilience of vegetation, it is possible to identify from the source the vegetation that is difficult to resist and recover under drought stress in the evaluation area, thereby enabling relevant departments to scientifically and accurately prevent the adverse effects of drought stress on vegetation. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a framework diagram of the vegetation resistance and resilience evaluation system under drought stress based on hysteresis and cumulative effects of the present invention;

[0043] Figure 2 The present invention is a flow chart of a method for evaluating vegetation resistance and resilience under drought stress. DETAILED DESCRIPTION

[0044] The present invention will be further described below in conjunction with the embodiments and the accompanying drawings.

[0045] The present invention is a system and method for evaluating the resistance and resilience of vegetation under drought stress based on hysteresis and cumulative effects. Taking vegetation under drought stress as the object, the system scientifically and accurately evaluates and analyzes the resistance and resilience of vegetation to drought stress, determines the ability of vegetation to resist drought and recover from drought stress to its original state, thereby being able to identify vegetation that is difficult to resist and recover under drought stress from the source, and further scientifically and effectively manage the vegetation in the region.

[0046] Combination Figure 1 As shown, the vegetation resistance and resilience assessment system based on hysteresis and cumulative effects under drought stress of the present invention comprises a data collection module, a data storage module, a data processing module and an analysis and assessment module; the data collection module is used to collect vegetation resistance and resilience related data; the data storage module is used to store the vegetation resistance and resilience related data; the data processing module is provided with a plurality of sub-data processing modules according to the response level of vegetation to drought stress, and is used to process the vegetation index corresponding to each response level;

[0047] In the embodiment of the present invention, the response level of vegetation to drought stress includes three response levels: physiological, structural and functional. Therefore, three sub-data processing modules are set in the corresponding data processing module, namely, a vegetation physiological index processing sub-module, a vegetation structural index processing sub-module, and a vegetation functional index processing sub-module. The vegetation physiological index processing sub-module is used to process the vegetation physiological index corresponding to the vegetation physiological response level; the vegetation structural index processing sub-module is used to process the vegetation structural index corresponding to the vegetation structural response level; the vegetation functional index processing sub-module is used to process the vegetation functional index corresponding to the vegetation functional response level.

[0048] The vegetation resistance and resilience assessment system of the present invention can be used for the assessment of vegetation resistance and resilience. With the help of the system, the entire process of vegetation resistance and resilience assessment, including data collection, data storage, and grade assessment, can be completed, thereby conducting a scientific and comprehensive assessment of the resistance and resilience of vegetation under drought stress.

[0049] The method for evaluating vegetation resistance and resilience under drought stress based on hysteresis and cumulative effects of the present invention uses the system for evaluating vegetation resistance and resilience under drought stress based on hysteresis and cumulative effects of the present invention to evaluate vegetation resistance and resilience. Figure 2As shown, the method first determines the assessment area, and determines the vegetation under drought stress in the assessment area through investigation and analysis of the basic conditions of regional vegetation. Usually, a certain type of vegetation or vegetation within a certain range is selected as the assessment object according to the assessment requirements. Through the data collection module, the vegetation resistance and resilience related data in the assessment area are collected, and the vegetation resistance and resilience related data include remote sensing image data, vegetation index data, and drought index data, and the vegetation resistance and resilience related data are stored in the data storage module, so as to evaluate the vegetation resistance and resilience under drought stress based on these data.

[0050] After the preliminary work is completed, for different response levels of vegetation under drought stress, a vegetation resistance index and resilience index evaluation model is established according to the vegetation index corresponding to each response level of vegetation under drought stress and the lagged cumulative correlation coefficient. The vegetation resistance index and resilience index evaluation model includes the resistance index and resilience index corresponding to each response level of vegetation under drought stress and the vegetation resistance index and resilience index of all response levels. The constructed vegetation resistance index and resilience index evaluation model is placed in the analysis and evaluation module of the vegetation resistance and resilience evaluation system based on hysteresis and cumulative effects under drought stress, so that the vegetation resistance and resilience evaluation system based on hysteresis and cumulative effects under drought stress can evaluate vegetation resistance and resilience more scientifically and accurately.

[0051] The vegetation index corresponding to each response level of vegetation under drought stress is used to characterize the impact of drought stress on different levels of vegetation, and the lagged cumulative correlation coefficient is used to identify the time and scale of drought stress that causes vegetation resistance and recovery. The constructed vegetation resistance index and resilience index evaluation model, based on the hysteresis and cumulative effects, considers the physiological response level, structural response level and functional response level of vegetation to drought stress, making the evaluation of vegetation resistance and resilience more accurate and comprehensive.

[0052] In the embodiment of the present invention, the response levels of vegetation to drought stress include physiology, structure, and function, so the corresponding vegetation index includes: vegetation physiological index, vegetation structural index, and vegetation functional index; the corresponding vegetation resistance index includes: vegetation physiological resistance index, vegetation structural resistance index, and vegetation functional resistance index; the corresponding vegetation resilience index includes vegetation physiological resilience index, vegetation structural resilience index, and vegetation functional resilience index. The calculation of these indexes and the construction process of the evaluation model are described in detail below in conjunction with the specific implementation process.

[0053] 1. Calculate vegetation index: In the embodiment of the present invention, three response levels of the vegetation under drought stress are included, namely, physiological, structural and functional. Correspondingly, the vegetation index includes a vegetation physiological index, a vegetation structural index and a vegetation functional index.

[0054] For vegetation physiological index, sunlight-induced chlorophyll fluorescence (SIF) is a long-wave signal released by vegetation during photosynthesis, which can reflect the actual dynamic changes of vegetation from a physiological level. Therefore, SIF is used as a vegetation physiological index. The SIF dataset is extracted from the database, and the SIF data is clipped using the boundary vector data of the study area to obtain the vegetation physiological index of the study area.

[0055] For the vegetation structure index, the enhanced vegetation index (EVI) is an improvement on the normalized vegetation index (NDVI). It has unique advantages in dynamic detection of vegetation structure by correcting soil reflection and atmospheric scattering. Therefore, EVI is selected as the vegetation structure index. Landsat remote sensing images with less than 10% cloud cover in the vegetation growing season are extracted from the database, and the images are calibrated by radiation and atmospheric correction. The remote sensing images of the study area are obtained by clipping with the boundary of the study area as a mask. Finally, the batch operation of EVI is realized through the Google Earth Engine platform. The calculation formula is as follows:

[0056]

[0057] In the formula, ρ NIR is the reflectivity in the near-infrared band; ρ Red is the reflectivity in the infrared band; ρ Blue is the reflectivity of the blue light band; G is the adjustment coefficient, G = 2.5; C 1 , C 2 is the atmospheric correction parameter, C 1 =6, C 2 =7.5; L is the soil adjustment factor, L = 1. After calculation, it is derived to obtain the vegetation structure index of the study area.

[0058] For the vegetation function index, gross primary productivity (GPP) is the total amount of organic carbon fixed by vegetation in a unit time by absorbing carbon dioxide in the atmosphere through photosynthesis. It represents the production function of vegetation, so GPP is used as the vegetation function index. The MODIS MOD17A3HGF.v006 version dataset was extracted from the database, and the GPP data was extracted, spliced ​​and mosaicked through the MODIS Reprojection Tool. Finally, the vegetation function index of the study area was obtained by clipping the vector data of the study area boundary.

[0059] 2. Constructing vegetation resistance index and vegetation resilience index evaluation model

[0060] 2.1 Establishment of lagged cumulative correlation coefficient (LCCC): In order to clarify the time point and time scale of drought stress that causes vegetation resistance and recovery, the lagged cumulative correlation coefficient (LCCC) was constructed using the Pearson correlation coefficient method:

[0061]

[0062] In the formula, E s is the time series of vegetation index; is the time series of drought index; i is the lag time of vegetation index relative to drought stress; f is the cumulative impact time of drought stress on vegetation index, f = 1, 2, 3…48; t n is the time (month); and are the average values ​​of vegetation index and drought index, respectively. When LCCC reaches the maximum value, the corresponding i and f values ​​are recorded to determine the SPEI month and time scale that causes vegetation resistance and recovery.

[0063] 2.2. Calculate the vegetation resistance index and vegetation resilience index: The vegetation resistance index and vegetation resilience index are used to characterize the resistance and recovery level of vegetation to drought stress. In the embodiment of the present invention, the vegetation response to drought stress includes three response levels: physiological, structural, and functional. Correspondingly, the vegetation resistance index includes: vegetation physiological resistance index, vegetation structural resistance index, and vegetation functional resistance index; the vegetation resilience index includes vegetation physiological resilience index, vegetation structural resilience index, and vegetation functional resilience index. The vegetation physiological index, vegetation structural index, and vegetation functional index data obtained and calculated in 1 and the SPEI data identified in 2.1 are respectively input into the vegetation physiological resistance index and vegetation physiological resilience index evaluation model, the vegetation structural resistance index and vegetation structural resilience index evaluation model, and the vegetation functional resistance index and vegetation functional resilience index evaluation model.

[0064] The evaluation model of vegetation physiological resistance index and vegetation physiological resilience index is:

[0065]

[0066] In the formula, α SIF is the vegetation physiological resistance index; β SIF is the vegetation physiological resilience index; f(SIF) t is the vegetation physiological index at time t; is the standardized precipitation evapotranspiration index at time ti, f is the time scale of the SPEI index, i and f are obtained by establishing the lagged cumulative correlation coefficient (LCCC) between the vegetation physiological index and the SPEI index at different time scales; ε t is the model residual;

[0067] The evaluation model of vegetation structure resistance index and vegetation structure resilience index is:

[0068]

[0069] In the formula, α EVI is the vegetation structure resistance index; β EVI f(EVI) is the vegetation structure resilience index; t is the vegetation structure index at time t; is the standardized precipitation evapotranspiration index at time ti, f is the time scale of the SPEI index, i and f are obtained by establishing the lagged cumulative correlation coefficient (LCCC) between the vegetation structure index and the SPEI index at different time scales; ε t is the model residual;

[0070] The evaluation models of vegetation function resistance index and vegetation function resilience index are as follows:

[0071]

[0072] In the formula, α GPP is the vegetation functional resistance index; β GPP is the vegetation functional resilience index; f(GPP) t is the vegetation function index at time t; is the standardized precipitation evapotranspiration index at time ti, f is the time scale of the SPEI index, i and f are obtained by establishing the lagged cumulative correlation coefficient (LCCC) between the vegetation function index and the SPEI index at different time scales; ε t is the model residual.

[0073] Among them, α SIF and β SIF It is obtained by fitting the evaluation model of vegetation physiological resistance index and vegetation physiological resilience index; α EVI and β EVI It is obtained by fitting the vegetation structure resistance index and vegetation structure resilience index evaluation model; α GPP and β GPP It is obtained by fitting the vegetation function resistance index and vegetation function resilience index assessment model.

[0074] 2.3. Calculate the vegetation resistance index and resilience index of each response level: SIF , β SIF , α EVI , β EVI , α GPP , β GPP Substitute the following formula:

[0075] VS=w SIF α SIF +w EVI α EVI +wGPP α GPP

[0076] VL=w SIF β SIF +w EVI β EVI +w GPP β GPP

[0077] Where, VS is the vegetation resistance index; α SIF is the vegetation physiological resistance index; α EVI is the vegetation structure resistance index; α GPP is the vegetation functional resistance index; VL is the vegetation resilience index; β SIF is the vegetation physiological resilience index; β EVI is the vegetation structure resilience index; β GPP is the vegetation functional resilience index; w SIF 、w EVI 、w GPP are the weight of vegetation physiological resistance, the weight of vegetation structural resilience, and the weight of vegetation functional resilience. Since the importance of physiology, structure, and function of vegetation in the process of growth and development is the same, w SIF =w EVI =w GPP =1 / 3. The larger the absolute values ​​of VS and VL, the smaller the resistance and recovery of vegetation.

[0078] 3. Construct a classification of vegetation resistance and resilience

[0079] The vegetation resistance and resilience calculated in 2 are normalized to a value range of 0-1, and the vegetation resistance and resilience are divided into 5 levels as shown in the table. The classification criteria are shown in Table 1:

[0080] Table 1

[0081]

[0082] Visualization of vegetation resistance index and resilience index based on regional display.

[0083] The present invention takes vegetation under drought stress as the evaluation object and is based on the physiological, structural and functional response levels of vegetation. It can comprehensively, systematically and accurately evaluate and grade the resistance and resilience of vegetation under drought stress, and effectively identify vegetation in the evaluation area that is difficult to resist drought or recover from drought stress. The operation is simple and easy to implement.

Claims

1. A method for evaluating vegetation resistance and resilience under drought stress, characterized in that: The following steps are involved: Taking the vegetation under drought stress in the assessment area as the assessment object, obtaining and storing the data on the resistance and resilience of the vegetation in the assessment area; According to the different response levels of vegetation under drought stress, the lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales was established. Then, the vegetation resistance index and resilience index evaluation model were established according to the vegetation index and lagged cumulative correlation coefficient corresponding to each response level of vegetation under drought stress, and the vegetation resistance index and resilience index of all response levels were integrated. According to the vegetation resistance and resilience classification method, the vegetation resistance index and resilience index are divided into several levels. According to the divided levels, the resistance and resilience of vegetation to drought stress are evaluated.

2. The method for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: The vegetation resistance and resilience data include: remote sensing image data, vegetation index data, and drought index data.

3. The method for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: The lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales is as follows: In the formula, E s represents the time series of vegetation index; is the time series of drought index; i is the lag time of vegetation index relative to drought index, N is the longest lag time of vegetation index relative to drought index; f is the cumulative impact time of drought index on vegetation index, in months, f = 1, 2, 3…48; t n For time; and are respectively the average values ​​of the vegetation index and the drought index; the vegetation index is one of the vegetation physiological index, the vegetation structural index and the vegetation functional index; When the lagged cumulative correlation coefficient LCCC reaches its maximum value, the lag time i value of the corresponding vegetation index relative to the drought index and the cumulative impact time f value of the drought index on the vegetation index are recorded.

4. The method for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: The vegetation resistance index and resilience index evaluation model is established according to the vegetation index and the lagged cumulative correlation coefficient corresponding to each response level of the vegetation under drought stress, and is obtained by the following formula: Where V k represents the vegetation index corresponding to the kth response level; is the standardized precipitation evapotranspiration index at time ti, f is the time scale of the SPEI index, i and f are obtained by establishing the lagged cumulative correlation coefficient LCCC between the vegetation index and the SPEI index at different time scales; ε t is the model residual.

5. The method for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: The vegetation resistance index and resilience index of all response levels are as follows: Where, VS represents the vegetation resistance index; α k represents the resistance index corresponding to the kth response level of vegetation under drought stress; VL represents the vegetation resilience index; β k represents the resilience index corresponding to the kth response level of vegetation under drought stress; w k represents the weight corresponding to the kth response level of vegetation under drought stress; m represents the type of response level; Among them, α k , β k Obtained by evaluating model fit.

6. The method for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: According to the vegetation resistance and resilience classification method, the vegetation resistance index and the resilience index are classified into several levels, and the resistance and resilience of vegetation to drought stress are evaluated according to the classified levels, including the following steps: The vegetation resistance index and resilience index are normalized, compared with the set threshold range, and divided into multiple levels; the vegetation resistance index and resilience index are visualized based on regional display; The larger the resistance index and resilience index, the smaller the resistance and resilience of the vegetation.

7. The system for evaluating vegetation resistance and resilience under drought stress according to claim 1, characterized in that: include: The data collection module is used to obtain vegetation resistance and resilience data; The data storage module is used to store the vegetation resistance and resilience data; The data processing module is used to process the vegetation index corresponding to each response level according to the response level of vegetation to drought stress; The analysis and evaluation module is used to analyze and evaluate the resistance and resilience of vegetation.

8. The system for evaluating vegetation resistance and resilience under drought stress according to claim 7, characterized in that: The data processing module comprises: The vegetation physiological index processing submodule is used to obtain the vegetation physiological index according to the vegetation index data; The vegetation structure index processing submodule is used to obtain the vegetation structure index based on remote sensing image data; The vegetation function index processing submodule is used to obtain the vegetation function index according to the vegetation index data.

9. The system for evaluating vegetation resistance and resilience under drought stress according to claim 7, characterized in that: The analysis and evaluation module comprises: The lagged cumulative correlation coefficient calculation submodule is used to establish the lagged cumulative correlation coefficient between the vegetation index and the SPEI index at different time scales according to the different response levels of vegetation under drought stress; The vegetation resistance index and resilience index evaluation model submodule is used to establish the vegetation resistance index and resilience index evaluation model according to the vegetation index and lagged cumulative correlation coefficient corresponding to each response level of vegetation under drought stress, and integrate the vegetation resistance index and resilience index of all response levels; The vegetation resistance and resilience grading submodule is used to divide the vegetation resistance index and resilience index into several grades according to the vegetation resistance and resilience grading method, and evaluate the resistance and resilience of vegetation to drought stress according to the divided grades.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the method for evaluating vegetation resistance and resilience based on hysteresis and cumulative effects under drought stress as described in any one of claims 1 to 6 is implemented.

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