Land second ploughing comprehensive evaluation and analysis method, storage medium and system

Abstract

The invention relates to a land second ploughing comprehensive evaluation and analysis method, a storage medium and a system, and relates to the technical field of data processing, and the method comprises the steps: obtaining the soil data of a to-be-evaluated land; constructing a soil quality dynamic evaluation index mathematical model according to the soil data, and calculating a soil quality dynamic evaluation index of the land; establishing a vegetation recovery condition evaluation mathematical model according to the soil data, and calculating a vegetation recovery index of the land; constructing a landform recovery degree quantitative mathematical model according to the soil data, and calculating a landform recovery index of the land; establishing a comprehensive evaluation index calculation model, and performing comprehensive evaluation by fusing the soil quality dynamic evaluation index, the vegetation recovery index and the landform recovery index of the land to obtain a comprehensive evaluation index of the land; and based on the comprehensive evaluation index, performing evaluation result grading on land second ploughing and implementing dynamic early warning. According to the invention, the accuracy of land second ploughing comprehensive evaluation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a comprehensive evaluation and analysis method, system, electronic device, and non-transitory computer-readable storage medium for land reclamation. Background Art

[0002] In the current land reclamation process, the evaluation and analysis mainly rely on traditional methods such as on-site surveys, soil tests, and vegetation restoration monitoring. These methods usually include soil nutrient analysis, geomorphic feature investigation, and vegetation coverage assessment. Researchers gradually establish a land reclamation effect evaluation model through regular sampling and laboratory tests, combined with remote sensing technology.

[0003] However, the traditional methods have a long cycle and high cost, and it is difficult to achieve rapid feedback. Secondly, although remote sensing technology can provide large-scale data, it still has limitations in detail feature recognition and long-time series analysis. Summary of the Invention

[0004] The present invention aims at the technical problems existing in the prior art, and provides a comprehensive evaluation and analysis method, system, electronic device, and non-transitory computer-readable storage medium for land reclamation that can improve the accuracy of land reclamation evaluation.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] The present invention provides a comprehensive evaluation and analysis method for land reclamation, and the method includes:

[0007] Establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database, and obtain soil data of the land to be evaluated;

[0008] Construct a mathematical model for the dynamic evaluation index of soil quality according to the soil data, and calculate the dynamic evaluation index of the soil quality of the land;

[0009] Establish a mathematical model for evaluating the vegetation restoration status according to the soil data, and calculate the vegetation restoration index of the land;

[0010] Construct a mathematical model for quantifying the geomorphic restoration degree according to the soil data, and calculate the geomorphic restoration index of the land;

[0011] Establish a comprehensive evaluation index calculation model, and perform a comprehensive evaluation by integrating the dynamic evaluation index of soil quality, vegetation restoration index, and geomorphic restoration index of the land to obtain the comprehensive evaluation index of the land;

[0012] Based on the comprehensive evaluation index, grade the evaluation results of the land reclamation and implement dynamic early warning.

[0013] Optionally, constructing a mathematical model for the dynamic evaluation index of soil quality based on the soil data and calculating the dynamic evaluation index of soil quality for the land includes:

[0014] Extracting multiple soil indicators from the soil data and determining the soil indicator weights for each soil indicator;

[0015] Performing standardization processing on each soil indicator to obtain the soil parameter values for each soil indicator;

[0016] Obtaining the soil layer thickness and reclamation time of the land;

[0017] Training and constructing a mathematical model for the dynamic evaluation index of soil quality based on the soil indicator weights, soil parameter values of each soil indicator, and the soil layer thickness and reclamation time of the land, and calculating the dynamic evaluation index of soil quality for the land based on the mathematical model for the dynamic evaluation index of soil quality.

[0018] Optionally, the dynamic evaluation index of soil quality is expressed as:

[0019] SDQI = α∑(W i ×P i )×(1 + β×e -γt )×(1 - e -δH );

[0020] where SDQI is the dynamic evaluation index of soil quality, W i is the soil indicator weight of the i-th soil indicator, P i is the soil parameter value of the i-th soil indicator, t is the reclamation time, H is the soil layer thickness, and α, β, γ, and δ are the first adjustment coefficient, the second adjustment coefficient, the third adjustment coefficient, and the fourth adjustment coefficient, respectively.

[0021] Optionally, establishing a mathematical model for evaluating the vegetation restoration status based on the soil data and calculating the vegetation restoration index for the land includes:

[0022] Obtaining the vegetation coverage, community structure index, and species diversity of the land;

[0023] Obtaining the ratio between the current root development degree and the initial root condition of the land;

[0024] Training and establishing a mathematical model for evaluating the vegetation restoration status based on the vegetation coverage, community structure index, and species diversity of the land and the ratio, and calculating the vegetation restoration index for the land based on the mathematical model for evaluating the vegetation restoration status.

[0025] Optionally, the vegetation restoration index is expressed as:

[0026]

[0027] Among them, VRI is the vegetation restoration index, V c is the vegetation coverage, L s is the community structure index, D m is the species diversity, R t is the current root development degree, R0 is the initial root condition, θ is the first weight, and μ is the second weight.

[0028] Optionally, constructing a quantitative mathematical model for landform restoration degree according to the soil data and calculating the landform restoration index of the land includes:

[0029] Obtaining each landform characteristic parameter and the target landform parameter of the land;

[0030] Obtaining the annual rainfall of the reclaimed area of the land;

[0031] Training and constructing a quantitative mathematical model for landform restoration degree according to each landform characteristic parameter, target landform parameter and annual rainfall of the land, and calculating the landform restoration index of the land based on the quantitative mathematical model for landform restoration degree.

[0032] Optionally, establishing a comprehensive evaluation index calculation model, integrating the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land for comprehensive evaluation to obtain the comprehensive evaluation index of the land, includes:

[0033] Obtaining the cumulative input duration of the land reclamation;

[0034] After weighted multiplication of the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land, combining the cumulative input duration, training and establishing a comprehensive evaluation index calculation model, and calculating the comprehensive evaluation index of the land based on the comprehensive evaluation index calculation model.

[0035] Optionally, based on the comprehensive evaluation index, grading the evaluation results of the land reclamation and implementing dynamic early warning, includes:

[0036] Setting an evaluation grade interval for the size of the comprehensive evaluation index;

[0037] Among them, when the comprehensive evaluation index is greater than 0.8, the evaluation grade of the land reclamation is determined to be excellent; when the comprehensive evaluation index is greater than or equal to 0.6 and less than 0.8, the evaluation grade of the land reclamation is determined to be good; when the comprehensive evaluation index is greater than or equal to 0.4 and less than 0.6, the evaluation grade of the land reclamation is determined to be qualified; when the comprehensive evaluation index is less than 0.4, the evaluation grade of the land reclamation is determined to be unqualified;

[0038] When the comprehensive evaluation index drops by more than 20% for three consecutive periods, the first warning level is triggered, and when it drops by more than 40% for three consecutive periods, the second warning level is triggered;

[0039] A multi-level warning response strategy library is established. According to the evaluation level and warning level of the land reclamation, an optimized suggestion plan including soil improvement, vegetation replanting, and soil and water conservation measures is automatically generated.

[0040] In addition, to achieve the above object, the present invention also provides an electronic device, including: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby implementing a comprehensive evaluation analysis method for land reclamation as described above.

[0041] In addition, to achieve the above object, the present invention also provides a non-transitory computer-readable storage medium, in which a computer software program is stored, and when the computer software program is executed by a processor, a comprehensive evaluation analysis method for land reclamation as described above is implemented.

[0042] The beneficial effects of the present invention are as follows:

[0043] (1) By introducing multi-source data such as ground sensors, UAV aerial photography, and satellite remote sensing, the present invention can realize real-time monitoring of soil, vegetation, and landforms, provide high-frequency data updates, and thus improve the efficiency and accuracy of evaluation. Various soil, vegetation, and landform parameters are standardized to eliminate the differences between different data sources, ensuring the comparability and operability of the data, and making the evaluation process more scientific and objective.

[0044] (2) By automatically calculating various indicators through a mathematical model, the present invention requires little manual intervention, reduces labor costs, and improves work efficiency. Traditional land reclamation evaluations often rely on a large number of on-site investigations and sample collections, while this solution can more efficiently utilize existing remote sensing and sensor data through multi-source data fusion, reducing the dependence on physical sample collections, thereby saving manpower, time, and financial resources.

[0045] (3) Through multiple indicators, the present invention comprehensively evaluates the soil quality, vegetation restoration situation, and landform restoration degree, and can conduct a comprehensive analysis of the reclamation effect from different angles, avoiding the deviation of a single indicator and ensuring the scientificity and reliability of the evaluation results. By organically integrating multiple indicators through a comprehensive evaluation index, the synergistic effect between indicators is ensured, and the one-sidedness caused by isolated evaluation is avoided. This systematic evaluation can better reflect the comprehensive impact during the reclamation process.

[0046] In summary, by comprehensively applying multi-source data, dynamic evaluation, and mathematical models, the present invention not only improves the accuracy and efficiency of evaluation, but also reduces labor costs and ensures the systematicness and comprehensiveness of the evaluation process. In addition, the flexibility, adaptability, and environmental protection advantages of the solution make it a powerful tool in land reclamation management, contributing to the sustainable utilization of land resources and the continuous improvement of the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a scenario diagram of a comprehensive evaluation and analysis method for land reclamation provided by the present invention;

[0048] Figure 2 It is a flowchart of a comprehensive evaluation and analysis method for land reclamation provided by the present invention;

[0049] Figure 3 It is a schematic structural diagram of a comprehensive evaluation and analysis system for land reclamation provided by the present invention;

[0050] Figure 4 It is a schematic hardware structure diagram of a possible electronic device provided by the present invention;

[0051] Figure 5 It is a schematic hardware structure diagram of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0053] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0054] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without the use of these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but rather to be in line with the broadest scope consistent with the principles and features disclosed in the present invention.

[0055] Please refer to Figure 1 , Figure 1 which is a scenario diagram of a comprehensive evaluation and analysis method for land reclamation provided by the present invention. As Figure 1 shown, the terminal and the server are connected through a network, for example, through a wired or wireless network connection, etc. Among them, the terminal may include, but is not limited to, portable terminals such as mobile phones and tablets installed with various network platform applications, as well as fixed terminals such as computers, inquiry machines, and advertising machines. Among them, the server provides various business services for users, including service push servers, user recommendation servers, etc.

[0056] It should be noted that Figure 1 the scenario diagram of a comprehensive evaluation and analysis method for land reclamation shown is merely an example. The terminal, server, and application scenarios described in the embodiments of the present invention are for more clearly explaining the technical solutions of the embodiments of the present invention, and do not generate limitations on the technical solutions provided by the embodiments of the present invention. Those of ordinary skill in the art can know that with the evolution of the system and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.

[0057] Among them, the terminal can be used for:

[0058] Establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database to obtain soil data of the land to be evaluated;

[0059] Construct a mathematical model of the dynamic evaluation index of soil quality according to the soil data, and calculate the dynamic evaluation index of the soil quality of the land;

[0060] Establish a mathematical model for evaluating the vegetation restoration status according to the soil data, and calculate the vegetation restoration index of the land;

[0061] Construct a quantitative mathematical model for the degree of landform restoration according to the soil data, and calculate the landform restoration index of the land;

[0062] Establish a comprehensive evaluation index calculation model, and conduct a comprehensive evaluation by integrating the dynamic evaluation index of the soil quality of the land, the vegetation restoration index, and the geomorphic restoration index to obtain the comprehensive evaluation index of the land;

[0063] Based on the comprehensive evaluation index, grade the evaluation results of the land reclamation and implement dynamic early warning.

[0064] Please refer to Figure 2 , which provides a flowchart of a comprehensive evaluation analysis method for land reclamation of the present invention, including the following steps:

[0065] Step S201: Establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database, and obtain the soil data of the land to be evaluated.

[0066] In some embodiments, the soil information of the land to be evaluated can be comprehensively obtained from multiple dimensions. For example, the ground sensor network: real-time monitoring of key indicators such as soil humidity, temperature, and nutrient content. UAV aerial photography: quickly obtain high-resolution surface images and monitor vegetation coverage and geomorphic features. Satellite remote sensing: large-scale monitoring of soil reflectance spectra, vegetation indices, and surface change trends. Historical reclamation database: provide soil evolution data of past reclamation projects to assist in model calibration.

[0067] Step S202: Construct a mathematical model for the dynamic evaluation index of soil quality according to the soil data, and calculate the dynamic evaluation index of the soil quality of the land.

[0068] In some embodiments, step S202 may include:

[0069] Extract multiple soil indicators from the soil data, and determine the soil indicator weights of each soil indicator;

[0070] Perform standardization processing on each soil indicator to obtain the soil parameter values of each soil indicator;

[0071] Obtain the soil layer thickness and reclamation time of the land;

[0072] According to the soil indicator weights, soil parameter values of each soil indicator, as well as the soil layer thickness and reclamation time of the land, train and construct a mathematical model for the dynamic evaluation index of soil quality, and calculate the dynamic evaluation index of the soil quality of the land based on the mathematical model for the dynamic evaluation index of soil quality.

[0073] In some embodiments, the dynamic evaluation index of soil quality is expressed as:

[0074] SDQI = α∑(W i ×P i)×(1 + β×e -γt )×(1 - e -δH );

[0075] Among them, SDQI is the soil quality dynamic evaluation index, and W i is the weight of the i-th soil index, P i is the soil parameter value of the i-th soil index, t is the reclamation time, H is the soil layer thickness, and α, β, γ, and δ are the first adjustment coefficient, the second adjustment coefficient, the third adjustment coefficient, and the fourth adjustment coefficient respectively.

[0076] In specific implementation, SDQI (Soil Quality Dynamic Index) is an important index used to evaluate the dynamic changes in soil quality during the land reclamation process. It synthesizes multiple soil quality parameters and conducts dynamic evaluation in combination with the reclamation time and soil layer thickness. The meanings and functions of the formula and each parameter are explained in detail below.

[0077] W i is the weight of each soil index, which is the weight of each soil index (such as soil water content, pH value, organic matter content, etc.). Different soil indexes have different impacts on soil quality. Therefore, the weight of each index should be determined according to its contribution to the reclamation effect. The weight can be obtained based on experience or through statistical analysis. For example, the soil organic matter content may have a relatively high weight in soil quality, while the soil pH value may have a relatively small impact.

[0078] P i is the standardized soil parameter value, which is the standardized value of each soil index. Standardization is to unify soil parameters with different dimensions and ranges into a comparable range (usually between 0 and 1). The standardized values enable direct comparison and weighting between different indexes. Standardization can be carried out by methods such as the maximum-minimum normalization method and the Z-score normalization method. If the actual value range of a certain soil index is 10 to 100, the value of this index after standardization can be converted into a value between 0 and 1 for subsequent weighting calculations.

[0079] t is the reclamation time, which is the time of land reclamation, usually expressed as the number of years or time period since the start of reclamation. The introduction of the reclamation time takes into account that as the reclamation time progresses, the soil quality will gradually improve. As time goes by, the restoration effect of the soil quality will gradually increase. Therefore, the impact of the reclamation time on SDQI is dynamically changing.

[0080] 1 + β×e -γt is an exponential decay function, which is used to represent that as time goes by, the reclamation effect gradually increases. Specifically, the effect improvement is relatively fast in the initial stage of reclamation, and as time goes by, the improvement effect tends to level off.

[0081] H is the soil layer thickness, that is, the thickness of the soil, usually referring to the depth of the effective soil layer, namely the depth of the soil layer available for plant root growth and nutrient absorption. The soil layer thickness directly affects the water and nutrient storage capacity of the soil. A thicker soil layer usually has better water retention and nutrient retention capabilities, which is beneficial to plant growth. Therefore, the soil layer thickness is one of the important factors of soil quality.

[0082] 1 - e -δH It indicates that the influence of the soil layer thickness on soil quality gradually increases. As the soil layer thickness increases, the SDQI also increases, but the increasing amplitude gradually slows down (similar to the diminishing marginal benefit).

[0083] α, β, γ, and δ are adjustment coefficients in the formula, used to adjust the sensitivity and applicability of the formula. α is a constant, usually used to adjust the scale of the overall calculation result. β and γ control the influence intensity and speed of the reclamation time (t) on the SDQI. δ controls the influence intensity of the soil layer thickness (H) on the SDQI. The adjustment coefficients ensure the flexibility of the formula, which can be adjusted according to the characteristics of different regions or different soil types to achieve the most reasonable evaluation results.

[0084] Soil index weights and standardized values: The weighted summation part ∑(W i ×P i ) reflects the comprehensive contribution of different soil indicators to soil quality. Reclamation time: It is represented by the exponential decay function (1 + β×e -γt ), indicating that the reclamation effect gradually improves over time. Soil layer thickness: It is represented by the exponential function (1 - e -δH ), indicating the influence of the soil layer thickness on soil quality. The thicker the soil layer, the more obvious the improvement of soil quality, but the influence gradually weakens.

[0085] Overall, the SDQI formula takes into account the comprehensive influence of various soil quality indicators, reclamation time, and soil layer thickness on soil quality, and at the same time adjusts the influence of these factors through adjustment coefficients, making this method adaptable to the characteristics of different regions and soil types.

[0086] Step S203: Establish a mathematical model for evaluating the vegetation restoration status based on the soil data, and calculate the vegetation restoration index of the land.

[0087] In some embodiments, step S203 may include:

[0088] Obtain the vegetation coverage, community structure index, and species diversity of the land;

[0089] Obtain the ratio between the current root development degree and the initial root condition of the land;

[0090] Train and establish a mathematical model for evaluating the vegetation restoration status based on the vegetation coverage, community structure index, species diversity of the land, and the ratio, and calculate the vegetation restoration index of the land based on the mathematical model for evaluating the vegetation restoration status.

[0091] In some embodiments, the vegetation restoration index is expressed as:

[0092]

[0093] where VRI is the vegetation restoration index, V c is the vegetation coverage, L s is the community structure index, D m is the species diversity, R t is the current root development degree, R0 is the initial root condition, θ is the first weight, and μ is the second weight.

[0094] In specific implementation, it comprehensively considers vegetation coverage, community structure, species diversity, and root development, and is an important indicator for measuring the vegetation restoration degree during the land reclamation process. The formula is divided into two parts, the comprehensive product (weighted index form) of vegetation coverage, community structure, and species diversity, and the logarithmic growth term of the root development degree (representing the underground ecological restoration). In this way, it not only considers the restoration of above-ground vegetation but also takes into account the growth of underground roots, comprehensively reflecting the overall restoration ability of the vegetation ecosystem.

[0095] V c is the vegetation coverage, that is, the proportion of the land surface covered by vegetation, usually measured by remote sensing images or field surveys, with a range of 0 to 1 (0 represents bare land, and 1 represents complete coverage). Vegetation coverage directly reflects the restoration of above-ground biomass and is an important basic indicator for measuring ecological restoration. The higher the coverage, the faster the vegetation restoration, the lower the risk of soil erosion, and the stronger the ecological stability. For example, after 2 years of reclamation in a certain place, the vegetation coverage increased from 0.2 to 0.6, indicating that the surface vegetation restoration has accelerated.

[0096] L s is the community structure index, representing the vertical layers, species functional groups, and spatial distribution structure of the vegetation community. It can be expressed by the Shannon diversity index or community evenness, reflecting the complexity of the internal structure of the plant community. A more complex and stable community structure often means stronger ecological resilience. The richer the community structure, the more stable the ecosystem and the higher the quality of vegetation restoration. For example, the structure index of a simple herbaceous community may be lower, but if trees, shrubs, and herbs coexist, the structure index will increase significantly.

[0097] D mIt is species diversity, which measures the richness of species in a community and can be expressed by species diversity indices (such as Simpson index, Shannon index). The higher the diversity, the more comprehensive the ecological restoration and the stronger the anti-interference ability. The land restored with a single species is prone to degradation, while a vegetation community with high diversity can better maintain ecological balance. For example, after a certain area is reclaimed for farming, the number of species increases from 3 to 12, the diversity index rises, and the ecological restoration potential is stronger.

[0098] R t It is the current root development degree, indicating the growth status of the current plant roots, such as indicators like root density, root length, root biomass, etc. The root system is the underground support system for vegetation restoration. Well-developed roots can enhance the stability of the soil structure and increase the soil nutrient cycling ability. The more developed the roots, the stronger the soil retention ability and the more stable the ecological restoration. For example, after 3 years of land reclamation for farming, the root biomass doubles, indicating the gradual restoration of the underground ecology.

[0099] R0 is the initial root condition, the root development level before or at the initial stage of reclamation for farming, serving as a comparison benchmark. It is used to measure the relative increment of root development, thereby quantifying the restoration degree. For example, the root density at the initial stage of reclamation for farming is 5 g / m 2 , and it increases to 20 g / m after 3 years 2 , and the root restoration is significant.

[0100] θ is the first weight, which controls the overall contribution of vegetation coverage, community structure, and species diversity to VRI. It adjusts the comprehensive influence of above-ground ecological parameters and can be flexibly set according to different ecological types. For example, in arid regions, more importance may be attached to vegetation coverage, so θ takes a larger value.

[0101] μ is the second weight, which controls the influence degree of the root restoration term. It adjusts the contribution of root restoration to the overall VRI and is applicable to adjusting the weight of the underground ecology in the overall restoration. For example, in mountainous ecosystems, root stability is crucial for preventing soil erosion, so μ may be relatively high.

[0102] The exponential product part (V c ×L s ×D m ) θ reflects the overall restoration level of vegetation coverage, structure, and species diversity. The product relationship ensures that each element restricts each other: when a certain index is low, it will pull down the overall restoration value, ensuring the comprehensiveness of the evaluation.

[0103] The logarithmic term of root restoration introduces a logarithmic function, indicating the marginal diminishing effect of root restoration (fast restoration in the initial stage and slowing down later). It makes the underground restoration process smoothly integrated into the overall evaluation and is closer to the natural restoration law.

[0104] It takes into account both above-ground vegetation and underground root systems, avoiding the one-sidedness of traditional methods that only focus on the surface. As time goes by, dynamic changes such as vegetation coverage and root system development will be fed back to the VRI index in real time, making it suitable for long-term monitoring. By adjusting the weight coefficient, it can adapt to different regions, climates and ecosystem types, and has strong promotion value.

[0105] Real-time calculation of the VRI index helps to quickly understand the state of vegetation recovery and provide a scientific basis for decision-making. For example, if the VRI is low but the root system recovers quickly, it means that the aboveground recovery is lagging behind, and drought-tolerant pioneer plants can be replanted in time.

[0106] In summary, the design of the VRI index of the present invention takes into account four key factors: vegetation coverage, community structure, species diversity and root recovery. It can not only reflect the overall progress of ecological restoration, but also dynamically capture the linkage relationship between underground and aboveground areas, providing a scientific, comprehensive and flexible quantitative tool for the precise management of land reclamation.

[0107] Step S204: construct a quantitative mathematical model of landform restoration degree according to the soil data, and calculate the landform restoration index of the land.

[0108] In some embodiments, step S204 may include:

[0109] Acquire various geomorphic characteristic parameters of the land, as well as target geomorphic parameters;

[0110] Obtain the annual rainfall in the recultivated area of ​​the land;

[0111] According to the various geomorphic characteristic parameters, target geomorphic parameters and annual rainfall of the land, a mathematical model for quantifying the degree of geomorphic restoration is trained and constructed, and a geomorphic restoration index of the land is calculated based on the mathematical model for quantifying the degree of geomorphic restoration.

[0112] In some embodiments, the landform restoration index may be expressed as:

[0113] TRI=∑(λ i ×|G i -G0|)×(1-ρ×e -σY );

[0114] Among them, TRI is the landform restoration index, G i is the i-th geomorphic characteristic parameter, G0 is the target geomorphic parameter, Y is the annual rainfall, λ i , ρ, σ are the first correction coefficient, the second correction coefficient and the third correction coefficient respectively.

[0115] In specific implementation, this index aims to quantify the degree to which the geomorphic features gradually approach the target state during the land reclamation process, while considering the long-term impact of natural factors such as rainfall. There are two core logics: Degree of deviation of geomorphic features: Measure the distance between the current geomorphology and the target geomorphology through the absolute difference of characteristic parameters. Dynamic correction of rainfall: Adjust the geomorphic restoration speed with rainfall to reflect the impact of natural conditions on the restoration process. In this way, both the direct state differences in geomorphic restoration are considered, and the long-term impact of external environmental factors is dynamically integrated, making the assessment closer to the actual ecological evolution process.

[0116] G i is the i-th geomorphic feature parameter, representing a key geomorphic feature value of the current land surface, such as: surface undulation degree, erosion gully density, slope, slope aspect, soil water erosion intensity, vegetation cover height difference. These parameters jointly reflect the degree of restoration of the surface morphology and determine the ecological stability of the land. If a certain feature has a large gap from the target value, it indicates that the geomorphic restoration lags behind and targeted intervention is needed. For example, the target slope is 5°, and the current slope is 15° → the slope restoration is insufficient, and vegetation fixation or artificial slope adjustment may be required.

[0117] G0 is the target geomorphic parameter, the geomorphic feature value in the ideal state, which can be the average value of the ecologically intact area before reclamation or the restoration target value set based on geological and ecological models. As a reference baseline for evaluating the restoration degree, it helps to quantify the current degree of geomorphic deviation. For example, the target gully erosion density is 0.2 km / km 2 , and the actual density is 0.5 km / km 2 , indicating insufficient erosion restoration.

[0118] λ i is the first correction coefficient, which adjusts the contribution of each geomorphic feature to the overall restoration index, equivalent to the weight of the feature. Higher weights are given to key features. For example, in areas prone to soil and water loss, slope and erosion gully density may be more important. For example, in mountainous areas, the slope weight may be set to 0.6, while in plain areas it may be reduced to 0.3.

[0119] Y is the annual rainfall, the total annual precipitation in the reclaimed area, representing the driving force of natural precipitation on geomorphic evolution. Rainfall can both promote vegetation growth and accelerate soil consolidation, and may also cause increased erosion and hinder geomorphic restoration. Therefore, it must be included in the dynamic adjustment. For example, large rainfall → fast vegetation restoration → more stable geomorphology; but excessive rainfall → may lead to the expansion of gully erosion.

[0120] ρ is the second correction coefficient, the rainfall impact intensity coefficient, which controls the magnitude of the positive and negative effects of rainfall on geomorphic restoration. Adjust the sensitivity of rainfall to the restoration process, which can be flexibly adjusted according to the regional ecological characteristics. For example, in arid areas, ρ may be smaller (rainfall promotes restoration); while in easily eroded areas, ρ is larger (rainfall exacerbates damage).

[0121] σ is the third correction coefficient, the rainfall impact attenuation coefficient, which describes the degree of diminishing marginal effect of increasing rainfall on the geomorphic restoration rate. It restricts the non-linear impact of rainfall to avoid abnormal growth of the restoration rate caused by infinite increase in rainfall. For example, the initial rainfall significantly increases the restoration rate, but after reaching a certain threshold, the restoration rate gradually slows down.

[0122] Geomorphic feature deviation term ∑(λ i ×|G i -G0|), which sums up the absolute differences between multiple features and the target value after weighting. The smaller the difference, the higher the degree of restoration; the larger the difference, the more lagged the restoration. The weight λ i ensures that key features have more influence.

[0123] Rainfall correction term (1 - ρ×e -σY ), as the rainfall increases, the restoration potential is gradually released, but the correction effect will decrease. If rainfall brings erosion risks, the correction term may reduce the overall restoration index.

[0124] The present invention incorporates multiple geomorphic elements into a unified index to quantify the overall restoration process. It uses rainfall to adjust the restoration rate and avoids ignoring the complex impacts of natural processes. By adjusting the correction coefficients, it can adapt to various ecological types such as arid areas, mountains, and wetlands.

[0125] Only as an example, for the assessment of the geomorphic restoration of a certain area after 3 years of reclamation, the relevant data are as follows:

[0126] Current slope: 12°, target slope: 5°;

[0127] Current erosion gully density: 0.4 km / km 2 and target density: 0.2 km / km 2 ;

[0128] Annual rainfall: 800 m;

[0129] Set parameters: λ1 = 0.5, λ1 = 0.5, ρ = 0.3, σ = 0.01.

[0130] Substitute into the formula: TRI = 3.6×0.97 ≈ 3.49.

[0131] It shows that the degree of geomorphic restoration is close to 70%, the restoration trend is good, but the slope is still relatively large and continuous intervention is needed.

[0132] In summary, the TRI index of the present invention comprehensively integrates geomorphic features, restoration objectives, and the impact of natural rainfall, and is a powerful tool for evaluating the geomorphic restoration status of reclaimed land. By flexibly adjusting the correction coefficient, it can adapt to the ecological characteristics of different regions and provide a scientific basis for precise restoration. Finally, TRI, together with the Vegetation Restoration Index (VRI) and the Soil Quality Index (SDQI), constitutes a comprehensive evaluation system to help comprehensively grasp the ecological process of reclamation.

[0133] Step S205: Establish a comprehensive evaluation index calculation model, and perform a comprehensive evaluation by integrating the dynamic soil quality evaluation index, vegetation restoration index, and geomorphic restoration index of the land to obtain the comprehensive evaluation index of the land.

[0134] In some embodiments, step S205 may include:

[0135] Obtain the cumulative input duration of the land reclamation;

[0136] After performing weighted multiplication on the dynamic soil quality evaluation index, vegetation restoration index, and geomorphic restoration index of the land, combine the cumulative input duration, train and establish a comprehensive evaluation index calculation model, and calculate the comprehensive evaluation index of the land based on the comprehensive evaluation index calculation model.

[0137] In some embodiments, the comprehensive evaluation index can be expressed as:

[0138] CEI=(SDQI a ×VRI b ×TRI c )×(1 + k×ln(1 + T));

[0139] Where CEI is the comprehensive evaluation index, T is the cumulative input duration, a, b, and c are the third weight, fourth weight, and fifth weight respectively, and k is the time impact factor.

[0140] In specific implementation, this step is the core of the entire reclamation evaluation system, integrating the three core elements of soil quality, vegetation restoration, and geomorphic restoration, and introducing dynamic correction of time input. Finally, a quantitative index for comprehensively measuring the reclamation effect is obtained.

[0141] Main product term: The weighted product of the three indexes of soil quality, vegetation restoration, and geomorphic restoration, representing the comprehensive ecological restoration level of the three. Time correction term: The logarithmic function of the cumulative input duration is used to reflect the promoting effect of long-term input on the restoration effect and simulate the non-linear time effect of ecological restoration. This not only ensures the systematicness of each ecological element in the reclamation process but also dynamically considers the impact of time factors on the restoration speed, making the evaluation result closer to the actual situation.

[0142] The SDQI is the Soil Quality Dynamic Evaluation Index, which measures the degree of restoration of core soil parameters such as soil nutrients, structure, and thickness. It represents the restoration of the soil as an ecological foundation. Fast restoration → significant growth in CEI; slow restoration → dragging down the overall restoration process. For example, if the soil organic matter and water content are restored well and the SDQI is high, it helps to improve the overall evaluation value.

[0143] The VRI is the Vegetation Restoration Index, which comprehensively reflects the above-ground vegetation coverage, community structure, and underground root development. It represents the ecological reconstruction of the surface vegetation. Fast vegetation restoration → accelerating increase in CEI; slow restoration → lack of ecological stability. For example, with an increase in species diversity and perfect root development, the VRI is high, driving up the overall restoration index.

[0144] The TRI is the Geomorphic Restoration Index, which quantifies the degree of proximity between the current geomorphic features and the target geomorphic state, considering the correction of natural factors such as rainfall. It represents the ecological restoration of the land surface morphology. Good geomorphic restoration → steady increase in CEI; lagging restoration → may restrict the long-term restoration potential. For example, with a gentler slope and fewer erosion ditches, the TRI increases, promoting the overall restoration index.

[0145] a, b, and c are the index weight coefficients, which control the influence degree of the three major indices of soil, vegetation, and geomorphology on the comprehensive evaluation result. They are flexibly adjusted according to the regional ecological characteristics, giving greater weight to key elements. Soil-dominated type (such as farmland): a is large, b and c are small. Vegetation-dominated type (such as grassland): b is large, a and c are small. Geomorphology-sensitive type (such as mountainous areas): c is large, a and b are small. For example, in the reclamation of mountainous areas, the geomorphic stability has a great impact → set c = 0.5, a = 0.3, b = 0.2.

[0146] T is the cumulative input duration, which is the cumulative number of years or months of input in the reclamation project, reflecting the long-term intervention effect of human, material, and time. It guides the gradual increase of CEI with time input, simulating the slow accumulation process of ecological restoration. For example, the restoration is slow in the initial stage of reclamation, but long-term input promotes the gradual increase of the restoration index.

[0147] k is the time impact factor, which controls the gain degree of time input on the restoration effect. It adjusts the sensitivity of the time correction term and determines the response intensity of the restoration speed to time. A large k → stronger restoration gain brought by time input. A small k → weaker gain of time input, more dependent on the restoration of the ecological background. For example, in areas with a high intensity of artificial intervention → k takes a larger value to reflect the high return of engineering measures.

[0148] The exponential product term SDQI a ×VRI b ×TRI c , which is the comprehensive restoration effect of the three elements of soil, vegetation, and geomorphology. The product form ensures that each element restricts each other: an extremely low index will significantly drag down the overall restoration value, ensuring the comprehensiveness of the evaluation.

[0149] The time correction term is 1 + k×ln(1 + T), which simulates the non-linear time effect of ecological restoration. The initial restoration is slow → the longer the time, the restoration potential is gradually released, which conforms to the law of natural ecological evolution.

[0150] Only as an example, the relevant data of the comprehensive evaluation of a certain area after 5 years of reclamation are as follows:

[0151] Soil restoration index: SDQI = 0.7;

[0152] Vegetation restoration index: VRI = 0.8;

[0153] Topography restoration index: TRI = 0.6;

[0154] Accumulated input duration: T = 5 years;

[0155] Set weights: a = 0.4, b = 0.3, c = 0.3;

[0156] Time impact factor: k = 0.2;

[0157] Substitute into the formula: CEI = 0.714×1.358≈0.97.

[0158] In summary, the CEI index of the present invention comprehensively integrates the three elements of soil, vegetation, and topography, and dynamically introduces time correction. It is a powerful tool for evaluating the effectiveness of reclamation. The weights can be flexibly adjusted to adapt to the ecological characteristics of different regions, ensuring that the evaluation system is accurately adapted to various ecological environments. The dynamic adjustment of time conforms to the law of natural restoration, avoiding static misjudgment at a single time point, and is more suitable for long-term monitoring and decision-making optimization.

[0159] Step S206, based on the comprehensive evaluation index, grade the evaluation results of the land reclamation and implement dynamic early warning.

[0160] In some embodiments, step S206 may include:

[0161] Set an evaluation grade interval for the size of the comprehensive evaluation index;

[0162] Among them, when the comprehensive evaluation index is greater than 0.8, the evaluation grade of the land reclamation is determined to be excellent; when the comprehensive evaluation index is greater than or equal to 0.6 and less than 0.8, the evaluation grade of the land reclamation is determined to be good; when the comprehensive evaluation index is greater than or equal to 0.4 and less than 0.6, the evaluation grade of the land reclamation is determined to be qualified; when the comprehensive evaluation index is less than 0.4, the evaluation grade of the land reclamation is determined to be unqualified;

[0163] When the comprehensive evaluation index drops by more than 20% for three consecutive periods, the first warning registration is triggered. When it drops by more than 40% for three consecutive periods, the second warning level is triggered.

[0164] Establish a multi-level warning response strategy library. According to the evaluation level and warning level of the land reclamation, an optimized suggestion plan including soil improvement, vegetation replanting, and soil and water conservation measures is automatically generated.

[0165] Specifically, according to the size of the comprehensive evaluation index (CEI), the land reclamation effect is divided into 4 levels:

[0166] Excellent (CEI > 0.8): The overall restoration of soil, vegetation, and landform is good, and the ecosystem is basically stable. It is suitable for promoting experience and serving as a benchmark area.

[0167] Good (0.6 ≤ CEI < 0.8): The reclamation effect is relatively good, but some indicators are still not fully up to standard. Local optimization is required, such as improving vegetation diversity and soil structure.

[0168] Qualified (0.4 ≤ CEI < 0.6): The reclamation basically meets the standard, but the overall ecological restoration is unbalanced. Key interventions are needed, such as strengthening soil and water conservation or increasing investment.

[0169] Unqualified (CEI < 0.4): The reclamation effect is poor, the ecosystem has not been effectively restored, and there is even a risk of degradation. A comprehensive assessment of the failure reasons is required, and a systematic repair plan should be formulated.

[0170] To prevent irreversible degradation risks during the ecological restoration process, the system sets up dynamic warnings:

[0171] First-level warning: CEI drops by more than 20% for three consecutive periods. There may be local ecological degradation, such as soil erosion and vegetation decline. Timely intervention is needed to prevent the problem from expanding.

[0172] Second-level warning: CEI drops by more than 40% for three consecutive periods. It indicates that the ecosystem may have suffered serious interference, such as extreme weather, pests and diseases, or engineering failures. Emergency repair measures need to be initiated to prevent ecological collapse.

[0173] Once the warning is triggered, the system will automatically generate an optimized plan from the strategy library according to the evaluation level and warning level, including:

[0174] Soil improvement measures: Adjust the soil formula (such as applying organic fertilizers and improving saline-alkali land). Enhance the soil water storage capacity and improve the soil structure.

[0175] Vegetation replanting strategy: Select more suitable drought-tolerant and barren-tolerant plants. Adjust the planting density to promote species diversity.

[0176] Soil and water conservation projects: Construct terraced fields and build drainage ditches to prevent soil erosion. Adopt ecological slope protection technology to stabilize the landform structure.

[0177] These measures can quickly repair ecological defects and promote the gradual restoration of the reclaimed area to a stable state. Continuously track the changes in CEI and dynamically adjust the evaluation results. Early warning of potential degradation risks to avoid ecological collapse. Based on historical data and the strategy library, accurately match the restoration plan to reduce the pressure of manual decision-making. Overall, this evaluation and early warning system makes the reclamation management more scientific and efficient, and can greatly improve the success rate of ecological restoration.

[0178] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a comprehensive evaluation and analysis system for land reclamation provided by the present invention.

[0179] As Figure 3 shown, a comprehensive evaluation and analysis system for land reclamation proposed in an embodiment of the present invention includes:

[0180] A data acquisition module 301, configured to establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database, and acquire soil data of the land to be evaluated;

[0181] A first calculation module 302, configured to construct a mathematical model for dynamically evaluating the soil quality index according to the soil data, and calculate the dynamically evaluated soil quality index of the land;

[0182] A second calculation module 303, configured to establish a mathematical model for evaluating the vegetation restoration status according to the soil data, and calculate the vegetation restoration index of the land;

[0183] A third calculation module 304, configured to construct a mathematical model for quantifying the degree of landform restoration according to the soil data, and calculate the landform restoration index of the land;

[0184] A comprehensive evaluation module 305, configured to establish a comprehensive evaluation index calculation model, and perform a comprehensive evaluation by integrating the dynamically evaluated soil quality index, vegetation restoration index, and landform restoration index of the land to obtain the comprehensive evaluation index of the land;

[0185] An evaluation optimization module 306, configured to classify the evaluation results of the land reclamation and implement dynamic early warning based on the comprehensive evaluation index.

[0186] Please refer to Figure 4 , Figure 4 which is a schematic diagram of an embodiment of an electronic device provided in an embodiment of the present invention. As Figure 4As shown in the figure, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored on the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0187] Establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database, and obtain soil data of the land to be evaluated;

[0188] Construct a mathematical model for the dynamic evaluation index of soil quality based on the soil data, and calculate the dynamic evaluation index of the soil quality of the land;

[0189] Establish a mathematical model for evaluating the vegetation restoration status based on the soil data, and calculate the vegetation restoration index of the land;

[0190] Construct a quantitative mathematical model for the degree of landform restoration based on the soil data, and calculate the landform restoration index of the land;

[0191] Establish a comprehensive evaluation index calculation model, integrate the dynamic evaluation index of soil quality, vegetation restoration index, and landform restoration index of the land for comprehensive evaluation, and obtain the comprehensive evaluation index of the land;

[0192] Based on the comprehensive evaluation index, grade the evaluation results of the land reclamation and implement dynamic early warning.

[0193] Please refer to Figure 5 , Figure 5 which is a schematic diagram of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. As Figure 5 shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0194] Establish a multi-source data acquisition system including a ground sensor network, UAV aerial photography, satellite remote sensing, and a historical database, and obtain soil data of the land to be evaluated;

[0195] Construct a mathematical model for the dynamic evaluation index of soil quality based on the soil data, and calculate the dynamic evaluation index of the soil quality of the land;

[0196] Establish a mathematical model for evaluating the vegetation restoration status based on the soil data, and calculate the vegetation restoration index of the land;

[0197] Construct a quantitative mathematical model for the degree of landform restoration based on the soil data, and calculate the landform restoration index of the land;

[0198] Establish a comprehensive evaluation index calculation model, and conduct a comprehensive evaluation by integrating the dynamic evaluation index of the soil quality, the vegetation restoration index, and the geomorphic restoration index of the land to obtain the comprehensive evaluation index of the land;

[0199] Based on the comprehensive evaluation index, grade the evaluation results of the land reclamation and implement dynamic early warning.

[0200] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0201] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0202] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a system for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0203] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction system, and the instruction system implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0204] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the functions specified in one process Figure 1steps of one process or multiple processes and / or blocks Figure 1 steps of functions specified in one block or multiple blocks.

[0205] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0206] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A comprehensive evaluation and analysis method for land reclamation, characterized in that: The method comprises: Establish a multi-source data collection system including ground sensor networks, drone aerial photography, satellite remote sensing and historical databases to obtain soil data of the land to be evaluated; Constructing a soil quality dynamic evaluation index mathematical model based on the soil data to calculate the soil quality dynamic evaluation index of the land; Establishing a vegetation restoration status assessment mathematical model based on the soil data, and calculating the vegetation restoration index of the land; Constructing a quantitative mathematical model of landform restoration degree based on the soil data, and calculating the landform restoration index of the land; Establishing a comprehensive evaluation index calculation model, integrating the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land for comprehensive evaluation, and obtaining a comprehensive evaluation index of the land; Based on the comprehensive evaluation index, the evaluation results of the land reclamation are graded and dynamic early warning is implemented.

2. The comprehensive evaluation and analysis method for land reclamation according to claim 1 is characterized in that: The step of constructing a soil quality dynamic evaluation index mathematical model according to the soil data and calculating the soil quality dynamic evaluation index of the land comprises: Extracting a plurality of soil indicators from the soil data, and determining a soil indicator weight of each of the soil indicators; Performing standardization processing on each of the soil indicators to obtain a soil parameter value of each of the soil indicators; Obtaining the soil thickness and recultivation time of the land; According to the soil indicator weight, soil parameter value of each soil indicator, as well as the soil layer thickness and recultivation time of the land, a soil quality dynamic evaluation index mathematical model is trained and constructed, and the soil quality dynamic evaluation index of the land is calculated based on the soil quality dynamic evaluation index mathematical model.

3. The comprehensive evaluation and analysis method for land reclamation according to claim 2 is characterized in that: The soil quality dynamic evaluation index is expressed as: SDQI=α∑(W i ×P i )×(1+β×e -γt )×(1-e -δH ); Among them, SDQI is the soil quality dynamic evaluation index, W i is the soil index weight of the ith soil index, P i is the soil parameter value of the i-th soil index, t is the recultivation time, H is the soil thickness, α, β, γ, δ are the first adjustment coefficient, the second adjustment coefficient, the third adjustment coefficient, and the fourth adjustment coefficient, respectively.

4. The comprehensive evaluation and analysis method for land reclamation according to claim 3 is characterized in that: The step of establishing a vegetation restoration status assessment mathematical model based on the soil data and calculating the vegetation restoration index of the land includes: Obtaining vegetation coverage, community structure index and species diversity of the land; Obtaining a ratio between the current root system development degree and the initial root system condition of the land; According to the vegetation coverage, community structure index and species diversity of the land and the ratio, a mathematical model for evaluating the status of vegetation restoration is trained and established, and the vegetation restoration index of the land is calculated based on the mathematical model for evaluating the status of vegetation restoration.

5. The comprehensive evaluation and analysis method for land reclamation according to claim 4 is characterized in that: The vegetation restoration index is expressed as: Among them, VRI is the vegetation restoration index, V c is the vegetation coverage, L s is the community structure index, D m is species diversity, R t is the current root development degree, R0 is the initial root condition, θ is the first weight, and μ is the second weight.

6. The comprehensive evaluation and analysis method for land reclamation according to claim 5 is characterized in that: The step of constructing a mathematical model for quantifying the degree of landform restoration according to the soil data and calculating the landform restoration index of the land comprises: Acquire various geomorphic characteristic parameters of the land, as well as target geomorphic parameters; Obtain the annual rainfall in the recultivated area of ​​the land; According to the various geomorphic characteristic parameters, target geomorphic parameters and annual rainfall of the land, a mathematical model for quantifying the degree of geomorphic restoration is trained and constructed, and a geomorphic restoration index of the land is calculated based on the mathematical model for quantifying the degree of geomorphic restoration.

7. The comprehensive evaluation and analysis method for land reclamation according to claim 6 is characterized in that: The comprehensive evaluation index calculation model is established to integrate the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land for comprehensive evaluation to obtain the comprehensive evaluation index of the land, including: Obtain the cumulative time invested in reclaiming the land; After weighted multiplication of the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land, combined with the accumulated investment time, a comprehensive evaluation index calculation model is trained and established, and the comprehensive evaluation index of the land is calculated based on the comprehensive evaluation index calculation model.

8. The comprehensive evaluation and analysis method for land reclamation according to claim 7 is characterized in that: Based on the comprehensive evaluation index, the land reclamation evaluation results are graded and dynamic early warning is implemented, including: Setting an evaluation level interval for the size of the comprehensive evaluation index; Among them, when the comprehensive evaluation index is greater than 0.8, the evaluation level of the land reclamation is determined to be excellent; when the comprehensive evaluation index is greater than or equal to 0.6 and less than 0.8, the evaluation level of the land reclamation is determined to be good; when the comprehensive evaluation index is greater than or equal to 0.4 and less than 0.6, the evaluation level of the land reclamation is determined to be qualified; when the comprehensive evaluation index is less than 0.4, the evaluation level of the land reclamation is determined to be unqualified; When the comprehensive evaluation index drops by more than 20% for three consecutive periods, the first warning registration is triggered, and when it drops by more than 40% for three consecutive periods, the second warning level is triggered; A multi-level early warning response strategy library is established to automatically generate optimization proposals including soil improvement, vegetation replanting, and soil and water conservation measures based on the evaluation level and early warning level of the land reclamation.

9. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores a computer software program, which, when executed by a processor, implements the land reclamation comprehensive evaluation and analysis method as described in any one of claims 1 to 8.

10. A land reclamation comprehensive evaluation and analysis system, characterized in that: The system comprises: The data acquisition module is used to establish a multi-source data acquisition system including ground sensor networks, drone aerial photography, satellite remote sensing and historical databases to obtain soil data of the land to be evaluated; A first calculation module is used to construct a soil quality dynamic evaluation index mathematical model according to the soil data, and calculate the soil quality dynamic evaluation index of the land; A second calculation module is used to establish a vegetation restoration status assessment mathematical model based on the soil data and calculate the vegetation restoration index of the land; A third calculation module is used to construct a quantitative mathematical model of landform restoration degree according to the soil data and calculate the landform restoration index of the land; A comprehensive evaluation module is used to establish a comprehensive evaluation index calculation model, integrate the soil quality dynamic evaluation index, vegetation restoration index and landform restoration index of the land for comprehensive evaluation, and obtain the comprehensive evaluation index of the land; An evaluation and optimization module is used to classify the evaluation results of the land reclamation based on the comprehensive evaluation index and implement dynamic early warning.

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