Black soil area ecological stability-restoring force coupling partition method and system

Abstract

The invention discloses a black soil area ecological stability-restoring force coupling zoning method and system, and relates to the technical field of ecological environment protection. Collecting multi-source spatio-temporal data of a target black soil area, and analyzing and obtaining the ecological stability and ecological restorability of the area; according to the spatial heterogeneity of the ecological stability and the restoring force, spatial difference characteristics of ecological variables in different geographic units are mined, and spatial coupling analysis is carried out on the ecological stability and the ecological restoring force through restoring force prediction; and according to a coupling analysis result, performing ecological stability-restoring force coupling partition management on the target black soil area. According to the invention, space identification and differentiation management of the ecological system state of the black soil area are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological environment protection, in particular to a black soil region ecological stability-recovery force coupling partitioning method and system. BACKGROUND

[0002] With the intensification of global climate change and human activities, the stability and recovery force of the ecological system are facing severe challenges, especially in ecologically fragile areas such as black soil regions. Traditional ecological risk assessment methods have certain limitations in spatial distribution analysis, making it difficult to effectively identify ecological problems and potential recovery forces in different regions. The existing technology often ignores the complex coupling relationship between ecological stability and recovery force, as well as their heterogeneous distribution in space, so it is urgent to propose a new partitioning method to optimize the protection and restoration of the ecological environment. The black soil region is an important grain production base in China, with high organic matter content and strong productivity. However, in recent years, due to unreasonable utilization, overdevelopment, and climate change, the ecological system in the black soil region is facing problems such as declining stability and weakening recovery force. Therefore, how to scientifically evaluate the stability and recovery force of the regional ecological system and carry out classified management accordingly is the key to realizing the sustainable development of the black soil region. In the existing technology, although there are methods for evaluating ecological stability or recovery force, most of them fail to effectively integrate the two and lack systematic identification of their spatial coupling relationship. At the same time, ecological processes have significant spatial heterogeneity characteristics, and the existing technology has the following defects: (1) insufficient consideration of the core influence of soil organic matter on ecological system recovery force: soil organic matter is an important basis for ecological stability and plays a core role in maintaining soil structure, enhancing microbial activity, and regulating water and nutrient circulation. In current ecological risk assessment and recovery strategies, the dynamic changes of soil organic matter content in different ecological succession stages and its driving effect on ecological system recovery force are often ignored, leading to deviations between the evaluation results and the actual ecological succession trend, and restricting the scientificity and accuracy of the recovery measures. (2) Lack of systematic evaluation of the importance of spatial and temporal heterogeneity and influencing factors of ecological system: ecological system has significant spatial and temporal heterogeneity, i.e., ecological characteristics and ecological processes have significant differences and imbalances in space and time scales. Most existing researches use static average values or single-period data for ecological risk analysis, ignoring the change trends of key ecological factors at different spatial and temporal scales, which makes it difficult to support the development of partitioning classification management and differentiated restoration strategies. Therefore, there is an urgent need for a comprehensive partitioning method that considers spatial non-stationarity and key driving factor identification. SUMMARY

[0003] To solve the above problems, the purpose of the present application is to provide a black soil region ecological stability-recovery force coupling partitioning technology to realize the spatial identification and differentiated management of the ecological system state in the black soil region.

[0004] In order to achieve the above technical purposes, the present application provides a black soil area ecological stability-recovery force coupling partition method, comprising the following steps:

[0005] Collecting multi-source spatio-temporal data of the target black soil area, and analyzing and obtaining the ecological stability and ecological recovery force of the area, wherein the multi-source spatio-temporal data includes land use, meteorological conditions, topography and vegetation;

[0006] According to the spatial heterogeneity of ecological stability and recovery force, the spatial difference characteristics of ecological variables in different geographical units are mined, and the spatial coupling analysis of ecological stability and ecological recovery force is carried out through recovery force prediction.

[0007] According to the coupling analysis result, the target black soil area is managed by ecological stability-recovery force coupling partition.

[0008] Preferably, when obtaining the ecological stability, the ecological stability is obtained according to the landscape index, the soil organic carbon content and the landscape vulnerability index.

[0009] Preferably, when obtaining the ecological stability, the ecological stability is expressed as:

[0010]

[0011] In the formula, ES k is the ecological stability of the kth area, and α, β and γ are the coefficients of different landscape indexes; n i is the number of patches of landscape type i, A i is the area of landscape type i, A is the total area of all landscapes, A ki is the area of landscape type i in the kth area, A k is the total area of the kth area, n is the landscape type; P i is the perimeter of landscape type i, OC k is the soil organic carbon content of the kth area.

[0012] Preferably, when obtaining the ecological recovery force, the ecological recovery force is obtained according to the normalized vegetation index and the soil organic carbon content, wherein the ecological recovery force is expressed as:

[0013]

[0014] In the formula, ER k is the ecological recovery force of the kth area, N k is the normalized vegetation index of the kth area.

[0015] Preferably, in the acquisition of spatial heterogeneity of ecological stability and resilience, the role of spatial heterogeneity in ecological stability and resilience partition is analyzed by the optimal geographical zoning model GOZH, the geographical zoning is optimized by minimizing the sum of squares of the explanatory variables SSW in the partition, and the maximum contribution of each explanatory variable in the regional partition is identified to mine the spatial difference characteristics of ecological variables in different geographical units.

[0016] Preferably, in the resilience prediction, the XGBoost algorithm is combined with the SHAP method to identify the key driving factors of ecological stability and ecological resilience, and the contribution of each variable is quantified by the SHAP value for resilience prediction.

[0017] Preferably, in the spatial coupling analysis, the bivariate Moran index method is used to analyze the spatial coupling of ecological stability and ecological resilience.

[0018] Preferably, in the ecological stability-resilience coupling partition, based on the spatial clustering characteristics obtained from the spatial coupling analysis, the region is divided into four types of partitions according to the spatial clustering mode: high stability-high recovery area, high stability-low recovery area, low stability-high recovery area and low stability-low recovery area.

[0019] The application also discloses a black soil area ecological stability-resilience coupling partition system for realizing the above-mentioned black soil area ecological stability-resilience coupling partition method, which comprises:

[0020] A data acquisition and analysis module is used to acquire multi-source spatio-temporal data of a target black soil area, and analyze and obtain the ecological stability and ecological resilience of the area, wherein the multi-source spatio-temporal data comprises land use, meteorological conditions, topography and vegetation.

[0021] A spatial coupling analysis module is used to mine the spatial difference characteristics of ecological variables in different geographical units according to the spatial heterogeneity of ecological stability and resilience, and analyze the spatial coupling of ecological stability and ecological resilience through resilience prediction.

[0022] A coupling partition management module is used to manage the ecological stability-resilience coupling partition of the target black soil area according to the coupling analysis result.

[0023] The application discloses the following technical effects:

[0024] (1) Simultaneously evaluating ecological stability and resilience, and comprehensively depicting ecological state;

[0025] (2) Introducing the GOZH model to identify spatial heterogeneity and improve spatial expression ability;

[0026] (3) Identify key driving factors using XGBoost+SHAP model to enhance model interpretability;

[0027] (4) Identify spatial coupling between the two by bivariate spatial autocorrelation analysis;

[0028] (5) The partitioned results are clear and can directly guide differentiated ecological protection and restoration management. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0030] Figure 1 The method flowchart of the embodiments of the present application;

[0031] Figure 2 The spatial variability of the influence factors of ecological stability in the typical black soil region in the embodiments of the present application;

[0032] Figure 3 The spatial variability of the influence factors of ecological restoration in the typical black soil region in the embodiments of the present application;

[0033] Figure 4 The relative importance of ecological stability in the typical black soil region in the embodiments of the present application;

[0034] Figure 5 The relative importance of ecological restoration in the typical black soil region in the embodiments of the present application;

[0035] Figure 6 The density distribution of ecological stability and ecological restoration in the typical black soil region in the embodiments of the present application in 2001 and 2022. DETAILED DESCRIPTION

[0036] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present application.

[0037] As shown in Figures 1-6 The present application provides a black soil region ecological stability-recovery force coupling partition method, the steps of which include:

[0038] Collecting multi-source spatio-temporal data of land use, meteorological conditions, topography and vegetation of the target region (target black soil region);

[0039] Based on the landscape index, soil organic carbon content and landscape vulnerability index, the regional ecological stability is calculated, and the calculation formula is as follows:

[0040]

[0041] Wherein, ES k is the ecological stability of the kth region, and alpha, beta and gamma are the weights of different landscape indexes, which are based on experience and can be specifically valued according to the actual black soil region condition; n i is the number of patches of landscape type i, A i is the area of landscape type i, A is the total area of all landscapes, A ki is the area of landscape type i in the kth region, A k is the total area of the kth region, and n is the landscape type; P i is the perimeter of landscape type i, OC k is the soil organic carbon content of the kth region.

[0042] Wherein, the landscape vulnerability index Vi can be valued according to experience or specifically valued according to the actual black soil region condition according to different landscape types.

[0043] Based on the normalized difference vegetation index (NDVI) and the soil organic carbon content, the ecological recovery force is calculated, and the calculation formula is as follows:

[0044]

[0045] Wherein, ER kN is the ecological resilience of the kth region. k NDVI is the normalized difference vegetation index of the kth region.

[0046] The GOZH (Geographical Optimal Zoning Model) is used to analyze the role of spatial heterogeneity in ecological stability and resilience zoning, and the geographical zoning is optimized by minimizing the sum of squares of the explanatory variables (SSW) within the zoning, so as to identify the maximum contribution of each explanatory variable in the regional zoning. The formula for calculating the Omega value based on the GOZH model is as follows:

[0047]

[0048] In the formula, X is the explanatory variable, D is the hierarchical variable describing the geographical region, SSW X,D is the minimum sum of squares of the explanatory variable X within the region D, which is determined by the explanatory variable X, and SST represents the total sum of squares of the entire geographical region.

[0049] Based on the extreme gradient boosting (XGBoost) and SHAP (Shapley Additive Explanations) interpretation algorithm, the key driving factors of ecological stability and ecological resilience are identified, and the contribution of each variable is quantified by SHAP value, so as to guide the decision-making of ecological management in black soil region. The SHAP value is calculated as follows:

[0050]

[0051] In the formula, φ j represents the contribution of the jth feature, x represents the feature value vector of the instance to be explained, and p represents the total number of features. f x (S) represents the prediction value after marginalizing the features not contained in S in the subset S, j and i are the input variables and data samples respectively, and n is the number of samples.

[0052] The present application uses the bivariate Moran's index method to analyze the spatial coupling of ecological stability and ecological resilience, and identifies the spatial clustering characteristics thereof;

[0053] According to the spatial coupling result, the region is divided into four types of zoning: high stability-high recovery region, high stability-low recovery region, low stability-high recovery region, and low stability-low recovery region, and further classified as:

[0054] Ecological protection zone: high stability-high recovery, priority protection;

[0055] Ecological fragile zone: low stability-low recovery, priority repair;

[0056] Ecological adaptation zone: the rest type, implement adaptive management and enhance its resilience;

[0057] The present application proposes a corresponding ecological management strategy to complete the construction of the ecological stability-recovery force coupling partition of the black soil area.

[0058] Embodiment: The present embodiment provides a black soil area ecological stability-recovery force coupling partition method for realizing the spatial heterogeneity feature recognition and partition management optimization of the black soil area ecosystem, and the flow chart is as shown in Figure 1

[0059] S1. Collecting multi-source spatio-temporal data of land use, meteorological conditions, topography and vegetation of the target area.

[0060] Taking the Sanjiang Plain as an example, according to the characteristics of the regional ecosystem, multi-source data sets are collected, including land use data, meteorological data (annual average precipitation, air temperature and annual maximum land surface temperature, actual evapotranspiration), topographic data (elevation and slope), remote sensing normalized difference vegetation index data (NDVI), gross primary productivity data (GPP) and soil organic carbon content data (OC). The above data are in grid format, and the spatial resolution is preferably 30 meters.

[0061] S2. Calculating the regional ecological stability based on the landscape index, landscape vulnerability index and soil organic carbon content.

[0062] (1) Landscape index calculation.

[0063] The Fragstats model is used to calculate the landscape index of the typical black soil area, including the number of landscape type patches (n), the area of landscape type (A) and the perimeter of landscape type (P).

[0064] (2) Landscape vulnerability index calculation (V i ): According to the different landscape types (claim 3), the value can be taken according to experience, or the actual black soil area conditions can be taken specifically, and the higher the value, the weaker the ecological anti-interference ability. Preferably, the V i The value in the present embodiment is shown in Table 1.

[0065] Table 1

[0066]

[0067]

[0068] (3) According to the landscape index, landscape vulnerability index and soil organic carbon content, the ecological stability of the target area is calculated, and the ecological stability ESk is calculated according to the following formula:

[0069]

[0070] Wherein, ES k ​Ecological stability of the kth region, a, b and g are the coefficients of different landscape indices, which are based on experience and can be valued according to the actual conditions of the black soil region. The values of a, b and g in this embodiment are 0.5, 0.3 and 0.2 respectively; ni is the number of patches of landscape type i, A i Area of landscape type i, A is the total area of all landscapes, Ak i Area of landscape type i in the kth region, A k Total area of the kth region, n is the landscape type; P i Perimeter of landscape type i, OC k Soil organic carbon content of the kth region.

[0071] The ecological stability of the typical black soil region is evaluated in this embodiment. The minimum value, 5% value, average value, median value, 95% value and maximum value of the ecological stability of the black soil region are shown in Table 2. As can be seen from Table 2, the ecological stability of the typical black soil region shows an overall upward trend from 2001 to 2022, reflecting the gradual improvement of the regional ecological conditions. From the synchronous rise of the 5% value and the 95% value, the ecological stability of the typical black soil region not only improves in average, but also becomes more concentrated in overall distribution, indicating that the regional ecological conditions tend to be stable and convergent. The difference between the median value and the average value is small, indicating that the data distribution is relatively symmetrical, and the extreme values have little effect on the overall, and the ecological system shows good balance. The overall stability index is high and further improved, indicating that the regional ecological system may have entered a higher steady state stage, providing a good foundation for subsequent ecological management and optimization.

[0072] Table 2

[0073] Indicator name Ecological stability in 2001 Ecological stability in 2022 Minimum value 0.7608 0.8699 5% value 0.8166 0.9021 Average value 0.8693 0.9311 Median value 0.8653 0.9282 95% value 0.9345 0.9647 Maximum value 1.0000 1.0000

[0074] S3. Based on the normalized vegetation index and soil organic carbon content, the ecological resilience of the region is calculated. The calculation formula of ecological resilience is:

[0075]

[0076] Wherein, ER k Ecological resilience of the kth region, N k Normalized vegetation index of the kth region.

[0077] The minimum value, 5% value, average value, median value, 95% value and maximum value of the ecological restoration capacity of the typical black soil region are shown in Table 3. As can be seen from Table 3, the ecological restoration capacity of the typical black soil region as a whole improved during this period, and the restoration capacity of the regional ecosystem gradually increased. From the increase in the 5% value and the 95% value, it can be seen that not only the average level improved, but also the distribution range of the regional ecological restoration capacity as a whole moved to a higher level, indicating that the improvement was global rather than local. The minimum value increased from 0.1149 to 0.2425, indicating that the originally weak restoration region has improved significantly, which is of great significance for the optimization of ecological restoration strategies.

[0078] Table 3

[0079] Indicator name Ecosystem resilience in 2001 Ecosystem resilience in 2022 Minimum value 0.1149 0.2425 5% value 0.5764 0.6413 Average value 0.6933 0.7412 Median value 0.7009 0.7489 95% value 0.7747 0.8184 Maximum value 0.8004 0.8463

[0080] S4. Based on the optimal geographical zoning model (GOZH), the role of spatial heterogeneity in ecological stability and restoration capacity zoning was analyzed. The geographical zoning was optimized by minimizing the sum of squares of the explanatory variables (SSW) within the zoning, and then the maximum contribution of each explanatory variable in the regional zoning was identified. The formula for calculating the Ω value based on the GOZH model is:

[0081]

[0082] where X is the explanatory variable, D is the hierarchical variable describing the geographical region, SSW X,D is the minimum sum of squares of the explanatory variable X within the region D, determined by the explanatory variable X, and SST represents the total sum of squares of the entire geographical region.

[0083] The spatial heterogeneity of the influencing factors of ecological stability and ecological restoration capacity in the typical black soil region in 2001 and 2022 was analyzed using the GOZH model. The spatial heterogeneity of the influencing factors of ecological stability in the typical black soil region in 2001 and 2022 is shown in Table 4. Figure 2The impact of slope and elevation was the most significant among the factors affecting ecological stability in 2001, with Ω values of 0.17 and 0.22, respectively, and statistical significance at the 99% confidence level. The impact of total primary productivity and actual evapotranspiration was relatively small, but also statistically significant at the 95% confidence level. Maximum land surface temperature, precipitation, and air temperature had no significant impact. In 2022, the impact of slope and elevation remained significant, with Ω values increasing to 0.29 and 0.31, respectively, and statistical significance at the 99% confidence level. The Ω value of total primary productivity increased but was not significant, and the Ω value of precipitation decreased but was statistically significant at the 99% confidence level. These results indicate that the factors affecting ecological stability in the black soil region have changed over time, which may be related to external factors such as climate change and land use change. Therefore, when conducting ecological protection and restoration, these factors need to be considered comprehensively, and appropriate measures need to be taken to improve the stability of the ecosystem.

[0084] The spatial heterogeneity of factors affecting ecological resilience in the typical black soil region in 2001 and 2022 is shown in Figure 3 As shown in the table, all factors affecting ecological resilience in 2001 and 2022 were statistically significant at the 99% confidence level. Specifically, total primary productivity was the main factor affecting ecological resilience in both 2001 and 2022, with Ω values of 0.30 and 0.31, respectively, and statistical significance at the 99% confidence level. In addition, slope and elevation were important factors in both years, and their impact increased, which may be related to climate change and human activities. Actual evapotranspiration, maximum land surface temperature, and precipitation had relatively small impacts in both years, but air temperature varied in the two years, with a stronger impact in 2001 and a weaker impact in 2022. Therefore, the ecological resilience of the black soil region is affected by multiple factors, and the impact of these factors varies in different years, providing scientific basis for ecological protection and restoration in the black soil region. It can be seen that the factors affecting ecological stability and ecological resilience in the typical black soil region show significant differences in the time scale, indicating that the ecological system of the black soil region responds dynamically to environmental factors.

[0085] S5. Based on the extreme gradient boosting (XGBoost) and SHAP (Shapley Additive exPlanations) interpretation algorithm, the key driving factors of ecological stability and ecological resilience are identified, and the contribution of each variable is quantified through SHAP values, thereby guiding the decision-making of ecological management in the black soil region. The calculation formula is as follows:

[0086]

[0087] where φ j represents the contribution of the jth feature, x represents the feature value vector of the instance to be explained, and p represents the total number of features. x (S) represents the predicted value after marginalizing the features not contained in S in the subset S, j and i are the input variables and data samples, respectively, and n is the number of samples.

[0088] The relative importance of the influencing factors of ecological stability and ecological resilience in the typical black soil region in 2001 and 2022 was analyzed using the XGBoost-SHAP model. The relative importance of ecological stability in the typical black soil region in 2001 and 2022 is shown in Figure 4 , slope and elevation are the main factors affecting ecological stability, with SHAP values of 0.004 and 0.010 in 2001 and 2022, respectively, indicating that they have a significant impact on ecological stability. Total primary productivity, actual evapotranspiration, maximum land surface temperature, precipitation and air temperature have relatively small effects on ecological stability. In 2001 and 2022, slope and elevation were always the most important factors affecting ecological stability, while actual evapotranspiration, maximum land surface temperature, precipitation and air temperature also showed some influence, but the degree of influence was relatively small. These results show that the ecological stability of the black soil region is affected by multiple factors, and the degree of influence of these factors varies in different years, providing a scientific basis for the ecological protection and restoration of the black soil region.

[0089] The spatial heterogeneity of the influencing factors of ecological resilience in the typical black soil region in 2001 and 2022 is shown in Figure 5 , total primary productivity is the most important factor affecting ecological resilience in both years, indicating that total primary productivity has a significant impact on ecological resilience, with SHAP values of 0.021 and 0.018, respectively. In addition, elevation and air temperature also showed high SHAP values in both years, indicating that they also have important effects on ecological resilience. Other factors such as actual evapotranspiration, maximum land surface temperature, precipitation and air temperature also have some influence on ecological resilience, but the degree of influence is relatively small. These results show that the ecological resilience of the black soil region is affected by multiple factors, and the degree of influence of these factors varies in different years.

[0090] S6. Spatial coupling analysis of ecological stability and ecological resilience using bivariate Moran's index method to identify spatial clustering characteristics.

[0091] (1) To further explore the spatial distribution correlation between ecological stability and ecological resilience, this embodiment uses density maps to systematically analyze the relationship between the two, such as... Figure 6 As shown in the figure, the density map visually illustrates the distribution relationship between ecological stability and ecological resilience. A clear positive correlation exists between them; that is, areas with higher ecological stability also have relatively higher ecological resilience, indicating that improving ecological resilience helps enhance ecological stability. Furthermore, the figure shows a clustering characteristic between ecological stability and ecological resilience, with peak densities of 101.5 in 2001 and 213.0 in 2022. In certain regions, areas with similar levels of ecological stability and resilience tend to cluster together, meaning that points with high stability and high resilience, or low stability and low resilience, are more concentrated. From a time-series comparison, the high-density range for ecological stability shifted upwards from around 0.85 in 2001 to around 0.93 in 2022, and the high-density range for ecological resilience also shifted upwards from around 0.68 in 2001 to around 0.72, indicating that the system is undergoing an evolutionary process of upward shift in high-density areas.

[0092] The clustering characteristics between ecological stability and ecological resilience provide important scientific basis for ecological management, which helps to achieve the virtuous cycle and self-regulation of the ecosystem, thus providing a potential path for improving the ecological stability and resilience of the black soil region.

[0093] (2) Spatial coupling analysis of ecological stability and ecological resilience was conducted using the bivariate Moran index method. The calculation formula for the bivariate Moran index method is as follows:

[0094]

[0095] In the formula, M L Denotes the local Moran index of the bivariate system, x ki (x lj ) represents the attribute value of variable k(l), x k (x l ) represents the average value of variable k(l), σ k (σ l Let ) be the variance of variable k(l), and w ij This is the spatial weight matrix.

[0096] Based on the spatial coupling results, the region is divided into four categories: high stability-high recovery zone, high stability-low recovery zone, low stability-high recovery zone, and low stability-low recovery zone. Based on this, it is further classified as follows: high stability-high recovery zone is an ecological protection zone, low stability-low recovery zone is an ecologically fragile zone, and the other types are ecologically adapted zones.

[0097] From 2001 to 2022, the area of each ecological function zone in the typical black soil region is shown in Table 4. The area of the ecological protection zone (high stability-high recovery zone) increased from 21.07% to 22.07%, an increase of 1 percentage point, indicating that the ecological stability and recovery of the region continue to improve, benefiting from ecological protection measures and natural recovery; the area of the ecological fragile zone (low stability-low recovery zone) decreased from 6.05% to 5.72%, a decrease of 0.33 percentage points, reflecting that the ecological degradation area has shrunk slightly; the area of the ecological adaptation zone (high stability-low recovery zone, low stability-high recovery zone, and insignificant area) decreased from 72.88% to 72.21%, a decrease of 0.67 percentage points, but the overall proportion is still more than 70%, indicating that this region is the main part of the black soil region, and needs to balance stability and recovery through adaptive management.

[0098] Table 4

[0099] Ecological management zone type Proportion in 2001 / % Proportion in 2022 / % Ecologically protected area 21.07％ 22.07％ Ecologically fragile area 6.05％ 5.72％ Ecologically adaptive area 72.88％ 72.21％

[0100] The present application is not only applicable to the ecological stability and recovery coupling partitioning of the black soil region, but also can be extended to the ecosystem management of different climate zones and geographical regions. Specifically, by adjusting the weights of factors such as climate, vegetation, and soil type, the ecological stability and recovery of different regions can be optimized. For example, in temperate regions, the analysis of forest types and soil moisture can be strengthened; in arid and semi-arid regions, the consideration of soil salinization and water can be increased; and in plateau and mountainous regions, the analysis of topographic factors can be optimized. Through these adjustments, personalized protection and recovery solutions can be provided for different ecological environments. In addition, the present application can also be combined with other ecological protection measures to further enhance the ecological recovery and provide more dimensional ecological security solutions.

[0101] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks.

[0102] In the description of the application, it needs to be understood that the terms "first", "second" are only for the purpose of description and can not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0103] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method for coupling ecological stability and resilience in black soil regions, characterized in that, The method comprises the following steps: Collecting multi-source spatio-temporal data of the target black soil region, and analyzing and obtaining the ecological stability and ecological restoration capacity of the region, wherein the multi-source spatio-temporal data comprises land use, meteorological conditions, topography and vegetation; According to the spatial heterogeneity of ecological stability and restoration capacity, the spatial difference characteristics of ecological variables in different geographical units are mined, and spatial coupling analysis of ecological stability and ecological restoration capacity is performed through restoration capacity prediction; According to the coupling analysis result, the target black soil region is managed by ecological stability-ecological restoration capacity coupling zoning.

2. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 1, wherein: When obtaining the ecological stability, the ecological stability is obtained according to the landscape index, the soil organic carbon content and the landscape vulnerability index.

3. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 2, wherein: When obtaining the ecological stability, the ecological stability is represented as: In the formula, ES k Ecological stability of the kth region, α, β and γ are the coefficients of different landscape indices; n i The number of patches of landscape type i, A i The area of landscape type i, A is the total area of all landscapes, A ki The area of landscape type i in the kth region, A k The total area of the kth region, n is the landscape type; P i The perimeter of landscape type i, OC k The soil organic carbon content of the kth region.

4. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 3, wherein: When obtaining the ecological restoration capacity, the ecological restoration capacity is obtained according to the normalized difference vegetation index and the soil organic carbon content, wherein the ecological restoration capacity is represented as: In the formula, ER k is the ecological restoration force of the kth region, N k is the normalized vegetation index of the kth region.

5. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 4, wherein: When obtaining the spatial heterogeneity of ecological stability and restoration capacity, the role of spatial heterogeneity in ecological stability and restoration capacity zoning is analyzed through the optimal geographical zoning model GOZH, the geographical zoning is optimized by minimizing the sum of squares of the explanatory variables SSW in the zoning, and then the maximum contribution of each explanatory variable in the regional zoning is identified to mine the spatial difference characteristics of ecological variables in different geographical units.

6. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 5, wherein: When performing the restoration capacity prediction, the XGBoost algorithm is combined with the SHAP method to identify the key driving factors of ecological stability and ecological restoration capacity, and the contribution of each variable is quantified by the SHAP value to perform the restoration capacity prediction.

7. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 6, wherein: When performing the spatial coupling analysis, the bivariate Moran's index method is used to perform the spatial coupling analysis of ecological stability and ecological restoration capacity.

8. The black soil region ecological stability-ecological restoration capacity coupling zoning method according to claim 7, wherein: When performing the ecological stability-ecological restoration capacity coupling zoning, based on the spatial clustering characteristics obtained from the spatial coupling analysis, the region is divided into four types of zones according to the spatial clustering mode: high stability-high restoration zone, high stability-low restoration zone, low stability-high restoration zone and low stability-low restoration zone.

9. A system for implementing a method for coupling ecological stability and resilience in a black soil region, as claimed in claim 1, characterized in that, The method comprises the following steps: Collecting multi-source spatio-temporal data of the target black soil region, and analyzing and obtaining the ecological stability and ecological restoration capacity of the region, wherein the multi-source spatio-temporal data comprises land use, meteorological conditions, topography and vegetation; The spatial coupling analysis module is configured to, according to the spatial heterogeneity of the ecological stability and the ecological resilience, mine spatial difference characteristics of the ecological variables in different geographical units, and perform spatial coupling analysis on the ecological stability and the ecological resilience through the resilience prediction. The coupling partition management module is configured to, according to the coupling analysis result, perform ecological stability-resilience coupling partition management on the target black soil region.

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