Ecological compensation and biodiversity monitoring method based on big data

Abstract

The invention relates to the technical field of ecological compensation, and discloses an ecological compensation and biodiversity monitoring method based on big data, comprising the following steps: S101, acquiring ecological data of a to-be-monitored area, regularly dividing the area into N grid units, and constructing corresponding ecological data structure units; s102, based on the ecological service characteristic parameters and the biodiversity characteristic parameters, calculating ecological service value characteristics and biodiversity pressure indexes; s103, carrying out coupling processing on the ecological service value characteristics and the biodiversity pressure index, and calculating an ecological coordination coefficient and an elastic regulation coefficient; s104, calculating an ecological compensation amount through a first preset decision function; s105, calculating a cost-benefit ratio according to the ecological service value characteristics and the ecological compensation amount, and performing automatic adjustment when the cost-benefit ratio does not reach a preset performance standard threshold value; according to the invention, accurate identification, dynamic adjustment and performance closed-loop optimization of ecological compensation are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of ecological compensation, and particularly relates to a method for ecological compensation and biodiversity monitoring based on big data. Background Art

[0002] With the continuous advancement of ecological civilization construction, ecological compensation, as an important policy tool for achieving regional ecological interest balance and sustainable utilization of ecological resources, has been widely applied in the fields of forest, water source, wetland protection, etc. However, the existing ecological compensation technology system generally has the following problems: 1. The ecological service value assessment method is relatively single, mainly relying on fixed-value models or macro empirical parameters, lacking fine characterization of regional differences, temporal dynamics, and the comprehensive contribution of ecosystems; 2. The compensation object identification mechanism is imperfect, making it difficult to comprehensively consider the trade-off between ecological supply and ecological vulnerability, and prone to the miscompensation phenomenon of "emphasizing quantity and neglecting quality"; 3. The existing compensation decisions are mostly static configurations, lacking the dynamic response ability to the changing trend of ecosystems and unable to adjust strategies based on real-time monitoring data. Summary of the Invention

[0003] The present invention provides a method for ecological compensation and biodiversity monitoring based on big data, which solves the technical problems of rough ecological service assessment, inaccurate compensation object identification, and lack of dynamic adjustment and performance feedback mechanisms for compensation strategies in related technologies.

[0004] The present invention provides a method for ecological compensation and biodiversity monitoring based on big data, including the following steps:

[0005] S101, obtaining ecological data of the area to be monitored, regularly dividing the area to be monitored into N grid units, and constructing an ecological data structure unit corresponding to each grid unit, where N is a user-defined parameter;

[0006] S102, extracting ecological service characteristic parameters and biodiversity characteristic parameters according to the ecological data structure unit, and calculating the ecological service value characteristics and biodiversity pressure index;

[0007] S103, presetting an analysis period, performing coupling processing on the ecological service value characteristics and biodiversity pressure index within the current analysis period, and calculating the ecological coordination coefficient; and calculating the elastic regulation coefficient based on the difference between the ecological coordination coefficient in the current analysis period and the ecological coordination coefficient in the previous analysis period;

[0008] S104, calculating the ecological compensation amount based on the preset basic compensation rate, ecological coordination coefficient, elastic regulation coefficient, and ecological service value characteristics according to the first preset decision function;

[0009] S105. Calculate the cost-benefit ratio based on the ecological service value characteristics and the ecological compensation amount, and automatically adjust the basic compensation rate, ecological coordination coefficient, and elastic regulation coefficient when the cost-benefit ratio does not reach the preset performance standard threshold.

[0010] Further, the ecological data includes: remote sensing images, annual precipitation, species types, and species quantities.

[0011] Further, the ecological service characteristic parameters include: carbon sequestration volume, water conservation volume;

[0012] Among them, the carbon sequestration volume is obtained by multiplying the unit vegetation coverage area by the preset carbon storage coefficient per unit area; the unit vegetation coverage area is obtained by threshold screening of the vegetation index NDVI extracted from the remote sensing image and counting the area;

[0013] The water conservation volume is obtained by the difference between the annual precipitation and the preset actual evapotranspiration;

[0014] The ecological service value characteristics are obtained by multiplying the carbon sequestration volume and the water conservation volume by the corresponding preset market price coefficients respectively.

[0015] Further, the biodiversity characteristic parameters include: species diversity index, species evenness, and species richness;

[0016] Among them, the species diversity index is obtained by multiplying the frequencies of various species appearing in the area to be monitored by their corresponding logarithm conversion values and summing them up;

[0017] The species evenness is obtained by the ratio of the species diversity index to the preset theoretical maximum diversity index;

[0018] The species richness is represented by the number of species in the area to be monitored;

[0019] The biodiversity pressure index is obtained by normalizing and weighting the species diversity index, species evenness, and species richness.

[0020] Further, the first normalized value is obtained by the ratio of the ecological service value characteristics of the ecological data structure unit to the maximum value of the ecological service value characteristics in the area to be monitored, and the second normalized value is obtained by the ratio of the biodiversity pressure index of this ecological data structure unit to the maximum value of the biodiversity pressure index in the area to be monitored. The first normalized value and the second normalized value are combined to obtain the ecological coordination coefficient of this ecological data structure unit;

[0021] When the ecological coordination coefficient is higher than the first preset threshold, identify the corresponding ecological data structure unit as the priority compensation object and conduct priority compensation.

[0022] Further, the elastic regulation coefficient is obtained by combining the difference in the ecological coordination coefficients of the ecological data structure units in adjacent analysis periods with a preset sensitivity coefficient.

[0023] Further, the calculation formula of the first preset decision function is:

[0024] Comp i,t = R0 * (w1 * CE i,t + w2 * EF i,t ) * ESV i,t ;

[0025] where Comp i,t represents the ecological compensation amount of the i-th ecological data structure unit in the t-th analysis period, R0 represents the preset basic compensation rate, w1 and w2 respectively represent the first weight coefficient and the second weight coefficient, and the sum of the first weight coefficient and the second weight coefficient is 1. CE i,t represents the ecological coordination coefficient of the i-th ecological data structure unit in the t-th analysis period, EF i,t represents the elastic regulation coefficient of the i-th ecological data structure unit in the t-th analysis period, ESV i,t represents the ecological service value characteristic of the i-th ecological data structure unit in the t-th analysis period, i represents the index of the ecological data structure unit, and t represents the analysis period index.

[0026] Further, when the change range of the biodiversity pressure index of the ecological data structure unit in the current analysis period compared to the previous analysis period exceeds the second preset threshold, an immediate compensation addition mechanism is triggered. The immediate compensation addition mechanism includes: calculating the immediate compensation addition ratio based on the part where the change range exceeds the second preset threshold, and adjusting the ecological compensation amount of the corresponding ecological data structure unit based on the immediate compensation addition ratio.

[0027] Further, by accumulating the differences in the ecological service value characteristics of each ecological data structure unit over T analysis periods, the total increment of the ecological service value is obtained, and then the ratio of the total increment of the ecological service value to the sum of the ecological compensation amounts over T analysis periods is calculated to obtain the cost-benefit ratio. T represents the number of preset analysis periods. The calculation formula of the cost-benefit ratio is:

[0028]

[0029] where BCR represents the cost-benefit ratio, ESV i,T represents the ecological service value characteristic of the i-th ecological data structure unit in the T-th analysis period, ESV i,1 represents the ecological service value characteristic of the i-th ecological data structure unit in the 1st analysis period, and N represents the number of ecological data structure units.

[0030] The beneficial effects of the present invention are as follows: By constructing the ecological service value characteristics and the biodiversity pressure index, and combining with the grid processing of multi-source ecological data, the present invention realizes the spatial quantitative assessment of the ecosystem state and the synchronous analysis of the functional pressure; By introducing the ecological coordination coefficient and the elastic regulation coefficient, a compensation decision-making mechanism integrating priority identification and dynamic regulation is constructed to realize the precise screening of ecological compensation objects and the flexible control of the response intensity of compensation funds; Further, by comparing the ecological compensation amount with the ecological service value in multiple periods, calculating the cost-benefit ratio, and using it as the basis for model optimization, the adaptive adjustment of the basic compensation rate, coordination weight and regulation parameters is realized.

[0031] Through the organic integration of data collection, index fusion, trend perception and feedback evaluation, the present invention realizes the transformation of ecological compensation from static allocation to dynamic optimization, and has the advantages of strong identification accuracy, high regulation flexibility, clear performance drive, etc., improving the efficiency of ecological fund allocation and the effectiveness of ecosystem protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flowchart of the method for ecological compensation and biodiversity monitoring based on big data of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] Reference will now be made to example embodiments to discuss the subject matter described herein. It should be understood that discussing these embodiments is only to enable those skilled in the art to better understand and thus implement the subject matter described herein, and the functions and arrangements of the elements discussed can be changed without departing from the scope of protection of the content of this specification. Each example can omit, substitute or add various processes or components as needed. Additionally, the features described relative to some examples can also be combined in other examples.

[0034] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in one or more embodiments of the present invention should have the ordinary meaning understood by those of ordinary skill in the field to which the present invention pertains. The terms "first", "second" and similar words used in one or more embodiments of the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Words such as "comprising" or "including" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. Words such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Upper", "lower", "left", "right", etc. are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0035] As Figure 1 shown, the ecological compensation and biodiversity monitoring method based on big data includes the following steps:

[0036] S101. Obtain the ecological data of the area to be monitored, regularly divide the area to be monitored into N grid units, and construct an ecological data structure unit corresponding to each grid unit, where N is a user-defined parameter;

[0037] S102. Extract ecological service characteristic parameters and biodiversity characteristic parameters according to the ecological data structure unit, and calculate the ecological service value characteristics and the biodiversity pressure index;

[0038] S103. Preset an analysis period, perform coupling processing on the ecological service value characteristics and the biodiversity pressure index within the current analysis period, and calculate the ecological coordination coefficient; and calculate the elastic regulation coefficient based on the difference between the ecological coordination coefficient in the current analysis period and the ecological coordination coefficient in the previous analysis period;

[0039] S104. Calculate the ecological compensation amount based on the preset basic compensation rate, ecological coordination coefficient, elastic regulation coefficient, and ecological service value characteristics according to the first preset decision function;

[0040] S105. Calculate the cost-benefit ratio according to the ecological service value characteristics and the ecological compensation amount, and automatically adjust the basic compensation rate, ecological coordination coefficient, and elastic regulation coefficient when the cost-benefit ratio does not reach the preset performance standard threshold.

[0041] In an embodiment of the present invention, the ecological data includes: remote sensing images, annual precipitation, species types, and species quantities; the area to be monitored is regularly divided into N grid units as the spatial boundaries of the ecological data structure units, and the ecological data structure units are used to uniformly organize and manage the ecological data related to this spatial range within each grid unit, serving as the basic unit for subsequent index calculation and analysis.

[0042] Specifically, remote sensing images are obtained through the national remote sensing data and application service platform, annual precipitation is obtained through the China Meteorological Data Network, and plant and animal species are monitored through drones and infrared cameras to obtain species types and species quantities.

[0043] In an embodiment of the present invention, the ecological data is preprocessed, and the preprocessing steps include:

[0044] S201, perform spatial registration processing on the ecological data to ensure that the remote sensing images, annual precipitation, species types, and species quantities are aligned under a unified coordinate system;

[0045] S202, use the difference method to replace the outliers in the ecological data;

[0046] S203, perform normalization processing on the replaced ecological data using the maximum-minimum normalization method to unify the dimensions.

[0047] In an embodiment of the present invention, the ecological service characteristic parameters include: carbon sequestration amount, water conservation amount; the biodiversity characteristic parameters include: species diversity index, species evenness, and species richness;

[0048] The carbon sequestration amount is obtained by multiplying the unit vegetation coverage area by the preset unit area carbon storage coefficient;

[0049] Specifically, the carbon sequestration amount refers to the ability of regional vegetation to absorb carbon dioxide in the atmosphere through photosynthesis and convert it into organic carbon in plants within a preset time period and preset spatial range, reflecting the total amount of carbon fixed by the regional ecosystem. The unit vegetation coverage area refers to the surface area actually covered by vegetation in the area to be monitored. In this embodiment, the vegetation index NDVI is obtained by processing the remote sensing images, and a vegetation recognition threshold is set. The pixels with NDVI values greater than or equal to the vegetation recognition threshold are determined as vegetation-covered areas. Then, the number of remote sensing pixels that meet the conditions in the area to be monitored is statistically calculated in space, and this number is multiplied by the actual ground area of a single pixel to obtain the unit vegetation coverage area. During the above processing, it can be further corrected in combination with the land use classification map to exclude non-vegetation land types such as buildings and water bodies, thereby improving the accuracy and applicability of the estimation results.

[0050] The water conservation capacity is obtained by the difference between the annual precipitation and the preset actual evapotranspiration;

[0051] Specifically, water conservation capacity refers to the net amount of water retained by the regional natural system through the interception, accumulation and infiltration of precipitation through plants, soil and other factors within a preset time period and a preset spatial scope. Actual evapotranspiration refers to the amount of water lost to the atmosphere through soil evaporation and plant leaf transpiration within a preset spatial scope, which is preset based on land cover type, vegetation growth conditions and soil permeability.

[0052] The ecological service value characteristics are obtained by multiplying the carbon sink and water conservation amounts with the corresponding preset market price coefficients, and are used to measure the comprehensive contribution of the ecosystem in the monitored area in carbon sink and water conservation. The market price coefficient specifically includes the unit carbon price in the carbon trading market and the local water price, and can be adjusted according to actual conditions.

[0053] The species diversity index is obtained by multiplying the frequency of occurrence of various species in the monitored area by their corresponding logarithmic transformation values and summing them up. It is used to measure the richness of species in the ecosystem and reflect the complexity of the overall biodiversity. The higher the species diversity index, the richer the species distribution. The calculation formula of the species diversity index is: I spd =-∑p j *log(p j ), where I spd represents the species diversity index, p j represents the frequency of species j in the monitored area, log(p j ) indicates p j The corresponding logarithmic transformed values;

[0054] Species evenness is obtained by comparing the species diversity index to the preset theoretical maximum diversity index. It is used to measure the degree of balance in the distribution of species in an ecosystem and reflect whether the number of species is evenly distributed or whether there are dominant species. The theoretical maximum diversity index is set according to the total number of species in the monitored area.

[0055] The species richness is represented by the number of species in the area to be monitored.

[0056] The biodiversity pressure index is obtained by normalizing and weighting the species diversity index, species evenness and species richness. The biodiversity pressure index is used to measure the degree to which species diversity is threatened or degraded in the monitored area.

[0057] In one embodiment of the present invention, the calculation formula of the ecological coordination coefficient is:

[0058]

[0059] Among them, CE i,t represents the ecological coordination coefficient of the i-th ecological data structure unit in the t-th analysis period, ESV i,t represents the ecological service value characteristics of the i-th ecological data structure unit in the t-th analysis period, ESV max represents the maximum value of the ecological service value characteristics in the t-th analysis period in the area to be monitored, BPI i,t represents the biodiversity pressure index of the i-th ecological data structure unit in the t-th analysis period, BPI max represents the maximum value of the biodiversity pressure index in the t-th analysis period in the area to be monitored. i represents the index of the ecological data structure unit, and t represents the analysis period index.

[0060] Among them, the ecological coordination coefficient is used to comprehensively reflect the performance of the ecological data structure unit in two dimensions: ecological service value and biodiversity vulnerability. The higher the value, the higher the level of ecological service function provided by the unit, and at the same time, its ecosystem is at a higher risk of degradation or sensitivity. When the ecological coordination coefficient of a certain ecological data structure unit is higher than the first preset threshold, it is determined that the unit is in the "high contribution - high pressure" state, that is, the area plays a key role in ecological function supply and also faces a greater risk of degradation. Therefore, this unit is identified as a priority compensation object and given priority in subsequent ecological compensation resource allocation, such as assigning a higher weight in the calculation of ecological compensation amount or disbursing funds in advance.

[0061] In an embodiment of the present invention, the calculation formula of the elastic regulation coefficient is:

[0062] EF i,t = 1 + α * (CE i,t - CE i,t-1 );

[0063] Among them, EF i,t represents the elastic regulation coefficient of the i-th ecological data structure unit in the t-th analysis period, which is used to adjust the response amplitude of the ecological compensation amount to the change of the ecological coordination coefficient. CE i,t-1 represents the ecological coordination coefficient of the i-th ecological data structure unit in the (t - 1)-th analysis period. α represents the sensitivity coefficient, and its value range is from 0 to 1. Preferably, it is set to 0.5. When the elastic regulation coefficient is greater than 1, it means that this ecological data structure unit needs to increase compensation. When the elastic regulation coefficient is less than 1, it means that this ecological data structure unit needs to reduce compensation.

[0064] In an embodiment of the present invention, the calculation formula of the first preset decision function is:

[0065] Comp i,t= R0 * (w1 * CE i,t + w2 * EF i,t ) * ESV i,t ;

[0066] where Comp i,t represents the ecological compensation amount of the i-th ecological data structure unit in the t-th analysis period, which is used for capital investment in the actual area represented by the ecological data structure unit. R0 represents the preset basic compensation rate, w1 and w2 respectively represent the first weight coefficient and the second weight coefficient, and the sum of the first weight coefficient and the second weight coefficient is 1; by setting w1 and w2, different influence weights are given to the ecological coordination coefficient and the elastic regulation coefficient respectively, so as to control the response focus of the compensation strategy; ESV i,t represents the ecological service value characteristics of the i-th ecological data structure unit in the t-th analysis period.

[0067] The first preset decision function can implement a compensation strategy based on ecological supply - priority identification - trend regulation, reflecting the accuracy and adaptive ability of the present invention in ecological fund allocation.

[0068] In an embodiment of the present invention, an immediate compensation addition mechanism is introduced. This mechanism judges whether the ecosystem has deteriorated significantly by monitoring the change of the biodiversity pressure index in the ecological data structure unit within consecutive analysis periods;

[0069] Specifically, when the change range of the biodiversity pressure index in the current analysis period compared with the value in the previous analysis period exceeds the second preset threshold, the immediate compensation addition mechanism is triggered. This mechanism calculates the immediate compensation addition ratio according to the value part exceeding the second preset threshold, and this ratio reflects the severity of the ecological pressure increase. Further, based on the immediate compensation addition ratio, the ecological compensation amount corresponding to this ecological data structure unit is dynamically adjusted, that is, the capital investment is increased proportionally on the basis of the basic compensation amount to strengthen the protection of this area. Through the immediate compensation addition mechanism, the allocation of ecological compensation funds is more flexible and targeted, can respond to sudden changes in the ecological environment in a timely manner, effectively prevent the expansion of the ecological degradation trend, and realize the dynamic management and precise investment of ecological compensation.

[0070] In an embodiment of the present invention, by accumulating the differences in the ecological service value characteristics of each ecological data structure unit within T analysis periods, the total increment of ecological service value is obtained, and then the ratio of it to the sum of the ecological compensation amounts within T analysis periods is calculated to obtain the cost - benefit ratio, so as to measure the degree of improvement in ecological benefits brought by the compensation investment. T represents the preset number of analysis periods; among them, the calculation formula of the cost - benefit ratio is:

[0071]

[0072] Among them, BCR represents the cost-benefit ratio, and ESV i,T represents the ecological service value characteristics of the i-th ecological data structure unit in the T-th analysis period. ESV i,1 The ecological service value characteristics of the i-th ecological data structure unit in the 1st analysis period. i represents the ecological data structure unit index, N represents the number of ecological data structure units, t represents the analysis period index, and Comp i,t represents the ecological compensation amount of the i-th ecological data structure unit in the t-th analysis period.

[0073] When the calculated cost-benefit ratio does not reach the set performance standard threshold, the basic compensation rate, ecological coordination coefficient, and elastic regulation coefficient will be automatically adjusted. Preferably, the performance standard threshold is set to 1;

[0074] Specifically, for the basic compensation rate, ecological coordination coefficient, and elastic regulation coefficient, on the basis of the original values, they are proportionally adjusted at a fixed step size. The default adjustment amplitude is 5%; the adjusted parameters will be used in the next analysis period to calculate the new ecological compensation amount.

[0075] It should be noted that the setting of the interval and threshold size is for the convenience of comparison. Among them, the size of the threshold depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data, as long as it does not affect the proportional relationship between the parameters and the quantified values. And the above formulas are all calculations of taking the numerical value without dimension. The formulas are all obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0076] The above describes the embodiments of the present invention, but the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of this embodiment, those of ordinary skill in the art can also make many forms, all of which fall within the protection scope of this embodiment.

Claims

1. A method for ecological compensation and biodiversity monitoring based on big data, characterized in that, It includes the following steps: S101. Obtain the ecological data of the area to be monitored, regularly divide the area to be monitored into N grid units, and construct an ecological data structure unit corresponding to each grid unit, where N is a custom parameter; S102. Extract the ecological service characteristic parameters and biodiversity characteristic parameters according to the ecological data structure unit, and calculate the ecological service value characteristics and biodiversity pressure index; S103. Preset an analysis period, perform coupling processing on the ecological service value characteristics and biodiversity pressure index within the current analysis period, and calculate the ecological coordination coefficient; and calculate the elastic regulation coefficient based on the difference between the ecological coordination coefficient in the current analysis period and the ecological coordination coefficient in the previous analysis period; S104. Calculate the ecological compensation amount based on the preset basic compensation rate, ecological coordination coefficient, elastic regulation coefficient, and ecological service value characteristics according to the first preset decision function; S105. Calculate the cost-benefit ratio based on the ecological service value characteristics and ecological compensation amount, and automatically adjust the basic compensation rate, ecological coordination coefficient, and elastic regulation coefficient when the cost-benefit ratio does not reach the preset performance standard threshold.

2. The method for ecological compensation and biodiversity monitoring based on big data according to claim 1, wherein The ecological data includes: remote sensing images, annual precipitation, species types, and species quantities.

3. The method for ecological compensation and biodiversity monitoring based on big data according to claim 2, wherein The ecological service characteristic parameters include: carbon sequestration amount, water conservation amount; Among them, the carbon sequestration amount is obtained by multiplying the unit vegetation coverage area by the preset unit area carbon storage coefficient; the unit vegetation coverage area is obtained by threshold screening the vegetation index NDVI extracted from the remote sensing image and counting the area; The water conservation amount is obtained by subtracting the preset actual evapotranspiration amount from the annual precipitation; The ecological service value characteristics are obtained by multiplying the carbon sequestration amount and the water conservation amount by the corresponding preset market price coefficients respectively.

4. The method for ecological compensation and biodiversity monitoring based on big data according to claim 2, wherein The biodiversity characteristic parameters include: species diversity index, species evenness, and species richness; Among them, the species diversity index is obtained by multiplying the occurrence frequency of each type of species in the area to be monitored by its corresponding logarithm conversion value and summing them up; The species evenness is obtained by the ratio of the species diversity index to the preset theoretical maximum diversity index; The species richness is represented by the number of species in the area to be monitored; The biodiversity pressure index is obtained by normalizing and weighting the species diversity index, species evenness, and species richness.

5. The method for ecological compensation and biodiversity monitoring based on big data according to claim 3, wherein The first normalization value is obtained by the ratio of the ecological service value characteristics of the ecological data structure unit to the maximum value of the ecological service value characteristics in the area to be monitored, and the second normalization value is obtained by the ratio of the biodiversity pressure index of this ecological data structure unit to the maximum value of the biodiversity pressure index in the area to be monitored. The first normalization value and the second normalization value are combined to obtain the ecological coordination coefficient of this ecological data structure unit; When the ecological coordination coefficient is higher than the first preset threshold, identify the corresponding ecological data structure unit as the priority compensation object and conduct priority compensation.

6. The method for ecological compensation and biodiversity monitoring based on big data according to claim 5, characterized in that The elastic regulation coefficient is obtained by combining the difference in the ecological coordination coefficients of the ecological data structure units in adjacent analysis periods with the preset sensitivity coefficient.

7. The method for ecological compensation and biodiversity monitoring based on big data according to claim 6, wherein, The calculation formula of the first preset decision function is as follows: Comp i,t = R0 * (w1 * CE i,t + w2 * EF i,t ) * ESV i,t ; Among them, Comp i,t represents the ecological compensation amount of the i-th ecological data structure unit in the t-th analysis period. R0 represents the preset basic compensation rate. w1 and w2 respectively represent the first weight coefficient and the second weight coefficient, and the sum of the first weight coefficient and the second weight coefficient is 1. CE i,t represents the ecological coordination coefficient of the i-th ecological data structure unit in the t-th analysis period. EF i,t represents the elastic regulation coefficient of the i-th ecological data structure unit in the t-th analysis period. ESV i,t represents the ecological service value characteristic of the i-th ecological data structure unit in the t-th analysis period. i represents the index of the ecological data structure unit, and t represents the analysis period index.

8. The method for ecological compensation and biodiversity monitoring based on big data according to claim 4, wherein When the change range of the biodiversity pressure index of the ecological data structure unit in the current analysis period compared with the previous analysis period exceeds the second preset threshold, an immediate compensation addition mechanism is triggered. The immediate compensation addition mechanism includes: calculating the immediate compensation addition ratio according to the part where the change range exceeds the second preset threshold, and adjusting the ecological compensation amount of the corresponding ecological data structure unit based on the immediate compensation addition ratio.

9. The method for ecological compensation and biodiversity monitoring based on big data according to claim 7, characterized in that, By accumulating the differences in the ecological service value characteristics of each ecological data structure unit in T analysis periods, the total increment of ecological service value is obtained, and then it is divided by the sum of the ecological compensation amounts in T analysis periods to calculate the cost-benefit ratio, where T represents the number of preset analysis periods; among them, the calculation formula of the cost-benefit ratio is: Among them, BCR represents the cost-benefit ratio, and ESV i,T represents the ecological service value characteristics of the i-th ecological data structure unit in the T-th analysis period. ESV i,1 represents the ecological service value characteristics of the i-th ecological data structure unit in the 1st analysis period, and N represents the number of ecological data structure units.

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