Drought comprehensive monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses a drought comprehensive monitoring method and device, electronic equipment and a storage medium. The drought comprehensive monitoring method comprises the following steps: acquiring various observation data and a Palmer drought severity index within a preset time period; dividing the drought process into a first stage and a second stage, and dividing the plurality of basic drought indexes into a first type of drought indexes and a second type of drought indexes according to the drought process; a vegetation response factor of a first stage is obtained according to the first type of drought indexes and the Paralmer drought severity index, and a vegetation response factor of a second stage is obtained according to the second type of drought indexes and the Paralmer drought severity index; various drought stress indexes are obtained through the vegetation response factors and the corresponding basic drought indexes; and constructing a drought comprehensive index according to the plurality of drought stress indexes. According to the drought comprehensive monitoring method, the drought process can be decomposed in detail, the vegetation response difference is deeply coupled, and the requirements of drought early warning, disaster assessment, water resource management and the like can be met.

Description

Technical Field

[0001] The present invention relates to the technical field of drought monitoring, and more specifically, to a comprehensive drought monitoring method, device, electronic equipment and storage medium. Background Art

[0002] Drought is a serious natural disaster that affects a wide range of areas, including precipitation, temperature, soil moisture, vegetation growth, etc. Accurately and comprehensively revealing the manifestations of drought events in multiple dimensions and deeply exploring the overall characteristics of drought in terms of time and space play a vital role in regional water resources management, ecological and environmental protection, and global climate change assessment.

[0003] Drought index provides a quantitative representation of drought events and an efficient analytical tool for drought classification, drought impact assessment and comparison. According to the degree of integration of drought indices or products, existing drought indices can be divided into two categories: drought indices based on a single data source and comprehensive indices based on multiple data sources. Single drought indices are mainly represented by the following indices, including vegetation condition index (VCI), temperature condition index (TCI), soil moisture condition index (SMCI) and precipitation condition index (PCI). These indices have the advantages of strong physical mechanism, low data requirements and easy construction methods, but the complexity of the drought process leads to great limitations of a single drought index, which cannot fully reveal the overall characteristics of drought.

[0004] In addition, although the integrated drought monitoring method has made rapid progress in recent years in terms of the integration and fusion of single indices in multiple dimensions, it has neglected the deep characteristics of the drought process and has great defects in explaining the spatiotemporal evolution and intensity of drought, as shown in the following: (1) Vegetation has different sensitivities to drought stress during drought, and existing models and methods do not adequately consider this aspect when designing; (2) Existing models and methods focus on the deep integration of multiple indices, while neglecting the physical modeling of drought processes. In order to achieve more comprehensive and accurate drought monitoring, it is urgent to take into account the physical mechanism of drought impact propagation; (3) Drought is a physical process that develops slowly and accumulates gradually. Most existing technologies only focus on the drought stress caused by current environmental factors, but do not fully consider the historical cumulative effects of drought and the slow-changing characteristics of drought.

[0005] Due to the above-mentioned deficiencies, the existing drought monitoring methods have relatively low accuracy in reflecting the intensity, spatial scope and temporal evolution trend of drought stress, and there are large errors in drought monitoring results. Summary of the invention

[0006] The purpose of the present invention is to provide a new technical solution of a comprehensive drought monitoring method, device, electronic device and storage medium, which can deeply understand the influence mechanism of external drought conditions (such as precipitation, high temperature, soil moisture) on vegetation.

[0007] According to a first aspect of the present invention, a method for comprehensive drought monitoring is provided, comprising the following steps: obtaining a plurality of observation data and the Palmer Drought Severity Index within a preset time period; obtaining a plurality of basic drought indices for reflecting drought conditions based on the plurality of observation data; dividing the drought process into a first stage and a second stage, the first stage being from physical disaster factors to drought stress, and the second stage being from the drought stress to the impact of drought on vegetation, and dividing the plurality of basic drought indices into a first type of drought index and a second type of drought index according to the drought process, the first type of drought index being used to characterize the intensity of drought disaster factors from different angles, and the second type of drought index being used to measure the degree of impact of drought on vegetation; obtaining a vegetation response factor for the first stage according to the first type of drought index and the Palmer Drought Severity Index, and obtaining a vegetation response factor for the second stage according to the second type of drought index and the Palmer Drought Severity Index; obtaining a plurality of drought stress indices through the vegetation response factors and the corresponding basic drought indices; and constructing a comprehensive drought index according to the plurality of drought stress indices.

[0008] Optionally, the comprehensive drought monitoring method further comprises the following step: preprocessing the observation data, the preprocessing step comprising at least one of cloud removal in space, outlier removal and mean aggregation in time scale.

[0009] Optionally, the observation data includes at least one of remote sensing data, reanalysis data, land surface assimilation system data and Palmer Drought Severity Index.

[0010] Optionally, the first type of drought index includes a surface temperature condition index, a soil moisture condition index and a precipitation condition index, and the second type of drought index includes a vegetation condition index.

[0011] Optionally, the basic drought index is calculated on a time scale of one month.

[0012] Optionally, the step of constructing a comprehensive drought index according to the drought stress index adopts a principal component analysis method.

[0013] Optionally, the vegetation response factors include drought response factors of woodlands, grasslands and farmlands.

[0014] According to a second aspect of the present invention, a comprehensive drought monitoring device is provided, including: an observation data acquisition module, the observation data acquisition module is used to acquire a variety of observation data and the Palmer Drought Severity Index within a preset time period; a basic drought index acquisition module, the basic drought index acquisition module obtains a variety of basic drought indices for reflecting drought conditions based on the multiple observation data; a drought process stage model construction module, the drought process stage model is used to divide the drought process into a first stage and a second stage and obtain vegetation response factors corresponding to the first stage and the second stage, wherein the first stage is from physical disaster factors to drought stress, and the second stage is from the drought stress to the impact of drought on vegetation, and the multiple basic drought indices are obtained according to the drought process. The index is divided into a first-class drought index and a second-class drought index. The first-class drought index is used to characterize the intensity of drought disaster factors from different angles, and the second-class drought index is used to measure the impact of drought on vegetation. The drought process stage model obtains the vegetation response factor of the first stage according to the first-class drought index and the Palmer Drought Severity Index, and obtains the vegetation response factor of the second stage according to the second-class drought index and the Palmer Drought Severity Index; a drought stress index acquisition module, the drought stress index acquisition module obtains a variety of drought stress indices through the vegetation response factor and the corresponding basic drought index; a drought comprehensive index construction module, the drought comprehensive index construction module constructs a drought comprehensive index according to a variety of drought stress indices.

[0015] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor and a memory, wherein computer program instructions are stored in the memory, wherein when the computer program instructions are executed by the processor, the processor executes the steps of the above method.

[0016] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the steps of the above method.

[0017] In the embodiment of the present invention, an intermediate variable "drought stress" is proposed, and based on this intermediate variable, the drought process is decomposed into two drought sub-processes: (1) from physical disaster factors to drought stress; (2) from drought stress to vegetation being affected. This division helps to deeply understand the mechanism of the influence of external drought conditions (precipitation, high temperature, soil moisture) on vegetation.

[0018] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0020] Figure 1 is an overall flow chart of the comprehensive drought monitoring method according to an embodiment of the present invention; Figure 2 The drought comprehensive monitoring method of the embodiment of the present invention is compared with other drought comprehensive indexes; Figure 3 It is a comparison between the drought comprehensive monitoring method of the embodiment of the present invention and the meteorological comprehensive drought index (MCI) product of the China Meteorological Administration; Figure 4 is the vegetation response factor calculated in the Chinese region in the embodiment of the present invention; Figure 5 The embodiment of the present invention is to solve the vegetation drought response factor to improve the performance of different indexes; Figure 6 is the performance of the comprehensive drought monitoring method under different α weights of the embodiment of the present invention; Figure 7 is a schematic diagram of an electronic device according to an embodiment of the present invention.

[0021] Reference numerals: Electronic device 200; Processor 201; Memory 202; operating system 2021; application program 2022; Network interface 203; Input device 204; Hard disk 205; Display device 206. DETAILED DESCRIPTION

[0022] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0023] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0024] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0025] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0026] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0027] The comprehensive drought monitoring method according to an embodiment of the present invention is first described in detail below with reference to the accompanying drawings.

[0028] The comprehensive drought monitoring method disclosed in the present invention comprises the following steps: Get multiple observations for a preset time period and the Palmer Drought Severity Index (PDSI).

[0029] Based on a variety of observation data, a variety of basic drought indices are obtained to reflect drought conditions. For example, different types of drought indices are calculated for each type of data, including vegetation condition index (VCI), temperature condition index (TCI), soil moisture condition index (SMCI) and precipitation condition index (PCI). It can be seen that the basic drought index can also be defined as a drought condition index.

[0030] The drought process is divided into the first stage and the second stage. The first stage is from physical disaster factors to drought stress, and the second stage is from drought stress to the impact of drought on vegetation. According to the drought process, a variety of basic drought indices are divided into the first type of drought index and the second type of drought index. The first type of drought index is used to characterize the intensity of drought disaster factors from different angles, and the second type of drought index is used to measure the impact of drought on vegetation. That is to say, in the embodiment of the present invention, the intermediate variable "drought stress" is proposed, and based on this intermediate variable, the drought process is decomposed into two drought sub-processes: (1) from physical disaster factors to drought stress; (2) from drought stress to vegetation being affected. This division helps to deeply understand the impact mechanism of external drought conditions (precipitation, high temperature, soil moisture) on vegetation.

[0031] The vegetation response factor of the first stage is obtained according to the first type drought index and the Palmer drought severity index, and the vegetation response factor of the second stage is obtained according to the second type drought index and the Palmer drought severity index; Various drought stress indices were obtained through vegetation response factors and corresponding basic drought indices; A comprehensive drought index was constructed based on multiple drought stress indices.

[0032] According to one embodiment of the present invention, the comprehensive drought monitoring method also includes the following steps: preprocessing the observed data, the preprocessing step includes at least one of cloud removal in space, outlier removal and mean aggregation in time scale. That is to say, in this embodiment, the collected multi-source data is preprocessed, including removing data holes caused by cloud and fog noise, standardization processing, etc., to ensure the accuracy of the data. In addition, the temporal and spatial resolutions of the data can also be unified, for example, the temporal resolution of all data is unified to one month, and the spatial resolution is unified to 1 kilometer. Optionally, the temporal resolution of comprehensive drought monitoring can be further shortened to achieve more intensive dynamic monitoring of drought. Optionally, the spatial resolution of the data can also be improved to achieve a more detailed capture of the spatial distribution pattern of drought.

[0033] In some specific embodiments of the present invention, the observation data includes at least one of remote sensing data, reanalysis data, land surface assimilation system data, and Palmer Drought Severity Index (PDSI). That is, the observation data includes at least one of soil moisture data, vegetation index data, surface temperature data, and precipitation data. Soil moisture data, vegetation index data, surface temperature data, and precipitation data can be obtained through satellite remote sensing technology or from existing data products. In the present invention, these data are all open source data to ensure the accessibility of the data and the universality of the invention.

[0034] That is to say, in this embodiment, in order to improve the application potential of a large range and across regions, this embodiment obtains a large amount of open source data from existing different platforms, including remote sensing data, reanalysis data, land surface assimilation system data, Palmer Drought Severity Index, etc. These data are specifically divided into vegetation spectral data, land surface temperature data, soil moisture data, precipitation data, etc. from the monitoring perspective of drought. Optionally, the time range of these data is from 2001 to 2020.

[0035] According to one embodiment of the present invention, the first type of drought index includes a surface temperature index, a soil moisture index and a precipitation index, and the second type of drought index includes a vegetation index, such as the soil moisture index (SMCI), the vegetation index (VCI), the surface temperature index (TCI) and the precipitation index (PCI), which can reflect drought conditions from different perspectives.

[0036] According to one embodiment of the present invention, the step of constructing a comprehensive drought index according to the drought stress index adopts a principal component analysis method, which is an unsupervised method that can integrate information of multiple indicators without prior knowledge and has been widely used in data fusion and synthesis of comprehensive drought index.

[0037] In some specific embodiments of the present invention, the vegetation response factors include drought response factors of woodlands, grasslands and farmlands, and the vegetation response factors, drought stress indexes, etc. of different vegetation types can be obtained, which is conducive to exploring the drought sensitivity of different vegetation types.

[0038] The invention also discloses a drought comprehensive monitoring device, which comprises an observation data acquisition module, a basic drought index acquisition module, a drought process stage model construction module, a drought stress index acquisition module and a drought comprehensive index construction module.

[0039] Specifically, the observation data acquisition module is used to obtain a variety of observation data and the Palmer Drought Severity Index within a preset time period, and the basic drought index acquisition module obtains a variety of basic drought indices for reflecting drought conditions based on the various observation data.

[0040] Among them, the drought process stage model is used to divide the drought process into the first stage and the second stage and to obtain the vegetation response factors corresponding to the first stage and the second stage. The first stage is from physical disaster factors to drought stress, and the second stage is from drought stress to the impact of drought on vegetation. According to the drought process, a variety of basic drought indices are divided into the first type of drought index and the second type of drought index. The first type of drought index is used to characterize the intensity of drought disaster factors from different angles, and the second type of drought index is used to measure the impact of drought on vegetation.

[0041] In addition, the drought process stage model obtains the vegetation response factor of the first stage according to the first type of drought index and the Palmer drought severity index, and obtains the vegetation response factor of the second stage according to the second type of drought index and the Palmer drought severity index. For example, the drought process is first modeled in stages and divided into two stages, and the vegetation response factor is calculated in each stage (the first stage relies on TCI, SMCI, PCI and Palmer drought index calculation, and the calculation formula is formula (2), and the second stage relies on VCI and Palmer drought index calculation, and the calculation formula is formula (3)). The above-mentioned drought process stage model actually includes the calculation of vegetation response factors. The drought stress index acquisition module obtains multiple drought stress indices through vegetation response factors and corresponding basic drought indices. The drought comprehensive index construction module constructs a drought comprehensive index based on multiple drought stress indices.

[0042] The comprehensive drought monitoring method proposed in the present invention is described in detail below in conjunction with specific embodiments.

[0043] Example 1 Step S1, multi-source observation data acquisition and preprocessing.

[0044] In order to make this embodiment 1 have a wide range of cross-regional application potential, this embodiment 1 obtains a large amount of open source data from existing different platforms, including remote sensing data, reanalysis data, land surface assimilation system data, and Palmer Drought Severity Index (PDSI). The above observation data are specifically divided into vegetation spectral data, land surface temperature data, soil moisture data, and precipitation data according to the monitoring perspective of drought. Moreover, the time range of these observation data is from 2001 to 2020.

[0045] Furthermore, these observational data are preprocessed, including cloud removal in space, outlier removal, and mean aggregation in time scale.

[0046] Step S2: construct multiple types of basic drought indices.

[0047] Using the various observation data obtained and preprocessed in step S1, different types of basic drought indices are calculated, including vegetation condition index (VCI), temperature condition index (TCI), soil moisture condition index (SMCI) and precipitation condition index (PCI). The calculation of these basic drought indices is based on a time scale of one month. The calculation formula is as follows (1) (taking VCI as an example), where , and They represent the minimum and maximum values ​​of the normalized difference vegetation index calculated using vegetation spectral data and its multi-year time series in the same period of history.

[0048] (1) Step S3: Model the drought process in stages.

[0049] In this embodiment 1, the drought process is divided into the following two sub-stages: (1) The first stage: from physical hazards to drought stress; (2) The second stage: from drought stress to the impact of drought on vegetation.

[0050] Accordingly, in this embodiment 1, the four indices constructed in step S2 are also divided into two categories, wherein the first type of drought index includes temperature condition index (TCI), soil moisture condition index (SMCI) and precipitation condition index (PCI), and the second type of drought index is vegetation condition index (VCI). The first type of drought index is used to characterize the intensity of drought disaster factors from different angles, while the second type of drought index is used to measure the impact of drought on vegetation.

[0051] Step S4: Calculate the vegetation response factor.

[0052] According to the staged results of the drought process in step S3, this embodiment 1 takes TCI as the representative of the drought disaster factor {TCI, SMCI, PCI} to introduce the overall process of calculating the vegetation response factor in the first and second stages, wherein ds is replaced by the Palmer Drought Index PDSI in the calculation process, that is, when solving the vegetation response factor in formulas (2) and (3), ds is replaced by PDSI.

[0053] First, the process of solving the vegetation response factor in the first stage is explained in detail.

[0054] Theoretically, the value range of TCI is from 0 to 1, and the lower the TCI value, the more severe the high temperature condition. In addition, in vegetation-covered areas, the temperature is regulated by vegetation. Therefore, in this Example 1, the drought stress index caused by temperature anomaly is defined as ds, the degree of temperature anomaly is defined as (1-TCI), and the vegetation response factor is defined as ω. Then, in this Example 1, a linear model is used to combine these parameters and propose a drought stress equation (2): (2) Among them, ε is used as a noise term. The physical mechanism of equation (2) is that the drought stress index (ds) caused by temperature anomaly is mainly affected by the thermal condition (1-TCI) and the vegetation response factor (ω). Optionally, ε is omitted in the calculation process. This is because it is small and can be ignored in practical applications, so ε can be omitted in the calculation process; optionally, ε is not omitted in the calculation process for the sake of rigor.

[0055] Next, the process of solving the vegetation response factor in the second stage is explained in detail.

[0056] In this Example 1, vegetation damage mainly refers to the impact of drought stress on vegetation health, which can be reflected in the change of spectral characteristics, such as the decrease of NDVI or VCI values. In addition, due to different drought sensitivities, the performance of vegetation under drought stress is also different. Therefore, in the second stage, the vegetation drought response equation (3) is proposed in this Example 1: (3) Where (1-VCI) represents the change in VCI caused by drought stress. It should be noted that the main focus here is drought, so it is assumed that drought stress is the main cause of VCI change. The physical mechanism of equation (3) is that when subjected to drought stress (ds), the response of different vegetation (ds×ω) is manifested as the change in vegetation index (1-VCI).

[0057] For example, China experienced a very serious drought disaster in 2009, so the data of 2009 was selected in this embodiment 1 to solve the vegetation response factor. For the 34 administrative divisions in China, this paper constructed an overdetermined equation system containing 34×7=238 sub-equations in the growing season of 2009: (4) Among them, the vegetation response factors are divided into drought response factors of forest land, grassland and farmland. , and are drought response factors for forest land, grassland and farmland, respectively. , and Represents the number of pixels in forestland, grassland and farmland respectively, and Norm (PDSI) represents the normalized result of the Palmer Drought Severity Index data. The drought response factors of forestland, grassland and farmland can be solved by the least squares method.

[0058] It can be seen that the basic drought index can be used here to construct a staged model of drought process. The drought process can be divided into the first stage and the second stage through the staged model of drought process, and the vegetation response factor can also be solved.

[0059] In addition, the vegetation response factor results obtained for China in this Example 1 are as follows: Figure 4 shown.

[0060] As attached Figure 5 As shown in Figure 1, when the calculated vegetation response factor is applied to other years, the drought index's monitoring ability for drought has been improved to varying degrees. It can be seen that when conducting comprehensive drought monitoring in other years in China, the early vegetation response factor calculation step can be omitted, and the vegetation response factor result calculated in step S4 can be directly used (see Figure 1). Figure 5 ) can still achieve good improvement.

[0061] Step S5: Fine-tune and improve the drought index.

[0062] After obtaining the vegetation response factors of different vegetation types in step S4, these vegetation response factors are substituted back into formula (2) and formula (3).

[0063] Considering the design rules of the drought index, more severe droughts are often represented by smaller drought index values, so a negative sign is added to the above two equations to ensure that the constructed drought stress is consistent with the existing drought index. Therefore, in the present invention, the drought stress index based on TCI can be expressed as: (5) Other drought stress indices expressed by single drought condition indices (such as and ) can also be obtained through the same steps. Similarly, the drought stress based on VCI can be calculated according to formula (6): (6) Step S6: Fusion of multiple types of drought indices.

[0064] In order to integrate the above-mentioned drought stress index from different dimensions, the principal component analysis (PCA) method is selected in this embodiment 1 to complete the fusion task of the above-mentioned reconstruction index, as shown in formula (7). (7) in, It represents the result of PCA fusion of multiple types of drought index. , and These are comprehensive indices that are further constructed based on the four fine-tuned and improved drought indices mentioned above. Principal component analysis is an unsupervised method that can integrate the information of multiple indicators without prior knowledge and has been widely used in data fusion and synthesis of comprehensive drought indices.

[0065] In addition, unlike the prior art, the drought comprehensive monitoring method constructed in this embodiment 1 also considers the potential of the existing comprehensive index in the field of drought comprehensive monitoring. Specifically, ds in formula (7) fused In addition to using the drought stress index represented by four basic indices, the calculation also combines two or three of the four drought stress indices (the combination method refers to the construction process of three commonly used drought comprehensive monitoring indices, VHI, SDCI, and MIDI). Therefore, here it refers to taking these three comprehensive indices into consideration.

[0066] Step S7: Accumulated weighting of drought stress.

[0067] After obtaining the multiple index fusion results of step S6 Afterwards, this embodiment further weights the fusion results of the previous and next phases to obtain the final comprehensive drought index, which is named MTRADI in this embodiment. The “previous and next phases” here refer to the previous observation time and the next observation time.

[0068] The weighting process is shown in formula (8).

[0069] (8) In formula (8), α Represents the contribution of the previous months’ cumulative impact on the current month. i Represents the monitoring month.

[0070] In Example 1, a comprehensive drought monitoring method considering vegetation sensitivity and drought process characteristics is developed by integrating multi-source data. The specific process is as shown in the attached Figure 1 It can be seen that a new comprehensive drought monitoring index can be developed by further integrating the advantages of multidimensional drought indices and the cumulative impact of drought stress in historical phases.

[0071] Furthermore, in this embodiment 1, the principal component analysis method is used to fuse the above-mentioned multiple drought indices, and the drought stress in the historical phase and the drought stress in the current phase are linearly weighted. After calculation, when α is 0.5 in this embodiment 1, the effect of the constructed MTRADI is the best. In addition, in practical applications, this embodiment recommends setting this parameter to 0.5 to achieve the best comprehensive monitoring performance.

[0072] In order to verify the effectiveness of this embodiment 1, a comparative experiment was conducted, and the specific experiment is as follows: The drought event in China in October 2019 was selected as the research object, four multi-source observation data in China were collected, and the drought comprehensive index MTRADI of the present invention was constructed according to the above method. At the same time, the constructed MTRADI was compared with the comprehensive meteorological drought index (MCI) product released by the National Climate Center of the China Meteorological Administration. The experimental results are shown in the attached figure. Figure 3 shown.

[0073] The comparison results show that the correlation between the MTRADI of this embodiment 1 and the product map of the National Climate Center is close. It can be seen that MTRADI has advantages in continuously tracking the development of drought and identifying the spatial scope and scale of drought events. This shows that this embodiment has high accuracy and reliability in practical applications.

[0074] That is to say, the MTRADI proposed in the present invention has good accuracy and effectiveness in the entire Chinese region, significantly outperforming other existing comprehensive drought indices, and has robust performance in multi-year drought comprehensive monitoring tasks. It can be seen that the present invention proposes a comprehensive drought monitoring index that takes into account vegetation drought response and drought process, and comprehensively evaluates drought conditions through the integration of four heterogeneous data and the fusion of multiple basic indices. In addition, in this embodiment 1, the index selected China to carry out method application, and calculated and obtained the vegetation response factors in China. These response factors are universal in China and are particularly suitable for expanded applications in China.

[0075] It can be seen that in Example 1, the observation data of vegetation spectrum, surface temperature, soil moisture, precipitation, and Palmer Drought Index (PDSI) are first obtained; then, the basic drought index (VCI, TCI, SMCI, PCI) is obtained through the observation data; then, different vegetation response factors are calculated using these basic drought indexes and Palmer Drought Index (PDSI); the response factors are back-substituted to obtain drought stress (ds TCI ,ds SMCI ,ds PCI ,ds VCI, ), where the corresponding combination can further obtain ds VHI ,ds SDCI ,ds MIDI The drought stress index represented by these seven different indices was fused through PCA to obtain ds fused ; Last ds fused The final drought comprehensive index MTRADI is obtained by time series weighting.

[0076] It can be seen that when solving the vegetation response factor in formulas (2) and (3), ds is replaced by PDSI. After the vegetation response factor is calculated, it is back-substituted to obtain ds expressed by different drought indices. These ds now have information about different drought indices. TCI At this point, not only the influence of different vegetation response factors is eliminated, but also TCI (temperature) information is obtained. fused , we can obtain a comprehensive index that takes into account the information of different indices.

[0077] That is to say, in the first stage, TCI, SMCI, PCI, and PDSI are used to calculate the corresponding ω, and then back-substituting them into formula (2) to obtain ds expressed by TCI, SMCI, and PCI respectively. TCI 、ds SMCI 、ds PCI , which represent the drought stress of temperature, soil moisture and precipitation respectively. In the second stage, formula (3) can be used. Similarly, VCI and Palmer Drought Index (PDSI) can be used to obtain the drought stress ds of vegetation. VCI. Among them, four types of drought stress were obtained in the first and second stages: ds TCI ,ds SMCI ,ds PCI ,ds VCI These four types of drought stress are obtained in parallel, and then two or three of them are combined (the combination logic refers to the process of constructing VHI, SDCI, and MIDI) to construct ds VHI ,ds SDCI,ds MIDI Finally, these seven indices are fused into one index using PCA (taking the first band after PCA processing), which is the ds in this paper. fused .ds fused After time-series weighting, we get the final index MTRADI.

[0078] In summary, the present invention aims to address the problems of insufficient modeling of drought processes and lack of exploration of vegetation drought response characteristics in the prior art. By modeling the drought process in stages and exploring the drought sensitivity of different vegetation types, a new drought comprehensive monitoring method, MTRADI, is proposed. Specifically, in the embodiments of the present invention, in view of the various defects of the existing drought comprehensive monitoring methods, especially the insufficient consideration of the development characteristics of the drought process and the insufficient exploration of the drought response laws of vegetation, the present invention aims to propose a comprehensive and sophisticated drought comprehensive monitoring method.

[0079] This method comprehensively considers multiple drought-causing factors and complex drought manifestations, decomposes the drought process in detail and conducts staged modeling, deeply couples the differences in vegetation response, and proposes a comprehensive drought monitoring method that takes into account the characteristics of the drought process and the sensitivity of vegetation, and has a wide range of application capabilities to meet the needs of drought early warning, disaster assessment, water resources management, etc. For example, the multi-source data used in the present invention are all open source data, which are easy to obtain, and the data preprocessing method and the calculation process of the basic index are relatively mature and reliable. At the same time, the construction method of the comprehensive index is simple and clear, which is convenient for practical application.

[0080] In the embodiment of the present invention, by comprehensively considering a variety of drought-related observation data and integrating a variety of drought indices with different characteristics of drought, the present invention can more comprehensively and accurately assess the drought situation. In addition, the present invention innovatively adds consideration of the drought process and vegetation response laws, and the assessment of drought is more accurate, which can provide strong support for drought relief work in agriculture, forestry and other departments.

[0081] The present invention further provides an electronic device 200, comprising: a processor 201 and a memory 202, wherein the memory 202 stores computer program instructions, wherein when the computer program instructions are executed by the processor 201, the processor 201 executes the steps of the method in the above embodiment.

[0082] Furthermore, if Figure 7 As shown, the electronic device 200 further includes a network interface 203 , an input device 204 , a hard disk 205 , and a display device 206 .

[0083] The above-mentioned interfaces and devices can be interconnected through a bus architecture. The bus architecture can include any number of interconnected buses and bridges. Specifically, one or more central processing units 201 (CPUs) represented by the processor 201 and various circuits of one or more memories 202 represented by the memory 202 are connected together. The bus architecture can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits together. It can be understood that the bus architecture is used to achieve connection and communication between these components. In addition to the data bus, the bus architecture also includes a power bus, a control bus, and a status signal bus, which are all well known in the art, so they will not be described in detail herein.

[0084] The network interface 203 can be connected to a network (such as the Internet, a local area network, etc.), obtain relevant data from the network, and save it in the hard disk 205.

[0085] The input device 204 can receive various instructions input by the operator and send them to the processor 201 for execution. The input device 204 can include a keyboard or a pointing device (for example, a mouse, a trackball, a touch pad or a touch screen, etc.).

[0086] The display device 206 can display the result obtained by the processor 201 executing the instruction.

[0087] The memory 202 is used to store programs and data necessary for the operation of the operating system 2021, as well as data such as intermediate results during the calculation process of the processor 201.

[0088] It is understood that the memory 202 in the embodiment of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. The memory 202 of the apparatus and method described herein is intended to include, but is not limited to, these and any other suitable types of memory 202.

[0089] In some implementations, the memory 202 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system 2021 and application programs 2022 .

[0090] The operating system 2021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 2022 includes various application programs 2022, such as a browser, etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present invention can be included in the application 2022.

[0091] The processor 201 executes the steps of the method according to the above embodiment when calling and executing the application 2022 and data stored in the memory 202, specifically, the program or instructions stored in the application 2022.

[0092] The method disclosed in the above embodiment of the present invention can be applied to the processor 201, or implemented by the processor 201. The processor 201 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 201 or the instruction in the form of software. The above processor 201 can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a readily available programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general processor can be a microprocessor or the processor 201 can also be any conventional processor 201, etc. The steps of the method disclosed in conjunction with the embodiment of the present invention can be directly embodied as a hardware decoding processor to be executed, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 202, and the processor 201 reads the information in the memory 202 and completes the steps of the above method in combination with its hardware.

[0093] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions of the present invention or a combination thereof.

[0094] For software implementation, the technology herein can be implemented by modules (e.g., procedures, functions, etc.) that perform the functions herein. The software code can be stored in the memory 202 and executed by the processor 201. The memory 202 can be implemented in the processor 201 or outside the processor 201.

[0095] Specifically, the processor 201 is also used to read the computer program and execute the following steps: the method predicts and outputs the answer to the question asked by the user.

[0096] The present invention further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by the processor 201, the processor 201 executes the steps of the method in the above embodiment.

[0097] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0098] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be physically included separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0099] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform some steps of the sending and receiving methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0100] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will be appreciated by those skilled in the art that the above embodiments may be modified without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A comprehensive drought monitoring method, characterized in that: The steps include: Get multiple observation data and the Palmer Drought Severity Index for a preset time period; Obtaining a plurality of basic drought indices for reflecting drought conditions based on a plurality of the observation data; The drought process is divided into a first stage and a second stage, the first stage is from physical disaster factors to drought stress, and the second stage is from the drought stress to the impact of drought on vegetation. According to the drought process, the various basic drought indices are divided into a first type of drought index and a second type of drought index. The first type of drought index is used to characterize the intensity of drought disaster factors from different angles, and the second type of drought index is used to measure the impact of drought on vegetation. Obtaining a vegetation response factor for the first stage according to the first type of drought index and the Palmer Drought Severity Index, and obtaining a vegetation response factor for the second stage according to the second type of drought index and the Palmer Drought Severity Index; Obtaining a plurality of drought stress indices through the vegetation response factor and the corresponding basic drought index; A comprehensive drought index is constructed based on a plurality of the drought stress indices.

2. The drought comprehensive monitoring method according to claim 1, characterized in that: The following steps are also included: The observation data is preprocessed, and the preprocessing step includes at least one of cloud removal in space, outlier removal, and mean aggregation in time scale.

3. The drought comprehensive monitoring method according to claim 1, characterized in that: The observation data includes at least one of remote sensing data, reanalysis data, land surface assimilation system data and Palmer Drought Severity Index.

4. The comprehensive drought monitoring method according to claim 3, characterized in that: The first type of drought index includes a surface temperature condition index, a soil moisture condition index and a precipitation condition index, and the second type of drought index includes a vegetation condition index.

5. The drought comprehensive monitoring method according to claim 1, characterized in that: The basic drought index is calculated on a time scale of one month.

6. The drought comprehensive monitoring method according to claim 1, characterized in that: The step of constructing a comprehensive drought index according to the drought stress index adopts a principal component analysis method.

7. The drought comprehensive monitoring method according to claim 1, characterized in that: The vegetation response factors include drought response factors of forest land, grassland and farmland.

8. A drought comprehensive monitoring device, characterized in that: include: An observation data acquisition module, wherein the observation data acquisition module is used to acquire a variety of observation data and the Palmer Drought Severity Index within a preset time period; A basic drought index acquisition module, wherein the basic drought index acquisition module obtains a plurality of basic drought indexes for reflecting drought conditions based on a plurality of the observation data; A drought process stage model construction module, wherein the drought process stage model is used to divide the drought process into a first stage and a second stage and obtain vegetation response factors corresponding to the first stage and the second stage, wherein the first stage is from physical disaster factors to drought stress, and the second stage is from the drought stress to the impact of drought on vegetation. According to the drought process, a plurality of basic drought indices are divided into a first type of drought index and a second type of drought index, wherein the first type of drought index is used to characterize the intensity of drought disaster factors from different angles, and the second type of drought index is used to measure the degree of impact of drought on vegetation. The drought process stage model obtains the vegetation response factor of the first stage according to the first type of drought index and the Palmer Drought Severity Index, and obtains the vegetation response factor of the second stage according to the second type of drought index and the Palmer Drought Severity Index; A drought stress index acquisition module, wherein the drought stress index acquisition module obtains a plurality of drought stress indices through the vegetation response factor and the corresponding basic drought index; A drought comprehensive index construction module is used to construct a drought comprehensive index according to a plurality of drought stress indices.

9. An electronic device, characterized in that: include: A processor and a memory, wherein computer program instructions are stored in the memory, wherein when the computer program instructions are executed by the processor, the processor is caused to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 7.

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