Degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database

Abstract

The present invention discloses a degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database, which relates to the technical field of quantitative assessment of degraded forests, including a degraded forest assessment management platform, wherein the degraded forest assessment management platform is communicatively connected with a degraded forest data acquisition module, a feature extraction module, an identification and analysis module, an assessment and prediction module and a management strategy generation module, wherein the modules are connected by electrical signals. The present invention realizes the identification of degraded forests by integrating multi-source data including ecology, soil and meteorology. Compared with the traditional manual monitoring method, the present invention can automatically and in real time process a large amount of data, quickly locate and identify degraded forest areas, and significantly improve the accuracy and efficiency of monitoring, which not only reduces the workload of forestry workers, but also further ensures the timeliness and accuracy of monitoring results, laying a solid foundation for subsequent assessment and management work.

Description

Technical Field

[0001] The present invention relates to the technical field of quantitative assessment of degraded forests, and in particular to a degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland databases. Background Art

[0002] With the rapid development of information technology, the forestry field has also ushered in a wave of informatization and modernization. In order to achieve scientific management and efficient utilization of forestry resources, building a digital and intelligent forestry information system has become an inevitable choice. Degraded forest refers to forest land whose stand quality has declined and the ecosystem service function has weakened due to natural factors or human activities. Degraded forest not only affects the productivity and ecological benefits of forest land, but may also cause ecological and environmental problems such as soil erosion and reduction of biodiversity. Therefore, timely and accurate analysis and evaluation of degraded forests is the premise and basis for formulating scientific and reasonable forestry restoration and reconstruction measures.

[0003] For example, the method and system for quantifying the degree of degradation of the ecological geological environment in the transition zone between agriculture, animal husbandry and forestry is disclosed in Chinese Patent Publication No. CN112561398A. The system for quantifying the degree of degradation of the ecological geological environment in the transition zone between agriculture, animal husbandry and forestry includes: an image data acquisition module, an image preprocessing module, an image feature extraction module, an image edge information statistics module, an evaluation index establishment module, a central control module, a quantitative model construction module, a degradation degree quantification module, a data storage module, and an update display module.

[0004] In the existing technology, by establishing an indicator diagnosis method for degradation assessment system with different utilization degrees, screening grassland vegetation and soil indicator systems with different utilization modes and different degradation degrees, screening grassland degradation indicator systems and analyzing the differences, sensitivity and uncertainty of degradation degrees, the degree of land degradation is fully characterized. However, the analysis process of degraded forests involves multiple characteristic variables. Due to the differences in the characteristics of different degraded forests, it is difficult to conduct a comprehensive assessment based on different degraded forest characteristics, resulting in certain deviations in the assessment results. Therefore, how to improve the applicability and comprehensive effect of degraded forest analysis and assessment, and propose corresponding management measures in a targeted manner, is the problem we need to solve. To this end, a degraded forest analysis and assessment system based on intelligent identification of forest, grassland and wetland database is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a degraded forest analysis and evaluation system based on intelligent identification of forest, grass and wetland database to solve the problems raised in the above-mentioned background technology.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland databases, comprising a degraded forest assessment management platform, wherein the degraded forest assessment management platform is communicatively connected to a degraded forest data acquisition module, a feature extraction module, an identification and analysis module, an assessment and prediction module and a management strategy generation module, wherein electrical signals are connected between the modules;

[0008] The degraded forest data acquisition module is used to collect raw data related to degraded forest assessment from the forest, grassland and wetland database, including ecological survey data, soil survey data and meteorological data, and perform pre-processing operations such as cleaning, denoising and standardization on the collected raw data to solve data inconsistency and redundancy problems, improve the accuracy and efficiency of data analysis, reduce noise interference in the analysis process, ensure the comprehensiveness and timeliness of the data, and provide a solid foundation for subsequent analysis;

[0009] The feature extraction module is used to extract the relevant features of the ecological survey data, soil survey data, meteorological data and degraded forest features of the fixed area in the medium assessment period from the pre-processed raw data, and analyze the correlation between each feature and the degraded forest;

[0010] The identification and analysis module calculates the ecological assessment index, soil assessment index and meteorological assessment index respectively based on the extracted relevant features of the ecological survey data, soil survey data and meteorological data and the degraded forest features, and analyzes the impact of each feature on the degraded forest;

[0011] The assessment and prediction module constructs a degraded forest assessment model based on the identified degraded forest characteristics, identifies and classifies degraded forests, distinguishes different degrees of degradation, combines the analysis results of the impact of ecological conditions, soil conditions and meteorological conditions on degraded forests, and conducts a comprehensive assessment of the current state of degraded forests, providing forestry managers with timely degraded forest state information and future forecasts to assist in decision-making;

[0012] The management strategy generation module generates targeted degraded forest management strategies and recommendations based on the assessment results, and intuitively displays the assessment results in the form of charts, maps, etc., to facilitate user understanding and use, enhance the readability and dissemination of the assessment results, and facilitate decision makers and the public to quickly understand the status of degraded forests.

[0013] A further improvement of the technical solution of the present invention is that: in the degraded forest data acquisition module, the process of collecting the original data related to the degraded forest assessment is:

[0014] Clarify the data types required for degraded forest assessment and management, including ecological survey data, ground survey data and meteorological data, covering the spatial distribution, growth status, environmental factors and other aspects of degraded forests, which are the basis for subsequent analysis. Establish a data interface with the forest, grassland and wetland database to obtain access rights to ecological survey data, ground survey data and meteorological data, and use API, database query or file transfer to obtain data;

[0015] Access the forest, grassland and wetland database to select ecological survey data, ground survey and meteorological raw data related to degraded forest assessment. The MODIS and Landsat series remote sensing images are used to obtain forest coverage, vegetation type and health status information related to ecological survey data. Ground survey data are used to collect information on tree growth status, forest biomass, tree species composition, soil conditions, and pests and diseases, which are usually obtained by forestry departments or scientific research institutions through field surveys. Meteorological data are used to collect meteorological information on precipitation, temperature, humidity and light.

[0016] Perform pre-processing operations such as data cleaning, denoising and standardization on the collected raw data, and convert non-numerical data (such as soil type and pest and disease level) into numerical data for statistical analysis;

[0017] The preprocessed ecological survey data, ground survey data and meteorological data are stored in the data warehouse to ensure the security and accessibility of the data, and the data in the data warehouse are backed up regularly to prevent data loss.

[0018] A further improvement of the technical solution of the present invention is that in the feature extraction module, the extraction process of the relevant features of the ecological survey data, soil survey data, meteorological data and the degraded forest features is as follows:

[0019] The pre-processed ecological survey data, soil survey data, and meteorological data were integrated into a unified data set, which was segmented according to fixed regions and assessment periods. The historical data of the forest-grass-wetland database was combined to analyze the changing trends of degraded forest characteristics and determine the changing characteristics of degraded forests, which were tree mortality, decreased stand density, reduced vegetation cover, and signs of soil degradation, in order to facilitate analysis and regional comparison;

[0020] The ecological survey data were analyzed to determine the ecological characteristics of degraded forest analysis and evaluation, namely, vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species quantity characteristics, in order to reflect the overall status of the forest ecosystem. Vegetation coverage reflects the breadth and density of forest coverage, tree density changes measure the number of trees per unit area, and reflect the density of the forest. The greenness index evaluates the health of vegetation by analyzing the reflectivity of red and near-infrared light, and the number of species measures the richness and uniformity of species in the ecosystem.

[0021] Analyze the soil survey data to determine the soil characteristics for degraded forest analysis and evaluation, namely soil texture characteristics, soil nutrient content characteristics, soil pH characteristics, and soil erosion degree characteristics, to reflect the growth and health of the forest. Soil texture affects water retention and nutrient exchange capacity, soil nutrient content such as nitrogen, phosphorus, and potassium content affects plant growth, soil pH affects the availability of nutrients in the soil, and soil erosion degree reflects the severity of soil loss and degradation;

[0022] Meteorological data are analyzed to determine the meteorological influencing characteristics for degraded forest analysis and assessment, namely, precipitation characteristics, temperature characteristics, humidity characteristics, and light characteristics, to reflect the climate environment in which the forest is located. Precipitation affects water supply and plant growth, temperature affects the physiological activities and distribution of plants, humidity affects water evaporation and the water demand of plants, and light affects photosynthesis and plant growth;

[0023] Ecological characteristics, soil characteristics, and meteorological impact characteristics are extracted from the data sets of ecological survey data, soil survey data, and meteorological data, and associated with degraded forest characteristics to identify characteristics that are highly correlated with degraded forests.

[0024] A further improvement of the technical solution of the present invention is that in the identification and analysis module, the analysis process of the impact of each feature on the degraded forest is as follows:

[0025] Extract ecological characteristics such as vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species quantity characteristics from ecological survey data, obtain ecological characteristic data sets, build ecological assessment models in combination with neural network models, and analyze relevant data of ecological characteristics to obtain ecological assessment indexes, quantify the impact trend of ecological conditions on degraded forests, analyze the changes in degraded forest characteristics under different ecological assessment index values, determine the impact trend of ecological conditions on degraded forests, and identify the potential relationship between the deterioration of ecological conditions and the aggravation of degraded forests;

[0026] Extract soil characteristics such as soil texture, soil nutrient content, soil pH, and soil erosion degree from soil survey data, obtain soil characteristic data sets, build soil assessment models in combination with neural network models, and analyze relevant data on soil characteristics to obtain soil assessment indexes. Perform correlation analysis between soil assessment indexes and degraded forest characteristics, quantify the impact trend of soil conditions on degraded forests, analyze changes in degraded forest characteristics under different soil assessment index values, and identify the potential relationship between soil condition deterioration and aggravation of degraded forests.

[0027] Meteorological characteristics of precipitation, temperature, humidity, and light are extracted from meteorological data, and a meteorological characteristic data set is obtained. A meteorological assessment model is constructed in combination with the random forest algorithm. The relevant data of meteorological characteristics are analyzed to obtain a meteorological assessment index. The interaction between different meteorological factors and their nonlinear impact on forest ecosystems are analyzed. The meteorological assessment index is correlated with the characteristics of degraded forests, the impact of meteorological conditions on degraded forests is quantified, the changes in degraded forest characteristics under different meteorological conditions are analyzed, and the potential relationship between changes in meteorological conditions and the aggravation of degraded forests is identified.

[0028] A further improvement of the technical solution of the present invention is that the calculation formula of the ecological assessment index is:

[0029] ;

[0030] in, is the ecological assessment index, It is The vegetation coverage of the area, It is the baseline vegetation cover, representing the minimum cover of a normal or healthy forest. is the maximum observed vegetation cover, It is The change in tree density in the region, It is The greenness index of the region, It is the minimum value of the greenness index, representing the minimum limit of vegetation growth. It is The number of species in an area, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst ecological condition and 1 represents the best ecological condition;

[0031] The calculation formula of the soil evaluation index is:

[0032] ;

[0033] in, is the soil assessment index, It is The soil texture index for each area is calculated based on the soil particle size distribution. It is The soil nutrient content of each area, such as total nitrogen, phosphorus, and potassium content, and are the minimum and maximum values ​​of soil nutrient content, used for standardization, It is Soil pH value of the area, It is The degree of soil erosion in the region is the maximum value of soil erosion degree, used for normalization, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst soil condition and 1 represents the best soil condition;

[0034] The calculation formula of the meteorological assessment index is: ;

[0035] ;

[0036] in, is the meteorological assessment index, It is The amount of precipitation in the region, and are the minimum and maximum values ​​of precipitation, used for normalization, It is The temperature of the area, It is the best temperature for plant growth. is the suitable temperature range, It is The humidity of the area, is the maximum suitable humidity. is the light intensity adjustment function, It is The light intensity of the area, and are the minimum and maximum values ​​of light intensity, used for normalization, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst weather conditions and 1 represents the best weather conditions.

[0037] A further improvement of the technical solution of the present invention is that in the evaluation and prediction module, the process of comprehensively evaluating the current state of the degraded forest is as follows:

[0038] Select features related to degraded forests from ecological, soil and meteorological data, mark samples with known degradation status, obtain a degraded forest sample dataset, and divide the degraded forest sample dataset into a training set and a test set, with the ratio of training set to test set being 70% training set and 30% test set;

[0039] Using the labeled degraded forest sample data in the training set, select the support vector machine as the classification algorithm, configure the support vector machine to train the degraded forest classification model, and use the test set data to test the trained degraded forest classification model to achieve the optimal performance of the degraded forest classification model;

[0040] Combine the relevant characteristics of degraded forests and the classification model of degraded forests, and calculate the degraded forest assessment coefficient by integrating the ecological assessment index, soil assessment index and meteorological assessment index to assess the specific degree of degradation of degraded forests;

[0041] Based on the historical data of the forest, grassland and wetland database and the relevant characteristics of degraded forests, the degradation degree of degraded forests is divided into different degradation levels, namely healthy level, mild degradation level, moderate degradation level and severe degradation level, and the corresponding assessment threshold is matched for each degradation level in combination with the degraded forest assessment coefficient;

[0042] The degraded forest classification model is deployed in the actual production environment, and the current status of the degraded forest is comprehensively evaluated in combination with the degraded forest assessment coefficient. The specific degradation level of each degraded forest is determined based on the value of the degraded forest assessment coefficient.

[0043] A further improvement of the technical solution of the present invention is that the calculation formula of the degraded forest assessment coefficient is:

[0044] ;

[0045] in, is the degraded forest assessment coefficient, It is an ecological assessment index that reflects the comprehensive state of ecological conditions. is the average value of the ecological assessment index, It is a soil assessment index that reflects the comprehensive status of soil conditions. and are the minimum and maximum values ​​of the soil evaluation index, used for normalization, It is a meteorological assessment index that reflects the comprehensive state of meteorological conditions. , , , is a coefficient used to adjust the weight and impact of each indicator. The value range is from 0 to 1, where 0 represents the most degraded state and 1 represents the healthiest state.

[0046] A further improvement of the technical solution of the present invention is that: the multiple degradation levels correspond to multiple evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold;

[0047] The multiple degradation levels and the multiple evaluation thresholds satisfy the following relationship:

[0048] Health level ; The forest is in good condition with no obvious signs of degradation;

[0049] Mild degradation level ; The forest shows slight signs of degradation, but the overall condition is still controllable;

[0050] Moderate degradation level ; Forest degradation is quite obvious and measures need to be taken to restore it;

[0051] Severe degradation level ; Forest degradation is serious and restoration is difficult, requiring urgent intervention;

[0052] in, is the degraded forest assessment coefficient, is the lower threshold corresponding to the health level and the upper threshold corresponding to the mild degradation level, is the lower threshold corresponding to the mild degradation level and the upper threshold corresponding to the moderate degradation level, is the lower threshold corresponding to the moderate degradation level and the upper threshold corresponding to the severe degradation level, , , .

[0053] A further improvement of the technical solution of the present invention is that in the management strategy generation module, the process of generating targeted degraded forest management strategies and suggestions is as follows:

[0054] Conduct in-depth analysis of degraded forest assessment coefficients and degradation levels to understand the causes and extent of degradation, divide forest areas according to degradation levels, and identify areas that require priority treatment;

[0055] Set restoration and management targets for each degradation level, and develop corresponding management strategies for areas of different degradation levels based on the assessment results. For healthy levels, maintain the current status and prevent degradation. For mildly degraded levels, implement mild intervention measures, such as fertilization and moderate thinning. For moderately degraded levels, take more active restoration measures, such as reforestation and pest and disease control. For severely degraded levels, take emergency interventions, such as completely eliminating pests and diseases and implementing large-scale vegetation restoration plans.

[0056] Provide appropriate management recommendations for each area, including technical, economic and time feasibility analysis, and prioritize management recommendations based on the severity of degradation and resource availability;

[0057] Use diagrams to present degradation levels, management strategies, and expected outcomes, mark areas of different degradation levels on maps, along with corresponding management strategies, and prepare detailed management strategy reports, including background, methods, results, and recommendations.

[0058] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0059] 1. The present invention provides a degraded forest analysis and assessment system based on intelligent identification of forest, grassland and wetland database. By integrating multi-source data including ecology, soil and meteorology, the degraded forest can be identified. Compared with the traditional manual monitoring method, it can automatically and in real time process a large amount of data, quickly locate and identify degraded forest areas, and significantly improve the accuracy and efficiency of monitoring. It not only reduces the workload of forestry workers, but also further ensures the timeliness and accuracy of monitoring results, laying a solid foundation for subsequent evaluation and management work.

[0060] 2. The present invention provides a degraded forest analysis and assessment system based on intelligent identification of forest, grassland and wetland database. By constructing multi-dimensional assessment indexes of ecology, soil and meteorology and calculating the degraded forest assessment coefficient, the current status of the degraded forest is comprehensively assessed. Not only the characteristics of the degraded forest itself are considered, but also the influence of external environmental factors is taken into account, making the assessment results more objective. Based on the assessment results, targeted restoration strategies and suggestions can be provided to forestry managers, thereby promoting the ecological restoration of degraded forests. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0062] Figure 1 It is a module structure diagram of the present invention;

[0063] Figure 2 A flowchart for extracting relevant features of ecological survey data, soil survey data, meteorological data and degraded forest features of the present invention;

[0064] Figure 3 It is a flow chart of the analysis of the impact of various features of the present invention on degraded forests;

[0065] Figure 4 This is a flow chart of the comprehensive assessment of the current status of degraded forests in the present invention. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Embodiment 1, as Figure 1-Figure 3As shown, the present invention provides a degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database, including a degraded forest assessment management platform, the degraded forest assessment management platform is communicatively connected with a degraded forest data acquisition module, a feature extraction module, an identification and analysis module, an assessment and prediction module and a management strategy generation module, wherein the modules are connected by electrical signals;

[0068] The degraded forest data acquisition module is used to collect raw data related to degraded forest assessment from the forest, grassland and wetland database, including ecological survey data, soil survey data, and meteorological data, and perform pre-processing operations such as cleaning, denoising, and standardization on the collected raw data to solve data inconsistency and redundancy problems, improve the accuracy and efficiency of data analysis, reduce noise interference in the analysis process, ensure the comprehensiveness and timeliness of the data, and provide a solid foundation for subsequent analysis. It clarifies the data types required for degraded forest assessment and management, including ecological survey data, ground survey data, and meteorological data, covering the spatial distribution, growth status, environmental factors and other aspects of degraded forests, which are the basis for subsequent analysis. It also establishes a data interface with the forest, grassland and wetland database to obtain access to ecological survey data, ground survey data, and meteorological data. It uses API, database query or file transfer to obtain data, accesses the forest, grassland and wetland database, and screens out ecological survey data, ground survey and meteorological raw data related to degraded forest assessment. Among them, the forest coverage, vegetation type, and health status of the associated ecological survey data are obtained through remote sensing images of the MODIS and Landsat series. Information, collect tree growth status, forest biomass, tree species composition, soil conditions, and pest and disease information through ground survey data, which are usually obtained by forestry departments or scientific research institutions through field surveys. Collect meteorological information such as precipitation, temperature, humidity, and light through meteorological data. Perform preprocessing operations such as data cleaning, denoising, and standardization on the collected raw data. Data cleaning removes invalid data, deletes data records with too many missing values, obvious errors, or duplications, converts data from different sources into a unified format, performs spatial filtering on remote sensing images, reduces noise in images, and improves image quality. For time series data, use methods such as sliding average to remove random fluctuations, convert data of different dimensions to the same scale for subsequent analysis, ensure that all geographic spatial data (such as remote sensing images and ground survey points) are accurately aligned in the same coordinate system, and convert non-numerical data (such as soil type, pest and disease level) into numerical data for statistical analysis. Store the preprocessed ecological survey data, ground survey data, and meteorological data in the data warehouse to ensure data security and accessibility, and regularly back up data in the data warehouse to prevent data loss;

[0069] The feature extraction module is used to extract the relevant features and degraded forest features of the ecological survey data, soil survey data, and meteorological data of the fixed area in the medium assessment period from the preprocessed raw data, analyze the correlation between each feature and the degraded forest, integrate the preprocessed ecological survey data, soil survey data, and meteorological data into a unified data set, divide the data set according to the fixed area and assessment period, and analyze the changing trend of the degraded forest features in combination with the historical data of the forest, grassland and wetland database to determine the changing characteristics of the degraded forest, which are tree mortality, forest stand density decline, vegetation cover reduction, and soil degradation signs, so as to facilitate analysis and regional comparison. The ecological survey data is analyzed to determine the ecological characteristics of the degraded forest analysis and evaluation, which are vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species number characteristics, so as to reflect the overall status of the forest ecosystem. Among them, vegetation coverage reflects the breadth and density of forest coverage, and tree density changes measure the number of trees per unit area, reflecting the density of the forest. The greenness index evaluates the health of vegetation by analyzing the reflectivity of red light and near-infrared light, and the species number The soil characteristics of degraded forests are measured by measuring the richness and uniformity of species in the ecosystem. The soil survey data are analyzed to determine the soil characteristics for degraded forest analysis and evaluation, which are soil texture characteristics, soil nutrient content characteristics, soil pH characteristics, and soil erosion degree characteristics, so as to reflect the growth and health of the forest. Among them, soil texture affects the water retention and nutrient exchange capacity, soil nutrient content such as nitrogen, phosphorus, and potassium content affects plant growth, soil pH affects the availability of nutrients in the soil, and soil erosion degree reflects the severity of soil loss and degradation. The meteorological data are analyzed to determine the meteorological influence characteristics for degraded forest analysis and evaluation, which are precipitation characteristics, temperature characteristics, humidity characteristics, and light characteristics, so as to reflect the climatic environment in which the forest is located. Among them, precipitation affects water supply and plant growth, temperature affects the physiological activities and distribution of plants, humidity affects water evaporation and the water demand of plants, and light affects photosynthesis and plant growth. The ecological characteristics, soil characteristics, and meteorological influence characteristics are extracted from the data sets of ecological survey data, soil survey data, and meteorological data, and are associated with degraded forest characteristics to identify characteristics that are highly correlated with degraded forests.

[0070] The identification and analysis module calculates the ecological assessment index, soil assessment index and meteorological assessment index based on the extracted relevant features of the ecological survey data, soil survey data, meteorological data and the degraded forest characteristics, and analyzes the impact of each feature on the degraded forest; calculates the ecological assessment index based on the extracted relevant features of the ecological survey data and the degraded forest characteristics, analyzes the impact trend of ecological conditions on degraded forests, calculates the soil assessment index based on the relevant features of the soil survey data and the degraded forest characteristics, analyzes the impact trend of soil conditions on degraded forests, calculates the meteorological assessment index based on the relevant features of the meteorological data and the degraded forest characteristics, analyzes the impact of meteorological conditions on degraded forests, extracts ecological characteristics such as vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species quantity characteristics from the ecological survey data, obtains an ecological feature data set, constructs an ecological assessment model in combination with a neural network model, and analyzes the relevant data of ecological characteristics to obtain an ecological assessment index, quantifies the impact trend of ecological conditions on degraded forests, analyzes the changes in degraded forest characteristics under different ecological assessment index values, determines the impact trend of ecological conditions on degraded forests, and identifies the deterioration of ecological conditions. The potential relationship between soil deterioration and the aggravation of degraded forests is identified. Soil characteristics such as soil texture, soil nutrient content, soil pH value, and soil erosion degree are extracted from soil survey data to obtain soil characteristic data sets. A soil assessment model is constructed in combination with a neural network model. The relevant data of soil characteristics are analyzed to obtain a soil assessment index. The soil assessment index is correlated with degraded forest characteristics to quantify the impact trend of soil conditions on degraded forests. The changes in degraded forest characteristics under different soil assessment index values ​​are analyzed to identify the potential relationship between soil condition deterioration and the aggravation of degraded forests. Meteorological characteristics such as precipitation, temperature, humidity, and light are extracted from meteorological data to obtain meteorological characteristic data sets. A meteorological assessment model is constructed in combination with a random forest algorithm. The relevant data of meteorological characteristics are analyzed to obtain a meteorological assessment index. The interaction between different meteorological factors and their nonlinear effects on forest ecosystems are analyzed. The meteorological assessment index is correlated with degraded forest characteristics to quantify the impact of meteorological conditions on degraded forests. The changes in degraded forest characteristics under different meteorological conditions are analyzed to identify the potential relationship between changes in meteorological conditions and the aggravation of degraded forests.

[0071] Furthermore, the calculation formula of the ecological assessment index is: ;

[0072] in, is the ecological assessment index, It is The vegetation coverage of the area, It is the baseline vegetation cover, representing the minimum cover of a normal or healthy forest. is the maximum observed vegetation cover, It is The change in tree density in the region, It is The greenness index of the region, It is the minimum value of the greenness index, representing the minimum limit of vegetation growth. It is The number of species in an area, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst ecological condition and 1 represents the best ecological condition. , , and increase, Increase, indicating that the ecological conditions have improved. If any characteristic drops below the baseline value, will decrease, indicating that the ecological situation is deteriorating.

[0073] The vegetation cover was normalized to a range of 0 to 1, where 0 represents a value below the baseline and 1 represents a maximum value;

[0074] The calculation formula of soil assessment index is:

[0075] ;

[0076] in, is the soil assessment index, It is The soil texture index for each area is calculated based on the soil particle size distribution. It is The soil nutrient content of each area, such as total nitrogen, phosphorus, and potassium content, and are the minimum and maximum values ​​of soil nutrient content, used for standardization, It is Soil pH value of the area, It is The degree of soil erosion in the region is the maximum value of soil erosion degree, used for normalization, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst soil condition and 1 represents the best soil condition. The soil texture and nutrient content increase, the pH value approaches neutrality, and the degree of soil erosion decreases. will increase, indicating that soil conditions are improving. If any characteristic drops below the baseline value, will decrease, indicating that the soil condition has deteriorated. Reflects the physical structure of the soil, with high values ​​indicating good soil structure. Normalize soil nutrient content to a range of 0 to 1, where 0 represents below the minimum and 1 represents the maximum. Most plants grow best at a pH close to neutral, so an exponential function is used. Emphasize the importance of a pH value close to neutral, The degree of soil erosion was normalized, where 0 represents the maximum erosion and 1 represents no erosion;

[0077] The calculation formula of the meteorological assessment index is:

[0078] ;

[0079] ;

[0080] in, is the meteorological assessment index, It is The amount of precipitation in the region, and are the minimum and maximum values ​​of precipitation, used for normalization, It is The temperature of the area, It is the best temperature for plant growth. is the suitable temperature range, It is The humidity of the area, is the maximum suitable humidity. is the light intensity adjustment function, It is The light intensity of the area, and are the minimum and maximum values ​​of light intensity, used for normalization, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst meteorological conditions and 1 represents the best meteorological conditions. With the optimization of precipitation, temperature suitability, humidity and light intensity, Increase, indicating that meteorological conditions are more favorable for plant growth. If any characteristic deviates from the optimal range, will decrease, indicating unfavorable weather conditions. It means to normalize the precipitation to the range of 0 to 1, where 0 represents no precipitation and 1 represents maximum precipitation. It indicates the deviation between the calculated temperature and the most suitable temperature. The smaller the deviation, the larger the value. It means that the humidity is adjusted to punish high humidity. When the humidity is too high, the index decreases rapidly. It means using exponential function to emphasize the suitability of light intensity. Too strong or too weak light is not good.

[0081] The assessment and prediction module builds a degraded forest assessment model based on the identified degraded forest characteristics, identifies and classifies degraded forests, distinguishes different degrees of degradation, combines the results of the analysis of the impact of ecological conditions, soil conditions and meteorological conditions on degraded forests, and conducts a comprehensive assessment of the current status of degraded forests, providing forestry managers with timely degraded forest status information and future forecasts to assist in decision-making;

[0082] The management strategy generation module generates targeted degraded forest management strategies and recommendations based on the assessment results, and displays the assessment results intuitively in the form of charts, maps, etc., to facilitate user understanding and use, enhance the readability and dissemination of the assessment results, and help decision makers and the public quickly understand the status of degraded forests.

[0083] Embodiment 2, as Figure 4 As shown, based on Example 1, the present invention provides a technical solution: Preferably, in the evaluation and prediction module, the process of comprehensively evaluating the current state of the degraded forest is:

[0084] Features related to degraded forests were selected from ecological, soil and meteorological data, samples with known degradation status were marked, and a degraded forest sample data set was obtained. The degraded forest sample data set was divided into a training set and a test set, with the ratio of training set to test set being 70% and 30% respectively. The labeled degraded forest sample data in the training set were used, and support vector machine was selected as the classification algorithm. The support vector machine was configured to train the degraded forest classification model, and the trained degraded forest classification model was tested using the test set data to achieve the optimal performance of the degraded forest classification model. The degraded forest-related features and the degraded forest classification model were combined to obtain a comprehensive ecological assessment index. The degraded forest assessment coefficient is calculated based on the forest and grassland wetland database, soil assessment index and meteorological assessment index, and the specific degradation degree of the degraded forest is assessed. Based on the historical data of the forest, grassland and wetland database and the relevant characteristics of the degraded forest, the degradation degree of the degraded forest is divided into different degradation levels, namely healthy level, mild degradation level, moderate degradation level and severe degradation level. The corresponding assessment threshold is matched for each degradation level in combination with the degraded forest assessment coefficient. The degraded forest classification model is deployed in the actual production environment, and the current state of the degraded forest is comprehensively assessed in combination with the degraded forest assessment coefficient. According to the value of the degraded forest assessment coefficient, the specific degradation level of each degraded forest is determined;

[0085] Furthermore, the calculation formula of the degraded forest assessment coefficient is:

[0086] ;

[0087] in, is the degraded forest assessment coefficient, It is an ecological assessment index that reflects the comprehensive state of ecological conditions. is the average value of the ecological assessment index, It is a soil assessment index that reflects the comprehensive status of soil conditions. and are the minimum and maximum values ​​of the soil evaluation index, used for normalization, It is a meteorological assessment index that reflects the comprehensive state of meteorological conditions. , , , is a coefficient used to adjust the weight and impact of each indicator. The value range is from 0 to 1, where 0 represents the most severe degradation state and 1 represents the healthiest state. , , increase, The value of tends to 1, indicating that the degree of degradation decreases. If any index decreases, The value of will decrease, Indicates that the degree of degradation increases, indicating that the Gaussian function (a type of exponential function) is used to process the ecological assessment index, where Controls the steepness of the curve. Controls the overall impact of this part, distance from the average The farther away, the smaller the impact. Indicates that the soil evaluation index is standardized and expressed as to adjust its weight in the overall score, It indicates that the natural logarithm function is used to process the meteorological assessment index, increasing nonlinearity and reducing the impact of extreme values;

[0088] Furthermore, the plurality of degradation levels correspond to a plurality of evaluation thresholds, wherein the evaluation threshold comprises an upper threshold and a lower threshold;

[0089] Multiple degradation levels and multiple evaluation thresholds satisfy the following relationship:

[0090] Health level ; The forest is in good condition with no obvious signs of degradation;

[0091] Mild degradation level ; The forest shows slight signs of degradation, but the overall condition is still controllable;

[0092] Moderate degradation level ; Forest degradation is quite obvious and measures need to be taken to restore it;

[0093] Severe degradation level ; Forest degradation is serious and restoration is difficult, requiring urgent intervention;

[0094] in, is the degraded forest assessment coefficient, is the lower threshold corresponding to the health level and the upper threshold corresponding to the mild degradation level, is the lower threshold corresponding to the mild degradation level and the upper threshold corresponding to the moderate degradation level, is the lower threshold corresponding to the moderate degradation level and the upper threshold corresponding to the severe degradation level, , , ;

[0095] In the management strategy generation module, the process of generating targeted degraded forest management strategies and recommendations is as follows:

[0096] In-depth analysis of the degraded forest assessment coefficient and degradation level, understanding the causes and extent of degradation, and dividing forest areas according to the degradation level, identifying areas that need priority treatment, setting restoration and management goals for each degradation level, and formulating corresponding management strategies for areas with different degradation levels based on the assessment results. For the health level, maintain the current status and prevent degradation. For the mildly degraded level, implement mild intervention measures such as fertilization and moderate thinning. For the moderately degraded level, take more active restoration measures such as reforestation and pest and disease control. For the severely degraded level, emergency intervention is carried out, such as completely eliminating pests and diseases and implementing large-scale vegetation restoration plans. Provide corresponding management recommendations for each area, including technical, economic and time feasibility analysis, and prioritize management recommendations according to the severity of degradation and resource availability. Use charts to display the degradation level, management strategy and expected results. Mark areas of different degradation levels and corresponding management strategies on the map, and prepare a detailed management strategy report, including background, methods, results and recommendations.

[0097] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database, including a degraded forest assessment and management platform, characterized by: The degraded forest assessment and management platform is communicatively connected to a degraded forest data acquisition module, a feature extraction module, an identification and analysis module, an assessment and prediction module, and a management strategy generation module, wherein the modules are connected by electrical signals; The degraded forest data acquisition module is used to collect raw data related to the degraded forest assessment from the forest, grassland and wetland database, and perform preprocessing operations on the collected raw data; The feature extraction module is used to extract the relevant features of the ecological survey data, soil survey data, meteorological data and degraded forest features in the medium assessment period of the fixed area from the pre-processed raw data, and analyze the degree of correlation between each feature and the degraded forest. In the feature extraction module, the relevant features of the ecological survey data, soil survey data, meteorological data and degraded forest features are extracted as follows: The pre-processed ecological survey data, soil survey data, and meteorological data were integrated into a unified data set, which was segmented according to fixed areas and assessment periods. The historical data of the forest, grassland, and wetland database were combined to analyze the changing trends of degraded forest characteristics and determine the changing characteristics of degraded forests, which were tree mortality, decreased stand density, reduced vegetation cover, and signs of soil degradation. The ecological survey data were analyzed to determine the ecological characteristics of degraded forest analysis and evaluation, namely, vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species quantity characteristics, in order to reflect the overall status of the forest ecosystem; Analyze soil survey data to determine soil characteristics for degraded forest analysis and assessment, including soil texture characteristics, soil nutrient content characteristics, soil pH characteristics, and soil erosion degree characteristics, to reflect forest growth and health status; Analyze meteorological data to determine the meteorological impact characteristics for degraded forest analysis and assessment, namely precipitation characteristics, temperature characteristics, humidity characteristics, and light characteristics, to reflect the climate environment in which the forest is located; Extract ecological characteristics, soil characteristics, and meteorological impact characteristics from the data sets of ecological survey data, soil survey data, and meteorological data, and associate them with degraded forest characteristics to identify characteristics that are highly correlated with degraded forests; The identification and analysis module calculates the ecological assessment index, soil assessment index and meteorological assessment index respectively based on the extracted relevant features of the ecological survey data, soil survey data and meteorological data and the degraded forest features, and analyzes the impact of each feature on the degraded forest. In the identification and analysis module, the analysis process of the impact of each feature on the degraded forest is as follows: Extract ecological characteristics such as vegetation coverage characteristics, tree density change characteristics, greenness index characteristics, and species quantity characteristics from ecological survey data, obtain ecological characteristic data sets, build ecological assessment models in combination with neural network models, and analyze relevant data of ecological characteristics to obtain ecological assessment indexes, quantify the impact trend of ecological conditions on degraded forests, analyze the changes in degraded forest characteristics under different ecological assessment index values, determine the impact trend of ecological conditions on degraded forests, and identify the potential relationship between the deterioration of ecological conditions and the aggravation of degraded forests; Extract soil characteristics such as soil texture, soil nutrient content, soil pH, and soil erosion degree from soil survey data, obtain soil characteristic data sets, build soil assessment models in combination with neural network models, and analyze relevant data on soil characteristics to obtain soil assessment indexes. Perform correlation analysis between soil assessment indexes and degraded forest characteristics, quantify the impact trend of soil conditions on degraded forests, analyze changes in degraded forest characteristics under different soil assessment index values, and identify the potential relationship between soil condition deterioration and aggravation of degraded forests. The meteorological characteristics of precipitation, temperature, humidity and light are extracted from the meteorological data, and the meteorological characteristic data set is obtained. The meteorological assessment model is constructed in combination with the random forest algorithm, and the relevant data of meteorological characteristics are analyzed to obtain the meteorological assessment index. The interaction between different meteorological factors and the nonlinear impact on the forest ecosystem are analyzed. The meteorological assessment index is correlated with the characteristics of degraded forests to quantify the impact of meteorological conditions on degraded forests. The changes in the characteristics of degraded forests under different meteorological conditions are analyzed, and the potential relationship between changes in meteorological conditions and the aggravation of degraded forests is identified. The calculation formula of the ecological assessment index is: ； in, is the ecological assessment index, It is The vegetation coverage of the area, is the baseline vegetation coverage, is the maximum observed vegetation cover, It is The change in tree density in the region, It is The greenness index of the region, It is the minimum value of the greenness index, representing the growth of vegetation. At a minimum, It is The number of species in an area, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst ecological condition and 1 represents the best ecological condition; The calculation formula of the soil evaluation index is: ； in, is the soil assessment index, It is Soil texture index of the region, It is The soil nutrient content of the area and are the minimum and maximum values ​​of soil nutrient content, It is Soil pH value of the area, It is The degree of soil erosion in the region is the maximum value of soil erosion. is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst soil condition and 1 represents the best soil condition; The calculation formula of the meteorological assessment index is: ； ； in, is the meteorological assessment index, It is The precipitation in the area, and are the minimum and maximum values ​​of precipitation, It is The temperature of the area, It is the best temperature for plant growth. is the suitable temperature range, It is The humidity of the area, is the maximum suitable humidity. is the light intensity adjustment function, It is The light intensity of the area, and are the minimum and maximum values ​​of light intensity, is the total number of regions evaluated, The value range is from 0 to 1, where 0 represents the worst weather conditions and 1 represents the best weather conditions; The evaluation and prediction module constructs a degraded forest evaluation model based on the identified degraded forest characteristics, identifies and classifies the degraded forest, distinguishes different degrees of degradation, and comprehensively evaluates the current state of the degraded forest. In the evaluation and prediction module, the process of comprehensively evaluating the current state of the degraded forest is as follows: Select features related to degraded forests from ecological, soil and meteorological data, mark samples with known degradation status, obtain a degraded forest sample dataset, and divide the degraded forest sample dataset into a training set and a test set; Using the labeled degraded forest sample data in the training set, select support vector machine as the classification algorithm, configure the support vector machine to train the degraded forest classification model, and use the test set data to test the trained degraded forest classification model; Combine the relevant characteristics of degraded forests and the classification model of degraded forests, and calculate the degraded forest assessment coefficient by integrating the ecological assessment index, soil assessment index and meteorological assessment index to assess the specific degree of degradation of degraded forests; Based on the historical data of the forest, grassland and wetland database and the relevant characteristics of degraded forests, the degradation degree of degraded forests is divided into different degradation levels, namely healthy level, mild degradation level, moderate degradation level and severe degradation level, and the corresponding assessment threshold is matched for each degradation level in combination with the degraded forest assessment coefficient; The degraded forest classification model is deployed in the actual production environment, and the current state of the degraded forest is comprehensively evaluated in combination with the degraded forest assessment coefficient. The specific degradation level of each degraded forest is determined according to the value of the degraded forest assessment coefficient. The calculation formula of the degraded forest assessment coefficient is: ； in, is the degraded forest assessment coefficient, is the ecological assessment index, is the average value of the ecological assessment index, is the soil assessment index, and are the minimum and maximum values ​​of the soil evaluation index, is the meteorological assessment index, , , , is a coefficient used to adjust the weight and impact of each indicator. The value range is from 0 to 1, where 0 represents the most degraded state and 1 represents the healthiest state; The management strategy generation module generates targeted degraded forest management strategies and suggestions based on the evaluation results.

2. The degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database according to claim 1 is characterized by: In the degraded forest data acquisition module, the process of collecting raw data related to degraded forest assessment is as follows: Clarify the types of data required for degraded forest assessment and management, including ecological survey data, ground survey data and meteorological data, and establish a data interface with the forest, grassland and wetland database to obtain access rights to ecological survey data, ground survey data and meteorological data; Access the forest, grassland and wetland database and select ecological survey data, ground survey and meteorological raw data related to degraded forest assessment; Perform pre-processing operations such as data cleaning, denoising and standardization on the collected raw data, and convert non-numerical data into numerical data for statistical analysis; The preprocessed ecological survey data, ground survey data and meteorological data are stored in the data warehouse, and the data in the data warehouse are backed up regularly.

3. The degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database according to claim 1 is characterized by: The plurality of degradation levels correspond to the plurality of evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold; The multiple degradation levels and the multiple evaluation thresholds satisfy the following relationship: Health level ; Mild degradation level ; Moderate degradation level ; Severe degradation level ; in, is the degraded forest assessment coefficient, is the lower threshold corresponding to the health level and the upper threshold corresponding to the mild degradation level, is the lower threshold corresponding to the mild degradation level and the upper threshold corresponding to the moderate degradation level, It is the lower threshold corresponding to the moderate degradation level and the upper threshold corresponding to the severe degradation level.

4. The degraded forest analysis and assessment system based on intelligent identification of forest, grass and wetland database according to claim 3 is characterized by: In the management strategy generation module, the process of generating targeted degraded forest management strategies and suggestions is as follows: Conduct in-depth analysis of degraded forest assessment coefficients and degradation levels to understand the causes and extent of degradation, divide forest areas according to degradation levels, and identify areas that require priority treatment; Set restoration and management targets for each degradation level and, based on the assessment results, develop appropriate management strategies for areas of different degradation levels; Provide appropriate management recommendations for each area, including technical, economic and time feasibility analysis, and prioritize management recommendations based on the severity of degradation and resource availability; Use diagrams to present degradation levels, management strategies, and expected outcomes, mark areas of different degradation levels on maps, along with corresponding management strategies, and prepare detailed management strategy reports, including background, methods, results, and recommendations.

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