Plateau area wetland vulnerability assessment method, device and equipment

Abstract

The invention provides a plateau area wetland vulnerability assessment method, device and equipment, and belongs to the technical field of ecological protection. The plateau area wetland vulnerability assessment method comprises the steps that vulnerability assessment data of a target plateau area wetland area are acquired, and the vulnerability assessment data comprise ecological system state data, ecological system structure data, ecological system process data and ecological system function data; according to the vulnerability evaluation data, obtaining vulnerability evaluation indexes and weights corresponding to the vulnerability evaluation indexes; and according to the vulnerability evaluation indexes and the weight corresponding to each vulnerability evaluation index, calculating to obtain a vulnerability score of the wetland area of the target plateau area.

Description

Technical Field

[0001] The present disclosure relates to the field of ecological protection technology, and more specifically, to a method, device and equipment for assessing wetland vulnerability in plateau areas. Background Art

[0002] Wetlands are important components of aquatic and terrestrial ecosystems, contributing to hydrological regulation, biodiversity conservation, carbon sequestration and maintaining regional ecological balance. However, the dynamics of wetlands have significantly altered their area, quantity, type and structure. Wetland vulnerability refers to the degree to which wetland ecosystems are susceptible to various stresses or disturbances that may have a negative impact on their ecological integrity, processes and functions.

[0003] In related technologies, ecological vulnerability assessment models mainly focus on specific external disturbances or internal states, and the evaluation is not comprehensive. Summary of the invention

[0004] In view of this, the present disclosure provides a method, device, equipment, medium and program product for assessing wetland vulnerability in plateau areas.

[0005] One aspect of the present disclosure provides a method for assessing wetland vulnerability in a plateau region, comprising: obtaining vulnerability assessment data of a target plateau wetland region, wherein the vulnerability assessment data comprises ecosystem status data, ecosystem structure data, ecosystem process data and ecosystem function data; obtaining vulnerability assessment indicators and weights corresponding to the vulnerability assessment indicators based on the vulnerability assessment data; and calculating a vulnerability score of the target plateau wetland region based on the vulnerability assessment indicators and the weights corresponding to the vulnerability assessment indicators.

[0006] According to an embodiment of the present disclosure, the above-mentioned ecosystem status data includes one or more of elevation, slope, terrain undulation, vegetation coverage, soil organic matter content, and soil erodibility level.

[0007] According to an embodiment of the present disclosure, the above-mentioned ecosystem structure data includes one or more of the maximum patch index, area-weighted average shape index, area-weighted average patch fractal dimension, spread index, landscape aggregation index, and average nearest neighbor distance.

[0008] According to an embodiment of the present disclosure, the above-mentioned ecosystem process data includes one or more of water occurrence frequency, nutrient cycle, hydrological cycle, and water transparency.

[0009] According to an embodiment of the present disclosure, the above-mentioned ecosystem function data includes one or more of habitat quality, carbon sequestration, water production, and cultural and recreational function values.

[0010] According to an embodiment of the present disclosure, the above-mentioned ecosystem function data includes cultural and entertainment function values.

[0011] According to an embodiment of the present disclosure, the cultural and entertainment function values ​​are determined based on water transparency and accessibility, and the accessibility represents the difficulty of reaching the target plateau wetland area.

[0012] According to an embodiment of the present disclosure, the accessibility is obtained through the following steps: generating a resistance layer of the above-mentioned target plateau wetland area in a geographic information system software based on the slope, land use type and road data of the above-mentioned target plateau wetland area; calculating the above-mentioned resistance layer using a cost distance function to obtain the above-mentioned accessibility.

[0013] According to an embodiment of the present disclosure, the resistance layer of the target plateau area wetland area is generated in the geographic information system software according to the slope, land use type and road data of the target plateau area wetland area, including: obtaining the slope resistance layer of the target plateau area wetland area according to the slope and the resistance values ​​corresponding to different slopes; obtaining the land use resistance layer of the target plateau area wetland area according to the land use conditions and the resistance values ​​of different land use types; obtaining the landscape resistance layer of the target plateau area wetland area according to the slope resistance layer and the land use resistance layer; obtaining the resistance layer of the target plateau area wetland area according to the road data and the landscape resistance layer.

[0014] According to an embodiment of the present disclosure, the water transparency is calculated using formula (5):

[0015] (5);

[0016] Among them, SDD is the water transparency, RED is the red band value in the atmospheric top reflectance image, BLUE is the blue band value in the atmospheric top reflectance image, and a and b are constants.

[0017] According to an embodiment of the present disclosure, obtaining vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator based on the vulnerability assessment data includes: normalizing the vulnerability assessment data to obtain normalized vulnerability assessment data; and processing the normalized vulnerability assessment data using a principal component analysis method to obtain the vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator.

[0018] According to an embodiment of the present disclosure, a clustering algorithm is used to classify the vulnerability scores of the above-mentioned plateau wetlands to obtain the vulnerability level of the above-mentioned target plateau wetland areas, and the above-mentioned vulnerability level includes at least one of the following: potential vulnerability, slight vulnerability, moderate vulnerability, severe vulnerability and extreme vulnerability.

[0019] Another aspect of the present disclosure provides a wetland vulnerability assessment device in a plateau area, comprising: an acquisition module for acquiring vulnerability assessment data of a target plateau wetland area, wherein the vulnerability assessment data includes ecosystem state data, ecosystem structure data, ecosystem process data and ecosystem function data; an acquisition module for obtaining vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator based on the vulnerability assessment data; and a calculation module for calculating a vulnerability score of the target plateau wetland area based on the vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator.

[0020] Another aspect of the present disclosure provides an electronic device, comprising:

[0021] one or more processors;

[0022] a memory for storing one or more programs,

[0023] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0024] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the above method when executed.

[0025] Another aspect of the present disclosure provides a computer program product, which includes computer executable instructions, and when the instructions are executed, are used to implement the method as described above.

[0026] According to the embodiment of the present disclosure, vulnerability assessment data including ecosystem status data, ecosystem structure data, ecosystem process data and ecosystem function data are used to obtain vulnerability assessment indicators and their weights, and then the vulnerability score of the wetland area in the target plateau area is calculated based on the vulnerability assessment indicators and their weights. The vulnerability score comprehensively considers the ecosystem status, ecosystem structure, ecosystem process and ecosystem function, is not limited by geographical regions or ecosystem types, and can better reflect the health status and vulnerability of the wetland area in the target plateau area. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0028] Figure 1 The exemplary system architecture to which the method and device for assessing wetland vulnerability in plateau areas can be applied according to an embodiment of the present disclosure is schematically shown;

[0029] Figure 2 A flowchart of a wetland vulnerability assessment method in a plateau region according to an embodiment of the present disclosure is schematically shown;

[0030] Figure 3 A block diagram schematically shows a device for assessing wetland vulnerability in plateau areas according to an embodiment of the present disclosure; and

[0031] Figure 4 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0033] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0034] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0035] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0036] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information and network security.

[0037] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0038] Vulnerability is an inherent attribute and characteristic of an ecosystem, reflecting the sensitivity and stability of the ecosystem to various internal and external factors, and how the ecosystem responds to the impact of these factors. Related technologies rely on a single indicator, such as the frequency of wetland water, to assess wetland vulnerability. However, this approach fails to cover multiple dimensions of the ecosystem, fails to solve ecological problems, and cannot identify the source of vulnerability. That is, in related technologies, the ecological vulnerability assessment model mainly focuses on specific external disturbances or internal states, and the evaluation is not comprehensive.

[0039] In the process of realizing the concept of the present disclosure, it was found that an ecosystem state-structure-process-function framework can be constructed to consider the uniqueness of wetland ecosystems and their dynamic mechanisms to comprehensively understand and assess the vulnerability of wetlands in plateau areas.

[0040] In view of this, an embodiment of the present disclosure provides a method for assessing wetland vulnerability in a plateau area, comprising: obtaining vulnerability assessment data of a target plateau wetland area, wherein the vulnerability assessment data includes ecosystem status data, ecosystem structure data, ecosystem process data and ecosystem function data; obtaining vulnerability evaluation indicators and weights corresponding to each vulnerability evaluation indicator based on the vulnerability assessment data; and calculating a vulnerability score of the target plateau wetland area based on the vulnerability evaluation indicators and the weights corresponding to each vulnerability evaluation indicator.

[0041] Figure 1 The exemplary system architecture 100 to which the method and device for assessing wetland vulnerability in plateau areas according to an embodiment of the present disclosure can be applied is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0042] like Figure 1As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0043] The user may use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software, etc. (only for example).

[0044] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0045] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0046] It should be noted that the plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the plateau wetland vulnerability assessment device provided by the embodiment of the present disclosure can generally be set in the server 105. The plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Correspondingly, the plateau wetland vulnerability assessment device provided by the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Alternatively, the plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102 or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103. Accordingly, the plateau wetland vulnerability assessment device provided by the embodiment of the present disclosure may also be arranged in the first terminal device 101, the second terminal device 102 or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103.

[0047] For example, the vulnerability assessment data of the target plateau wetland area may be originally stored in any one of the first terminal device 101, the second terminal device 102 or the third terminal device 103 (for example, the first terminal device 101, but not limited thereto), or stored in an external storage device and imported into the first terminal device 101. Then, the first terminal device 101 may locally execute the plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure, or send the vulnerability assessment data of the target plateau wetland area to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the vulnerability assessment data of the target plateau wetland area may execute the plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure.

[0048] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0049] Figure 2 The flowchart of the wetland vulnerability assessment method in plateau areas according to an embodiment of the present disclosure is schematically shown.

[0050] like Figure 2As shown, the method includes operations S210 to S230.

[0051] In operation S210, vulnerability assessment data of a wetland area in a target plateau region is obtained, wherein the vulnerability assessment data includes ecosystem state data, ecosystem structure data, ecosystem process data, and ecosystem function data.

[0052] In operation S220, vulnerability evaluation indicators and weights corresponding to the vulnerability evaluation indicators are obtained according to the vulnerability assessment data.

[0053] In operation S230, a vulnerability score of the wetland area in the target plateau region is calculated based on the vulnerability assessment indicators and the weights corresponding to the vulnerability assessment indicators.

[0054] According to the embodiment of the present disclosure, vulnerability assessment data including ecosystem status data, ecosystem structure data, ecosystem process data and ecosystem function data are used to obtain vulnerability assessment indicators and their weights, and then the vulnerability score of the wetland area in the target plateau area is calculated based on the vulnerability assessment indicators and their weights. The vulnerability score comprehensively considers the ecosystem status, ecosystem structure, ecosystem process and ecosystem function, is not limited by geographical regions or ecosystem types, and can better reflect the health status and vulnerability of the wetland area in the target plateau area.

[0055] The wetland vulnerability assessment method for plateau areas provided by the disclosed embodiment can improve the understanding of how ecosystems work, including how vulnerability is generated and how to develop sustainable ecosystem management strategies; and allow scholars to select appropriate assessment data and indicators for ecosystem status, structure, process and function based on regional characteristics and ecosystem types. For example, in grassland vulnerability assessment, more attention can be paid to ecosystem processes such as grassland degradation and land desertification, and ecosystem functions such as soil conservation can be given priority.

[0056] According to an embodiment of the present disclosure, before operation 210, the plateau wetland vulnerability assessment method further includes: selecting typical wetland areas in the plateau to determine the target plateau wetland areas for conducting wetland vulnerability assessment; and determining the target plateau wetland areas for conducting plateau wetland vulnerability assessment based on the characteristics of the plateau wetland areas.

[0057] According to the embodiments of the present disclosure, the state of the ecosystem refers to the ecological environment on which species or species groups depend for survival, mainly including natural environmental factors such as topography, vegetation and soil conditions, etc. Therefore, data on topography, vegetation and soil conditions can be selected to represent the habitat status of the wetland ecosystem.

[0058] According to an embodiment of the present disclosure, ecosystem structure is the geographical pattern of landscape components, including their size, type, quantity and spatial distribution. Landscape is closely related to ecological processes and has a significant impact on the ability to maintain ecosystem stability and integrity. One or more of the data such as patch area, patch shape, patch clustering and patch distance can be selected as ecosystem structure data.

[0059] According to an embodiment of the present disclosure, an ecosystem process refers to the dynamic characteristics of the occurrence and development of an event or phenomenon. Data such as wetland degradation, nutrient cycling, hydrological cycle, and eutrophication of water bodies can be selected to quantify ecosystem processes. The rich vegetation in the wetland not only supports a diverse biological community, but also ensures an adequate supply of nutrients. Wetlands with sufficient nutrient cycling can better resist and adapt to challenges such as climate change, human interference, and other external pressures. An increase in the hydrological cycle can provide water resources and help with water purification, thereby reducing the vulnerability of wetlands.

[0060] According to the embodiments of the present disclosure, ecosystem functions refer to various key activities performed by the ecosystem in order to maintain the stability of the ecosystem, such as support services, regulation services, supply services, and cultural services. Data related to support services, regulation services, supply services, and cultural services can be selected as ecosystem function data.

[0061] According to an embodiment of the present disclosure, before operation 210, the plateau wetland vulnerability assessment method further includes: establishing a plateau wetland ecosystem vulnerability assessment system, the plateau wetland ecosystem vulnerability assessment system including ecosystem state indicators, ecosystem structure indicators, ecosystem process indicators and ecosystem function indicators. The plateau wetland ecosystem vulnerability assessment system can be constructed with reference to formula (1):

[0062] (1);

[0063] Among them, WVI represents the vulnerability of wetland ecosystems in the plateau area, EC represents the ecosystem state, ES represents the ecosystem structure, EP represents the ecosystem process, and EF represents the ecosystem function.

[0064] According to the embodiments of the present disclosure, various indicators in the plateau wetland ecosystem vulnerability assessment system may correspond to the vulnerability assessment data of the target plateau wetland area.

[0065] Prior to operation 210, the plateau wetland vulnerability assessment method further includes: collecting data on the target plateau wetland area according to the plateau wetland ecosystem vulnerability assessment system.

[0066] According to an embodiment of the present disclosure, ecosystem status data or ecosystem status indicators may include terrain conditions, vegetation conditions and soil quality. Specifically, terrain conditions may be characterized by elevation, slope and terrain relief. Vegetation conditions may be represented by vegetation coverage. Soil organic matter content and soil erodibility level may be used to represent soil quality. That is, ecosystem status data may include one or more of elevation, slope, terrain relief, vegetation coverage, soil organic matter content and soil erodibility level.

[0067] Among them, elevation can represent the height difference between a certain place and sea level. Slope can represent the steepness of the surface unit. Topographic undulation can represent the difference between the highest point and the lowest point in a specific area. Vegetation cover can represent the percentage of the vertical projection area of ​​vegetation (including leaves, stems, and branches) on the ground to the total area of ​​the statistical area. Soil organic matter content can represent the percentage of all carbon-containing organic matter in various forms in the soil. Soil erodibility can represent the sensitivity of soil to erosion.

[0068] The calculation method of ecosystem status refers to formula (2):

[0069] (2);

[0070] Where EC is the ecosystem state, and are the standardized value and weight of the kth ecosystem status indicator, respectively, and m is the number of ecosystem status indicators.

[0071] According to an embodiment of the present disclosure, ecosystem structure data or ecosystem structure indicators may include one or more of patch area (maximum patch index), patch shape (area-weighted average shape index and area-weighted average patch fractal dimension), patch aggregation (spread index and landscape aggregation index), and patch distance (average nearest neighbor distance). That is, the ecosystem structure data includes one or more of the maximum patch index, area-weighted average shape index, area-weighted average patch fractal dimension, spread index, landscape aggregation index, and average nearest neighbor distance.

[0072] Among them, the maximum patch index can characterize the proportion of the largest patch to the landscape area. The area-weighted average shape index can characterize the area-weighted patch shape index. If the patch shape is square or circular (the most regular shape), the shape index is small; the more complex the shape (such as irregular polygons), the larger the shape index. The product-weighted average patch fractal dimension can characterize the shape complexity of the patch. The spread index can characterize the degree of aggregation of landscape elements in space, reflecting the spatial heterogeneity and connectivity of the landscape. The landscape aggregation index can characterize the degree of spatial aggregation of patches of the same type in the landscape. The average nearest neighbor distance can characterize the aggregation or dispersion pattern of points or patches in space. The distance from each point or patch to its nearest neighbor is calculated, and the average value of all points is taken to reflect the overall spatial distribution pattern.

[0073] According to an embodiment of the present disclosure, the wetland extent may be obtained from the Global Surface Water Dataset (GSW dataset) and calculated using landscape pattern index calculation software, for example, using Fragstats4.2 at a 30 m grid scale.

[0074] According to an embodiment of the present disclosure, the ecosystem process data or ecosystem process indicators include one or more of water occurrence frequency, nutrient cycle, hydrological cycle, and water transparency. The water occurrence frequency can represent the frequency of water occurrence in a certain area within a specific time period. The water transparency can represent the depth of light propagation in the water, reflecting the clarity of the water.

[0075] According to the embodiments of the present disclosure, water presence frequency (WPF) can reflect wetland degradation. If the water presence frequency in a wetland area is low, it may not provide a healthy wetland habitat. Therefore, the target year and the two years before and after can be selected to calculate the monthly surface water distribution data, and the water presence frequency of each grid can be calculated. The specific calculation method can refer to formula (3):

[0076] (3);

[0077] In the formula, is the calculated water frequency for pixel p, is the frequency of the jth pixel where water appears in image X, and N is the number of images.

[0078] According to an embodiment of the present disclosure, nutrient cycling can be reflected by the normalized difference vegetation index (NDVI). The normalized difference vegetation index can characterize vegetation coverage and growth conditions. The rich vegetation in the wetland not only supports a diverse biological community, but also ensures sufficient nutrient supply. Wetlands with sufficient nutrient cycling are more capable of withstanding and adapting to challenges such as climate change, human interference and other external pressures. NDVI can be calculated using satellite images, for example, using images from Landsat 5 and Landsat 8. The specific calculation method can refer to formula (4):

[0079] (4);

[0080] Where RED is the value of the red band and NIR is the value of the infrared band.

[0081] According to an embodiment of the present disclosure, an increase in the hydrological cycle can provide water resources and contribute to water purification, thereby reducing the vulnerability of wetlands. The hydrological cycle can be the difference between precipitation and evapotranspiration. Among them, the actual evapotranspiration can characterize the total amount of water consumption by water evaporation (from soil, surface water, etc.) and plant transpiration (through plant leaves) occurring in a region under actual environmental conditions. Precipitation can characterize liquid or solid water that falls from the atmosphere to the surface. The actual evapotranspiration and precipitation data can come from monthly climate and climate water balance datasets of the land surface, such as the Terra Climate dataset, and are used to reflect hydrological cycle conditions.

[0082] According to an embodiment of the present disclosure, eutrophication is one of the most obvious manifestations of China's water quality problems. Water transparency is usually called Secchi Disk Depth (SDD), which can reflect the nutrient status of aquatic ecosystems. Based on a geographic information system platform, such as the GEE platform (Google Earth Engine platform), satellite remote sensing images in the ice-free season (May to October) can be collected. Reflectivity images (TOA images) when they reach the ground after passing through the atmosphere, such as TOA images of Landsat5 and Landsat 8, can be used to calculate SDD.

[0083] According to an embodiment of the present disclosure, water transparency can be calculated using formula (5):

[0084] (5)

[0085] Among them, SDD is the water transparency, RED is the red band value in the atmospheric top reflectance image, BLUE is the blue band value in the atmospheric top reflectance image, and a and b are constants. a can be -5.6828, and b can be 7.8413.

[0086] According to an embodiment of the present disclosure, ecosystem function data or ecosystem function indicators include one or more of habitat quality, carbon sequestration, water production, and cultural and recreational function values. Among them, habitat quality can characterize the suitability of the habitat for species survival and reproduction. Carbon sequestration can characterize the ability to fix carbon through photosynthesis in an ecosystem. Water production can characterize the amount of available water generated from water resources such as precipitation, runoff, and groundwater in a specific area or time period. Cultural and recreational function values ​​can characterize the non-material benefits obtained by humans through interaction with the environment.

[0087] According to an embodiment of the present disclosure, habitat quality can be used to indicate the ability of an ecosystem to support biodiversity. A high-quality ecosystem can provide more resources for population survival, thereby enabling sustainable development of biodiversity. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model can be used to calculate habitat quality by combining the pressure intensity of various land use types and their sensitivity to threatening factors. When using the InVEST model to calculate habitat quality, a threat source table and a sensitivity table are required, as shown in Tables 1 and 2, where Table 1 shows the threat source weights and maximum impact distances, and Table 2 shows the habitat suitability and sensitivity to threat sources of each land use type. Land use data can come from the China Land Cover Dataset (CLCD). Habitat quality can be calculated with reference to formulas (6) and (7):

[0088] (6)

[0089] (7)

[0090] in, is the habitat quality of grid x in land use type j; represents the habitat suitability of land use type j; represents the habitat degradation index of grid x; z is the normalization parameter, which is usually set to 2.5 in the InVEST model; k is the half-saturation coefficient, which is set to 0.05; R represents the number of threat factors; r represents a single threat factor; represents the number of grids occupied by threat factor r; y represents the grid where threat factor r is located; Represents the weight of threat factor r; Represents the intensity of threat factors; Represents the impact of threat factors on each grid; Represents the relative sensitivity of land use types to different threat factors.

[0091] Table 1

[0092]

[0093] Table 2

[0094]

[0095] According to an embodiment of the present disclosure, net primary productivity (NPP) refers to the carbon fixed by organisms in an ecosystem through photosynthesis, which is crucial to mitigating climate change. Carbon sequestration can be evaluated based on net primary productivity. The basic assumption may be that according to the photosynthesis equation, vegetation fixes 1.63 carbon units per unit of NPP accumulation. NPP data may come from data acquired by a medium-resolution imaging spectrometer on a satellite, such as data acquired by the MOD17A3HGF V6.1 product, with a resolution of 500m. The data is derived from the sum of 8-day net photosynthesis (PSN) products (e.g., MOD17A2H). The PSN value is the difference (GPP-MR) between gross primary productivity (GPP) and maintenance respiration (MR). Specifically, it may be calculated with reference to formula (8):

[0096] (8)

[0097] Where CS is carbon sequestration and NPP is net primary productivity, both in kg·C / m 2 .

[0098] According to an embodiment of the present disclosure, as one of the ecosystem supply services, water production service contributes to human survival and activities as well as industrial water use. Reference evapotranspiration and precipitation can come from monthly climate and climate water balance datasets of the land surface, such as the TerraClimate dataset, land use can come from the China Land Cover Dataset (CLCD), and the root limiting layer depth data can come from the Depth to bedrock dataset, with a resolution of 100m. The data can be based on the integrated prediction of random forest and gradient boosting tree models, showing higher accuracy and more spatial details. The soil dataset can come from the Harmonized World Soil Database (HWSD) with a resolution of 1000m.

[0099] According to the embodiments of the present disclosure, the InVEST model can be used to calculate the water yield, which reflects the difference between precipitation and evapotranspiration of vegetation surface. Specifically, the calculation can be performed with reference to formulas (9) to (15):

[0100] (9)

[0101] (10)

[0102] (11)

[0103] (12)

[0104] (13)

[0105] (14)

[0106] (15)

[0107] In the formula, is the water yield of grid x in land use type j, is the actual evapotranspiration of grid x in land use type j, is the annual precipitation in raster x. is the ratio coefficient of actual evaporation to average annual precipitation, using an approximate algorithm based on the Budyko curve; is the annual average potential evapotranspiration of grid cell x on land use type j (mm); is the non-physical empirical fitting parameter of the natural climate-soil properties of the x grid unit, representing the ratio of the annual available water to precipitation corrected by the vegetation conditions of the x grid, dimensionless; is the crop coefficient of grid cell x on land use type j; is the reference crop evapotranspiration (mm); AWC is the plant available water content (mm); Z is a seasonal factor representing the regional precipitation distribution and other hydrogeological characteristics, with a value of 1 to 30; is the maximum soil depth of the x grid cell; is the root depth of the x grid unit; OC, OM, SAND, SLIT and CLAY represent the organic carbon content, organic matter content, sand content, silt content and clay content. The key coefficients of the biophysical table can be set in Table 3.

[0108] Table 3

[0109]

[0110] Note: lucode: land use type code; root_depth: maximum root depth of each land use type (mm); Kc: plant evapotranspiration coefficient of each land use type; LULC_veg: surface vegetation coverage, with vegetation coverage as 1 and no vegetation coverage as 0.

[0111] According to an embodiment of the present disclosure, the ecosystem function data includes cultural and entertainment function values.

[0112] According to an embodiment of the present disclosure, cultural services are non-material benefits obtained by humans through interaction with the environment. Culture and entertainment can be evaluated by considering the recreational potential of nature and its accessibility. Recreation potential is defined as the ability of an ecosystem to provide recreational opportunities due to natural biophysical conditions. Water transparency affects tourists' aesthetic perception of the water body, thereby changing their tourism interests and values. Increased water transparency prolongs tourists' recreational time and promotes tourism spending. Therefore, water transparency can be used to represent recreational potential. In addition, only areas that can actually be reached have the ability to provide cultural and recreational services. Therefore, the accessibility of transportation infrastructure such as railways and roads should be considered. Cultural and recreational functions can be determined based on water transparency and accessibility, and accessibility characterizes the difficulty of reaching the wetland area in the target plateau area.

[0113] According to an embodiment of the present disclosure, accessibility can be obtained through the following steps: generating a resistance layer of the target plateau wetland area in a geographic information system software based on the slope, land use type and road data of the target plateau wetland area; calculating the resistance layer using a cost distance function to obtain accessibility.

[0114] According to an embodiment of the present disclosure, factors affecting wetland accessibility may be considered, and resistance may be set for crossing terrain and land cover types. For example, resistance values ​​may be set with reference to Table 4, which is a terrain and land cover type resistance table.

[0115] Table 4

[0116]

[0117] According to an embodiment of the present disclosure, a resistance layer of a wetland area in a target plateau area with water transparency is generated in a geographic information system software according to the slope, land use type and road data of a wetland area in a target plateau area with water transparency, including: obtaining a slope resistance layer of the wetland area in the target plateau area according to the slope and resistance values ​​corresponding to different slopes; obtaining a land use resistance layer of the wetland area in the target plateau area according to the land use conditions and resistance values ​​of different land use types; obtaining a landscape resistance layer of the wetland area in the target plateau area according to the slope resistance layer and the land use resistance layer; and obtaining a resistance layer of the wetland area in the target plateau area according to the road data and the landscape resistance layer.

[0118] According to an embodiment of the present disclosure, equal weights or different weights can be assigned to land use and terrain (slope), for example, both can be 0.5, or the weight of land use can be set to 0.6 and the weight of terrain can be set to 0.4. The two resistance layers are combined to generate a single grid landscape resistance layer. The landscape resistance can be specifically calculated with reference to formula (16):

[0119] (16);

[0120] Where R is the landscape resistance, SLOPE is the slope value after classification, WS is the slope weight, LULC is the land use value after classification, and WL is the land use weight.

[0121] According to an embodiment of the present disclosure, road data can be obtained from OpenStreetMap. The road data can be formed into a road layer, and the road layer can be integrated into the landscape resistance layer. Where there is a road, the grid cell can be assigned a value of 1, and other places can be assigned a landscape resistance value to generate the final resistance layer.

[0122] According to an embodiment of the present disclosure, the accessibility of the wetland area in the target plateau region may be calculated using a cost distance function in geographic information system software, such as ArcGIS software.

[0123] According to the embodiments of the present disclosure, weights may be assigned to water transparency and accessibility. Specifically, water transparency and accessibility may be assigned the same weight or different weights, and recreational potential and accessibility may be superimposed to represent cultural and recreational function values. Specifically, the calculation may be performed with reference to formula (17):

[0124] (17)

[0125] In the formula, EC represents cultural and recreational services, SDD represents the recreational potential of the water body, Wd represents the weight of the recreational potential of the water body, A represents accessibility, and W a Represents the weight of accessibility.

[0126] According to an embodiment of the present disclosure, water transparency can be calculated using formula (5).

[0127] According to an embodiment of the present disclosure, based on vulnerability assessment data, vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator are obtained, including:

[0128] Normalizing the vulnerability assessment data to obtain normalized vulnerability assessment data;

[0129] The principal component analysis method is used to process the normalized vulnerability assessment data to obtain the vulnerability assessment indicators and the corresponding weights of each vulnerability assessment indicator.

[0130] According to the embodiments of the present disclosure, a normalization method can be used to normalize all data or indicators. Since different vulnerability indicators often have different dimensions and units, in order to compare the vulnerability assessment results and summarize the indicators of different dimensions and scales, all evaluation indicators can be normalized so that each data or indicator is in the same order of magnitude. In addition, the annual changes in the wetland ecosystem vulnerability index can be focused on. To this end, the minimum-maximum normalization method can be used to normalize each data or indicator so that its indicator range is between 0 and 1, which is convenient for aggregation between indicators. According to the relationship between the wetland ecosystem vulnerability index and the indicator, the indicator can be divided into positive indicators and negative indicators. Specifically, refer to formula (18) and formula (19) for calculation:

[0131] (18)

[0132] (19)

[0133] In the formula, is the normalized value of index i, is the attribute value of index i, and are the minimum and maximum values ​​of index i respectively.

[0134] According to the embodiments of the present disclosure, principal component analysis (PCA) is an objective and commonly used method for determining the weights of each component. It extracts important indicators and objectively transforms their related indicators into a set. As an objective method, principal component analysis can effectively avoid subjective influences in the vulnerability assessment process. The purpose of using principal component analysis to determine weights is to solve the collinearity and redundancy that may exist between indicators, and to reduce the dimensionality of multidimensional data, so as to extract representative principal components and determine the weights of each indicator when constructing the ecological vulnerability index. The information of each indicator can be more effectively and comprehensively utilized, reducing information redundancy while avoiding excessive consideration of highly correlated indicators. For the principal component calculation method, refer to formulas (20) to (22):

[0135] (20);

[0136] In the formula, is the principal component score, w is the principal component loading, x is the observed value of the variable, i is the number of principal components, and p is the total number of variables.

[0137] (twenty one);

[0138] In the formula, is the wetland ecosystem vulnerability index, r is the principal component contribution rate, PC is the principal component score, and q is the number of principal components retained. Referring to the formula, the calculation method of the principal component contribution rate r is as follows:

[0139] (twenty two);

[0140] In the formula, is the contribution rate of the principal component, is the eigenvalue of the i-th principal component.

[0141] According to an embodiment of the present disclosure, the principal component analysis method is used to determine the component weights by extracting basic indicators and objectively converting their related variables into a set of indicators, thereby reducing subjective bias that may occur in the weight determination process.

[0142] According to the embodiments of the present disclosure, each vulnerability assessment index and its weight may be weighted and summed to obtain the vulnerability score of the wetland area in the target plateau region. The specific calculation may be performed with reference to formula (23).

[0143] (twenty three);

[0144] Among them, WVI represents the vulnerability of wetland ecosystems in the plateau region, EC represents the ecosystem state, ES represents the ecosystem structure, EP represents the ecosystem process, and EF represents the ecosystem function. They represent the weights of ecosystem state, ecosystem structure, ecosystem process, and ecosystem function respectively.

[0145] According to an embodiment of the present disclosure, the vulnerability score can be used to evaluate the vulnerability level of the target plateau wetland area. The plateau wetland vulnerability assessment method also includes: using a clustering algorithm to classify the plateau wetland vulnerability score to obtain the vulnerability level of the target plateau wetland area, and the vulnerability level includes at least one of the following: potential vulnerability, slight vulnerability, moderate vulnerability, severe vulnerability and extreme vulnerability.

[0146] According to an embodiment of the present disclosure, the fragility of wetland ecosystems may be classified using a K-means clustering algorithm.

[0147] The plateau wetland vulnerability assessment method provided by the embodiment of the present disclosure can better reflect the health status and vulnerability of the target plateau wetland area; improve the understanding of how the ecosystem works, including how vulnerability is generated and how to formulate sustainable ecosystem management strategies.

[0148] Figure 3 A block diagram of a device for assessing wetland vulnerability in plateau areas according to an embodiment of the present disclosure is schematically shown.

[0149] like Figure 3 As shown, the device 300 for assessing wetland vulnerability in plateau areas includes an acquisition module 310 , an obtaining module 320 , and a calculation module 330 .

[0150] The acquisition module 310 is used to acquire vulnerability assessment data of wetland areas in the target plateau region, wherein the vulnerability assessment data includes ecosystem state data, ecosystem structure data, ecosystem process data and ecosystem function data.

[0151] The acquisition module 320 is used to obtain vulnerability evaluation indicators and weights corresponding to each vulnerability evaluation indicator according to the vulnerability assessment data.

[0152] The calculation module 330 is used to calculate the vulnerability score of the wetland area in the target plateau area according to the vulnerability assessment indicators and the weights corresponding to the vulnerability assessment indicators.

[0153] According to an embodiment of the present disclosure, the acquisition module 310 includes a reachability calculation submodule, which includes a generation unit and a calculation unit. The generation unit is used to generate a resistance layer of a wetland area in a plateau area of ​​water transparency target in a geographic information system software according to the slope, land use type and road data of the wetland area in the plateau area of ​​water transparency target; the calculation unit is used to calculate the water transparency resistance layer using a cost distance function to obtain water transparency accessibility.

[0154] According to an embodiment of the present disclosure, the generating unit includes a first obtaining subunit, a second obtaining subunit, a third obtaining subunit and a fourth obtaining subunit. Among them, the first obtaining subunit is used to obtain the slope resistance layer of the wetland area in the plateau region of the water body transparency target according to the water body transparency slope and the resistance values ​​corresponding to different slopes; the second obtaining subunit is used to obtain the land use resistance layer of the wetland area in the plateau region of the water body transparency target according to the water body transparency land use situation and the resistance values ​​of different land use types; the third obtaining subunit is used to obtain the landscape resistance layer of the wetland area in the plateau region of the water body transparency target according to the water body transparency slope resistance layer and the water body transparency land use resistance layer; the fourth obtaining subunit is used to obtain the resistance layer of the wetland area in the plateau region of the water body transparency target according to the water body transparency road data and the water body transparency landscape resistance layer.

[0155] The acquisition module 320 includes a first processing submodule and a second processing submodule. The first processing submodule is used to normalize the water transparency vulnerability assessment data to obtain normalized vulnerability assessment data; the first processing submodule is used to process the normalized water transparency vulnerability assessment data using the principal component analysis method to obtain water transparency vulnerability assessment indicators and weights corresponding to each water transparency vulnerability assessment indicator.

[0156] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging circuits, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0157] For example, any multiple of the acquisition module 310, the acquisition module 320, and the calculation module 330 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the acquisition module 310, the acquisition module 320, and the calculation module 330 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the acquisition module 310 , the obtaining module 320 , and the calculation module 330 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be executed.

[0158] It should be noted that the data processing system part in the embodiments of the present disclosure corresponds to the data processing method part in the embodiments of the present disclosure. The description of the data processing system part specifically refers to the data processing method part, which will not be repeated here.

[0159] Figure 4 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0160] like Figure 4 As shown, the electronic device 400 according to an embodiment of the present disclosure includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage part 408 to a random access memory (RAM) 403. The processor 401 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 401 may also include an onboard memory for caching purposes. The processor 401 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0161] In RAM 403, various programs and data required for the operation of electronic device 400 are stored. Processor 401, ROM 402 and RAM 403 are connected to each other via bus 404. Processor 401 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 402 and / or RAM 403. It should be noted that the program can also be stored in one or more memories other than ROM 402 and RAM 403. Processor 401 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0162] According to an embodiment of the present disclosure, the electronic device 400 may further include an input / output (I / O) interface 405, which is also connected to the bus 404. The electronic device 400 may further include one or more of the following components connected to the input / output (I / O) interface 405: an input portion 406 including a keyboard, a mouse, etc.; an output portion 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 408 including a hard disk, etc.; and a communication portion 409 including a network interface card such as a LAN card, a modem, etc. The communication portion 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output (I / O) interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage portion 408 as needed.

[0163] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the processor 401, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0164] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0165] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: 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), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0166] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 402 and / or the RAM 403 described above and / or one or more memories other than the ROM 402 and the RAM 403 .

[0167] The embodiments of the present disclosure also include a computer program product, which includes a computer program, which contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the method for assessing wetland vulnerability in plateau areas provided by the embodiments of the present disclosure.

[0168] When the computer program is executed by the processor 401, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0169] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 409, and / or installed from the removable medium 411. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0170] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0171] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0172] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for assessing wetland vulnerability in plateau areas, comprising: Acquire vulnerability assessment data of wetland areas in the target plateau region, wherein the vulnerability assessment data includes ecosystem status data, ecosystem structure data, ecosystem process data, and ecosystem function data; According to the vulnerability assessment data, vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator are obtained; The vulnerability score of the wetland area in the target plateau region is calculated based on the vulnerability assessment indicators and the weights corresponding to the respective vulnerability assessment indicators.

2. The method according to claim 1, wherein: The ecosystem status data includes one or more of elevation, slope, terrain relief, vegetation coverage, soil organic matter content, and soil erodibility level; The ecosystem structure data include one or more of the largest patch index, area-weighted average shape index, area-weighted average patch fractal dimension, spread index, landscape aggregation index, and average nearest neighbor distance; The ecosystem process data include one or more of water occurrence frequency, nutrient cycle, hydrological cycle, and water transparency; The ecosystem function data includes one or more of habitat quality, carbon sequestration, water yield, and cultural and recreational function values.

3. The method according to claim 1 or 2, wherein: The ecosystem function data include cultural and recreational function values; Among them, the cultural and recreational function value is determined based on water transparency and accessibility, and the accessibility represents the difficulty of reaching the target plateau wetland area.

4. The method according to claim 3, wherein: The accessibility is obtained by the following steps: Generating a resistance layer of the target plateau wetland area in a geographic information system software according to the slope, land use type and road data of the target plateau wetland area; The resistance layer is calculated using a cost distance function to obtain the accessibility.

5. The method according to claim 4, wherein: The step of generating the resistance layer of the target plateau wetland area in the geographic information system software according to the slope, land use type and road data of the target plateau wetland area includes: According to the slope and the resistance values ​​corresponding to different slopes, a slope resistance layer of the wetland area in the target plateau region is obtained; According to the land use conditions and resistance values ​​of different land use types, a land use resistance layer of the wetland area in the target plateau region is obtained; According to the slope resistance layer and the land use resistance layer, a landscape resistance layer of the wetland area in the target plateau region is obtained; The resistance layer of the wetland area in the target plateau region is obtained according to the road data and the landscape resistance layer.

6. The method according to claim 3, wherein: The water transparency is calculated using formula (5): （5）； Among them, SDD is the water transparency, RED is the red band value in the atmospheric top reflectance image, BLUE is the blue band value in the atmospheric top reflectance image, and a and b are constants.

7. The method according to claim 1 or 2, wherein: The vulnerability assessment index and the weight corresponding to each vulnerability assessment index are obtained according to the vulnerability assessment data, including: Normalizing the vulnerability assessment data to obtain normalized vulnerability assessment data; The normalized vulnerability assessment data is processed by principal component analysis to obtain the vulnerability assessment index and the weight corresponding to each vulnerability assessment index.

8. The method according to claim 1 or 2, further comprising: A clustering algorithm is used to classify the vulnerability scores of the plateau wetlands to obtain the vulnerability level of the target plateau wetland area, and the vulnerability level includes at least one of the following: potential vulnerability, slight vulnerability, moderate vulnerability, severe vulnerability and extreme vulnerability.

9. A device for assessing wetland vulnerability in plateau areas, comprising: An acquisition module, used to acquire vulnerability assessment data of wetland areas in a target plateau region, wherein the vulnerability assessment data includes ecosystem status data, ecosystem structure data, ecosystem process data and ecosystem function data; An acquisition module, used to obtain vulnerability assessment indicators and weights corresponding to each vulnerability assessment indicator according to the vulnerability assessment data; The calculation module is used to calculate the vulnerability score of the wetland area in the target plateau area according to the vulnerability assessment index and the weight corresponding to each vulnerability assessment index.

10. An electronic device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 8.

Images