Ecological system service threshold effect evaluation method, system and device and storage medium

Abstract

The invention relates to the technical field of ecosystem services, and particularly discloses an ecosystem service threshold effect evaluation method, system and device and a storage medium, and the method comprises the steps: obtaining the historical data of a target ecosystem service of a target region, and constructing a plurality of driving factors of the target ecosystem service; and determining a threshold effect of the target ecosystem service on each driving factor based on historical data of the target ecosystem service of the target area. According to the invention, by evaluating the threshold effect of the driving factors of the ecological system service, the response change trend of the ecological system service to various driving factors can be determined, the development and utilization red line of the ecological environment is delimited, and the alarm clock is timely knocked before the ecological system service is subjected to unrecoverable damage. Under the condition that the ecological environment is guaranteed, urban economic prosperous construction and resource development maximization are promoted to the maximum extent.

Description

Background Art

[0002] Ecosystems not only provide a variety of important production resources, but also provide indispensable ecological services in climate regulation, air purification, soil conservation, leisure and entertainment. These ecological services not only support human development and well-being, but also contribute to the coordinated stability between regional ecological security and social economy. Limited by factors such as resources and the environment, urban development and resource development and utilization will have a significant impact on ecosystem services. However, current research on driving factors is often limited to evaluating the response intensity of various driving factors to ecosystem services, and there is little analysis of threshold effects.

[0003] Therefore, it is urgent to provide a technical solution to solve the above problems. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an ecosystem service threshold effect assessment method, system, device and storage medium.

[0005] In a first aspect, the present invention provides a method for evaluating the threshold effect of ecosystem services, and the technical solution of the method is as follows:

[0006] Obtain historical data on target ecosystem services in target areas and construct multiple drivers of target ecosystem services;

[0007] Determine the threshold effect of the target ecosystem service for each driver based on historical data on the target ecosystem service in the target area.

[0008] The beneficial effects of an ecosystem service threshold effect assessment method of the present invention are as follows:

[0009] The method of the present invention can evaluate the threshold effect of the driving factors of ecosystem services, clarify the changing trend of the response of ecosystem services to various driving factors, delineate the red line of development and utilization of the ecological environment, and sound the alarm in time before the ecosystem services suffer irreversible damage. Under the condition of ensuring the ecological environment, it can promote the prosperity of urban economy and maximize the development of resources.

[0010] Based on the above scheme, the ecosystem service threshold effect assessment method of the present invention can also be improved as follows.

[0011] In an optional approach, the threshold effect includes: a critical threshold turning point and an optimal threshold interval; based on the historical data of the target ecosystem service in the target area, the steps of determining the threshold effect of the target ecosystem service on each driver include:

[0012] Using a piecewise linear regression model, combined with historical data on the target ecosystem service in the target area and multiple drivers of the target ecosystem service, critical threshold turning points for the target ecosystem service for each driver were identified;

[0013] The random forest model was used to determine the optimal threshold interval of the target ecosystem service for each driver, combined with the historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service.

[0014] In one optional approach, using a piecewise linear regression model, combined with historical data on the target ecosystem service in the target area and multiple drivers of the target ecosystem service, the steps to identify critical threshold turning points for the target ecosystem service for each driver include:

[0015] Taking the historical data of the target ecosystem service in the target area as the dependent variable of the piecewise linear regression model and any driving factor of the target ecosystem service as the independent variable of the piecewise linear regression model, a target piecewise linear regression model corresponding to the driving factor is constructed, and based on the target piecewise linear regression model corresponding to the driving factor, the critical threshold turning point of the target ecosystem service for the driving factor is determined until the critical threshold turning point of the target ecosystem service for each driving factor is determined.

[0016] In an optional approach, the driving factors include: natural factors and social factors.

[0017] In one alternative approach, the targeted ecosystem services are: water yield, habitat quality, soil conservation, carbon storage, carbon sequestration and oxygen release, food production, water purification, or tourism and recreation.

[0018] In an optional manner, the method further includes:

[0019] Based on the threshold effect of the target ecosystem service on the target driver and the current measured value of the target driver in the target area, it is determined whether to output the early warning information of the target ecosystem service in the target area.

[0020] In a second aspect, the present invention provides an ecosystem service threshold effect assessment system, the technical solution of which is as follows:

[0021] Includes: processing module and evaluation module;

[0022] The processing module is used to: obtain historical data of target ecosystem services in the target area and construct multiple drivers of target ecosystem services;

[0023] The assessment module is used to: determine the threshold effect of the target ecosystem service for each driver based on the historical data of the target ecosystem service in the target area.

[0024] The beneficial effects of an ecosystem service threshold effect assessment system of the present invention are as follows:

[0025] The system of the present invention can evaluate the threshold effect of the driving factors of ecosystem services, clarify the changing trend of the response of ecosystem services to various driving factors, delineate the red line of development and utilization of the ecological environment, and sound the alarm in time before the ecosystem services suffer irreversible damage. Under the condition of ensuring the ecological environment, it can promote the prosperity of urban economy and maximize the development of resources.

[0026] Based on the above scheme, the ecosystem service threshold effect assessment system of the present invention can also be improved as follows.

[0027] In an optional manner, the threshold effect includes: a critical threshold turning point and an optimal threshold interval; the evaluation module is specifically used for:

[0028] Using a piecewise linear regression model, combined with historical data on the target ecosystem service in the target area and multiple drivers of the target ecosystem service, critical threshold turning points for the target ecosystem service for each driver were identified;

[0029] The random forest model was used to determine the optimal threshold interval of the target ecosystem service for each driver, combined with the historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service.

[0030] In a third aspect, a technical solution of an electronic device of the present invention is as follows:

[0031] The invention comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps of the method for assessing the threshold effect of ecosystem services of the present invention are implemented.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium having the following technical solution:

[0033] Instructions are stored in the computer-readable storage medium. When the computer-readable storage medium reads the instructions, the computer-readable storage medium executes the steps of the ecosystem service threshold effect assessment method of the present invention.

[0034] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0036] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for assessing threshold effects of ecosystem services of the present invention;

[0037] Figure 2 is a schematic flow chart of step S2;

[0038] Figure 3 It is a structural schematic diagram of an embodiment of an ecosystem service threshold effect assessment system of the present invention;

[0039] Figure 4 The figure is a schematic structural diagram of an embodiment of an electronic device of the present invention. DETAILED DESCRIPTION

[0040] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0041] Figure 1 A flow chart of an embodiment of an ecosystem service threshold effect assessment method provided by the present invention is shown, and the ecosystem service threshold effect assessment method can be executed by an electronic device such as a terminal device or a server. The terminal device can be any fixed or mobile terminal such as a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. The server can be a single server or a server cluster composed of multiple servers. Any electronic device can implement the ecosystem service threshold effect assessment method by calling computer-readable instructions stored in a memory through a processor. For example Figure 1 As shown, the following steps are included:

[0042] S1. Obtain historical data on target ecosystem services in the target area and construct multiple drivers of target ecosystem services.

[0043] Among them, ecosystem services include but are not limited to: water yield, habitat quality, soil conservation, carbon storage, carbon fixation and oxygen release, food production, water purification or tourism and recreation. The target ecosystem service is any one of the above ecosystem services. The target area can be any region or city, and the historical time period can be 5 years (with each year or each month as the collection time point), and there is no restriction here. Historical data refers to: ecosystem service data within the historical time period. Historical data can be obtained based on land use, precipitation, evapotranspiration, NDVI, NPP, DEM, and statistical yearbook data, and can also be combined with the INVEST model and NDVI allocation method to characterize the spatiotemporal change trend of historical spatiotemporal data. For example, when the ecosystem service is water yield, the historical data refers to: water yield data within the historical time period.

[0044] Among them, multiple driving factors include: natural factors and social factors. Natural factors include: grassland proportion, elevation, forest land proportion, cultivated land proportion, vegetation coverage, precipitation, temperature, and evapotranspiration. Social factors include: GDP, POP, convenient medical services, convenient living services, construction land proportion, transportation facilities services, and residents' savings level.

[0045] S2. Determine the threshold effect of the target ecosystem service for each driver based on historical data of the target ecosystem service in the target area.

[0046] Among them, the threshold effect includes: critical threshold turning point and optimal threshold interval.

[0047] Specifically, Figure 2 As shown, S2 includes:

[0048] S21. Use a piecewise linear regression model and combine historical data on the target ecosystem service in the target area and multiple drivers of the target ecosystem service to determine the critical threshold turning points of the target ecosystem service for each driver.

[0049] Among them, the piecewise linear regression model was constructed by R language. The historical data of the target ecosystem service in the target area was used as the dependent variable of the piecewise linear regression model, and any driving factor of the target ecosystem service was used as the independent variable of the piecewise linear regression model. The target piecewise linear regression model corresponding to the driving factor was constructed, and the critical threshold turning point of the target ecosystem service for the driving factor was determined according to the target piecewise linear regression model corresponding to the driving factor, until the critical threshold turning point of the target ecosystem service for each driving factor was determined.

[0050] S22. Use the random forest model and combine the historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service to determine the optimal threshold range of the target ecosystem service for each driver.

[0051] Among them, Python was used to build a random forest model. The historical data of the target ecosystem service in the target area and multiple driving factors of the target ecosystem service were input into the random forest model to obtain the optimal threshold interval of the target ecosystem service for each driving factor.

[0052] In an optional manner, the method further includes:

[0053] S3. Determine whether to output early warning information of the target ecosystem service in the target area based on the threshold effect of the target ecosystem service on the target driver and the current measured value of the target driver in the target area.

[0054] Among them, the current measurement value is the measurement value of the driving factor in the current year (month or date). For example, when the driving factor is grassland proportion and the target ecosystem service is soil conservation, it is determined whether the soil conservation reaches the threshold according to the threshold effect of soil conservation on grassland proportion in the target area and the current measurement value of grassland proportion, so as to determine whether to output the early warning information of soil conservation in the target area. The early warning information can be a warning information in the form of text, voice, light, etc., and there is no limitation here. The early warning information can be sent to the terminal device for prompting.

[0055] The technical solution of this embodiment can evaluate the threshold effect of the driving factors of ecosystem services, clarify the changing trend of the response of ecosystem services to various driving factors, delineate the red line of development and utilization of the ecological environment, and sound the alarm in time before the ecosystem services suffer irreversible damage. Under the condition of ensuring the ecological environment, it can promote the prosperity of urban economy and maximize the development of resources.

[0056] Figure 3 FIG. 2 is a schematic diagram showing a structure of an embodiment of an ecosystem service threshold effect assessment system 200 provided by the present invention. Figure 3 As shown, the system 200 includes: a processing module 210 and an evaluation module 220;

[0057] The processing module 210 is used to: obtain historical data of target ecosystem services in the target area and construct multiple driving factors of the target ecosystem services;

[0058] The evaluation module 220 is used to determine the threshold effect of the target ecosystem service on each driving factor based on the historical data of the target ecosystem service in the target area.

[0059] In an optional manner, the threshold effect includes: a critical threshold turning point and an optimal threshold interval; the evaluation module 220 is specifically used for:

[0060] Using a piecewise linear regression model, combined with historical data on the target ecosystem service in the target area and multiple drivers of the target ecosystem service, critical threshold turning points for the target ecosystem service for each driver were identified;

[0061] The random forest model was used to determine the optimal threshold interval of the target ecosystem service for each driver, combined with the historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service.

[0062] In an optional manner, the evaluation module 220 is further configured to:

[0063] Taking the historical data of the target ecosystem service in the target area as the dependent variable of the piecewise linear regression model and any driving factor of the target ecosystem service as the independent variable of the piecewise linear regression model, a target piecewise linear regression model corresponding to the driving factor is constructed, and based on the target piecewise linear regression model corresponding to the driving factor, the critical threshold turning point of the target ecosystem service for the driving factor is determined until the critical threshold turning point of the target ecosystem service for each driving factor is determined.

[0064] In an optional approach, the driving factors include: natural factors and social factors.

[0065] In one alternative approach, the targeted ecosystem services are: water yield, habitat quality, soil conservation, carbon storage, carbon sequestration and oxygen release, food production, water purification, or tourism and recreation.

[0066] In an optional manner, the determination module;

[0067] The determination module is used to determine whether to output early warning information of the target ecosystem service in the target area based on the threshold effect of the target ecosystem service on the target driving factor and the current measured value of the target driving factor in the target area.

[0068] The technical solution of this embodiment can evaluate the threshold effect of the driving factors of ecosystem services, clarify the changing trend of the response of ecosystem services to various driving factors, delineate the red line of development and utilization of the ecological environment, and sound the alarm in time before the ecosystem services suffer irreversible damage. Under the condition of ensuring the ecological environment, it can promote the prosperity of urban economy and maximize the development of resources.

[0069] The above-mentioned parameters and steps for each module to implement corresponding functions in the ecosystem service threshold effect assessment system 200 of this embodiment can refer to the parameters and steps in the embodiment of the ecosystem service threshold effect assessment method above, and will not be repeated here.

[0070] like Figure 4As shown, an electronic device 300 of an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the electronic device 300 implements any of the above-mentioned ecosystem service threshold effect assessment methods, specifically:

[0071] The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein the one or more memories 310 store at least one computer program 330, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any of the ecosystem service threshold effect assessment methods provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the electronic device 300 may also include other components for implementing device functions, which will not be described in detail here.

[0072] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements any of the above-mentioned ecosystem service threshold effect assessment methods.

[0073] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0074] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs any of the above-mentioned ecosystem service threshold effect assessment methods.

[0075] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0076] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0077] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0078] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for assessing the threshold effect of ecosystem services, characterized in that: include: Obtain historical data on target ecosystem services in target areas and construct multiple drivers of said target ecosystem services; Based on the historical data of the target ecosystem service in the target area, the threshold effect of the target ecosystem service on each driver is determined.

2. The ecosystem service threshold effect assessment method according to claim 1, characterized in that: The threshold effect includes: a critical threshold turning point and an optimal threshold interval; based on the historical data of the target ecosystem service in the target area, the step of determining the threshold effect of the target ecosystem service on each driving factor includes: Using a piecewise linear regression model, combined with historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service, determine the critical threshold turning points of the target ecosystem service for each driver; The random forest model is used to determine the optimal threshold range of the target ecosystem service for each driving factor in combination with the historical data of the target ecosystem service in the target area and multiple driving factors of the target ecosystem service.

3. The method for assessing the threshold effect of ecosystem services according to claim 2, characterized in that: The steps of determining the critical threshold turning points of the target ecosystem service for each driver using a piecewise linear regression model and combining historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service include: Taking the historical data of the target ecosystem service in the target area as the dependent variable of the piecewise linear regression model and any driving factor of the target ecosystem service as the independent variable of the piecewise linear regression model, a target piecewise linear regression model corresponding to the driving factor is constructed, and according to the target piecewise linear regression model corresponding to the driving factor, the key threshold turning point of the target ecosystem service for the driving factor is determined until the key threshold turning point of the target ecosystem service for each driving factor is determined.

4. The method for assessing the threshold effect of ecosystem services according to any one of claims 1 to 3, characterized in that: Driving factors include: natural factors and social factors.

5. The method for assessing the threshold effect of ecosystem services according to any one of claims 1 to 3, characterized in that: The target ecosystem services are: water yield, habitat quality, soil conservation, carbon storage, carbon fixation and oxygen release, food production, water purification or tourism and recreation.

6. The method for assessing the threshold effect of ecosystem services according to claim 1, characterized in that: Also includes: Based on the threshold effect of the target ecosystem service on the target driving factor and the current measured value of the target driving factor in the target area, it is determined whether to output early warning information of the target ecosystem service in the target area.

7. An ecosystem service threshold effect assessment system, characterized in that: include: Processing module and evaluation module; The processing module is used to: obtain historical data of target ecosystem services in a target area and construct multiple driving factors of the target ecosystem services; The assessment module is used to determine the threshold effect of the target ecosystem service on each driving factor based on the historical data of the target ecosystem service in the target area.

8. The ecosystem service threshold effect assessment system according to claim 7, characterized in that: The threshold effect includes: a critical threshold turning point and an optimal threshold interval; the evaluation module is specifically used for: Using a piecewise linear regression model, combined with historical data of the target ecosystem service in the target area and multiple drivers of the target ecosystem service, determine the critical threshold turning points of the target ecosystem service for each driver; The random forest model is used to determine the optimal threshold range of the target ecosystem service for each driving factor in combination with the historical data of the target ecosystem service in the target area and multiple driving factors of the target ecosystem service.

9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor so that the electronic device implements the ecosystem service threshold effect assessment method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that the computer-readable storage medium implements the ecosystem service threshold effect assessment method according to any one of claims 1 to 6.

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