A forest quality improvement method based on three values

Abstract

The application relates to a forest quality improvement method based on three values, which comprises the following steps: obtaining original values of multiple indexes of an evaluated object, the multiple indexes being classified into economic value, ecological value and social and cultural value; determining value class weights corresponding to each value class from at least two groups of preset weight combinations according to a forest management target type of the evaluated object; weighting the original values of the indexes according to corresponding index weights to obtain evaluation scores, and then sequentially aggregating the evaluation scores to value scores of the value classes, and then weighting and summing the value scores according to the value class weights to obtain a comprehensive evaluation score of the forest quality; determining a value class with the lowest value score as a short board value class, and cutting part of trees of the evaluated object and replanting target tree species corresponding to the short board value class. According to the method, corresponding management measures are implemented according to the value short board identified in the evaluation, the management reconstruction corresponds to the value short board, and thus the forest quality is improved.

Description

Technical Field

[0001] This application relates to the field of forest resource management, and in particular to a method for improving forest quality based on three values. Background Technology

[0002] Forests simultaneously fulfill multiple functions, including providing ecosystem services, supplying forest products, and providing socio-cultural services. Scientific forest management is fundamental to improving forest quality and achieving sustainable forest utilization. Forest management typically begins with an assessment of the current state of forest quality to understand its performance across various value dimensions, followed by implementation of management and transformation measures such as thinning and replanting. Current forest management practices often employ a single value dimension for evaluation indicators, such as economic or ecological indicators like forest stock volume or canopy closure, and use a uniform weighting system for all evaluated entities. Furthermore, the evaluation process is disconnected from subsequent management and transformation phases.

[0003] The aforementioned methods suffer from the following shortcomings: Because the evaluation indicators are organized around a single value dimension and the weighting system uses a fixed allocation for all evaluated objects, the trade-offs between forest ecosystem services, forest product supply, and socio-cultural services are difficult to reflect in the evaluation results. Consequently, forests with significantly different management orientations, such as commercial forests, public welfare forests, and health and wellness landscape forests, cannot obtain comparable and comprehensive evaluations tailored to their respective management objectives within the same framework. Furthermore, distinctive features carrying health and wellness and cultural values, such as forest appearance, plant essence, and the distribution of ancient and famous trees, are difficult to quantify within the existing system. This results in the long-term absence or underestimation of socio-cultural value in the evaluation results, and the overall quality of forests cannot be fully presented through the evaluation results. Consequently, the forest quality cannot be effectively improved after management cost investment, and the multiple functions of forests are difficult to coordinate and develop. Therefore, this field needs a method that can objectively identify the shortcomings of forests in the three major value directions of economy, ecology, and socio-cultural aspects, and implement corresponding management and transformation measures for these shortcomings. Summary of the Invention

[0004] In order to comprehensively evaluate the economic, ecological, and socio-cultural value of forests, diagnose the shortcomings in forest quality in these three value directions, and accordingly implement targeted management and transformation of forests to improve forest quality, this application provides a method for improving forest quality based on the evaluation of these three values.

[0005] This application provides a method for improving forest quality based on three key values, employing the following technical solution: A method for improving forest quality based on three key values ​​includes the following steps: S1. Obtain the original values ​​of multiple indicators of the evaluated object obtained from the forest resource database through forest resource survey and measurement. The multiple indicators represent the forest status of the evaluated object and are organized into three major value categories, namely economic value, ecological value and socio-cultural value. S2. Based on the forest management target type of the evaluated object, determine the value class weights corresponding to each of the three value categories from at least two preset combinations of the three value weights. Different combinations of the at least two sets of the three value weights correspond to different types of the forest management target type, and the specific allocation of the value class weights of the three value categories in different combinations is different. S3. The original values ​​of the multiple indicators are weighted according to their respective weights in the multi-level indicator system to obtain the evaluation scores of each of the multiple indicators. The multiple indicators include positive indicators and negative indicators. The evaluation scores of the positive indicators change in the same direction as the original values ​​of the positive indicators, and the evaluation scores of the negative indicators change in the opposite direction as the original values ​​of the negative indicators. S4. The evaluation scores of each of the multiple indicators are weighted and aggregated according to the multi-level indicator system to the value scores of each of the three value categories, and the value scores of each of the three value categories are weighted and summed according to the value category weights to obtain the comprehensive forest quality evaluation score of the evaluated object; the comprehensive forest quality evaluation score represents the forest quality of the evaluated object, and the value scores of each of the three value categories are used to determine the weak value category of the evaluated object; S5. Based on the value scores of the three value categories, the value category with the lowest value score among the three value categories is determined as the short-board value category of the evaluated object, and forest management measures corresponding to the short-board value category are implemented on the evaluated object. The forest management measures include felling some trees in the evaluated object to adjust the stand retention density, and replanting target tree species corresponding to the short-board value category in the stand gaps to adjust the tree species configuration structure. The target tree species are tree species that have a positive contribution to the value score of the short-board value category. When the short-board value category is an economic value category, the target tree species include precious timber tree species. When the short-board value category is an ecological value category, the target tree species include native broad-leaved tree species. When the short-board value category is a socio-cultural value category, the target tree species include at least one of landscape tree species and beneficial plant spirit tree species, so as to improve the forest quality of the evaluated object. S6. Re-execute S1 to S4 on the evaluated object after implementing the forest management measures to obtain the updated value scores of the three major value categories and the updated comprehensive forest quality evaluation score, so as to verify the effect of the forest management measures on improving the forest quality of the evaluated object, and return to execute S5 when it is necessary to further improve the forest quality of the evaluated object.

[0006] By adopting the above technical solution, the weakest value category among the three value categories is identified as the "weak value category," allowing for the objective identification of the weaknesses of the evaluated object in the three value directions of economy, ecology, and socio-cultural aspects. By implementing forest management measures corresponding to the weak value category and replanting target tree species that positively contribute to the value score of the weak value category, the management and transformation direction precisely matches the diagnosed value weaknesses. This achieves an increase in the corresponding value score and an overall improvement in forest quality at a lower management cost. Consequently, the original values ​​of the evaluated object's indicators change after the management measures are implemented. By re-executing the above steps, an updated comprehensive forest quality evaluation score can be obtained, forming a closed loop that connects evaluation diagnosis and management and transformation.

[0007] Optionally, the forest management objective type includes at least one of the following: regional comprehensive evaluation, commercial forest evaluation, public welfare forest evaluation, and health and wellness landscape forest evaluation. The pre-defined at least two sets of three major value weight combinations include: a first combination corresponding to the regional comprehensive evaluation, where the value weight of the ecological value category is greater than the respective value weights of the economic value category and the socio-cultural value category, and the value weight of the economic value category is equal to the value weight of the socio-cultural value category; a second combination corresponding to the commercial forest evaluation, where the value weight of the economic value category is greater than the respective value weights of the ecological value category and the socio-cultural value category; a third combination corresponding to the public welfare forest evaluation, where the value weight of the ecological value category is greater than the respective value weights of the economic value category and the socio-cultural value category; and a fourth combination corresponding to the health and wellness landscape forest evaluation, where the value weight of the socio-cultural value category is greater than the respective value weights of the economic value category and the ecological value category.

[0008] By adopting the above technical solution, three value weight combinations with differentiated weight ranking are preset for four typical forest management objectives, so that the dynamic weight switching mechanism has clear target-weight correspondence rules and improves the operability of the evaluation method in different management scenarios.

[0009] Optionally, multiple indicators can be organized into a multi-level indicator system. The multi-level indicator system includes primary indicators, which include forest productivity and forest multifunctionality indicators belonging to the economic value category, forest structure, forest health and forest ecological benefits indicators belonging to the ecological value category, and landscape forest, health and wellness forest and scientific research and education indicators belonging to the socio-cultural value category.

[0010] By adopting the above technical solution, an architecture is introduced in which eight primary indicators are classified into three major value categories. This allows the value scores of each of the three value categories to be obtained by summarizing the lower-level indicators with clear classification relationships, thus forming a clear mapping path from indicators to value categories.

[0011] Optional, the indicators for health and wellness forests include the proportion of area of ​​tree species with high plant essence and the proportion of area of ​​tree species with moderate plant essence. The tree species with high plant essence and the tree species with moderate plant essence are determined according to the preset tree species plant essence classification rules. The preset tree species plant essence classification rules select tree species with high plant essence and the tree species with moderate plant essence from the tree species based on the plant essence intensity of various plant families.

[0012] By adopting the above technical solutions, the essence of plants is used as a quantitative basis for health and wellness value, so that the abstract health and wellness function of forests can be transformed into measurable and comparable specific indicators through the area ratio of beneficial high-essence tree species and beneficial medium-essence tree species.

[0013] Optional, the landscape forest index includes the proportion of forest stand area with excellent forest quality. Forest stands with excellent forest quality are determined when the three elements of canopy closure, number of forest stand layers and stand growth health simultaneously reach their respective preset judgment thresholds.

[0014] By adopting the above technical solution, the combined threshold of three factors—canopy closure, number of forest stand layers, and stand growth health—is used to determine forest stands with excellent appearance, so that the aesthetic value of forest landscape can be characterized through quantifiable multi-factor combination rules.

[0015] Optional scientific research and education indicators include the distribution density of ancient and famous trees, which is the ratio of the number of ancient and famous trees in the area of ​​the evaluated object to the area of ​​the evaluated object.

[0016] By adopting the above technical solution, the distribution density of ancient and famous trees is used instead of the simple number of ancient and famous trees as the quantitative basis for scientific research and education indicators, so that forests in different areas are comparable in terms of this indicator, and the evaluation bias caused by the absolute number advantage of large areas is avoided.

[0017] Optionally, forest health indicators include forest flammability indicators, which include the proportion of area of ​​fire-resistant forests, the proportion of area of ​​combustible forests, and the proportion of area of ​​easily combustible forests. The proportion of area of ​​fire-resistant forests is a positive indicator, while the proportions of area of ​​combustible forests and easily combustible forests are negative indicators.

[0018] By adopting the above technical solutions, the forest flammability is divided into three levels: fire-retardant, combustible, and flammable, with corresponding area proportions, and these are incorporated into the evaluation in the opposite direction. This allows the forest's natural resistance to fire to be scientifically quantified as a component of forest health indicators.

[0019] Optionally, the multi-level indicator system also includes secondary, tertiary, and quaternary indicators. Secondary indicators belong to the corresponding primary indicators, tertiary indicators belong to the corresponding secondary indicators, and quaternary indicators belong to the corresponding tertiary indicators.

[0020] By adopting the above technical solution, a hierarchical structure of second-level, third-level, and fourth-level indicators is introduced on the basis of the first-level indicators, so that each first-level indicator can be specifically quantified through lower-level indicators with finer granularity, thereby improving the sufficiency of indicator support for the evaluation results.

[0021] Optionally, in the first combination corresponding to the regional comprehensive evaluation category, the value class weights for economic value, ecological value, and socio-cultural value are 0.3, 0.4, and 0.3, respectively; in the second combination corresponding to the commercial forest evaluation category, the value class weights for economic value, ecological value, and socio-cultural value are 0.6, 0.2, and 0.2, respectively; in the third combination corresponding to the public welfare forest evaluation category, the value class weights for economic value, ecological value, and socio-cultural value are 0.2, 0.6, and 0.2, respectively; and in the fourth combination corresponding to the health and wellness landscape forest evaluation category, the value class weights for economic value, ecological value, and socio-cultural value are 0.2, 0.2, and 0.6, respectively.

[0022] By adopting the above technical solution, specific numerical schemes for the combination of the three major value weights corresponding to the four types of business objectives are given, so that the dynamic weight switching has directly applicable parameter configurations.

[0023] Optionally, in S3, the evaluation score of a positive indicator is the product of the ratio of the original value of the positive indicator to the maximum value corresponding to the positive indicator and the indicator weight corresponding to the positive indicator; the evaluation score of a negative indicator is 1, the product of the difference between the original value of the negative indicator and the ratio of the maximum value corresponding to the negative indicator and the indicator weight corresponding to the negative indicator.

[0024] By adopting the above technical solution, the dimensionless processing of positive and negative indicators is unified into a relative ratio form with the maximum value as the reference, so that indicators with different dimensions can be converted into superimposed standardized scores before weighted summation.

[0025] Optionally, in S4, the steps of weighting and summing the evaluation scores of multiple indicators according to the multi-level indicator system to the value scores of the three value categories include: gathering the evaluation scores of multiple indicators at the lowest level of the multi-level indicator system; from the lowest level indicator upwards, summing the evaluation scores of the next level indicator according to the hierarchical weights corresponding to the previous level indicator to obtain the evaluation score of the previous level indicator; repeating this process until the scores of the three value categories are summarized.

[0026] By adopting the above technical solution, specific weighted aggregation execution steps from the lowest level indicators to the three major value categories are provided, so that the hierarchical aggregation process of the multi-level indicator system has an executable algorithm path.

[0027] Optional tree species that are beneficial to high levels of plant essence include those belonging to the Ginkgoaceae, Pinaceae, Taxaceae, Cupressaceae, Podocarpus, Cephalotaxaceae, Taxaceae, Magnoliaceae, Lauraceae, Rosaceae, Araliaceae, Theaceae, Myrtaceae, Rutaceae, and Verbenaceae families. Tree species that are beneficial to medium levels of plant essence include those belonging to the Fabaceae, Hamamelidaceae, Salicaceae, Betulaceae, Myricaceae, Fagaceae, Ulmaceae, Moraceae, Euphorbiaceae, Elaeocarpus, Aquifoliaceae, Oleaceae, and Rubiaceae families.

[0028] By adopting the above technical solution, the specific plant categories to which the classification rules for the grading of plant essence are applicable are given, so that the identification of beneficial high-essence tree species and beneficial medium-essence tree species has a directly comparable basis for judgment.

[0029] Optionally, forests classified as fire-retardant, combustible, and flammable are determined based on the tree species combustion type specified in the current national standards.

[0030] By adopting the above technical solutions and introducing existing national standards as the basis for determining the flammability of forests, the classification of fire-retardant forests, combustible forests, and flammable forests has a standardized and traceable basis.

[0031] Optionally, there are a total of 33 secondary, tertiary and quaternary indicators in the multi-level indicator system, which correspond to the specific quantitative objects of various indicators under the primary indicators, such as forest productivity, forest multifunctionality, forest structure, forest health, forest ecological benefits, landscape forest, health and wellness forest and scientific research and education.

[0032] By adopting the above technical solution, 33 specific indicators are provided as complete quantitative objects at the lower level of the multi-level indicator system, so that the evaluation method has a complete indicator foundation that can be directly applied.

[0033] Optionally, in S5, after removing some trees from the evaluated forest, the stand retention density of the evaluated forest is 100 trees / hm². 2 Up to 1050 plants / hm 2When replanting the target tree species, the number of trees to be replanted should be 300 per hectare. 2 Up to 1260 plants / hm 2 .

[0034] By adopting the above technical solution, the range of stand retention density after partial felling and the range of replanting numbers for target tree species are given, so that forest management measures have directly applicable density parameters and replanting number parameters when adjusting stand retention density and tree species configuration structure.

[0035] In summary, this application includes at least one of the following beneficial technical effects: 1. By listing economic value, ecological value, and socio-cultural value as the primary dimensions of forest quality evaluation, and by using a mechanism to dynamically determine the value category weights from at least two pre-set combinations of the three major value weights based on the type of forest management objectives, the evaluation method can not only fully present the multiple functions undertaken by forests, but also dynamically adapt the relative importance of each value dimension according to the management orientation of the evaluated object, thus avoiding the disconnect between the evaluation results and actual management needs caused by treating all forests the same with fixed weights.

[0036] 2. By introducing quantitative schemes for characteristic indicators such as the classification and grading of tree species based on plant essence, the joint judgment of multiple factors for forest stands with excellent appearance, and the distribution density of ancient and famous trees, the previously difficult-to-quantify objects such as the health and wellness value, aesthetic value, and cultural heritage value of forests are transformed into measurable and comparable specific indicators, thus improving the quantitative foundation of lower-level indicators of social and cultural value.

[0037] 3. By differentiating multiple indicators according to their positive and negative attributes, and combining them with a multi-level indicator system structure of four levels (from level one to level four), the indicators of different natures can accurately reflect their actual contribution to forest quality in the comprehensive evaluation, and the evaluation results are supported by sufficient lower-level indicators, thereby improving the scientificity and comparability of the evaluation method.

[0038] 4. By determining the weakness value category of the evaluated object based on the value scores of the three value categories, and implementing forest management measures for the evaluated object that correspond to the weakness value category and replant target tree species that have a positive contribution to the weakness value category, the management and transformation of the forest can accurately correspond to the diagnosed value weakness, improve the corresponding value score and improve forest quality at a lower management cost, and the management measures can be re-evaluated after implementation to form a closed loop, realizing the organic combination of evaluation diagnosis and forest management. Attached Figure Description

[0039] Figure 1 A flowchart illustrating a forest quality improvement method based on three key values ​​is shown in one embodiment of the present invention. Detailed Implementation

[0040] The following is in conjunction with the appendix Figure 1 This application will be further described in detail below. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0041] This application provides a method for improving forest quality based on three major values. This method categorizes the multiple functions of forests—including ecosystem services, forest product supply, and socio-cultural services—into three major value categories: economic value, ecological value, and socio-cultural value. It organizes multiple indicators into a multi-level indicator system according to these three value categories, and dynamically determines the weight of each value category from at least two preset combinations of weights based on the forest management objectives of the evaluated object. The method then assesses the value of the forest state obtained from forest resource surveys, yielding the value score of the evaluated object in each of the three value categories and a comprehensive forest quality evaluation score. Furthermore, the method calculates the value score based on the value of each of the three value categories. The evaluation process identifies the value deficiencies of the evaluated entity and implements corresponding forest management measures based on these deficiencies. These measures include adjusting stand density by felling some trees and replanting target tree species that positively contribute to the value deficiencies to adjust the tree species configuration, thereby changing the forest status of the evaluated entity. After implementing the forest management measures, measurements and assessments are repeated to verify the improvement effect. If value deficiencies still exist, corresponding forest management measures continue to be implemented to ensure that the direction of management and transformation corresponds to the identified value deficiencies, thereby improving the forest quality of the evaluated entity.

[0042] The following uses three evaluated objects as examples to illustrate the execution process of this method. Evaluation object 1's forest management objective type is commercial forest evaluation, evaluation object 2's is public welfare forest evaluation, and evaluation object 3's is health and wellness landscape forest evaluation. After obtaining the value scores for each of the three value categories in steps S1 to S4, the weakest value category is identified in step S5 based on its value score, and corresponding forest management measures are implemented. The following provides a detailed explanation of each step.

[0043] S1. Obtain the raw values ​​of multiple indicators of the evaluated object obtained from the forest resource database through forest resource survey and measurement. The multiple indicators represent the forest status of the evaluated object and are organized into three major value categories, namely economic value, ecological value and socio-cultural value.

[0044] The forest resource database can be a forest resource survey database maintained by forestry management departments. This database stores the original measurement data of each evaluated object obtained according to unified survey standards. The evaluated objects can be state-owned forest farms, nature reserves, or other forest management units with clearly defined boundaries. After retrieving the identification information of the evaluated object from the forest resource database, the original measurement values ​​of that object on multiple indicators are retrieved item by item as input data for subsequent evaluation processing.

[0045] For example, the raw values ​​of evaluated objects 1, 2, and 3 on multiple indicators are retrieved from the forest resource database. Indicators belonging to the economic value category involve the supply and direct utilization value of forest products; indicators belonging to the ecological value category involve the structural, health, and ecosystem service value of forests; and indicators belonging to the socio-cultural value category involve the landscape, health, and cultural heritage value of forests. By organizing multiple indicators in parallel according to these three value categories, the multiple functions of forests, such as ecosystem services, supply of forest products, and socio-cultural services, are all appropriately represented within the evaluation framework.

[0046] Specifically, multiple indicators are organized according to a multi-level indicator system. The multi-level indicator system includes primary indicators, which include forest productivity and forest multifunctionality indicators belonging to the economic value category, forest structure indicators, forest health indicators and forest ecological benefit indicators belonging to the ecological value category, and landscape forest indicators, health and wellness forest indicators and scientific research and education indicators belonging to the socio-cultural value category.

[0047] Forest productivity indicators reflect the forest's ability to produce timber; forest multifunctionality indicators reflect the forest's comprehensive ability to simultaneously undertake multiple production functions; forest structure indicators reflect the stand's own compositional structure; forest health indicators reflect the stand's resistance to stress factors such as pests, diseases, and fires; forest ecological benefit indicators reflect the forest's service effect on the local ecological environment; landscape forest indicators reflect the forest's aesthetic landscape value; health and wellness forest indicators reflect the forest's ability to support human health and wellness; and scientific research and education indicators reflect the cultural heritage and scientific research and education value carried by the forest. The multiple indicators obtained in S1 are assigned to the corresponding eight primary indicators mentioned above, and subsequently, in S3 and S4, they are weighted and aggregated level by level.

[0048] Furthermore, the multi-level indicator system also includes secondary, tertiary, and quaternary indicators. Secondary indicators belong to their corresponding primary indicators, tertiary indicators belong to their corresponding secondary indicators, and quaternary indicators belong to their corresponding tertiary indicators. For example, forest health indicators under the ecological value category, as primary indicators, can include forest flammability indicators as corresponding secondary indicators. Forest flammability indicators can further include indicators of the proportion of non-flammable forest area, the proportion of combustible forest area, and the proportion of easily flammable forest area as corresponding tertiary indicators. Indicators at each level are nested according to the above hierarchical relationship, forming a multi-level indicator system that proceeds from primary to quaternary indicators from top to bottom and from quaternary indicators to primary indicators from bottom to top.

[0049] In some embodiments, the multi-level indicator system comprises 33 secondary, tertiary, and quaternary indicators, each corresponding to a specific quantifiable object under the primary indicators for forest productivity, forest multifunctionality, forest structure, forest health, forest ecological benefits, landscape forests, health and wellness forests, and scientific research and education. Each primary indicator, based on the forest quality dimension it reflects, corresponds to several quantifiable specific indicators at the secondary, tertiary, or quaternary levels. These 33 specific indicators collectively cover the measurable dimensions of the three major values ​​involved in forest quality assessment: ecosystem services, forest product supply, and socio-cultural services.

[0050] S2. Based on the forest management objective type of the evaluated object, determine the value class weights corresponding to the three value categories from at least two pre-set combinations of the three value weights. Different combinations of the three value weights correspond to different types of forest management objective types, and the specific allocation of the value class weights of the three value categories is different in different combinations.

[0051] The relative importance of the three values ​​varies among forests with different management objectives: commercial forests, whose primary management objective is the supply of forest products, have a higher relative importance for economic value; public welfare forests, whose primary management objective is ecological protection, have a higher relative importance for ecological value; and health and wellness landscape forests, whose primary management objective is landscape and health and wellness services, have a higher relative importance for socio-cultural value. If the same value category weights are applied to all evaluated objects, the evaluation results will be difficult to reflect the relative performance of each evaluated object under its own management objective.

[0052] For example, if the forest management objective type of evaluated object 1 is commercial forest, the weight combination corresponding to the commercial forest evaluation type is determined from at least two pre-set combinations of the three major value weights as the value weight of evaluated object 1; if the forest management objective type of evaluated object 2 is public welfare forest, the weight combination corresponding to the public welfare forest evaluation type is determined as the value weight of evaluated object 2; and if the forest management objective type of evaluated object 3 is health and wellness landscape forest, the weight combination corresponding to the health and wellness landscape forest evaluation type is determined as the value weight of evaluated object 3. By setting different specific allocations of the three major value weight combinations corresponding to different forest management objective types, each evaluated object obtains a weight configuration that is compatible with its own management orientation during the evaluation process.

[0053] Specifically, forest management objectives include at least one of the following: regional comprehensive evaluation, commercial forest evaluation, public welfare forest evaluation, and health and wellness landscape forest evaluation. At least two pre-defined sets of weighted values ​​are included: a first set corresponding to the regional comprehensive evaluation, where the weight of ecological value is greater than the respective weights of economic and socio-cultural value, and the weight of economic value is equal to the weight of socio-cultural value; a second set corresponding to the commercial forest evaluation, where the weight of economic value is greater than the respective weights of ecological and socio-cultural value; a third set corresponding to the public welfare forest evaluation, where the weight of ecological value is greater than the respective weights of economic and socio-cultural value; and a fourth set corresponding to the health and wellness landscape forest evaluation, where the weight of socio-cultural value is greater than the respective weights of economic and ecological value.

[0054] The regional comprehensive evaluation category corresponds to a scenario that comprehensively evaluates the overall forest resources within a region. This category considers the three values ​​in a relatively balanced way, but ecological value is given a higher weight because it relates to the overall ecological service function of the region. The commercial forest evaluation category, public welfare forest evaluation category, and health and wellness landscape forest evaluation category correspond to forests whose main management objectives are economic output, ecological protection, and health and wellness landscape services, respectively. The weight of the corresponding value category is set to be greater than the weight of the other two value categories, so that the evaluation weight is consistent with the management orientation.

[0055] Following the previous example, the second combination is used as the value weight for evaluated object 1, the third combination is used as the value weight for evaluated object 2, and the fourth combination is used as the value weight for evaluated object 3.

[0056] In some embodiments, the value class weights of economic value, ecological value, and socio-cultural value in the first combination corresponding to the regional comprehensive evaluation category are 0.3, 0.4, and 0.3, respectively; the value class weights of economic value, ecological value, and socio-cultural value in the second combination corresponding to the commercial forest evaluation category are 0.6, 0.2, and 0.2, respectively; the value class weights of economic value, ecological value, and socio-cultural value in the third combination corresponding to the public welfare forest evaluation category are 0.2, 0.6, and 0.2, respectively; and the value class weights of economic value, ecological value, and socio-cultural value in the fourth combination corresponding to the health and wellness landscape forest evaluation category are 0.2, 0.2, and 0.6, respectively.

[0057] Following the previous example, the second combination applies to object 1, with a value class weight of 0.6 for economic value, 0.2 for ecological value, and 0.2 for socio-cultural value; the third combination applies to object 2, with value class weights of 0.2, 0.6, and 0.2 for economic value, ecological value, and socio-cultural value, respectively; and the fourth combination applies to object 3, with value class weights of 0.2, 0.2, and 0.6 for economic value, ecological value, and socio-cultural value, respectively.

[0058] For example, suppose there is an evaluated object 4 whose forest management objective type is regional comprehensive evaluation, and it is subject to the first combination. Its economic value, ecological value, and socio-cultural value weights are 0.3, 0.4, and 0.3, respectively. The value weight of the ecological value is higher than that of the economic value and socio-cultural value, and the value weight of the economic value is equal to that of the socio-cultural value. This is in line with the scenario of regional comprehensive evaluation, which conducts a comprehensive evaluation of the region as a whole, considers the three values ​​in a relatively balanced way, and gives appropriate emphasis to ecological value.

[0059] It should be understood that the specific values ​​of the above four sets of three major value weight combinations are only one value scheme provided by the embodiments of this application. In actual applications, the value weights in each combination can be adjusted accordingly based on the forest resource characteristics and actual management needs of the region. This application does not limit the specific values.

[0060] S3. The original values ​​of multiple indicators are weighted according to their respective weights in the multi-level indicator system to obtain the evaluation scores of each indicator. The multiple indicators include positive indicators and negative indicators. The evaluation scores of positive indicators change in the same direction as the original values ​​of the positive indicators, while the evaluation scores of negative indicators change in the opposite direction to the original values ​​of the negative indicators.

[0061] Positive and negative indicators are distinguished by the relationship between the direction of change of the original value of the indicator and the direction of its contribution to forest quality: if the larger the original value of the indicator, the better the forest quality, then the indicator is a positive indicator, such as forest stock volume, the proportion of beneficial tall plant species, and the proportion of non-flammable forest area; if the larger the original value of the indicator, the worse the forest quality, then the indicator is a negative indicator, such as the proportion of flammable forest area, the proportion of area with minor pests and diseases, the proportion of area with moderate pests and diseases, and the proportion of area with severe pests and diseases. The original values ​​of multiple indicators obtained in S1 are weighted to obtain the evaluation score of each indicator in the evaluation system. During weighting, the evaluation score of a positive indicator changes in the same direction as its original value, that is, the larger the original value of a positive indicator, the larger its evaluation score; the evaluation score of a negative indicator changes in the opposite direction to its original value, that is, the larger the original value of a negative indicator, the smaller its evaluation score.

[0062] For example, if the original value of a positive indicator for evaluated object 1 is greater than the original value of the same indicator for evaluated object 2, then the evaluation score for evaluated object 1 on that indicator is greater than the evaluation score for evaluated object 2 on that indicator. Conversely, if the original value of a negative indicator for evaluated object 1 is greater than the original value of the same indicator for evaluated object 2, then the evaluation score for evaluated object 1 on that indicator is less than the evaluation score for evaluated object 2 on that indicator. By distinguishing between positive and negative indicators, each indicator can accurately reflect its actual contribution to forest quality in the comprehensive evaluation.

[0063] Because different indicators use different dimensions and orders of magnitude for their raw values—for example, forest stock volume is measured in cubic meters, the density of ancient and famous trees is measured in trees per hectare, and the proportion of various areas is a dimensionless ratio—directly weighting and summing the raw values ​​of each indicator would result in indicators with larger dimensions and orders of magnitude having a disproportionate impact on the overall evaluation score. To eliminate these differences in dimensions and orders of magnitude, the weighting process first compares the raw value of each indicator with its maximum value across all evaluated objects, thus making the raw values ​​dimensionless. This maps each indicator's raw value to a relative quantity between zero and one, and then multiplies it by the corresponding indicator weight to obtain the evaluation score. After dimensionless processing, the evaluation scores obtained from different evaluated objects, regions, and years are under a unified benchmark, making them comparable.

[0064] In some embodiments, in S3, the evaluation score of the positive indicator is calculated using the following formula:

[0065] The evaluation score for the contrarian indicator is calculated using the following formula:

[0066] in, The evaluation score for the indicator. The original value of the indicator. This is the maximum value of the indicator among all the evaluated objects. This represents the weight of the indicator.

[0067] For example, the original values ​​of a positive indicator are 60, 80, and 50 for evaluated object 1, evaluated object 2, and evaluated object 3, respectively. The maximum value of this indicator among all evaluated objects is... The value is 80, which corresponds to the indicator weight. If the score is 0.2, then the evaluation score of the evaluated object 1 on this indicator is... The evaluation score of the evaluated object 2 on this indicator The evaluation score of the evaluated object 3 on this indicator .

[0068] It should be understood that, It can be the maximum measured value of the indicator among all the evaluated objects, or it can be the theoretical extreme value of the indicator or the reference maximum value set by industry standards. This application does not restrict the specific value selection method.

[0069] Specifically, the indicators for health and wellness forests include the proportion of area of ​​tree species with high plant energy and the proportion of area of ​​tree species with moderate plant energy. Tree species with high plant energy and tree species with moderate plant energy are determined according to the preset tree species plant energy classification rules. The preset tree species plant energy classification rules select tree species with high plant energy and tree species with moderate plant energy from the tree species based on the plant energy intensity of various plant families.

[0070] Plant essence refers to substances with plant-derived volatile characteristics released by tree species in forests through their leaves, branches, and roots. These substances have beneficial effects on human health. The intensity of plant essence released by tree species belonging to different plant families varies. The classification rules for plant essence by tree species select those with high beneficial plant essence intensity and those with moderate beneficial plant essence intensity from all tree species based on the intensity of their plant essence. Other tree species not selected are not included in this indicator calculation. The area proportion of trees with high beneficial plant essence intensity is the ratio of the area of ​​the stand containing these trees to the total area of ​​all stands within the evaluated area. The area proportion of trees with moderate beneficial plant essence intensity is the ratio of the area of ​​the stand containing these trees to the total area of ​​all stands within the evaluated area.

[0071] For example, the forest management objective type of evaluated object 3 is health and wellness landscape forest evaluation. In the area of ​​evaluated object 3, the area proportion of stands containing beneficial high-value tree species is 0.45%, and the area proportion of stands containing beneficial medium-value tree species is 0.30%, totaling 0.75%. Due to different management orientations, evaluated objects 1 and 2 may have a lower area proportion of beneficial high-value tree species in their corresponding areas than evaluated object 3, reflecting the differences in health and wellness value among the three evaluated objects. By screening beneficial high-value tree species according to grading and classification rules and quantifying them by area proportion, the health and wellness function of the forest is transformed into measurable and comparable specific indicators.

[0072] In some embodiments, beneficial tree species with high plant energy include those belonging to the Ginkgoaceae, Pinaceae, Taxaceae, Cupressaceae, Podocarpus, Cephalotaxaceae, Taxaceae, Magnoliaceae, Lauraceae, Rosaceae, Araliaceae, Theaceae, Myrtaceae, Rutaceae, and Verbenaceae families. Beneficial tree species with moderate plant energy include those belonging to the Fabaceae, Hamamelidaceae, Salicaceae, Betulaceae, Myricaceae, Fagaceae, Ulmaceae, Moraceae, Euphorbiaceae, Elaeocarpus, Aquifoliaceae, Oleaceae, and Rubiaceae families. For example, Ginkgo (Ginkgoaceae), Pinus massoniana and Pinus tabuliformis (Pinaceae), Cunninghamia lanceolata and Metasequoia glyptostroboides (Taxus chinensis), Platycladus orientalis and Cypress (Cupstem cypress) (Cupstem cypress) and Cinnamomum camphora (Lauraceae) are all beneficial tree species with high plant energy; Sophora japonica (Fabaceae), Quercus glauca and Quercus acutissima (Fagaceae), and Osmanthus fragrans (Oleaceae) are all beneficial tree species with moderate plant energy.

[0073] It should be understood that the plant subjects corresponding to the beneficial high-value plant species and the beneficial medium-value plant species are not limited to those listed above. The specific list of subjects can be expanded accordingly based on updates to existing literature on plant essence and qi. This application does not limit the specific subject scope.

[0074] Specifically, the landscape forest index includes the proportion of forest stand area with excellent forest quality. A forest stand with excellent forest quality is determined when three factors—canopy closure, number of forest stand layers, and stand growth health—simultaneously reach their respective preset judgment thresholds.

[0075] Canopy closure reflects the degree of coverage of the forest floor by the top of the canopy; the number of forest strata reflects the richness of different height levels within the stand; and stand health reflects the health status of the trees within the stand. These three elements, canopy cover, stratification, and growth status, collectively describe the aesthetic landscape value of a forest from three dimensions. Therefore, a forest stand of excellent quality must meet the corresponding preset thresholds in all three elements. The proportion of forest stand area with excellent quality is the ratio of the area occupied by forest stands with excellent quality to the total area of ​​all forest stands within the evaluated area.

[0076] For example, if some forest stands within the area of ​​evaluated object 3 have canopy closure, forest stand layer number, and forest stand health all meet the corresponding preset thresholds, these stands are classified as excellent forest stands. If any of these three elements fails to meet the corresponding preset threshold, the forest stand is not classified as an excellent forest stand. The proportion of excellent forest stand area in the landscape forest indicators for evaluated object 3 is higher than that for evaluated objects 1 and 2.

[0077] Specifically, the scientific research and education indicators include the distribution density of ancient and famous trees, which is the ratio of the number of ancient and famous trees in the area of ​​the evaluated object to the area of ​​the evaluated object.

[0078] Ancient trees refer to trees that are 100 years old or older, while famous trees refer to trees with significant historical, cultural, or scientific research value. Together, they embody the cultural heritage and scientific and educational value of forests. The distribution density of ancient and famous trees is normalized by dividing the number of ancient and famous trees by the area of ​​the evaluated region, making the evaluated regions of different areas comparable in this indicator and avoiding evaluation bias caused by the absolute number of trees in large areas.

[0079] For example, if the area of ​​evaluated object 1 is 1000 hectares and there are 50 ancient and famous trees in the area, then the distribution density of ancient and famous trees in evaluated object 1 is 0.05 trees / hectare; if the area of ​​evaluated object 2 is 2000 hectares and there are 60 ancient and famous trees in the area, then the distribution density of ancient and famous trees in evaluated object 2 is 0.03 trees / hectare; if the area of ​​evaluated object 3 is 1500 hectares and there are 90 ancient and famous trees in the area, then the distribution density of ancient and famous trees in evaluated object 3 is 0.06 trees / hectare. Quantified by distribution density, evaluated object 3's relative performance in scientific research and education indicators is higher than that of evaluated object 1 and evaluated object 2.

[0080] Specifically, forest health indicators include forest flammability indicators, which include the proportion of non-flammable forest area, the proportion of combustible forest area, and the proportion of easily flammable forest area. The proportion of non-flammable forest area is a positive indicator, while the proportions of combustible forest area and easily flammable forest area are negative indicators.

[0081] Forest flammability reflects the natural resistance of a forest stand to fire. Based on the combustion type of tree species within the stand, forests are classified into three categories: difficult-to-burn forests, combustible forests, and easily combustible forests. Difficult-to-burn forests are dominated by tree species with high fire resistance, exhibiting strong resistance under fire stress. Easily combustible forests are dominated by tree species with low fire resistance, exhibiting weaker resistance under fire stress. Combustible forests fall somewhere in between. A higher proportion of difficult-to-burn forest area indicates a stronger natural resistance to fire, thus it is a positive indicator. Conversely, higher proportions of combustible and easily combustible forest areas indicate weaker fire resistance, thus they are negative indicators.

[0082] For example, the forest management target type of the evaluated object 2 is public welfare forest evaluation. The proportion of non-flammable forest area in the area where evaluated object 2 is located is 0.65, the proportion of combustible forest area is 0.25, and the proportion of easily flammable forest area is 0.10, which reflects that the forest of the evaluated object has a strong natural resistance to fire.

[0083] In some embodiments, forest stands are classified as fire-retardant, combustible, and flammable based on the tree species combustion types specified in current national standards. For example, the classification of tree species combustion types in the "Technical Specification for Forest Fire Hazard Assessment" (XPC / LCP-01[S], 2021) and its appendices can be referenced to use the combustion type of the main tree species within the forest stand as the basis for determining the corresponding forest stand, thereby classifying the forest stand as fire-retardant, combustible, or flammable. By introducing current national standards as the basis for classification, the classification of forest flammability has a standardized and traceable basis for determination.

[0084] S4. The evaluation scores of multiple indicators are weighted and summarized according to the multi-level indicator system to the value scores of the three value categories. The value scores of the three value categories are then weighted and summed according to the value category weights to obtain the comprehensive forest quality evaluation score of the evaluated object. The comprehensive forest quality evaluation score represents the forest quality of the evaluated object, and the value scores of the three value categories are used to determine the weak value category of the evaluated object.

[0085] The evaluation scores of the multiple indicators obtained in S3 are weighted and summed from bottom to top according to the multi-level indicator system: the evaluation scores of the lowest-level indicators in the multi-level indicator system are weighted and summed according to the hierarchical weights of the indicators at the next higher level to obtain the evaluation score of that higher-level indicator; the evaluation scores of that higher-level indicator are then weighted and summed according to the hierarchical weights of its corresponding higher-level indicator, and summed level by level to the first-level indicator; the evaluation scores of each first-level indicator are weighted and summed according to the hierarchical weights of the value category to which it belongs to, to obtain the value scores of each of the three value categories. The value scores of each of the three value categories are then weighted and summed according to the value category weights determined in S2 to obtain the comprehensive forest quality evaluation score of the evaluated object.

[0086] For example, after the above-mentioned weighted summation, the economic value score of the evaluated object 1 is 0.50, the ecological value score is 0.45, and the socio-cultural value score is 0.40. Weighted and summed according to the second group's value category weights of 0.6, 0.2, and 0.2, the comprehensive forest quality evaluation score of the evaluated object 1 is: The comprehensive forest quality evaluation scores for evaluated objects 2 and 3 were obtained in a similar manner.

[0087] In some embodiments, S4 includes the following sub-steps: S41. At the lowest level of the multi-level indicator system, the evaluation scores of multiple indicators are aggregated. S42. Starting from the lowest level indicator and working upwards, sum the evaluation scores of the next level indicator by weighting them according to the corresponding hierarchical weights of the previous level indicator to obtain the evaluation score of the previous level indicator. S43. Repeat S42 until the values ​​are aggregated into the value scores of the three value categories.

[0088] Following the above sub-steps, S41 first aggregates the evaluation scores of the multiple indicators obtained in S3 at the lowest level of the multi-level indicator system. For example, at the fourth-level indicators, the evaluation scores of the fourth-level indicators are aggregated, and at the third-level indicators, the evaluation scores of the third-level indicators without further subdivision are aggregated. S42 aggregates from the lowest level indicators to the next higher level, weighting and summing the evaluation scores of each indicator at that level according to the level weight corresponding to the next higher level indicator to obtain the evaluation score of the next higher level indicator. S43 repeats the weighted summation operation of S42, aggregating from the fourth-level indicators to the third-level indicators, then from the third-level indicators to the second-level indicators, then from the second-level indicators to the first-level indicators, and finally from the first-level indicators to the value scores of the three major value categories.

[0089] For example, in S3, the evaluated object 1 obtains evaluation scores for each of the 33 secondary, tertiary, and quaternary indicators. After being summarized step by step through S41-S43, the scores are first summarized to the evaluation scores of each tertiary and secondary indicator, then to the evaluation scores of the eight primary indicators, and finally to the value scores of the economic value, ecological value, and socio-cultural value categories. The evaluated objects 2 and 3 are summarized step by step using the same sub-steps.

[0090] S5. Based on the value scores of the three value categories, the value category with the lowest value score among the three value categories is determined as the weakest value category of the evaluated object, and forest management measures corresponding to the weakest value category are implemented for the evaluated object. The forest management measures include felling some trees in the evaluated object to adjust the stand retention density, and replanting target tree species corresponding to the weakest value category in the stand gaps to adjust the tree species configuration structure. The target tree species are tree species that make a positive contribution to the value score of the weakest value category. When the weakest value category is economic value, the target tree species include valuable timber tree species; when the weakest value category is ecological value, the target tree species include native broad-leaved tree species; when the weakest value category is socio-cultural value, the target tree species include at least one of landscape tree species and beneficial plant spirit tree species, so as to improve the forest quality of the evaluated object.

[0091] After obtaining the value scores of the evaluated object in each of the three value categories through S4, the value category with the lowest value is determined as the weakest value category of the evaluated object. This weakest value category represents the weakest point of the evaluated object in that value direction compared to the other value directions, and is most in need of improvement through management and transformation. After determining the weakest value category, forest management measures corresponding to that category are implemented on the evaluated object. These measures involve, on the one hand, removing some trees from the evaluated object to adjust the stand density to a suitable range for replanting, providing growth space for the replanted tree species; on the other hand, replanting target tree species in the gaps created after the removal of trees to adjust the tree species configuration structure of the evaluated object.

[0092] The target tree species are those that make a positive contribution to the value score of the short-board value category. That is, after replanting the target tree species, the original values ​​of the relevant indicators under the short-board value category will change in the direction of increasing the value score of the value category. Specifically, when the weakness is classified as economic value, the target tree species include precious timber species. Replanting precious timber species can increase the number of precious tree species and the proportion of precious tree species in the area of ​​the evaluated object, which belong to the economic value category, thereby increasing the value score of the economic value category. When the weakness is classified as ecological value, the target tree species include native broad-leaved tree species. Replanting native broad-leaved tree species can improve the proportion of mixed coniferous and broad-leaved forests and the number of tree species in the area of ​​the evaluated object, which belong to the ecological value category, thereby increasing the value score of the ecological value category. When the weakness is classified as socio-cultural value, the target tree species include at least one of landscape tree species and beneficial plant species. Replanting landscape tree species can increase the number of landscape tree species and the proportion of landscape forest area, which belong to the landscape forest category. Replanting beneficial plant species can increase the proportion of beneficial tall and medium-sized beneficial plant species in the area of ​​the health and wellness forest category, which belong to the health and wellness forest category, thereby increasing the value score of the socio-cultural value category.

[0093] In some embodiments, valuable timber species, native broadleaf species, landscape species, and beneficial plant species can be selected from species such as *Machilus chinensis*, *Liquidambar formosana*, *Schima superba*, *Cinnamomum camphora*, *Quercus glauca*, *Taxus wallichiana*, *Ginkgo biloba*, *Magnolia officinalis*, *Melia azedarach*, and *Sapium sebiferum*, based on their corresponding value contributions. The same species can simultaneously contribute positively to multiple value categories. For example, *Taxus wallichiana* and *Ginkgo biloba*, as valuable timber species, contribute positively to the economic value category, and as beneficial plant species, they also contribute positively to the health and wellness forest index in the socio-cultural value category. *Quercus glauca* and *Schima superba*, as native broadleaf species, contribute positively to the ecological value category, and also contribute positively to the landscape forest index in the socio-cultural value category due to their good landscape performance. When replanting, priority should be given to native species that grow well and have high survival rates in the area where the evaluated object is located, thereby achieving an increase in the corresponding value score with lower operating costs.

[0094] In some embodiments, in S5, after felling some of the trees in the evaluated object, the stand retention density of the evaluated object is 100 trees / hm². 2 Up to 1050 plants / hm 2 When replanting the target tree species, the number of trees to be replanted should be 300 per hectare. 2 Up to 1260 plants / hm 2 Within the range of forest stand retention density and replanting number, both the existing trees retained and the target tree species replanted in the evaluated area can obtain suitable growth space, thus ensuring the growth performance of both the retained trees and the replanted tree species.

[0095] Following the previous example, the forest management objective type of evaluated object 1 is commercial forest. Through S4, its economic value, ecological value, and socio-cultural value scores are 0.50, 0.45, and 0.40, respectively. The socio-cultural value score is the lowest, thus it is identified as the weakest value category for evaluated object 1. Some trees in evaluated object 1 will be felled to adjust its stand density to a suitable range, and target tree species for landscape and beneficial plant growth will be planted in the gaps to improve the landscape and health-oriented forest indicators, thereby increasing its socio-cultural value score. The forest management objective type of evaluated object 2 is public welfare forest. Assuming that its economic value score is the lowest through S4, it is identified as the weakest value category for evaluated object 2. Target tree species for precious timber will be planted in evaluated object 2 to increase the number and proportion of precious tree species belonging to the economic value category. The forest management target type of the evaluated object 3 is the health and wellness landscape forest evaluation category. Assuming that its ecological value category has the lowest value score obtained through S4, the ecological value category is determined as the weak value category of the evaluated object 3. The evaluated object 3 will be replanted with native broad-leaved tree species to increase the proportion of its mixed coniferous and broad-leaved forest area and the number of tree species belonging to the ecological value category.

[0096] S6. Re-execute S1 to S4 on the evaluated object after the implementation of forest management measures to obtain the updated value scores of the three major value categories and the updated comprehensive forest quality evaluation score, so as to verify the effect of forest management measures on improving the forest quality of the evaluated object, and return to execute S5 when it is necessary to further improve the forest quality of the evaluated object.

[0097] In some embodiments, the above-mentioned forest management measures were implemented on the evaluated subjects in the middle-aged, near-mature, or mature forest age groups. The original trees retained and the target tree species replanted in the evaluated subjects showed year-on-year growth in continuous monitoring after the management and transformation. Among them, the growth performance of the replanted tree species in the middle-aged forest age group was better than that in the near-mature and mature forest age groups, reflecting that the above-mentioned forest management measures can achieve better forest quality improvement effect when implemented in the middle-aged forest age group stage.

[0098] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0099] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for improving forest quality based on three key values, characterized in that, Includes the following steps: S1. Obtain the original values ​​of multiple indicators of the evaluated object obtained from the forest resource database through forest resource survey and measurement. The multiple indicators represent the forest status of the evaluated object and are organized into three major value categories, namely economic value, ecological value and socio-cultural value. S2. Based on the forest management objective type of the evaluated object, determine the value class weights corresponding to each of the three value categories from at least two preset combinations of the three value weights. Different combinations of the at least two sets of the three value weights correspond to different types of the forest management objective type, and the allocation of the value class weights of the three value categories is different in different combinations. S3. The original values ​​of the multiple indicators are weighted according to their respective weights in the multi-level indicator system to obtain the evaluation scores of each of the multiple indicators. The multiple indicators include positive indicators and negative indicators. The evaluation scores of the positive indicators change in the same direction as the original values ​​of the positive indicators, and the evaluation scores of the negative indicators change in the opposite direction as the original values ​​of the negative indicators. S4. The evaluation scores of each of the multiple indicators are weighted and aggregated according to the multi-level indicator system to the value scores of each of the three value categories, and the value scores of each of the three value categories are weighted and summed according to the value category weights to obtain the comprehensive forest quality evaluation score of the evaluated object; the comprehensive forest quality evaluation score represents the forest quality of the evaluated object, and the value scores of each of the three value categories are used to determine the weak value category of the evaluated object; S5. Based on the value scores of the three value categories, the value category with the lowest value score among the three value categories is determined as the short-board value category of the evaluated object, and forest management measures corresponding to the short-board value category are implemented on the evaluated object. The forest management measures include felling some trees in the evaluated object to adjust the stand retention density, and replanting target tree species corresponding to the short-board value category in the stand gaps to adjust the tree species configuration structure. The target tree species are tree species that have a positive contribution to the value score of the short-board value category. When the short-board value category is an economic value category, the target tree species include precious timber tree species. When the short-board value category is an ecological value category, the target tree species include native broad-leaved tree species. When the short-board value category is a socio-cultural value category, the target tree species include at least one of landscape tree species and beneficial plant spirit tree species, so as to improve the forest quality of the evaluated object. S6. Re-execute S1 to S4 on the evaluated object after implementing the forest management measures to obtain the updated value scores of the three major value categories and the updated comprehensive forest quality evaluation score, so as to verify the effect of the forest management measures on improving the forest quality of the evaluated object, and return to execute S5 when it is necessary to further improve the forest quality of the evaluated object.

2. The forest quality improvement method based on three values ​​according to claim 1, characterized in that, The types of forest management objectives include at least one of the following: regional comprehensive evaluation, commercial forest evaluation, public welfare forest evaluation, and health and wellness landscape forest evaluation. The preset at least two sets of three major value weight combinations include: The first combination corresponding to the regional comprehensive evaluation category, wherein the value class weight of the ecological value category in the first combination is greater than the value class weight of the economic value category and the socio-cultural value category respectively, and the value class weight of the economic value category is equal to the value class weight of the socio-cultural value category; The second combination corresponding to the commercial forest evaluation category, wherein the value class weight of the economic value category in the second combination is greater than the value class weights of the ecological value category and the socio-cultural value category respectively; The third combination corresponding to the public welfare forest evaluation category has a value class weight of the ecological value category that is greater than the value class weights of the economic value category and the socio-cultural value category, respectively. The fourth combination corresponding to the health and wellness landscape forest evaluation category has a greater value class weight for the socio-cultural value category than for the economic value category and the ecological value category.

3. The forest quality improvement method based on three values ​​according to claim 1, characterized in that, The multiple indicators are organized according to a multi-level indicator system, which includes primary indicators. The primary indicators include forest productivity indicators and forest multifunctionality indicators belonging to the economic value category, forest structure indicators, forest health indicators and forest ecological benefit indicators belonging to the ecological value category, and landscape forest indicators, health and wellness forest indicators and scientific research and education indicators belonging to the socio-cultural value category.

4. The forest quality improvement method based on three values ​​according to claim 3, characterized in that, The health and wellness forest indicators include the proportion of area of ​​tree species with high beneficial plant essence and the proportion of area of ​​tree species with moderate beneficial plant essence. The tree species with high beneficial plant essence and the tree species with moderate beneficial plant essence are determined according to a preset tree species plant essence classification rule. The preset tree species plant essence classification rule selects the tree species with high beneficial plant essence and the tree species with moderate beneficial plant essence from the tree species based on the plant essence intensity of various plant families.

5. The forest quality improvement method based on three values ​​according to claim 3, characterized in that, The landscape forest index includes the proportion of forest stand area with excellent forest quality. The forest stand with excellent forest quality is determined when the three elements of forest canopy closure, forest stand layer number and forest stand growth health simultaneously reach their respective preset judgment thresholds.

6. The forest quality improvement method based on three values ​​according to claim 3, characterized in that, The scientific research and education indicators include the distribution density of ancient and famous trees, which is the ratio of the number of ancient and famous trees in the area of ​​the evaluated object to the area of ​​the evaluated object.

7. The forest quality improvement method based on three values ​​according to claim 3, characterized in that, The forest health indicators include forest flammability indicators, which include the proportion of area of ​​fire-resistant forests, the proportion of area of ​​combustible forests, and the proportion of area of ​​flammable forests. The proportion of area of ​​fire-resistant forests is the positive indicator, and the proportions of area of ​​combustible forests and the proportions of area of ​​flammable forests are the negative indicators.

8. The forest quality improvement method based on three values ​​according to claim 7, characterized in that, In S3, the evaluation score of a positive indicator is the product of the ratio of the original value of the positive indicator to the maximum value corresponding to the positive indicator and the indicator weight corresponding to the positive indicator. The evaluation score of a negative indicator is 1, the product of the difference between the original value of the negative indicator and the ratio of the maximum value corresponding to the negative indicator and the indicator weight corresponding to the negative indicator.

9. The forest quality improvement method based on three values ​​according to claim 3, characterized in that, The multi-level indicator system also includes secondary indicators, tertiary indicators, and quaternary indicators. The secondary indicators belong to the corresponding primary indicators, the tertiary indicators belong to the corresponding secondary indicators, and the quaternary indicators belong to the corresponding tertiary indicators.

10. The forest quality improvement method based on three values ​​according to claim 1, characterized in that, In S5, after felling some of the trees in the evaluated object, the stand retention density of the evaluated object is 100 trees / hm². 2 Up to 1050 plants / hm 2 When replanting the target tree species, the number of trees to be replanted is 300 per hectare. 2 Up to 1260 plants / hm 2 .

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