Ecological protection and restoration ecological benefit assessment method

Abstract

The invention discloses an ecological protection and restoration ecological benefit assessment method, which comprises the following steps: S1, N-level division of assessment indexes: dividing first-level indexes, and dividing second-level to N-level indexes in a tree structure based on the first-level indexes; s2, index data calculation: calculating and obtaining N-level index data, and then calculating and summarizing data level by level until first-level index data is obtained; and S3, metric value calculation: determining a weight coefficient of each first-level index by a structure entropy weight method, and calculating the first-level index data by a weighted summary algorithm to obtain an ecological protection and restoration ecological benefit metric value. According to the scheme, the structure entropy weight method and the weighted summary algorithm are combined, the uncertain influence possibly existing due to the difference of experts on index understanding can be reduced, the accuracy of weight coefficient determination is improved, and then the evaluation accuracy of the ecological protection and restoration ecological benefit measurement value is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological protection and restoration ecological benefit assessment, and particularly to an ecological protection and restoration ecological benefit assessment method. Background Art

[0002] Ecological protection and restoration projects aim to, on the basis of following the succession laws and internal mechanisms of natural ecosystems such as integrity, systematicness, continuity, and sustainability, through the integration of various funds and the comprehensive application of various engineering technologies, conduct overall protection, systematic restoration, and comprehensive management of damaged, degraded, and ecosystem services-declined ecosystems, so as to achieve the optimization of the ecological system pattern, system stability, and function improvement in the protection and restoration area.

[0003] The constituent elements of the ecological system in karst mountainous areas include forests, grasslands, wetlands, rivers, lakes, and farmlands, etc. The ecological structure is relatively complex. The technical process of its ecological protection and restoration project is generally divided into four stages: project planning, project design, project implementation, and management and maintenance. The project planning stage serves for the identification and diagnosis of macro problems at the regional (or basin) scale (Landscape Scale), the formulation of overall protection and restoration goals, and the determination of protection and restoration units and the layout of project sub-items; the project design stage mainly serves for the diagnosis of ecological problems of each protection and restoration unit at the ecosystem scale (Ecosystem Scale), the formulation of corresponding specific index systems and standards, and the determination of protection and restoration mode measures; the project implementation stage serves for the construction design and implementation of sub-items at the site scale (SiteScale). Management and maintenance, monitoring and evaluation, adaptive management, and supervision and inspection run through the whole process of ecological protection and restoration.

[0004] In terms of monitoring and evaluation, it mainly monitors the change trends of ecological problems, the protection and utilization of natural resources, the improvement of the ecological environment, the improvement of ecosystem service functions, and the ecological benefits obtained by the project, etc., and evaluates the relevant indicators of the ecosystem obtained by monitoring. In terms of ecological benefit measurement, a scoring method is generally adopted, that is, several indicators are divided, scores are given to each indicator, and then the scores of each indicator are accumulated to obtain the ecological benefit measurement value of ecological protection and restoration. For this method, due to the small number of indicators and the large subjective influence of manual scoring, the accuracy of the obtained measurement value is relatively low. Summary of the Invention

[0005] The purpose of the present invention is to provide an ecological protection and restoration ecological benefit assessment method, which can improve the evaluation accuracy of the ecological benefit measurement value of ecological protection and restoration.

[0006] To achieve the above purpose, an ecological protection and restoration ecological benefit assessment method is provided, which includes:

[0007] S1. N-level division of evaluation indicators:

[0008] Divide the first-level indicators and divide the second-level to N-level indicators based on the first-level indicators in a tree structure;

[0009] S2. Calculate the indicator data:

[0010] Calculate and obtain the N-level indicator data, and then calculate and summarize the data level by level until the first-level indicator data is obtained;

[0011] S3. Calculate the measurement value:

[0012] Determine the weight coefficients of each first-level indicator by the structural entropy weight method, and calculate the ecological protection and restoration ecological benefit measurement value by using the weighted aggregation algorithm for the first-level indicator data.

[0013] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S1, the first-level indicators include ecosystem pattern, ecosystem quality, ecosystem services, and ecological typical problems.

[0014] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S1, the second-level indicators divided based on the ecosystem pattern indicator include spatial pattern and landscape pattern;

[0015] The second-level indicators divided based on the ecosystem quality indicator include grassland degradation and restoration, vegetation condition, plant species diversity, and environmental quality;

[0016] The second-level indicators divided based on the ecosystem services indicator include water conservation, soil conservation, carbon sequestration and oxygen release, and water supply;

[0017] The second-level indicators divided based on the ecological typical problems indicator include rocky desertification, measurement of the conflict of production-living-ecological space, and dynamic change of land use.

[0018] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S1, the evaluation indicators are divided into three levels, where:

[0019] The third-level indicators divided based on the spatial pattern indicator include the area of ecosystem types, the conversion of ecosystem types, and the dynamic degree of ecosystem types;

[0020] The third-level indicators divided based on the landscape pattern indicator include the number of patches of ecosystem types, the patch density of ecosystem types, and the landscape aggregation index;

[0021] The third-level indicators divided based on the grassland degradation and restoration indicator include the classified area of grassland degradation and restoration, the proportion of the classified area of grassland degradation and restoration, and the change index of grassland degradation status;

[0022] The third-level indicators divided based on the vegetation condition indicator include vegetation biomass, vegetation coverage, and vegetation net primary productivity;

[0023] The third-level indicators divided based on plant species diversity indicators include species richness, species importance value, diversity index, and evenness index;

[0024] The third-level indicators divided based on environmental quality indicators include surface water environmental quality index, soil environmental quality index, and ambient air quality index;

[0025] The third-level indicators divided based on water conservation indicators include water conservation volume, retention rate of water conservation services, river runoff in dry season, and river runoff regulation coefficient in flood season;

[0026] The third-level indicators divided based on soil conservation indicators include soil conservation volume, retention rate of soil conservation services, and sediment content in river runoff;

[0027] The third-level indicators divided based on carbon sequestration and oxygen release indicators include total amount of carbon dioxide sequestration and total amount of oxygen release;

[0028] The third-level indicators divided based on water supply indicators include river runoff and groundwater resources;

[0029] The third-level indicators divided based on rocky desertification indicators include the area of production-living-ecological space and the intensity of production-living-ecological space conflict

[0030] The third-level indicators divided based on the measure index of production-living-ecological space conflict include the area of rocky desertification land and rocky desertification index;

[0031] The third-level indicators divided based on the indicators of dynamic changes in land use include the land cover degree index and the dynamic degree of land use.

[0032] According to the ecological benefit evaluation method for ecological protection and restoration described above, in step S2,

[0033] In the calculation steps of the ecosystem type conversion indicator:

[0034] Calculate the area change rate of each type of ecosystem, and calculate the ecosystem type conversion indicator by using the weighted aggregation algorithm for the area change rates of each type of ecosystem;

[0035] The calculation method of the area change rate of each type of ecosystem is

[0036]

[0037] S 转 = S T2 - S T1

[0038] Among them, P is the area change rate of a specific ecosystem type, S 原 is the original area of a specific ecosystem type, S 转 is the area of a specific ecosystem type converted to other ecosystem types, ST2 and S T1 are the areas of specific ecosystem types in the T2 period and the T1 period, respectively;

[0039] In the calculation steps of the dynamic degree index of ecosystem types,

[0040] The calculation method is

[0041]

[0042] where EC is the dynamic degree of ecosystem types, EU i is the area of the initial ecosystem type i, and ΔEU i-j is the sum of the areas where the ecosystem type i is converted into other ecosystem types j, and T is the research period;

[0043] In the calculation steps of the landscape diversity index indicator,

[0044] The calculation method is

[0045]

[0046] In the formula, H is the diversity index, Pi is the proportion of the area occupied by the ecosystem type i, and m is the number of ecosystem types.

[0047] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S2,

[0048] In the calculation steps of the grassland degradation status change index indicator,

[0049] The calculation method is

[0050]

[0051] In the formula, I is the grassland degradation status change index, and are the proportions of the grassland degradation areas in the T2 and T1 periods, respectively;

[0052] In the calculation steps of the vegetation coverage indicator,

[0053] The calculation method is

[0054]

[0055] In the formula, FVC is the vegetation coverage, NDVI soil is the NDVI value of the area that is completely bare soil or has no vegetation coverage, and NDVI veg represents the NDVI value of the pixels that are completely covered by vegetation.

[0056] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S2,

[0057] In the calculation steps of the intensity index of the conflict among production, living, and ecological spaces,

[0058] The calculation method is

[0059] LUCS = AWMPFD + E i - S

[0060] Wherein, LUCS is the intensity of the conflict among production, living, and ecological spaces, AWMPFD is the external pressure; E i is the vulnerability of the i-th type of space, and S is the stability;

[0061] In the calculation steps of the land cover degree index,

[0062] The calculation method is

[0063]

[0064] L is the land cover degree index, A i and C i are the grading index of the land use degree at the i-th level and the area percentage respectively;

[0065] In the calculation steps of the land use dynamic degree index,

[0066] The calculation method is

[0067]

[0068] Wherein, LC is the land use dynamic degree, LU i is the area of the initial land type i, ΔLU i-j is the sum of the areas of the conversion of land type i to other types j, and T is the research period.

[0069] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S2, calculate and obtain the N-level index data, determine the weight coefficients of each N-level index by the structural entropy weight method, and calculate and obtain the corresponding N - 1-level index data by the weighted aggregation algorithm; calculate in this way until obtaining the data of each first-level index.

[0070] According to the ecological protection and restoration ecological benefit evaluation method described above, in step S2, when calculating the area index of the ecosystem type:

[0071] The divided ecosystems include forest ecosystems, grassland ecosystems, wetland ecosystems, river and lake ecosystems, and farmland ecosystems;

[0072] Based on remote sensing data, extract the original patches of various ecosystems in the monitoring area in periods T1 and T2, and process the original patches to obtain sample patches;

[0073] Number each sample patch, sum up the areas of various types of sample patches in periods T1 and T2 respectively, and obtain the areas of various ecosystems in periods T1 and T2, which are denoted as S 森林 、S 草原 、S 湿地 、S 河湖 、S 农田 ; The average value of the total area of the ecosystem in periods T1 and T2 is denoted as the area index data of the third-level ecosystem type.

[0074] According to the ecological benefit evaluation method for ecological protection and restoration described above, based on remote sensing data, extract the original patches of various ecosystems in the monitoring area in periods T1 and T2, and the steps of processing the original patches to obtain sample patches include:

[0075] Data acquisition: Obtain remote sensing image data in periods T1 and T2, and extract the original patches of forest ecosystems, grassland ecosystems, wetland ecosystems, and farmland ecosystems, as well as the original water surface patches of river and lake ecosystems;

[0076] Processing of original water surface patches: Delete artificial ditch patches with a width less than the first threshold; obtain the location of the water surface, obtain the average water level elevation data at this location in the years of periods T1 and T2, obtain the topographic elevation data at this location, perform overlay analysis on the average water level elevation data and the topographic elevation data, obtain the average waterlogging range in the years of periods T1 and T2, obtain the boundary of this waterlogging range, enclose the boundary to form an intermediate patch, and merge the area outside the boundary of the intermediate patch with an elevation difference within the second threshold into the intermediate patch to form a new patch; traverse each tributary of the new patch, check whether the tributary water system line is continuous and whether the end of the tributary is connected to and flows into the main stream or lake, and if not, connect and correct it with the shortest straight line to reduce the number of patches; use the ThinNoPoint algorithm to thin the boundary line of the new patch, and then use the NURBfit algorithm to smooth the boundary line of the new patch to obtain the sample patches of river and lake ecosystems;

[0077] Processing of other original patches: Fuse the linear features contained in the original patches into the patches; delete the linear features between adjacent original patches of the same type, and merge the deleted area and adjacent patches to reduce the number of patches; fill the holes with an area ratio less than the third threshold in the original patches; use the ThinNoPoint algorithm to thin the boundary line of the patches, and then use the NURBfit algorithm to smooth the boundary line of the patches to obtain the sample patches of forest ecosystems, grassland ecosystems, wetland ecosystems, and farmland ecosystems;

[0078] Among them, 0 < the first threshold ≤ 3m, 0 < the third threshold ≤ 10%.

[0079] Beneficial effects: In the above solution, by combining the structural entropy weight method and the weighted aggregation algorithm, the uncertain influence that may exist due to the differences in experts' understanding of indicators can be reduced, the accuracy of determining the weight coefficient can be improved, and further the evaluation accuracy of the ecological benefit measurement value of ecological protection and restoration can be improved.

[0080] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The present invention will be further described below in conjunction with the drawings and embodiments:

[0082] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0083] This part will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the drawings. The function of the drawings is to supplement the description of the text part of the specification, enabling people to intuitively and vividly understand each technical feature and the overall technical solution of the present invention, but it cannot be understood as a limitation on the protection scope of the present invention.

[0084] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as up, down, front, back, left, right, etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation on the present invention.

[0085] In the description of the present invention, greater than, less than, exceeding, etc. are understood as not including the number itself, and above, below, within, etc. are understood as including the number itself. If there is a description of first and second, it is only for the purpose of distinguishing technical features and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or the sequence relationship of the indicated technical features.

[0086] In the description of the present invention, unless otherwise clearly defined, terms such as set, install, connect, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0087] Referring to Figure 1 , an ecological benefit evaluation method for ecological protection and restoration, which includes the following steps:

[0088] S1. N-level division of evaluation indicators:

[0089] Divide the first-level indicators, and divide the second-level to N-level indicators based on the first-level indicators in a tree structure;

[0090] S2. Calculate index data:

[0091] Calculate and obtain the N-level index data, and then calculate and summarize the data level by level until the first-level index data is obtained;

[0092] S3. Measure value calculation:

[0093] Determine the weight coefficients of each first-level index by the structural entropy weight method, and calculate the ecological protection and restoration ecological benefit measure value by the weighted aggregation algorithm for the first-level index data. In addition, after calculating and obtaining the N-level index data, also determine the weight coefficients of each N-level index by the structural entropy weight method, and calculate and obtain the corresponding N-1 level index data by the weighted aggregation algorithm; calculate in this way until the first-level index data of each item is obtained.

[0094] In the index system, the influences of the factors at the criterion layer on the target layer are not the same, there is a relative importance relationship among the factors, and the expression capabilities of the indexes in the sub-criterion layer for the upper-layer factors are also inconsistent. Therefore, it is necessary to distinguish the importance degrees among the factors and indexes in the index system, and use weights to represent the influence degree of the factors on the target and the expression capabilities of the indexes for the factors. The structural entropy weight method combines the subjective and objective assignment methods and combines qualitative and quantitative analysis.

[0095] As in the above scheme, after dividing the indexes at all levels and obtaining the N-level index data, determine the weight coefficients by the structural entropy weight method, calculate and obtain the upper-level index data by the weighted aggregation algorithm, calculate in this way until the first-level index data, and calculate and obtain the ecological protection and restoration ecological benefit measure value in the same way. In the above scheme, combining the structural entropy weight method and the weighted aggregation algorithm can reduce the uncertain influence that may exist due to the differences in experts' understanding of the indexes, improve the accuracy of determining the weight coefficients, and further improve the evaluation accuracy of the ecological protection and restoration ecological benefit measure value.

[0096] In the solution of the present invention, the ecological benefit evaluation indexes are divided into three levels. The first-level index division includes the ecosystem pattern, ecosystem quality, ecosystem services, and ecological typical problems, and their corresponding second-level and third-level index divisions are shown in the following table.

[0097] Ecological Benefit Evaluation Index Table

[0098]

[0099]

[0100] Based on the above index divisions at all levels, the meanings and calculation methods of the third-level indexes are as follows.

[0101] C11a Area of Ecosystem Types

[0102] Taking the karst mountainous area ecosystem as an example, first, the ecosystem is divided into forest ecosystem, grassland ecosystem, wetland ecosystem, river-lake ecosystem, and farmland ecosystem; based on remote sensing data, the original patches of various ecosystems in the monitoring area during T1 and T2 periods are extracted, and the original patches are processed to obtain sample patches; the sample patches are numbered, and the areas of various sample patches during T1 and T2 periods are summed respectively to obtain the areas of various ecosystems during T1 and T2 periods, denoted as S 森林 、S 草原 、S 湿地 、S 河湖 、S 农田 ; calculate the total area of various ecosystems during T1 period and calculate the total area of various ecosystems during T2 period, and take the average of the two total area data to obtain the area index data of ecosystem types.

[0103] Among them, the specific step content of "extracting the original patches of various ecosystems in the monitoring area during T1 and T2 periods based on remote sensing data, and processing the original patches to obtain sample patches" includes:

[0104] Data acquisition: Obtain remote sensing image data during T1 and T2 periods, and extract the original patches of forest ecosystem, grassland ecosystem, wetland ecosystem, and farmland ecosystem, as well as the original water surface patches of the river-lake ecosystem;

[0105] Processing of original water surface patches: Traverse the water surface patches and delete artificial ditches with a width less than the first threshold (such artificial ditches are numerous and have little impact on the ecology, so they are not included in the calculation to reduce the amount of analysis data); obtain the position of the water surface of the patch, obtain the average water level elevation data at this position for the years when T1 and T2 are located, obtain the topographic elevation data at this position, perform overlay analysis on the average water level elevation data and the topographic elevation data to obtain the average waterlogging range for the years when T1 and T2 are located, obtain the boundary of this waterlogging range, enclose the boundary to form an intermediate patch, and merge the area outside the boundary of the intermediate patch where the elevation difference is within the second threshold into the intermediate patch (that is, according to the first elevation value of the boundary of the intermediate patch, in the outer area adjacent to the intermediate patch, the area where the elevation difference compared to the boundary of the intermediate patch is within the second threshold is merged into the intermediate patch) to form a new patch (since the elevation data cannot directly determine the water surface position, and it is difficult for remote sensing images to accurately determine the boundary of the river and lake ecosystem, and because the river and lake ecosystem changes slowly, the patches obtained based on the above method have a high objectivity); traverse each tributary of the new patch, check whether the tributary water system line is continuous and whether the end of the tributary is connected to and flows into the main stream or lake, if not, correct it by connecting with the shortest straight line (that is, for each section of the same tributary, the end is directly connected to the beginning; the boundary between the end of the tributary and the main stream / lake is connected with a shortest straight line) to reduce the number of patches; use the ThinNoPoint algorithm to thin the boundary line of the new patch, and then use the NURBfit algorithm to smooth the boundary line of the new patch to obtain the sample patches of the river and lake ecosystem (the processed sample patches are subjected to fuzzy processing, with smooth boundary lines, reduced sharp corners, and easy for area analysis);

[0106] Processing of original patches: The linear features (such as roads, ridges, bridges, etc.) contained in the original patches are merged into the patches; the linear features between adjacent original patches of the same type are deleted, and the deleted area and adjacent patches are merged to form a new patch to reduce the number of patches; fill the holes in the original patches with an area ratio less than the third threshold; use the ThinNoPoint algorithm to thin the boundary line of the patches, and then use the NURBfit algorithm to smooth the boundary line of the patches to obtain the sample patches of the forest ecosystem, grassland ecosystem, wetland ecosystem, and farmland ecosystem;

[0107] Among them, 0 < the first threshold ≤ 3m, 0 < the third threshold ≤ 10%. During actual operation, a fixed value within the corresponding range is taken for the first threshold and the third threshold to participate in the calculation. For the second threshold, the second threshold for lake patches can be taken as not greater than 10m, and the second threshold for river patches can be taken as not greater than 6m.

[0108] C11b Ecosystem type conversion

[0109] Calculate the area change rates of various ecosystem types, and use a weighted aggregation algorithm for the area change rates of various ecosystem types to obtain the ecosystem type conversion index. Among them, the calculation method for the area change rate of each ecosystem type is

[0110]

[0111] S 转 = S T2 - S T1

[0112] Among them, P is the area change rate of a specific ecosystem type, S 原 is the original area of a specific ecosystem type, S 转 is the area converted from a specific ecosystem type to other ecosystem types, S T2 and S T1 are the areas of the specific ecosystem type in period T2 and period T1 respectively.

[0113] The dynamic degree of the C11c ecosystem type

[0114] The calculation method is

[0115]

[0116] Among them, EC is the dynamic degree of the ecosystem type, EU i is the area of the initial ecosystem type i, ΔEU i-j is the sum of the areas converted from ecosystem type i to other ecosystem types j, and T is the research period. Specifically, period T2 is the end period of the research, period T1 is the start period of the research, and the period between them is the research period T.

[0117] The number of patches of the C12a ecosystem type

[0118] According to the above-mentioned mapping of ecosystem type patches, count the number of patches of various ecosystem types in the research area: N 森林 、N 草原 、N 湿地 、N 河湖 、N 农田 . In this plan, obtain the total number of patches in period T2 and period T1 respectively, and take the average value as the ecosystem type patch number index.

[0119] The patch density of the C12b ecosystem type

[0120] The calculation method is

[0121]

[0122] Among them, D is the patch density of a specific ecosystem type, N is the number of patches of this ecosystem type, and S is the area of this ecosystem type. After calculating the patch density D of each ecosystem, the patch density of the ecosystem type is calculated using the weighted aggregation algorithm.

[0123] C12c Landscape Aggregation Index

[0124] The landscape aggregation index reflects the degree of agglomeration of ecosystem types and is calculated as follows

[0125]

[0126] In the formula, RC is the relative aggregation index, with a value between 0 and 1, C is the complexity index, and C max is the maximum possible value of C. After calculating the relative aggregation index of each ecosystem patch, the landscape aggregation index is calculated using the weighted aggregation algorithm.

[0127] C12d Landscape Diversity Index

[0128] The calculation method is

[0129]

[0130] In the formula, H is the diversity index, Pi is the proportion of the area occupied by ecosystem type i, and m is the number of ecosystem types. The larger the value of H, the greater the landscape diversity.

[0131] C21a Grassland Degradation and Restoration Classification Area

[0132] By separately counting the areas of grassland degradation and grassland restoration, S degradation and S restoration are obtained. The two obtained data are directly used to obtain weights by the structural entropy weight method and participate in the calculation of secondary indicators.

[0133] C21b Proportion of Grassland Degradation and Restoration Classification Area

[0134] On the basis of calculating the areas of grassland degradation and grassland restoration, the proportions of the areas of grassland degradation and grassland restoration in the regional area are further calculated, P 退化 and P 恢复 . The two obtained data are directly used to obtain weights by the structural entropy weight method and participate in the calculation of secondary indicators.

[0135] C21c Grassland Degradation Status Change Index

[0136] The grassland degradation status change index reflects the situation of grassland degradation within a specific period and is calculated as follows

[0137]

[0138] In the formula, I is the grassland degradation status change index, and are the proportions of the grassland degradation area during T2 and T1 periods, respectively.

[0139] C22a Vegetation biomass

[0140] The vegetation biomass is obtained by comprehensive estimation using multiple methods, mainly including large-scale estimation based on remote sensing and field sampling surveys.

[0141] C22b Vegetation coverage

[0142] The fractional vegetation cover (FVC) characterizes the surface vegetation coverage. Generally, the fractional vegetation cover is defined as the ratio of the vertical projection area of the vegetation canopy on the ground to the total land area. The fractional vegetation cover is calculated using the pixel dichotomy model as follows

[0143]

[0144] In the formula, FVC is the fractional vegetation cover, and NDVI soil is the NDVI value of the area that is completely bare soil or has no vegetation cover, and NDVI veg represents the NDVI value of the pixels that are completely covered by vegetation.

[0145] C22c Vegetation net primary productivity

[0146] The primary productivity refers to the total amount of organic matter produced by plant communities in an ecosystem per unit time and per unit area. It is calculated using the CASA (Carnegie-Ames-Stanford Approach) model.

[0147] C23a Species richness

[0148] Refers to the number of species in the selected community, which is obtained through investigation.

[0149] C23b Species importance value

[0150] The species importance value is an important indicator in calculating and evaluating species diversity, representing the relative importance of plant species in a community in a comprehensive numerical value. Importance value = relative abundance + relative frequency + relative dominance.

[0151] C23c Diversity index

[0152] The species diversity index refers to the ratio of the number of species to the number of individuals in a biological community.

[0153] C23d Evenness index

[0154] The evenness index is used to describe the distribution of the number of individuals of all species in a community or habitat.

[0155] C24a Surface water environmental quality index

[0156] Surface water is divided into four categories according to the main water quality indicators of surface water, namely, Category I, Category II, Category III, and Category IV.

[0157] C24b Soil environmental quality index

[0158] It is obtained by evaluating and calculating based on the data obtained from on-site sampling surveys according to the Technical Specification for Soil Environmental Quality Assessment.

[0159] C24c Ambient air quality index

[0160] The ambient air quality index is comprehensively obtained after monitoring the main air quality indicators and obtaining the data of each indicator.

[0161] C31a Water conservation capacity

[0162] Based on the water balance algorithm, considering various factors such as terrain, soil type, precipitation, etc., the water conservation capacity is obtained by calculating the differences of parameters such as precipitation, evaporation, and runoff.

[0163] C31b Retention rate of water conservation service

[0164] It refers to the level at which the water conservation capacity of a certain type of ecosystem in the evaluated area reaches that of the best-performing ecosystem of the same type.

[0165] C31c River runoff in the dry season

[0166] The river runoff in the dry season reflects the water resource retention status in the dry season of the region and is obtained by calculating based on the observation data of hydrological stations.

[0167] C31d River runoff regulation coefficient in the flood season

[0168] It refers to the ability of the ecosystem in the evaluated area to regulate river runoff in the summer flood season.

[0169] C32a Soil retention amount

[0170] It refers to the difference between the potential soil erosion amount without vegetation protection in the evaluated area and the soil erosion amount under the current vegetation cover status.

[0171] C32b Retention rate of soil conservation service

[0172] It refers to the level at which the soil retention amount of a certain type of ecosystem in the evaluated area reaches that of the best-performing ecosystem of the same type.

[0173] C32c Sediment concentration in river runoff

[0174] It is obtained by calculation through the observed data of hydrological stations, reflecting the soil and water loss situation in the area.

[0175] Total amount of carbon dioxide solidified by C33a

[0176] It is calculated by comprehensively considering data such as regional land use and carbon density, reflecting the carbon sequestration capacity of the regional ecosystem.

[0177] Total amount of oxygen released by C33b

[0178] It is calculated through an empirical model, combined with information such as the regional vegetation composition and vegetation-related attributes, reflecting the oxygen release capacity of the regional ecosystem.

[0179] River runoff of C34a

[0180] It is obtained by calculating through the observation records of hydrological stations, reflecting the status of surface water retention in the area.

[0181] Groundwater resources volume of C34b

[0182] It is obtained by calculating through the observation records of hydrological stations, reflecting the status of groundwater retention in the area.

[0183] Area of rocky desertified land of C41a

[0184] Collect relevant data and statistics on the area of rocky desertified land in the region.

[0185] Rocky desertification index of C41b

[0186] Rocky desertification reflects a land degradation phenomenon similar to desertification caused by human disturbance and climate change, resulting in the disappearance of vegetation.

[0187] Area of the three-functional space of C42a

[0188] The area of the ecological space, production space, and living space are summed up to obtain the area of the three-functional space.

[0189] Conflict intensity of the three-functional space of C42b

[0190] The conflict intensity of the three-functional space reflects the current situation of the conflict in the regional three-functional space, and the calculation method is

[0191] LUCS = AWMPFD + E i -S

[0192] In the formula, LUCS is the conflict intensity of the three-functional space, AWMPFD is the external pressure; E i is the vulnerability of the i-th type of space, and S is the stability. The LUCC values of the ecological space, production space, and living space are obtained respectively, and the conflict intensity of the three-functional space is calculated by the weighted aggregation algorithm.

[0193] C43a Land Cover Degree Index

[0194] It reflects the degree of land use change caused by factors such as human activities, and the calculation method is

[0195]

[0196] L is the land cover degree index, A i and C i are the classification index of land use degree at the i-th level and the area percentage respectively.

[0197] C43b Land Use Dynamics

[0198] The calculation method is

[0199]

[0200] In the formula, LC is the land use dynamics, LU i is the area of the initial land type i, and ΔLU i-j is the sum of the areas where the land type i is converted to other types j, and T is the research period.

[0201] In the above solutions, when the weighted aggregation algorithm needs to be used, the structural entropy weight method can be used to determine the weight coefficient. When there are multiple data obtained from the calculation of the remaining three-level indicators, the weights can be directly obtained by the structural entropy weight method for the obtained data, and then directly participate in the calculation of the secondary indicators.

[0202] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge scope of those of ordinary skill in the art.

Claims

1. Ecological benefit assessment method for ecological protection and restoration, characterized in that: include: S1. Evaluation indicators are divided into N levels: Divide the first-level indicators, and divide the second to N-level indicators in a tree structure based on the first-level indicators; S2. Calculate index data: Calculate and obtain N-level indicator data, and then calculate and summarize the data level by level until the first-level indicator data is obtained; S3. Metric value calculation: The structural entropy weight method is used to determine the weight coefficient of each primary indicator, and the primary indicator data is calculated using a weighted summary algorithm to obtain the ecological benefit measurement value of ecological protection and restoration.

2. The ecological benefit assessment method for ecological protection and restoration according to claim 1 is characterized in that: In step S1, the first-level indicators include ecosystem pattern, ecosystem quality, ecosystem services and typical ecological problems.

3. The ecological benefit assessment method for ecological protection and restoration according to claim 2 is characterized in that: In step S1, the secondary indicators based on the ecosystem pattern indicators include spatial pattern and landscape pattern; Secondary indicators based on the ecosystem quality index include grassland degradation and restoration, vegetation status, plant species diversity and environmental quality; Secondary indicators based on the ecosystem service indicators include water conservation, soil conservation, carbon fixation and oxygen release, and water supply; The secondary indicators based on the classification of typical ecological problem indicators include desertification, three-life spatial conflict measurement and dynamic changes in land use.

4. The ecological benefit assessment method for ecological protection and restoration according to claim 3 is characterized in that: In step S1, the evaluation index is divided into three levels, where: The three-level indicators based on spatial pattern indicators include ecosystem type area, ecosystem type conversion and ecosystem type dynamics; The three-level indicators based on landscape pattern indicators include the number of ecosystem type patches, the density of ecosystem type patches and the landscape aggregation index; The three-level indicators based on the classification of grassland degradation and restoration indicators include the classified area of ​​grassland degradation and restoration, the proportion of classified area of ​​grassland degradation and restoration, and the index of change in grassland degradation status; The three-level indicators based on vegetation status indicators include vegetation biomass, vegetation coverage and vegetation net primary productivity; The three-level indicators based on plant species diversity indicators include species richness, species importance value, diversity index and evenness index; The three-level indicators based on the classification of environmental quality indicators include surface water environmental quality index, soil environmental quality index and ambient air quality index; The three-level indicators based on water conservation indicators include water conservation capacity, water conservation service retention rate, river runoff in the dry season, and river runoff regulation coefficient in the flood season; The three-level indicators based on soil conservation index include soil conservation volume, soil conservation service retention rate and river runoff sediment content; The three-level indicators based on carbon fixation and oxygen release include the total amount of carbon dioxide fixed and the total amount of oxygen released; The three-level indicators based on the water supply index include river runoff and groundwater resources; The three-level indicators based on the rocky desertification index classification include the area of ​​the three-life space and the intensity of the conflict between the three-life space. The three-level indicators based on the three-life spatial conflict measurement indicators include rocky desertification land area and rocky desertification index; The three-level indicators based on the land use dynamic change indicators include land cover index and land use dynamics.

5. The ecological benefit assessment method for ecological protection and restoration according to claim 4 is characterized in that: In step S2, The calculation steps of ecosystem type conversion indicators are: Calculate the area change rate of each type of ecosystem, and use the weighted aggregation algorithm to calculate the area change rate of each type of ecosystem to obtain the ecosystem type conversion index; The calculation method of the area change rate of each ecosystem type is as follows: S 转 =S T2 -S T1 Where P is the rate of change in the area of ​​a specific ecosystem type, S 原 is the original area of ​​a specific ecosystem type, S 转 is the area converted from a specific ecosystem type to other ecosystem types, S T2 and S T1 are the areas of specific ecosystem types during periods T2 and T1, respectively; In the calculation step of ecosystem type dynamic index, The calculation method is Among them, EC is the dynamic degree of ecosystem type, EU i is the area of ​​the initial ecosystem type i, ΔEU i-j is the area of ​​ecosystem type i transformed into other ecosystem type j, and T is the research period; In the calculation step of landscape diversity index, The calculation method is Where H is the diversity index, Pi is the proportion of the area occupied by ecosystem type i, and m is the number of ecosystem types.

6. The ecological benefit assessment method for ecological protection and restoration according to claim 4 is characterized in that: In step S2, In the calculation steps of grassland degradation change index, The calculation method is Where I is the grassland degradation change index, and are the percentages of grassland degradation areas during T2 and T1, respectively; In the calculation step of vegetation coverage index, The calculation method is In the formula, FVC is the vegetation coverage, NDVI is soil is the NDVI value of the area with completely bare soil or no vegetation cover. veg It represents the NDVI value of the pixel completely covered by vegetation.

7. The ecological benefit assessment method for ecological protection and restoration according to claim 4 is characterized in that: In step S2, In the calculation steps of the land cover index indicator, The calculation method is L is the land cover index, A i and C i are the classification index and area percentage of the i-th level of land use, respectively; In the calculation steps of land use dynamic index, The calculation method is In the formula, LC is the land use dynamics, LU i is the initial area of ​​land type i, ΔLU i-j is the area converted from land type i to other types j, and T is the study period.

8. The ecological benefit assessment method for ecological protection and restoration according to any one of claims 1 to 7, characterized in that: In step S2, N-level indicator data is calculated and obtained, the weight coefficient of each N-level indicator is determined by the structural entropy weight method, and the corresponding N-1-level indicator data is calculated by the weighted aggregation algorithm; and the calculation is repeated in this way until the data of each first-level indicator is obtained.

9. The ecological benefit assessment method for ecological protection and restoration according to claim 4 or 5, characterized in that: In step S2, when calculating the ecosystem type area index: The ecosystems classified include forest ecosystems, grassland ecosystems, wetland ecosystems, river and lake ecosystems, and farmland ecosystems; Based on remote sensing data, the original patches of various ecosystems in the monitoring area during the T1 and T2 periods were extracted, and the original patches were processed to obtain sample patches. Each sample plot is numbered, and the areas of each sample plot in periods T1 and T2 are summed up to obtain the areas of each ecosystem in periods T1 and T2, which are respectively counted as S 森林 , S 草原 , S 湿地 , S 河湖 , S 农田 The average value of the total ecosystem area during T1 and T2 is counted as the area indicator data of the third-level ecosystem type.

10. The ecological benefit assessment method for ecological protection and restoration according to claim 9 is characterized in that: The steps of extracting original patches of various ecosystems in the monitoring area during periods T1 and T2 based on remote sensing data and processing the original patches to obtain sample patches include: Data acquisition: remote sensing image data of the T1 and T2 periods were obtained, and the original image patches of forest ecosystems, grassland ecosystems, wetland ecosystems and farmland ecosystems, as well as the original water surface image patches of river and lake ecosystems were extracted; Processing of original water surface spots: delete artificial ditch spots whose width is less than the first threshold; obtain the location of the water surface, obtain the average water level elevation data at the location in the years of T1 and T2, obtain the terrain elevation data at the location, overlay and analyze the average water level elevation data and terrain elevation data, obtain the average flooding range in the years of T1 and T2, obtain the boundary of the flooding range, enclose the boundary to form an intermediate spot, merge the elevation difference outside the boundary of the intermediate spot within the second threshold into the intermediate spot to form a new spot; traverse the tributaries of the new spot, check whether the tributary water system line is coherent and whether the end of the tributary is connected to the main stream or lake, if not, connect and correct it with the shortest straight line to reduce the number of spots; use the ThinNoPoint algorithm to thin the boundary line of the new spot, and then use the NURBfit algorithm to smooth the boundary line of the new spot to obtain the sample spot of the river and lake ecosystem; Other original spots are processed: the linear features contained in the original spots are merged into the spots; the linear features between adjacent original spots of the same type are deleted, and the deleted areas and adjacent spots are merged to reduce the number of spots; the holes in the original spots whose area ratio is less than the third threshold are filled; the ThinNoPoint algorithm is used to thin the spot boundary lines, and then the NURBfit algorithm is used to smooth the spot boundary lines to obtain sample spots of forest ecosystems, grassland ecosystems, wetland ecosystems and farmland ecosystems; Among them, 0<first threshold≤3m, 0<third threshold≤10%.

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