Public data splitting, integrating and storing system and method based on distributed storage

Abstract

The invention relates to the technical field of data processing, in particular to a public data splitting, integrating and storing system and method based on distributed storage, and the method comprises the steps that a to-be-stored data obtaining module carries out the regional splitting of a haloxylon ammodendron tree according to the geographic position distribution of the haloxylon ammodendron tree; obtaining first to-be-stored environment data and first to-be-stored terrain data of each region; the to-be-stored data analysis module constructs a haloxylon ammodendron tree anomaly identification model to identify a comprehensive haloxylon ammodendron tree region anomaly coefficient of each haloxylon ammodendron tree region; a to-be-stored data grading module determines a first haloxylon ammodendron region data storage priority of each haloxylon ammodendron region according to the abnormal coefficient; and the distributed storage module stores the haloxylon ammodendron tree data of each area to a haloxylon ammodendron tree distributed file system according to the priority. Through distributed storage of haloxylon ammodendron area data, the storage efficiency of desert haloxylon ammodendron growth monitoring data is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and specifically provides a public data splitting and integrating storage system and method based on distributed storage. Background Art

[0002] Haloxylon ammodendron in the desert is an important vegetation for wind prevention and sand fixation, and its growth monitoring and management are of great significance. At present, the data storage of desert Haloxylon ammodendron does not fully consider the comprehensive priority analysis based on the terrain data and environmental data of Haloxylon ammodendron, and does not fully consider the distributed database storage based on the comprehensive priority, resulting in limited storage efficiency of the growth monitoring data of desert Haloxylon ammodendron.

[0003] Therefore, a public data splitting and integrating storage system and method based on distributed storage are proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a public data splitting and integrating storage system and method based on distributed storage. The present invention relates to the technical field of data processing, and specifically provides a public data splitting and integrating storage system and method based on distributed storage, including: a to-be-stored data acquisition module splits Haloxylon ammodendron into regions according to the geographical location distribution of Haloxylon ammodendron in the desert, and acquires the first to-be-stored environmental data and the first to-be-stored terrain data of each region; a to-be-stored data analysis module constructs an abnormal identification model of Haloxylon ammodendron to identify the comprehensive abnormal coefficient of each Haloxylon ammodendron region; a to-be-stored data grading module determines the first data storage priority of each Haloxylon ammodendron region according to the abnormal coefficient; a distributed storage module stores the Haloxylon ammodendron data of each region into the Haloxylon ammodendron distributed file system according to the priority. The present invention improves the management ability of desert Haloxylon ammodendron growth monitoring through the distributed storage of Haloxylon ammodendron region data.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A public data splitting and integrating storage system based on distributed storage, including:

[0007] A to-be-stored data acquisition module splits Haloxylon ammodendron into regions according to the geographical location distribution of Haloxylon ammodendron in the desert, obtains each Haloxylon ammodendron region, and acquires the first to-be-stored environmental data and the first to-be-stored terrain data of each Haloxylon ammodendron region;

[0008] The data to be stored analysis module is used to construct a Haloxylon ammodendron anomaly recognition model to recognize the first data to be stored in the environment and the first data to be stored in the terrain. The Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer. The Haloxylon ammodendron time series feature analysis layer is used to obtain the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient. The comprehensive Haloxylon ammodendron area anomaly coefficient is obtained according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient.

[0009] The data to be stored grading module is used to obtain the first Haloxylon ammodendron area data storage priority according to the comprehensive Haloxylon ammodendron area anomaly coefficient and the preset threshold set.

[0010] The distributed storage module is used to store the data of each Haloxylon ammodendron area in the Haloxylon ammodendron distributed file system according to the first Haloxylon ammodendron area data storage priority of each Haloxylon ammodendron area. The Haloxylon ammodendron distributed file system includes the first Haloxylon ammodendron database, the second Haloxylon ammodendron database, and the third Haloxylon ammodendron database.

[0011] Preferably, the first data to be stored in the environment includes the environmental temperature, groundwater content, environmental humidity, wind speed, and light of each Haloxylon ammodendron within the first time window. The first data to be stored in the terrain includes the slope of the ground where each Haloxylon ammodendron is located within the first time window.

[0012] Preferably, the Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer.

[0013] The input layer is used to input the first data to be stored in the environment and the second data to be stored in the terrain into the Haloxylon ammodendron anomaly recognition model.

[0014] The preprocessing is used to preprocess the first data to be stored in the environment and the first data to be stored in the terrain, and respectively obtain the second data to be stored in the environment and the second data to be stored in the terrain.

[0015] The Haloxylon ammodendron time series feature extraction layer includes an environmental anomaly feature extraction unit and a terrain anomaly feature extraction unit. The environmental anomaly feature extraction unit is used to extract regional environmental time series features from the second data to be stored in the environment through LSTM. The regional environmental time series features include regional average environmental temperature, regional average wind speed, regional average light, regional average groundwater content, and regional average environmental humidity. The terrain anomaly feature extraction unit is used to extract regional terrain time series features from the second data to be stored in the terrain through LSTM. The regional terrain time series features include regional average maximum slope and regional average minimum slope.

[0016] The Haloxylon ammodendron tree time series feature analysis layer analyzes the regional environmental time series features and the regional terrain time series features respectively, and obtains the first Haloxylon ammodendron tree anomaly coefficient and the second Haloxylon ammodendron tree anomaly coefficient; and according to the first Haloxylon ammodendron tree anomaly coefficient and the second Haloxylon ammodendron tree anomaly coefficient, obtains the comprehensive Haloxylon ammodendron tree regional anomaly coefficient;

[0017] The Haloxylon ammodendron tree anomaly coefficient output layer is used to output the comprehensive Haloxylon ammodendron tree regional anomaly coefficient.

[0018] Preferably, the comprehensive Haloxylon ammodendron tree regional anomaly coefficient is:

[0019] RACIST i =WEI*EAC i +WAA*TAC i ;

[0020] Among them, RACIST i represents the comprehensive Haloxylon ammodendron tree regional anomaly coefficient of the i-th Haloxylon ammodendron tree region; WEI represents the Haloxylon ammodendron tree environmental anomaly influence weight; EAC i represents the first Haloxylon ammodendron tree anomaly coefficient of the i-th Haloxylon ammodendron tree region; WAA represents the Haloxylon ammodendron tree terrain anomaly influence weight; TAC i represents the second Haloxylon ammodendron tree anomaly coefficient of the i-th Haloxylon ammodendron tree region;

[0021] Preferably, the data storage priorities of the first Haloxylon ammodendron tree region include the first high storage priority, the second medium storage priority, and the third low storage priority; the Haloxylon ammodendron tree region data with the first high storage priority is stored in the first Haloxylon ammodendron tree database; the Haloxylon ammodendron tree region data with the second medium storage priority is stored in the second Haloxylon ammodendron tree database; the Haloxylon ammodendron tree region data with the third low storage priority is stored in the third Haloxylon ammodendron tree database.

[0022] A public data splitting and integrating storage method based on distributed storage includes:

[0023] S1. Split the Haloxylon ammodendron trees into regions according to the geographical location distribution of the Haloxylon ammodendron trees in the desert, obtain each Haloxylon ammodendron tree region, and acquire the first environmental data to be stored and the first terrain data to be stored of each Haloxylon ammodendron tree region;

[0024] S2. Construct a Haloxylon ammodendron tree anomaly recognition model to recognize the first environmental data to be stored and the first terrain data to be stored. The Haloxylon ammodendron tree anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron tree time series feature extraction layer, a Haloxylon ammodendron tree time series feature analysis layer, and a Haloxylon ammodendron tree anomaly coefficient output layer; the Haloxylon ammodendron tree time series feature analysis layer is used to obtain the first Haloxylon ammodendron tree anomaly coefficient and the second Haloxylon ammodendron tree anomaly coefficient; and obtain the comprehensive Haloxylon ammodendron tree regional anomaly coefficient according to the first Haloxylon ammodendron tree anomaly coefficient and the second Haloxylon ammodendron tree anomaly coefficient;

[0025] S3. Obtain the first Haloxylon ammodendron area data storage priority according to the comprehensive Haloxylon ammodendron area anomaly coefficient and the preset threshold set.

[0026] S4. According to the first Haloxylon ammodendron area data storage priority of each Haloxylon ammodendron area, store the data of each Haloxylon ammodendron area in the Haloxylon ammodendron distributed file system; the Haloxylon ammodendron distributed file system includes the first Haloxylon ammodendron database, the second Haloxylon ammodendron database, and the third Haloxylon ammodendron database.

[0027] Preferably, the first data to be stored in the environment includes the environmental temperature, groundwater content, environmental humidity, wind speed, and light of each Haloxylon ammodendron within the first time window; the first data to be stored in the terrain includes the slope of the ground where each Haloxylon ammodendron is located within the first time window.

[0028] Preferably, the Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer.

[0029] The input layer is used to input the first data to be stored in the environment and the second data to be stored in the terrain into the Haloxylon ammodendron anomaly recognition model.

[0030] The preprocessing layer is used to preprocess the first data to be stored in the environment and the first data to be stored in the terrain, and obtain the second data to be stored in the environment and the second data to be stored in the terrain respectively.

[0031] The Haloxylon ammodendron time series feature extraction layer includes an environmental anomaly feature extraction unit and a terrain anomaly feature extraction unit; the environmental anomaly feature extraction unit is used to extract features from the second data to be stored in the environment through LSTM, and extract the regional environmental time series features; the regional environmental time series features include the regional average environmental temperature, regional average wind speed, regional average light, regional average groundwater content, and regional average environmental humidity; the terrain anomaly feature extraction unit is used to extract features from the second data to be stored in the terrain through LSTM, and obtain the regional terrain time series features; the regional terrain time series features include the regional average maximum slope and the regional average minimum slope.

[0032] The Haloxylon ammodendron time series feature analysis layer analyzes the regional environmental time series features and the regional terrain time series features respectively, and obtains the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient respectively; and according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient, obtain the comprehensive Haloxylon ammodendron area anomaly coefficient.

[0033] The Haloxylon ammodendron anomaly coefficient output layer is used to output the comprehensive Haloxylon ammodendron area anomaly coefficient.

[0034] Preferably, the comprehensive Haloxylon ammodendron area anomaly coefficient is:

[0035] RACIST i = WEI * EAC i + WAA * TAC i ;

[0036] Wherein, RACIST i represents the comprehensive Haloxylon ammodendron area anomaly coefficient of the i-th Haloxylon ammodendron area; WEI represents the Haloxylon ammodendron environmental anomaly influence weight; EAC i represents the first Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area; WAA represents the Haloxylon ammodendron terrain anomaly influence weight; TAC i represents the second Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area;

[0037] Preferably, the data storage priorities of the first Haloxylon ammodendron area include the first high storage priority, the second medium storage priority, and the third low storage priority; storing the Haloxylon ammodendron area data with the first high storage priority into the first Haloxylon ammodendron database; storing the Haloxylon ammodendron area data with the second medium storage priority into the second Haloxylon ammodendron database; storing the Haloxylon ammodendron area data with the third low storage priority into the third Haloxylon ammodendron database.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] 1. Based on the geographical location distribution of Haloxylon ammodendron in the desert, the present invention divides Haloxylon ammodendron into multiple areas, obtains the environmental data and terrain data of each Haloxylon ammodendron, and constructs a Haloxylon ammodendron anomaly recognition model to identify the environmental data and terrain data. Through LSTM recognition, the regional environmental time series characteristics and regional terrain time series characteristics are obtained, and the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient are obtained respectively according to the regional environmental time series characteristics and regional terrain time series characteristics. By constructing the Haloxylon ammodendron anomaly recognition model, it provides an effective model basis for realizing the distributed storage of Haloxylon ammodendron area data, thus being beneficial to improving the storage efficiency of desert Haloxylon ammodendron growth monitoring data.

[0040] 2. By comprehensively considering the environmental anomalies and terrain anomalies of Haloxylon ammodendron, the present invention obtains the comprehensive Haloxylon ammodendron area anomaly coefficient of each Haloxylon ammodendron area, comprehensively and effectively improving the storage efficiency of desert Haloxylon ammodendron growth monitoring data.

[0041] 3. Based on the analysis of the comprehensive Haloxylon ammodendron area anomaly coefficient of each Haloxylon ammodendron area and the preset threshold, the present invention obtains the data storage priority of the first Haloxylon ammodendron area; and according to the data storage priority of the first Haloxylon ammodendron area of each Haloxylon ammodendron area; storing the data of each Haloxylon ammodendron area into the Haloxylon ammodendron distributed file system; the Haloxylon ammodendron distributed file system includes the first Haloxylon ammodendron database, the second Haloxylon ammodendron database, and the third Haloxylon ammodendron database. Through this priority function, the distributed storage ability of Haloxylon ammodendron data can be effectively realized, thus being beneficial to improving the storage efficiency of desert Haloxylon ammodendron growth monitoring data. Brief Description of the Drawings

[0042] Figure 1 FIG. is a schematic structural diagram of a public data splitting and integrating storage system based on distributed storage provided by an embodiment of the present invention;

[0043] Figure 2 FIG. is a schematic flowchart of a public data splitting and integrating storage method based on distributed storage provided by an embodiment of the present invention;

[0044] Figure 3 FIG. is a schematic structural diagram of a Haloxylon ammodendron anomaly recognition model provided by an embodiment of the present invention. Detailed Embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment 1

[0047] In order to improve the storage efficiency of the Haloxylon ammodendron growth monitoring data in Desert A, a public data splitting and integrating storage system based on distributed storage is applied;

[0048] Refer to Figure 1 FIG. is a schematic structural diagram of a public data splitting and integrating storage system based on distributed storage provided by an embodiment of the present invention, including:

[0049] A to-be-stored data acquisition module that splits the Haloxylon ammodendron into regions according to the geographical location distribution of the Haloxylon ammodendron in the desert to obtain each Haloxylon ammodendron region, and acquires the first to-be-stored environmental data and the first to-be-stored terrain data of each Haloxylon ammodendron region;

[0050] Furthermore, analyze the distribution of the Haloxylon ammodendron in Desert A through satellite remote sensing technology, and divide Desert A into M Haloxylon ammodendron regions according to the distribution density of the Haloxylon ammodendron. Each Haloxylon ammodendron region contains N i Haloxylon ammodendron; i represents the region index, i ∈ [1, M];

[0051] Furthermore, the first to-be-stored environmental data includes the environmental temperature, groundwater content, environmental humidity, wind speed, and light of each Haloxylon ammodendron within the first time window; the first to-be-stored terrain data includes the slope of the ground where each Haloxylon ammodendron is located within the first time window.

[0052] Obtain the ambient temperature of each Haloxylon ammodendron through a temperature sensor; obtain the ambient humidity of each Haloxylon ammodendron through a humidity sensor; obtain the groundwater content of each Haloxylon ammodendron through a soil humidity sensor; obtain the wind speed of each Haloxylon ammodendron through a wind speed sensor; obtain the illumination of each Haloxylon ammodendron through an illumination sensor; obtain the slope of the ground where each Haloxylon ammodendron is located through an inclination sensor;

[0053] A data analysis module to be stored, which is used to construct a Haloxylon ammodendron anomaly recognition model to recognize the first environmental data to be stored and the first terrain data to be stored. The Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer; the Haloxylon ammodendron time series feature analysis layer is used to obtain a first Haloxylon ammodendron anomaly coefficient and a second Haloxylon ammodendron anomaly coefficient; obtain a comprehensive Haloxylon ammodendron area anomaly coefficient according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient;

[0054] Furthermore, the Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer; as Figure 3 is a schematic structural diagram of a Haloxylon ammodendron anomaly recognition model provided by an embodiment of the present invention;

[0055] The input layer is used to input the first environmental data to be stored and the second terrain data to be stored into the Haloxylon ammodendron anomaly recognition model;

[0056] The preprocessing is used to preprocess the first environmental data to be stored and the first terrain data to be stored, and respectively obtain the second environmental data to be stored and the second terrain data to be stored; the preprocessing includes data cleaning operations;

[0057] The Haloxylon ammodendron time series feature extraction layer includes an environmental anomaly feature extraction unit and a terrain anomaly feature extraction unit; the environmental anomaly feature extraction unit is used to extract features from the second environmental data to be stored through LSTM to extract regional environmental time series features; the regional environmental time series features include regional average ambient temperature, regional average wind speed, regional average illumination, regional average groundwater content, and regional average ambient humidity; the terrain anomaly feature extraction unit is used to extract features from the second terrain data to be stored through LSTM to obtain regional terrain time series features; the regional terrain time series features include regional average maximum slope and regional average minimum slope;

[0058] The Haloxylon ammodendron time series feature analysis layer analyzes the regional environmental time series features and the regional terrain time series features respectively to obtain a first Haloxylon ammodendron anomaly coefficient and a second Haloxylon ammodendron anomaly coefficient; and obtain a comprehensive Haloxylon ammodendron area anomaly coefficient according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient;

[0059] The abnormal coefficient output layer of the Haloxylon ammodendron is used to output the comprehensive abnormal coefficient of the Haloxylon ammodendron area.

[0060] Further, the regional average environmental temperature is:

[0061]

[0062] where AVT i represents the regional average environmental temperature of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VTT i_m represents the average environmental temperature of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0063] Further, the regional average groundwater content is:

[0064]

[0065] where WVT i represents the regional average groundwater content of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VWT i_m represents the average groundwater content of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0066] Further, the regional average environmental humidity is:

[0067]

[0068] where SVT i represents the regional average environmental humidity of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VST i_m represents the average environmental humidity of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0069] Further, the regional average wind speed is:

[0070]

[0071] where FVT i represents the regional average wind speed of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VFT i_m represents the average wind speed of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0072] Further, the regional average illumination is:

[0073]

[0074] Among them, GVT i represents the regional average illumination of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area; VGT i_m represents the average illumination of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window;

[0075] Furthermore, the regional average maximum slope is:

[0076]

[0077] Among them, PMAT i represents the regional average maximum slope; MaxPT i_m represents the maximum slope of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area;

[0078] Furthermore, the regional average minimum slope is:

[0079]

[0080] Among them, PMIT i represents the regional average minimum slope; MinPT i_m represents the minimum slope of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area;

[0081] The time series feature analysis layer analyzes the regional environmental time series features and the regional terrain time series features respectively, and obtains the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; and according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient, obtains the comprehensive Haloxylon ammodendron area anomaly coefficient;

[0082] The first Haloxylon ammodendron anomaly coefficient is:

[0083]

[0084] Among them, EAC i represents the first Haloxylon ammodendron anomaly coefficient; AVT i represents the regional average environmental temperature; AVT iy represents the reference regional average environmental temperature; WVT i represents the regional average groundwater content; WVT iy represents the reference regional average groundwater content; SVTi Represents the regional average environmental humidity; SVT iy Represents the reference regional average environmental humidity; FVT i Represents the regional average wind speed; FVT iy Represents the reference regional average wind speed; GVT i Represents the regional average illumination; GVT iy Represents the reference regional average illumination; exp() represents the exponential function with base e;

[0085] The second Haloxylon ammodendron anomaly coefficient is:

[0086]

[0087] Wherein, TAC i Represents the second Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area; PMAT i Represents the regional average maximum slope; PMAT iy Represents the reference regional average maximum slope; PMIT i Represents the regional average minimum slope; PMIT iy Represents the reference regional average minimum slope; exp() represents the exponential function with base e;

[0088] Based on the geographical location distribution of Haloxylon ammodendron in the desert in this embodiment, the Haloxylon ammodendron is divided into multiple areas, and the environmental data and terrain data of each tree are obtained, and a Haloxylon ammodendron anomaly recognition model is constructed to recognize the environmental data and terrain data. The regional environmental time series characteristics and regional terrain time series characteristics are obtained through LSTM recognition, and the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient are obtained respectively according to the regional environmental time series characteristics and regional terrain time series characteristics. By constructing the Haloxylon ammodendron anomaly recognition model, an effective model basis is provided for realizing the distributed storage of Haloxylon ammodendron area data, which is beneficial to improving the storage efficiency of the growth monitoring data of desert Haloxylon ammodendron.

[0089] Furthermore, the comprehensive Haloxylon ammodendron area anomaly coefficient is:

[0090] RACIST i =WEI*EAC i +WAA*TAC i ;

[0091] Wherein, RACIST i Represents the comprehensive Haloxylon ammodendron area anomaly coefficient of the i-th Haloxylon ammodendron area; WEI represents the influence weight of Haloxylon ammodendron environmental anomaly; EAC i Represents the first Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area; WAA represents the influence weight of Haloxylon ammodendron terrain anomaly; TAC i Represents the second Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area;

[0092] In this embodiment, by comprehensively considering the environmental anomalies and topographic anomalies of Haloxylon ammodendron, the comprehensive Haloxylon ammodendron area anomaly coefficient of each Haloxylon ammodendron area is obtained, which comprehensively and effectively improves the storage efficiency of the growth monitoring data of desert Haloxylon ammodendron.

[0093] A data storage level module for obtaining the first Haloxylon ammodendron area data storage priority according to the comprehensive Haloxylon ammodendron area anomaly coefficient and the preset threshold set;

[0094] Furthermore, the preset threshold set includes a first comprehensive Haloxylon ammodendron area anomaly coefficient threshold and a second comprehensive Haloxylon ammodendron area anomaly coefficient threshold; the first Haloxylon ammodendron area data storage priority includes a first high storage priority, a second medium storage priority, and a third low storage priority; the first Haloxylon ammodendron area data storage priority is:

[0095]

[0096] Wherein, AP represents the first Haloxylon ammodendron area data storage priority; FA represents the first high storage priority; SA represents the second medium storage priority; TA represents the third low storage priority; T1 represents the first comprehensive Haloxylon ammodendron area anomaly coefficient threshold; T2 represents the second comprehensive Haloxylon ammodendron area anomaly coefficient threshold; RACIST represents the comprehensive Haloxylon ammodendron area anomaly coefficient;

[0097] A distributed storage module for storing the data of each Haloxylon ammodendron area in the Haloxylon ammodendron distributed file system according to the first Haloxylon ammodendron area data storage priority of each Haloxylon ammodendron area; the Haloxylon ammodendron distributed file system includes a first Haloxylon ammodendron database, a second Haloxylon ammodendron database, and a third Haloxylon ammodendron database.

[0098] Furthermore, the first Haloxylon ammodendron area data storage priority includes a first high storage priority, a second medium storage priority, and a third low storage priority; storing the Haloxylon ammodendron area data with the first high storage priority in the first Haloxylon ammodendron database; storing the Haloxylon ammodendron area data with the second medium storage priority in the second Haloxylon ammodendron database; storing the Haloxylon ammodendron area data with the third low storage priority in the third Haloxylon ammodendron database.

[0099] Based on the analysis of the comprehensive Haloxylon ammodendron area anomaly coefficient of each Haloxylon ammodendron area and the preset threshold, this embodiment obtains the first Haloxylon ammodendron area data storage priority; and stores the data of each Haloxylon ammodendron area in the Haloxylon ammodendron distributed file system according to the first Haloxylon ammodendron area data storage priority of each Haloxylon ammodendron area; the Haloxylon ammodendron distributed file system includes a first Haloxylon ammodendron database, a second Haloxylon ammodendron database, and a third Haloxylon ammodendron database. Through this priority function, the distributed storage ability of Haloxylon ammodendron data can be effectively realized, which is beneficial to improving the storage efficiency of the growth monitoring data of desert Haloxylon ammodendron.

[0100] To verify the effectiveness of a public data splitting, integrating and storing system based on distributed storage provided in this embodiment, the average query times of different systems for various growth monitoring data of Haloxylon ammodendron in Desert A were analyzed. The specific results are shown in Table 1; the growth monitoring data includes the environmental temperature, groundwater content, environmental humidity, wind speed, light of each Haloxylon ammodendron, and the slope of the ground where each Haloxylon ammodendron is located; System 1 is a public data splitting, integrating and storing system based on distributed storage provided in this embodiment; System 2 does not consider the comprehensive priority analysis based on the terrain data and environmental data of Haloxylon ammodendron on the basis of System 1; System 3 does not consider distributed database storage based on the comprehensive priority on the basis of System 1.

[0101] Table 1 Comparison of average query times of different systems for various growth monitoring data of Haloxylon ammodendron in Desert A

[0102] System Average query time System 1 1ms System 2 5ms System 3 6ms

[0103] As can be seen from Table 1, a public data splitting, integrating and storing system based on distributed storage provided in this embodiment has a certain effectiveness, effectively improving the storage efficiency of the growth monitoring data of Haloxylon ammodendron in the desert.

[0104] Embodiment 2

[0105] In order to improve the storage efficiency of the growth monitoring data of Haloxylon ammodendron in Desert B, a public data splitting, integrating and storing method based on distributed storage was applied.

[0106] Refer to Figure 2 which is a schematic flowchart of a public data splitting, integrating and storing method based on distributed storage provided in an embodiment of the present invention, including:

[0107] S1. Split the Haloxylon ammodendron according to the geographical location distribution of the Haloxylon ammodendron in the desert to obtain each Haloxylon ammodendron area, and obtain the first environmental data to be stored and the first terrain data to be stored in each Haloxylon ammodendron area.

[0108] Further, analyze the distribution of Haloxylon ammodendron in Desert B through satellite remote sensing technology, and divide Desert B into K Haloxylon ammodendron areas according to the distribution density of Haloxylon ammodendron. Each Haloxylon ammodendron area contains N i Haloxylon ammodendron; i represents the area index, i ∈ [1, K].

[0109] Further, the first environmental data to be stored includes the environmental temperature, groundwater content, environmental humidity, wind speed and light of each Haloxylon ammodendron within the first time window; the first terrain data to be stored includes the slope of the ground where each Haloxylon ammodendron is located within the first time window.

[0110] Obtain the ambient temperature of each Haloxylon ammodendron through a temperature sensor; obtain the ambient humidity of each Haloxylon ammodendron through a humidity sensor; obtain the groundwater content of each Haloxylon ammodendron through a soil humidity sensor; obtain the wind speed of each Haloxylon ammodendron through a wind speed sensor; obtain the illumination of each Haloxylon ammodendron through an illumination sensor; obtain the slope of the ground where each Haloxylon ammodendron is located through an inclination sensor;

[0111] S2. Construct a Haloxylon ammodendron anomaly recognition model to recognize the first environmental data to be stored and the first terrain data to be stored. The Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer; the Haloxylon ammodendron time series feature analysis layer is used to obtain a first Haloxylon ammodendron anomaly coefficient and a second Haloxylon ammodendron anomaly coefficient; obtain a comprehensive Haloxylon ammodendron area anomaly coefficient according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient;

[0112] Further, the Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer, and a Haloxylon ammodendron anomaly coefficient output layer; as Figure 3 is a schematic structural diagram of a Haloxylon ammodendron anomaly recognition model provided by an embodiment of the present invention;

[0113] The input layer is used to input the first environmental data to be stored and the second terrain data to be stored into the Haloxylon ammodendron anomaly recognition model;

[0114] The preprocessing is used to preprocess the first environmental data to be stored and the first terrain data to be stored, and respectively obtain second environmental data to be stored and second terrain data to be stored; the preprocessing includes data cleaning operations;

[0115] The Haloxylon ammodendron time series feature extraction layer includes an environmental anomaly feature extraction unit and a terrain anomaly feature extraction unit; the environmental anomaly feature extraction unit is used to extract regional environmental time series features from the second environmental data to be stored through LSTM; the regional environmental time series features include regional average ambient temperature, regional average wind speed, regional average illumination, regional average groundwater content, and regional average ambient humidity; the terrain anomaly feature extraction unit is used to extract regional terrain time series features from the second terrain data to be stored through LSTM; the regional terrain time series features include regional average maximum slope and regional average minimum slope;

[0116] The Haloxylon ammodendron time series feature analysis layer analyzes the regional environmental time series features and the regional terrain time series features respectively, and obtains a first Haloxylon ammodendron anomaly coefficient and a second Haloxylon ammodendron anomaly coefficient respectively; and obtain a comprehensive Haloxylon ammodendron area anomaly coefficient according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient;

[0117] The abnormal coefficient output layer of the Haloxylon ammodendron is used to output the comprehensive abnormal coefficient of the Haloxylon ammodendron area.

[0118] Further, the regional average ambient temperature is:

[0119]

[0120] where AVT i represents the regional average ambient temperature of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VTT i_m represents the average ambient temperature of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0121] Further, the regional average groundwater content is:

[0122]

[0123] where WVT i represents the regional average groundwater content of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VWT i_m represents the average groundwater content of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0124] Further, the regional average ambient humidity is:

[0125]

[0126] where SVT i represents the regional average ambient humidity of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VST i_m represents the average ambient humidity of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0127] Further, the regional average wind speed is:

[0128]

[0129] where FVT i represents the regional average wind speed of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron in the i-th Haloxylon ammodendron area; VFT i_m represents the average wind speed of the m-th Haloxylon ammodendron in the i-th Haloxylon ammodendron area within the first time window;

[0130] Further, the regional average light is:

[0131]

[0132] Among them, GVT i represents the regional average illumination of the i-th Haloxylon ammodendron area; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area; VGT i_m represents the average illumination of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window;

[0133] Furthermore, the regional average maximum slope is:

[0134]

[0135] Among them, PMAT i represents the regional average maximum slope; MaxPT i_m represents the maximum slope of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area;

[0136] Furthermore, the regional average minimum slope is:

[0137]

[0138] Among them, PMIT i represents the regional average minimum slope; MinPT i_m represents the minimum slope of the m-th Haloxylon ammodendron tree in the i-th Haloxylon ammodendron area within the first time window; N i represents the number of Haloxylon ammodendron trees in the i-th Haloxylon ammodendron area;

[0139] The time series feature analysis layer analyzes the regional environmental time series features and regional terrain time series features respectively, and obtains the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; and according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient, obtains the comprehensive Haloxylon ammodendron area anomaly coefficient;

[0140] The first Haloxylon ammodendron anomaly coefficient is:

[0141]

[0142] Among them, EAC i represents the first Haloxylon ammodendron anomaly coefficient; AVT i represents the regional average environmental temperature; AVT iy represents the reference regional average environmental temperature; WVT i represents the regional average groundwater content; WVT iy represents the reference regional average groundwater content; SVT iRepresents the regional average ambient humidity; SVT iy Represents the reference regional average ambient humidity; FVT i Represents the regional average wind speed; FVT iy Represents the reference regional average wind speed; GVT i Represents the regional average illumination; GVT iy Represents the reference regional average illumination; exp() represents the exponential function with base e;

[0143] The second Haloxylon ammodendron anomaly coefficient is as follows:

[0144]

[0145] Wherein, TAC i Represents the second Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area; PMAT i Represents the regional average maximum slope; PMAT iy Represents the reference regional average maximum slope; PMIT i Represents the regional average minimum slope; PMIT iy Represents the reference regional average minimum slope; exp() represents the exponential function with base e;

[0146] Furthermore, the comprehensive Haloxylon ammodendron area anomaly coefficient is as follows:

[0147] RACIST i = WEI * EAC i + WAA * TAC i ;

[0148] Wherein, RACIST i Represents the comprehensive Haloxylon ammodendron area anomaly coefficient of the i-th Haloxylon ammodendron area; WEI represents the weight of the Haloxylon ammodendron environmental anomaly impact; EAC i Represents the first Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area; WAA represents the weight of the Haloxylon ammodendron terrain anomaly impact; TAC i Represents the second Haloxylon ammodendron anomaly coefficient of the i-th Haloxylon ammodendron area;

[0149] S3. Obtain the storage priority of the first Haloxylon ammodendron area data according to the comprehensive Haloxylon ammodendron area anomaly coefficient and the preset threshold set;

[0150] Furthermore, the preset threshold set includes a first comprehensive Haloxylon ammodendron area anomaly coefficient threshold and a second comprehensive Haloxylon ammodendron area anomaly coefficient threshold; the storage priority of the first Haloxylon ammodendron area data includes a first high storage priority, a second medium storage priority, and a third low storage priority; the storage priority of the first Haloxylon ammodendron area data is as follows:

[0151]

[0152] Among them, AP represents the data storage priority of the first Haloxylon ammodendron area; FA represents the first high storage priority; SA represents the second medium storage priority; TA represents the third low storage priority; T1 represents the first comprehensive Haloxylon ammodendron area anomaly coefficient threshold; T2 represents the second comprehensive Haloxylon ammodendron area anomaly coefficient threshold; RACIST represents the comprehensive Haloxylon ammodendron area anomaly coefficient;

[0153] S4. According to the data storage priority of each Haloxylon ammodendron area, store the data of each Haloxylon ammodendron area in the Haloxylon ammodendron distributed file system; the Haloxylon ammodendron distributed file system includes the first Haloxylon ammodendron database, the second Haloxylon ammodendron database, and the third Haloxylon ammodendron database.

[0154] Furthermore, the data storage priority of the first Haloxylon ammodendron area includes the first high storage priority, the second medium storage priority, and the third low storage priority; store the data of the Haloxylon ammodendron area with the first high storage priority in the first Haloxylon ammodendron database; store the data of the Haloxylon ammodendron area with the second medium storage priority in the second Haloxylon ammodendron database; store the data of the Haloxylon ammodendron area with the third low storage priority in the third Haloxylon ammodendron database.

[0155] To verify the effectiveness of a public data splitting and integrating storage method based on distributed storage provided in this embodiment, analyze the average query time of various growth monitoring data of Haloxylon ammodendron in B Desert using different methods. The specific results are shown in Table 2; the growth monitoring data includes the environmental temperature, groundwater content, environmental humidity, wind speed, light, and the slope of the ground where each Haloxylon ammodendron is located.

[0156] Table 2 Comparison of the average query time of various growth monitoring data of Haloxylon ammodendron in B Desert using different methods

[0157] Method Average query time Method 1 2ms Method 2 6ms Method 3 7ms

[0158] Method 1 is a public data splitting and integrating storage method based on distributed storage provided in this embodiment; Method 2 does not consider the comprehensive priority analysis based on the terrain data and environmental data of Haloxylon ammodendron on the basis of Method 1; Method 3 does not consider the distributed database storage based on the comprehensive priority on the basis of Method 1. As can be seen from Table 2, a public data splitting and integrating storage method based on distributed storage provided in this embodiment has a certain effectiveness, effectively improving the storage efficiency of the growth monitoring data of desert Haloxylon ammodendron.

[0159] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A public data splitting and integration storage system based on distributed storage, characterized in that: include: The module for acquiring data to be stored divides the Haloxylon ammodendron trees into regions according to the geographical distribution of the Haloxylon ammodendron trees in the desert, and acquires first environmental data to be stored and first terrain data to be stored of each Haloxylon ammodendron tree region; The data analysis module to be stored is used to construct a Haloxylon ammodendron anomaly recognition model to identify the first environmental data to be stored and the first terrain data to be stored, wherein the Haloxylon ammodendron anomaly recognition model includes an input layer, a preprocessing layer, a Haloxylon ammodendron temporal feature extraction layer, a Haloxylon ammodendron temporal feature analysis layer and a Haloxylon ammodendron anomaly coefficient output layer; the Haloxylon ammodendron temporal feature analysis layer is used to obtain the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; the comprehensive Haloxylon ammodendron area anomaly coefficient is obtained according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; A data classification module to be stored, used for obtaining the data storage priority of the first Haloxylon ammodendron area according to the comprehensive Haloxylon ammodendron area abnormality coefficient and a preset threshold set; The distributed storage module is used to store the data of each Haloxylon ammodendron area in a Haloxylon ammodendron distributed file system according to the data storage priority of the first Haloxylon ammodendron area of ​​each Haloxylon ammodendron tree area; the Haloxylon ammodendron distributed file system includes the first Haloxylon ammodendron database, the second Haloxylon ammodendron database and the third Haloxylon ammodendron database.

2. The public data splitting and integration storage system based on distributed storage according to claim 1 is characterized by: The first environmental data to be stored include the environmental temperature, groundwater content, environmental humidity, wind speed and light intensity of each Haloxylon ammodendron tree in the first time window; the first terrain data to be stored include the slope of the ground where each Haloxylon ammodendron tree is located in the first time window.

3. The public data splitting and integration storage system based on distributed storage according to claim 1 is characterized in that: The Haloxylon ammodendron anomaly recognition model comprises an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer and a Haloxylon ammodendron anomaly coefficient output layer; The input layer is used to input the first environmental data to be stored and the second terrain data to be stored into the Haloxylon ammodendron anomaly recognition model; The preprocessing layer is used to preprocess the first environment data to be stored and the first terrain data to be stored to obtain second environment data to be stored and second terrain data to be stored respectively; The Haloxylon ammodendron temporal feature extraction layer includes an environmental anomaly feature advance unit and a terrain anomaly feature extraction unit; The environmental anomaly feature advance unit is used to extract features of the second environmental data to be stored through LSTM to extract regional environmental time series features; The regional environmental time series features include regional average ambient temperature, regional average wind speed, regional average light, regional average groundwater content and regional average ambient humidity; the terrain anomaly feature extraction unit is used to extract features from the second terrain data to be stored through LSTM to obtain regional terrain time series features; The regional topographic time series characteristics include the regional average maximum slope and the regional average minimum slope; The Haloxylon ammodendron time series characteristic analysis layer analyzes the regional environmental time series characteristics and the regional terrain time series characteristics respectively, and obtains the first Haloxylon ammodendron tree abnormality coefficient and the second Haloxylon ammodendron tree abnormality coefficient respectively; and obtains the comprehensive Haloxylon ammodendron tree regional abnormality coefficient according to the first Haloxylon ammodendron tree abnormality coefficient and the second Haloxylon ammodendron tree abnormality coefficient; The Haloxylon ammodendron anomaly coefficient output layer is used to output the comprehensive Haloxylon ammodendron regional anomaly coefficient.

4. The public data splitting and integration storage system based on distributed storage according to claim 1 is characterized in that: The comprehensive Haloxylon ammodendron regional anomaly coefficient is: RACIST i =WEI*EAC i +WAA*TAC i 4 Among them, RACIST i represents the comprehensive Haloxylon ammodendron regional anomaly coefficient of the ith Haloxylon ammodendron area; WEI represents the Haloxylon ammodendron environmental anomaly impact weight; EAC i represents the first Haloxylon ammodendron anomaly coefficient of the ith Haloxylon ammodendron area; WAA represents the influence weight of the Haloxylon ammodendron terrain anomaly; TAC i Represents the abnormal coefficient of the second Haloxylon ammodendron tree in the i-th Haloxylon ammodendron tree area.

5. The public data splitting and integration storage system based on distributed storage according to claim 1 is characterized in that: The first Haloxylon ammodendron area data storage priority includes a first high storage priority, a second medium storage priority and a third low storage priority; the Haloxylon ammodendron area data of the first high storage priority is stored in the first Haloxylon ammodendron database; storing the Haloxylon ammodendron tree area data of the second storage priority level into a second Haloxylon ammodendron tree database; The Haloxylon ammodendron tree area data with the third lowest storage priority is stored in the third Haloxylon ammodendron tree database.

6. A method for splitting, integrating and storing public data based on distributed storage, characterized in that: include: S1. Split the Haloxylon ammodendron trees into regions according to their geographical location distribution in the desert to obtain various Haloxylon ammodendron tree regions, and obtain the first environmental data to be stored and the first terrain data to be stored for each Haloxylon ammodendron tree region; S2. Constructing a Haloxylon ammodendron anomaly recognition model to identify the first environmental data to be stored and the first terrain data to be stored, wherein the Haloxylon ammodendron anomaly recognition model comprises an input layer, a preprocessing layer, a Haloxylon ammodendron temporal feature extraction layer, a Haloxylon ammodendron temporal feature analysis layer and a Haloxylon ammodendron anomaly coefficient output layer; the Haloxylon ammodendron temporal feature analysis layer is used to obtain the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; and obtaining a comprehensive Haloxylon ammodendron regional anomaly coefficient according to the first Haloxylon ammodendron anomaly coefficient and the second Haloxylon ammodendron anomaly coefficient; S3. The data storage priority of the first Haloxylon ammodendron tree region is obtained based on the comprehensive Haloxylon ammodendron tree region abnormal coefficient and the preset threshold set; S4. According to the data storage priority of the first Haloxylon ammodendron area of ​​each Haloxylon ammodendron tree area; storing the data of each Haloxylon ammodendron tree area in a Haloxylon ammodendron distributed file system; the Haloxylon ammodendron distributed file system includes a first Haloxylon ammodendron database, a second Haloxylon ammodendron database and a third Haloxylon ammodendron database.

7. The method for splitting, integrating and storing public data based on distributed storage according to claim 6 is characterized in that: The first environmental data to be stored include the environmental temperature, groundwater content, environmental humidity, wind speed and light intensity of each Haloxylon ammodendron tree in the first time window; the first terrain data to be stored include the slope of the ground where each Haloxylon ammodendron tree is located in the first time window.

8. The method for splitting, integrating and storing public data based on distributed storage according to claim 6 is characterized in that: The Haloxylon ammodendron anomaly recognition model comprises an input layer, a preprocessing layer, a Haloxylon ammodendron time series feature extraction layer, a Haloxylon ammodendron time series feature analysis layer and a Haloxylon ammodendron anomaly coefficient output layer; The input layer is used to input the first environmental data to be stored and the second terrain data to be stored into the Haloxylon ammodendron anomaly recognition model; The preprocessing is used to preprocess the first environment data to be stored and the first terrain data to be stored to obtain second environment data to be stored and second terrain data to be stored respectively; The Haloxylon ammodendron temporal feature extraction layer includes an environmental anomaly feature advance unit and a terrain anomaly feature extraction unit; The environmental anomaly feature advance unit is used to extract features of the second environmental data to be stored through LSTM to extract regional environmental time series features; The regional environmental time series features include regional average ambient temperature, regional average wind speed, regional average light, regional average groundwater content and regional average ambient humidity; the terrain anomaly feature extraction unit is used to extract features from the second terrain data to be stored through LSTM to obtain regional terrain time series features; The regional topographic time series characteristics include the regional average maximum slope and the regional average minimum slope; The Haloxylon ammodendron time series characteristic analysis layer analyzes the regional environmental time series characteristics and the regional terrain time series characteristics respectively, and obtains the first Haloxylon ammodendron tree abnormality coefficient and the second Haloxylon ammodendron tree abnormality coefficient respectively; and obtains the comprehensive Haloxylon ammodendron tree regional abnormality coefficient according to the first Haloxylon ammodendron tree abnormality coefficient and the second Haloxylon ammodendron tree abnormality coefficient; The Haloxylon ammodendron anomaly coefficient output layer is used to output the comprehensive Haloxylon ammodendron regional anomaly coefficient.

9. The method for splitting, integrating and storing public data based on distributed storage according to claim 6, characterized in that: The comprehensive Haloxylon ammodendron regional anomaly coefficient is: RACIST i =WEI*EAC i +WAA*TAC i 4 Among them, RACIST i represents the comprehensive Haloxylon ammodendron regional anomaly coefficient of the ith Haloxylon ammodendron area; WEI represents the Haloxylon ammodendron environmental anomaly impact weight; EAC i represents the first Haloxylon ammodendron anomaly coefficient of the ith Haloxylon ammodendron area; WAA represents the influence weight of the Haloxylon ammodendron terrain anomaly; TAC i Represents the abnormal coefficient of the second Haloxylon ammodendron tree in the i-th Haloxylon ammodendron tree area.

10. The method for splitting, integrating and storing public data based on distributed storage according to claim 6, characterized in that: The first Haloxylon ammodendron area data storage priority includes a first high storage priority, a second medium storage priority and a third low storage priority; the Haloxylon ammodendron area data of the first high storage priority is stored in the first Haloxylon ammodendron database; storing the Haloxylon ammodendron tree area data of the second storage priority level into a second Haloxylon ammodendron tree database; The Haloxylon ammodendron tree area data with the third lowest storage priority is stored in the third Haloxylon ammodendron tree database.

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