Index dynamic accounting system for farmland and forest land replacement

Abstract

The application relates to the technical field of resource accounting, and discloses an index dynamic accounting system for replacement of cultivated land resources and forest land resources. The system comprises a resource data acquisition unit, which acquires spatial distribution data of cultivated land resources, type and coverage range data of forest land resources, replacement constraint condition data, and performs space-time alignment to generate a resource multidimensional data set; a replacement index accounting unit, which performs resource adaptability reconstruction processing based on the resource multidimensional data set, separates target resource data and abnormal resource data; a replacement scheme generation unit, which generates an accounting result containing replacement area, weight and priority in combination with a preset replaceable rate and a developable rate; and a dynamic correction unit, which identifies an abnormal type based on the abnormal resource data and corrects the accounting result in real time. The system can comprehensively capture resource dynamics, improve the accuracy and timeliness of replacement accounting, and adapt to complex resource management requirements.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource accounting, in particular to an index dynamic accounting system for replacement of cultivated land resources and forest land resources. BACKGROUND

[0002] Under the dual demands of land resource management and ecological protection, the balance between cultivated land protection and forest land utilization has become a practical problem to be solved. With the acceleration of urbanization and the adjustment of agricultural production scale, the quantity and quality of cultivated land resources are under double pressure, while the protection and rational development of forest land as an important ecological resource are also related to the stability of the ecological system. In order to realize the efficient allocation of land resources, the replacement of cultivated land resources and forest land resources has become an important adjustment means. Through scientific replacement, the total amount of cultivated land can be guaranteed while the ecological function of forest land is taken into account.

[0003] The existing resource replacement accounting method has many shortcomings. Data collection is often limited to a single dimension or static information, lacking comprehensive capture of the dynamic changes of the spatial distribution of cultivated land resources and forest land resources, resulting in insufficient timeliness and accuracy of the data. In the accounting process, the consideration of replacement constraints is not sufficient, and key constraints such as ecological protection red lines and land use planning are not effectively integrated into the accounting system, making the generated replacement scheme less feasible. In addition, the traditional accounting method lacks a dynamic correction mechanism. When resource data is updated or abnormal, the accounting results cannot be adjusted in a timely manner, making it difficult to adapt to complex and changing resource management needs, and thus affecting the scientificity and rationality of resource replacement. SUMMARY

[0004] The purpose of the present application is to provide an index dynamic accounting system for replacement of cultivated land resources and forest land resources to solve the problems raised in the background art.

[0005] To achieve the above purpose, the present application provides an index dynamic accounting system for replacement of cultivated land resources and forest land resources, which comprises:

[0006] A resource data acquisition unit acquires spatial distribution data of cultivated land resources, type and coverage range data of forest land resources, and replacement constraint condition data, and performs spatio-temporal alignment on the spatial distribution data, type and coverage range data, and replacement constraint condition data to generate a resource multidimensional data set;

[0007] A replacement index accounting unit performs resource adaptability reconstruction processing based on the resource multidimensional data set, separates out target resource data for replacement accounting and abnormal resource data for dynamic correction accounting;

[0008] The replacement scheme generation unit generates a replacement index accounting result based on the target resource data, in combination with a preset arable land resource replaceable rate and a forest land resource developable rate. The replacement index accounting result includes an arable land resource replacement area, a forest land resource replacement weight, and a replacement priority.

[0009] The arable land resource replacement area is not a single area, but a set of areas after multi-factor area conversion.

[0010] The dynamic correction unit identifies an abnormal type in resource data updating based on the abnormal resource data, and corrects the replacement index accounting result in real time according to the abnormal type.

[0011] Preferably, the replacement scheme generation unit performs the following operations:

[0012] Integrating the arable land resource level in the target resource data, the forest land resource ecological value coefficient, and the geographic overlay area data in the replacement constraint condition;

[0013] According to the integrated data and the preset replacement rule, the matching relationship between the arable land resource replacement area and the forest land resource replacement weight is calculated, and the replacement index accounting result is output.

[0014] Preferably, the dynamic correction unit performs the following operations:

[0015] Monitoring the abnormal resource data, and positioning the arable land resource change block or the forest land resource ownership change data causing the abnormality;

[0016] Based on the monitoring result, the affected replacement priority and replacement area are re-evaluated, and the arable land resource replacement area and the replacement priority in the replacement index accounting result are corrected.

[0017] Preferably, the dynamic correction unit further performs the following operations:

[0018] Correlation analysis of the arable land resource change reasons and the forest land resource development restriction conditions corresponding to multiple abnormal resource data in the same administrative region to determine whether a cross-regional replacement adjustment is triggered;

[0019] If the cross-regional replacement adjustment is triggered, a multi-region replacement coordination strategy is executed to allocate standby arable land resource blocks and update the replacement priority.

[0020] Preferably, the resource adaptation reconstruction processing performed by the replacement index accounting unit includes:

[0021] Converting the spatio-temporal aligned resource multidimensional data set into a resource adaptation matrix;

[0022] Decomposing the resource adaptation matrix to obtain a resource core matrix and a resource abnormal matrix;

[0023] The resource core matrix comprises spatial matching characteristics of cultivated land resources and forest land resources, and the resource anomaly matrix identifies abnormal items of land ownership conflicts or ecological protection red line overlaps.

[0024] Preferably, when the resource data acquisition unit generates the resource multidimensional data set, the cultivated land resource parcel coordinates, the forest land resource boundary coordinates, and the administrative region boundary in the replacement constraint condition are spatially overlaid to generate a resource space mapping matrix.

[0025] The replacement index accounting unit further performs:

[0026] Based on the resource anomaly matrix, abnormal items are extracted and associated with the resource space mapping matrix, the spatial characteristics of the abnormal items are clustered, and a first type of abnormal sub-matrix and a second type of abnormal sub-matrix are generated.

[0027] The first type of abnormal sub-matrix represents abnormalities caused by changes in cultivated land resource ownership, and the second type of abnormal sub-matrix represents abnormalities caused by ecological restrictions on forest land resources.

[0028] Preferably, the replacement index accounting unit clustering the spatial characteristics of the abnormal items includes:

[0029] A multi-dimensional feature vector is added to each abnormal record, including parcel change time, administrative region code, and ecological protection area overlap area.

[0030] Based on the development intensity threshold in the replacement constraint condition, the multi-dimensional feature vector is configured with a weight;

[0031] The multi-dimensional feature vectors are grouped according to spatial proximity to generate the first type of abnormal sub-matrix and the second type of abnormal sub-matrix.

[0032] Preferably, the replacement index accounting unit performing resource adaptability reconstruction processing further includes:

[0033] A resource replacement coupling matrix is constructed to represent the supply and demand of cultivated land resources and forest land resources across administrative regions, as well as the associated matching relationship between the two;

[0034] When the resource adaptation matrix is decomposed, the resource replacement coupling matrix is introduced as a collaborative constraint term, and iterative solution is combined with the resource anomaly matrix to identify parallel abnormalities of cross-regional resource supply imbalance or ecological protection conflicts;

[0035] When the supply and demand correlation degree of any two regions in the resource replacement coupling matrix exceeds a preset threshold, and the value of the corresponding abnormal item in the resource anomaly matrix is out of limit, a multi-region replacement collaborative strategy is triggered.

[0036] Preferably, the dynamic correction unit calls the minimum ecological protection ratio in the replacement constraint condition when correcting the replacement index accounting result, and performs compliance calibration on the corrected forest land resource replacement weight.

[0037] Preferably, the dynamic correction unit further performs:

[0038] Based on the calibrated forest land resource replacement weight, the qualified rate of the cultivated land resource replacement area is recalculated;

[0039] When the qualified rate is lower than the preset threshold, the replacement scheme generation unit is triggered to regenerate the replacement index accounting result.

[0040] Compared with the prior art, the beneficial effects of the present application are:

[0041] Through the spatio-temporal alignment of multiple types of data by the resource data acquisition unit, a resource multidimensional dataset is generated, which can comprehensively and accurately reflect the actual conditions and dynamic changes of the two types of resources. This multidimensional data integration method breaks through the limitations of traditional data collection and provides a more reliable basis for subsequent replacement accounting.

[0042] The resource adaptability reconstruction processing performed by the replacement index accounting unit can effectively separate the target resource data and the abnormal resource data, so that the accounting process focuses more on the core resources that meet the replacement conditions, and the interference of irrelevant data is reduced. The replacement index accounting result generated in combination with the preset replaceable rate and the developable rate covers key information such as replacement area, weight and priority, providing clear guidance for the formulation of resource replacement schemes, which helps to improve the pertinence and operability of the schemes.

[0043] The dynamic correction unit identifies the abnormal type based on the abnormal resource data and corrects the accounting result in real time, so that the entire accounting system has the ability to respond to data updates and sudden situations. This dynamic adjustment mechanism can ensure that the accounting result always remains consistent with the actual conditions of the resources, avoiding decision-making bias caused by data lag or abnormalities. At the same time, the system naturally incorporates the replacement constraint conditions in the accounting process, so that the generated replacement scheme can better meet the requirements of ecological protection and land use planning, achieving efficient allocation of resources while maintaining the stability of the ecological system.

[0044] The units of the system work cooperatively to form a complete closed loop from data collection, accounting processing to dynamic correction, improving the automation and intelligence level of resource replacement accounting. By reducing human intervention, the possibility of human error is reduced, and the accounting efficiency is improved, which can quickly respond to the actual needs of resource management and provide timely and effective support for the decision-making of relevant departments. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 Time sequence diagram for the index dynamic accounting system of the cultivated land resource and forest land resource replacement described in the present application;

[0046] Figure 2 Flowchart for the matching accounting of the replacement scheme generation unit;

[0047] Figure 3 Flowchart for the cross-regional replacement collaborative strategy triggering;

[0048] Figure 4 Flowchart for the abnormal entry space feature clustering;

[0049] Figure 5 Flowchart for the abnormal entry multi-dimensional feature clustering. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0051] Please refer to Figure 1 The present application provides an index dynamic accounting system for cultivated land resource and forest land resource replacement, which comprises:

[0052] The resource data acquisition unit obtains the spatial distribution data of cultivated land resources, the type and coverage range data of forest land resources, and the replacement constraint condition data. These data are processed by spatio-temporal alignment to generate a resource multi-dimensional data set containing spatial coordinates, resource attributes, and constraint conditions. The replacement index accounting unit performs resource adaptability reconstruction processing on the resource multi-dimensional data set to separate target resource data and abnormal resource data. The target resource data is used for replacement accounting, and the abnormal resource data is used for dynamic correction. The replacement scheme generation unit outputs an accounting result containing replacement area, weight, and priority based on the target resource data, combined with the preset cultivated land resource replaceable rate and forest land resource developable rate. The dynamic correction unit monitors the abnormal resource data, identifies the abnormal type, and corrects the accounting result in real time to ensure the timeliness and accuracy of the replacement scheme.

[0053] Embodiment 1: Please refer to Figure 2The core function of the replacement scheme generation unit is to integrate the cultivated land resource level, forest land resource ecological value coefficient in the target resource data, and the geographic overlay area data in the replacement constraint condition, and generate the final replacement index accounting result based on the preset replacement rule. The division of cultivated land resource level includes soil quality, terrain slope, irrigation condition, and surrounding infrastructure supporting condition. Soil quality is obtained by sampling detection to obtain organic matter content, acid-base value, heavy metal pollution degree, and cultivated land concentration. Terrain slope is calculated based on digital elevation model. Irrigation condition is comprehensively evaluated by combining water conservancy facility distribution and water source guarantee capacity. After normalization processing, these indexes are divided into high, medium, and low levels by using weighted scoring method. Different levels correspond to different replacement priorities and area conversion coefficients.

[0054] The calculation of forest land resource ecological value coefficient involves vegetation type, biodiversity, carbon sink function, and ecological sensitivity. Vegetation type is determined by remote sensing image interpretation combined with field investigation, including tree forest, shrub forest, mixed forest, and other categories. Different vegetation types have different contributions to ecological function. Biodiversity assessment is based on species richness, rare and endangered species distribution, and habitat integrity. Carbon sink function is estimated according to vegetation biomass and soil carbon storage. Ecological sensitivity analysis considers soil and water loss risk and geological disaster susceptibility. After comprehensive analysis of these data, multi-index comprehensive evaluation method is used to calculate the ecological value coefficient of each forest land plot. Higher coefficient indicates greater ecological protection value of the forest land, and stricter replacement restriction condition.

[0055] Geographic overlay area data is generated by spatial overlay analysis. The specific process is to overlay the vector boundary of cultivated land resource plot with the vector boundary of forest land resource, and calculate the spatial proximity range and relative position relationship between them. Overlay analysis is realized by using geographic information system software. The output results include spatial proximity area, proximity ratio, and spatial distribution characteristics of associated area. These data are used to judge the potential replacement feasibility between cultivated land resource and forest land resource. Larger overlay area plot needs to be considered first in replacement accounting, in order to reduce ecological damage and improve land use efficiency.

[0056] The integrated data input pre-set substitution rule model, the core algorithm of which is based on linear programming method, takes maximizing ecological benefits and land use efficiency as objective function, while considering the constraint conditions of replaceable rate of arable land resources and developable rate of forest land resources. The replaceable rate of arable land resources is set according to the land block level and regional policy requirements, and the replaceable rate of high-level land block is lower to ensure the sustainable use of high-quality arable land. The developable rate of forest land resources is dynamically adjusted according to the ecological value coefficient and ecological protection red line range, and the development rate of forest land with high ecological value coefficient is strictly limited. The substitution rule model uses iterative optimization algorithm to gradually adjust the substitution area and weight distribution when calculating the matching relationship, until all the constraint conditions are met and the optimal solution is reached.

[0057] The output results include arable land resource substitution area, forest land resource substitution weight and substitution priority list. The substitution area is allocated in units of land blocks according to the level and matching degree, and the low-level land block with high matching degree is given priority to substitution. The substitution weight reflects the relative importance of forest land resources in substitution, and the land block with high weight needs to take more stringent ecological protection measures in subsequent development. The substitution priority list is sorted according to the matching degree, ecological benefits and administrative region demand, and is used to guide the implementation order of actual substitution work. All output data are presented in the form of structured table and spatial distribution map, which is convenient for decision-makers to understand intuitively and apply to actual management.

[0058] During the data integration and calculation process, the system uses a distributed computing framework to process large-scale spatial data, improving the operation efficiency. The data storage uses a spatio-temporal database to support historical version management and real-time update query. The user interaction interface provides parameter configuration, result visualization and report generation functions, allowing management personnel to adjust model parameters and view substitution schemes under different scenarios according to actual conditions. The whole implementation process emphasizes the accuracy of data and the transparency of algorithm, and all intermediate results and calculation logic can be traced back for auditing and optimization.

[0059] The operation of the substitution scheme generation unit depends on high-quality data input and reasonable parameter setting, so the data source needs to be strictly checked before implementation to ensure the integrity and consistency of spatial coordinates, attribute information and constraint conditions. Parameter setting needs to be combined with regional characteristics and policy requirements, and updated regularly to adapt to the dynamic changes of resource management needs. The system supports batch processing and real-time calculation modes to meet the needs of different application scenarios. Batch processing is suitable for large-scale regional planning, and real-time calculation is used to deal with sudden changes in resources or policy adjustments. Through continuous optimization of algorithm and enhancement of computing capacity, the substitution scheme generation unit can efficiently and accurately support the substitution decision of arable land resources and forest land resources.

[0060] Example 2: see Figure 3The core function of the dynamic correction unit is to monitor abnormal resource data, locate the farmland resource change block or forest resource ownership change data that causes the abnormality, and correct the replacement index calculation results in real time according to the abnormal type. The operation mechanism of this unit is based on the continuously updated data stream, and through real-time data docking with the real estate registration system, land survey database, ecological protection red line management platform and forestry system, the latest resource change information is obtained. The system uses incremental updating method, only processes the changed data entries, greatly reduces the calculation load and improves the response speed.

[0061] The identification of farmland resource change block is mainly realized by comparing historical data and real-time updated spatial boundaries. The system maintains a versioned spatial database, which records the boundary coordinates, ownership information and utilization status of each block at different time points. When new survey data or approval files are entered into the system, the change detection algorithm is automatically triggered. This algorithm first performs overlay analysis on the spatial boundaries, calculates the difference area between the current version and the historical version, and then combines the attribute information to determine the change type, such as block splitting, merging, use adjustment, etc. For the detected change block, the system extracts its spatial position, change time, change reason and new attribute data as an important part of abnormal resource data.

[0062] The acquisition of forest resource ownership change data depends on the data sharing mechanism with the forestry management department. The system regularly receives official documents such as forest right registration, use right transfer, ecological compensation area adjustment, etc., and extracts key information such as change block number, new ownership subject, change effective date, etc. through natural language processing technology. At the same time, the system accesses remote sensing monitoring data, identifies changes in forest coverage types such as logging sites and afforestation areas through image interpretation. These change data are cross-verified with ownership registration information to ensure the accuracy of abnormal detection. When a block with ownership change is found but not reflected in the replacement plan, the system automatically marks it as an abnormal entry.

[0063] The positioning of abnormal resource data uses a combination of spatial indexing and attribute filtering. The system establishes R-tree spatial index to quickly retrieve the surrounding blocks affected by the change. Attribute filtering is based on pre-set abnormal judgment rules such as sudden change of farmland resource level, abnormal fluctuation of forest ecological value coefficient, etc. After positioning, the system generates a detailed impact assessment report for each abnormal entry, including affected replacement plan number, original replacement area, original replacement priority and comparison of key parameters before and after the change. These information provides data support for subsequent re-evaluation.

[0064] The re-evaluation process is carried out for the affected replacement priority and replacement area. The system first calculates the deviation of the changed plot from the original replacement scheme, which integrates the spatial position offset, attribute difference, and ecological impact change. The spatial position offset is obtained by calculating the distance between the geometric centers of the plots before and after the change; the attribute difference is based on the variation range of key parameters such as soil quality and slope; and the ecological impact change is compared with the ecological value coefficient before and after the change. Abnormal items with a deviation exceeding the threshold enter the correction process.

[0065] The correction process adopts differentiated strategies according to the change type. For the change of cultivated land resource ownership, the system re-searches for alternative plots that meet the conditions and calculates the replacement parameters according to the same matching rules as the original scheme. The selection of alternative plots considers spatial proximity, grade similarity, and administrative region consistency, and gives priority to plots with the same administrative unit, same or higher grade. For the change of forest land resource ownership, the system re-evaluates its ecological value coefficient. If the change leads to an increase in the coefficient, the replacement weight of the plot is reduced or the plot is removed from the replacement scheme; if the coefficient decreases, it is carefully evaluated whether to increase the replacement weight.

[0066] Cross-regional anomaly processing is an important function of dynamic correction units. The system identifies systematic change patterns by correlating multiple abnormal resource data within the same administrative region, such as large-scale ecological restoration projects leading to concentrated adjustment of cultivated land resources, regional forestry policy changes causing batch changes in forest land ownership, etc. The analysis process uses spatial clustering methods to merge abnormal items with similar change reasons and geographical proximity into the same event. For the identified systematic changes, the system further judges whether to trigger cross-regional replacement adjustment.

[0067] The conditions for triggering cross-regional replacement adjustment include: insufficient supply of resources in a single administrative region, local replacement limited by ecological protection requirements, and major infrastructure projects occupying replacement plots, etc. When the triggering conditions are met, the system starts the multi-regional replacement coordination strategy. This strategy first builds a resource supply and demand network between regions, with nodes representing administrative regions and edges representing resource flow relationships, and the weight of the edge reflecting the supply capacity and demand intensity. Then, the network flow algorithm is used to calculate the optimal resource allocation scheme, which maximizes the overall replacement benefit while meeting the basic needs of each region.

[0068] The implementation of the multi-region replacement coordination strategy includes two main steps: allocating standby farmland resource plots and updating replacement priority. Standby plots are sourced from a cross-regional resource reserve maintained by the system, which records information on replaceable plots voluntarily provided by administrative regions. The allocation process takes into account indirect transportation costs related to resource allocation (indirect transportation and supporting costs related to the development, production and operation, and ecological restoration of standby plots in cross-regional replacement), topographic continuity, management convenience, and other factors, and preferentially selects plots in adjacent regions. The update of replacement priority is based on new supply and demand relationships and ecological protection requirements, and uses a multi-criteria decision-making method to reorder. The system generates detailed adjustment instructions, recording the basis and impact range of each change decision.

[0069] The implementation of the dynamic correction unit relies on a high-performance spatial computing engine and a real-time data processing architecture. The computing engine uses parallel computing technology to accelerate large-scale spatial analysis and network stream computing; the data processing architecture is based on an event-driven mode to ensure low latency for anomaly detection and correction. The user interface provides interactive correction review functions, allowing administrators to view automatic correction suggestions and manually adjust parameters. All correction operations are recorded in audit logs to support backtracking and responsibility tracing.

[0070] The system periodically evaluates the effectiveness of dynamic correction, and calculates the difference between replacement schemes before and after correction, the response time of abnormal processing, the success rate of cross-regional coordination, and other indicators. The evaluation results are used to optimize abnormal judgment rules, deviation threshold values, and coordination strategy parameters. At the same time, the system establishes a feedback mechanism to allow local management departments to report the actual implementation of the correction scheme, further calibrating the algorithm. This continuous improvement mechanism enables the dynamic correction unit to adapt to changing resource management needs and policy environments.

[0071] The dynamic correction unit and the replacement scheme generation unit form a closed-loop system. The corrected replacement index accounting results are automatically fed back to the scheme generation unit, triggering the necessary recalculation. The coordinated work of the two units ensures that the replacement scheme maintains long-term stability while being able to flexibly respond to sudden changes. The entire implementation process emphasizes the timeliness of data, the adaptability of algorithms, and the explainability of decisions, providing dynamic and precise management support for farmland and forest land replacement.

[0072] Example 3: The resource adaptation reconstruction process of the substitution index accounting unit is to convert the spatio-temporally aligned resource multidimensional dataset into a structured mathematical representation, facilitating subsequent analysis and calculation. The core of this process is to construct a resource adaptation matrix, which can fully express the spatial matching relationship and attribute compatibility between cultivated land resources and forest land resources. The row dimension of the matrix represents the cultivated land resource plot, the column dimension represents the forest land resource plot, and the matrix element value reflects the adaptation degree between the specific cultivated land plot and the forest land plot. The calculation of the adaptation degree comprehensively considers multiple dimensions such as spatial proximity, soil property matching degree, slope compatibility, and ecological function complementarity. Spatial proximity is quantified by calculating the Euclidean distance between the geometric centers of the plots, soil property matching degree is based on the similarity score of the soil types of the two plots, slope compatibility examines whether the slope of the cultivated land resource meets the engineering requirements of forest development, and ecological function complementarity assesses the stability of the overall ecosystem after substitution.

[0073] The mathematical representation of the resource adaptation matrix is:

[0074] ;

[0075] Among them: represents the adaptation score of the i-th cultivated land resource plot and the j-th forest land resource plot; is the spatial proximity score, which is inversely proportional to the distance between the centers of the two plots; is the soil property matching degree score, calculated according to the compatibility rules of the soil classification system; is the slope compatibility score, evaluated based on engineering feasibility standards; is the ecological function complementarity score, derived from the ecosystem service value evaluation model; , , , are the weight coefficients of each index, dynamically adjusted according to regional resource management policies. This formula ensures that the adaptation score can fully reflect the comprehensive conditions of resource substitution, avoiding the dominance of a single index in decision-making.

[0076] The matrix decomposition process uses an improved singular value decomposition method to decompose the resource adaptation matrix into a resource core matrix and a resource anomaly matrix. The resource core matrix retains data with an adaptation degree higher than a preset threshold, which represents the combination of cultivated land resources and forest land resources that meet the basic substitution conditions. The threshold is set according to regional development intensity and ecological protection requirements, and usually adopts a dynamic adjustment mechanism, appropriately reducing the threshold in resource-intensive areas and increasing the threshold in ecologically sensitive areas. The resource anomaly matrix captures all entries below the threshold and identifies their anomaly types, such as plot ownership conflicts, ecological protection red line overlaps, and data quality defects. Anomaly types are represented by additional marker fields, facilitating subsequent classification processing.

[0077] Constructing a resource exchange coupling matrix is ​​a crucial step in handling cross-administrative region resource exchanges. The rows and columns of this matrix represent different administrative regions, and the matrix element values ​​indicate the degree of matching between the supply of arable land resources and the demand for forest land resources between regions. The generation of the coupling matrix relies on statistical analysis of the resource endowments of each region and demand forecasting models. Supply data comes from the results of arable land resource surveys and evaluations, considering the total amount of exchangeable resources, quality grade distribution, and policy-permitted development scale in each region. Demand data is comprehensively calculated based on forest land resource protection planning, ecological restoration tasks, and economic development land demand. The dynamic updating mechanism of the coupling matrix allows it to reflect the latest trends in inter-regional resource flows.

[0078] Introducing a collaborative constraint term from the resource substitution coupling matrix during matrix factorization effectively identifies parallel anomalies such as cross-regional resource supply imbalances or ecological protection conflicts. This collaborative constraint term acts as a boundary condition on the singular value decomposition algorithm, restricting the decomposition result to satisfy the basic balance of resource flows between regions. Specifically, the coupling matrix is ​​converted into linear constraints and incorporated into the objective function using the Lagrange multiplier method. This approach ensures that the decomposed core resource matrix not only reflects the adaptability of the resources themselves but also embodies the overall requirements of regional coordination. When the supply-demand correlation between any two regions in the coupling matrix exceeds a preset threshold, and the corresponding anomaly entry in the resource anomaly matrix exceeds its limit, the system determines that a cross-regional resource mismatch problem requiring intervention exists.

[0079] The triggering mechanism for the multi-regional exchange coordination strategy employs a multi-level judgment mechanism. First, it calculates the inter-regional supply-demand correlation, which integrates factors such as the scale of resource flow, indirect transportation costs related to resource allocation (including indirect transportation costs associated with the development, production, and ecological restoration of reserve land in cross-regional exchanges), and policy compatibility. Then, it checks the anomaly intensity of relevant entries in the resource anomaly matrix, classifying anomaly intensity according to the magnitude and scope of deviation from normal values. When both conditions simultaneously meet preset trigger thresholds, the system automatically initiates the coordination strategy. The strategy execution process first establishes a cross-regional negotiation platform to share resource data and exchange needs; then, it formulates a resource allocation plan, clarifying the supply responsibilities and transfer rights of each region; finally, it adjusts the exchange priority to ensure that the protection needs of key ecological areas are met first.

[0080] The implementation of resource adaptive restructuring relies on a distributed matrix operation framework. The construction and decomposition of large-scale resource adaptation matrices are divided into multiple sub-matrices, distributed to different computing nodes for parallel processing. The intermediate results are synchronized through an efficient communication protocol, and finally aggregated into complete decomposition results. For operations involving cross-regional data exchange, blockchain technology is used to ensure data security and operation traceability. The user interface provides matrix visualization tools, supporting the display of resource adaptation relationships and regional coupling status through heat maps, network diagrams, and other forms, to assist management personnel in understanding complex resource associations.

[0081] The follow-up processing of abnormal entries adopts a classified policy approach. For data quality defects, the system automatically initiates a data verification request, requiring relevant departments to re-verify and submit accurate information. For ownership conflict anomalies, the ownership dispute resolution process is triggered to coordinate all parties to confirm the final effective ownership status. For ecological protection red line overlap anomalies, ecological impact assessment is started, and based on the assessment results, it is decided whether to adjust the protection red line range or cancel the replacement plan. Each type of anomaly has a corresponding processing time limit requirement, and the system tracks the processing progress through the workflow engine, and automatically escalates the anomaly to a higher decision level if it is not resolved within the time limit.

[0082] The optimization of the resource replacement coupling matrix is a continuous iterative process. The system regularly collects the actual execution of regional resource replacement schemes, and calculates indicators such as supply completion rate, demand satisfaction rate, and ecological protection compliance rate. These data are fed back to the coupling matrix generation algorithm to calibrate the resource flow parameters between regions. At the same time, the system monitors external environmental changes, such as major policy adjustments, natural disasters, and other events, and triggers emergency updates of the coupling matrix in a timely manner. This dynamic adjustment mechanism enables the system to adapt to the changing needs of resource management, maintaining the timeliness and applicability of decision-making recommendations.

[0083] The replacement index accounting unit and the dynamic correction unit form a close collaboration. When the dynamic correction unit detects major resource changes, it triggers partial reconstruction of the resource adaptation matrix, updating only the affected regional matrix blocks, rather than recalculating the entire matrix, significantly improving response efficiency. Conversely, systematic abnormalities discovered by the resource adaptive restructuring process also provide data support for rule optimization of the dynamic correction unit. The two units share an abnormal knowledge base and coordinate strategy library, accumulating and reusing processing experience, gradually improving the overall decision-making ability of the system.

[0084] The entire implementation process emphasizes the transparency and interpretability of the mathematical model. All intermediate results of matrix operations and parameter adjustment records are saved completely, supporting auditing and review. Key decision points are set with manual review links to ensure the rationality of automated processing. The system provides detailed explanatory reports to explain the generation logic and basis data of each replacement suggestion, helping decision-makers understand and trust the system output. This design not only fully leverages the efficiency advantages of data-driven decision-making, but also retains the necessary human supervision and judgment, achieving human-machine collaborative intelligent resource management.

[0085] Example 4: see Figure 4 and Figure 5 In the process of generating the resource multidimensional data set in the resource data acquisition unit, the system first performs spatial overlay analysis on the coordinates of the cultivated land resource plots, the boundary coordinates of the forest land resource, and the administrative region boundaries in the replacement constraint conditions. This process is implemented through a geographic information system platform, using a vector overlay algorithm to calculate the intersection relationship of the three types of spatial data. For example, in a certain county-level implementation case, the system processed spatial data containing 356 cultivated land resource plots and 128 forest land resource plots, and generated a resource space mapping matrix after overlaying. Each cell of the matrix records the spatial relationship between a specific cultivated land plot and a forest land plot, including the overlapping area, relative position, and administrative jurisdiction information. The structure of the resource space mapping matrix is shown in Table 1.

[0086] Table 1: The structure of the resource space mapping matrix is as follows.

[0087]

[0088] The "ecological protection zone overlap flag" field in the table is derived from the comparison results of the ecological protection red line database, marking the existence of overlapping ecological sensitive area combinations. This structured representation allows subsequent anomaly detection to directly locate resource combinations with potential conflicts.

[0089] When the replacement index accounting unit works based on the resource anomaly matrix, it first extracts abnormal entries and associates them with the resource space mapping matrix. In a practical application in a certain city, the system identified 42 abnormal records, including 19 cultivated land resource ownership change records and 23 forest land resource ecological restriction records. These abnormal records are clustered into two categories based on spatial characteristics: the first category of abnormal sub-matrix focuses on abnormal changes caused by cultivated land resource ownership changes, typically characterized by multiple ownership registrations in the same plot in adjacent time periods; the second category of abnormal sub-matrix focuses on abnormal changes caused by forest land resource ecological restrictions, mainly characterized by high ecological value forest land suddenly being included in the development range.

[0090] The construction of the multi-dimensional feature vector of the abnormal entry is the key link of this embodiment. The system extracts the following features for each abnormal record: plot change timestamp, six-digit statistical division code of the administrative region it belongs to, and the overlap area ratio with the ecological protection zone. For example, the feature vector of a certain cultivated land ownership change record contains the "2023-05-12T08:30:00" time marker, the "330522" administrative division code, and the "0.15" overlap ratio. After these features are standardized, they enter the weighted calculation process. The weight configuration scheme refers to the development intensity threshold in the replacement constraint condition, for example, in the ecological sensitive area, the weight of the overlap area ratio is set to three times that of the regular area, to strengthen the influence of the ecological protection factor.

[0091] The spatial proximity clustering is implemented using an improved DBSCAN algorithm. This algorithm does not need to preset the number of clusters, but automatically discovers the clustering patterns of abnormal entries based on density reachability. In a certain provincial case, the system divides 25 abnormal entries into 4 spatial clusters, two of which are classified as the first type of abnormal sub-matrix, containing 11 concentrated changes of cultivated land ownership; the other two clusters are classified as the second type of abnormal sub-matrix, containing 14 ecological restriction abnormalities. During the clustering process, the algorithm automatically identifies a concentrated area of cultivated land ownership abnormalities at the junction of three townships in the east of a certain county, and a clustered area of forest land development abnormalities in the buffer zone of a nature reserve.

[0092] The processing of the first type of abnormal sub-matrix focuses on the stability of the ownership verification. The system automatically generates an ownership change chain analysis diagram to show all the registration change records of a specific plot within half a year. For example, a plot was registered as village collective ownership, agricultural company lease, and state reserve land within three months, which triggered the ownership confirmation process. The system sends a verification request to the natural resource authority to provide the latest ownership identification documents, and updates the resource database according to the feedback.

[0093] The processing of the second type of abnormal sub-matrix focuses more on the ecological compliance review. The system retrieves the historical data of the ecological value assessment of the abnormal forest plot, and compares the current development plan with the original protection requirements. For example, a plot at the edge of a primary forest was newly included in the replacement range, and the system found that the plot belongs to a biodiversity maintenance area in the ecological function zoning, which triggered the ecological impact assessment process. The assessment report includes vegetation cover change simulation, species habitat connectivity analysis, and other contents, which serve as the basis for decision-making whether to allow replacement.

[0094] The data quality control measures in the implementation process include: coordinate system conversion before spatial overlay analysis to avoid positional deviation caused by projection differences; setting up data freshness check when detecting anomalies, and re-verifying historical data that exceeds the effective period; manual sampling review after clustering analysis to ensure the reliability of algorithm results. A regional implementation case shows that through these three layers of quality control, the construction accuracy of the spatial mapping matrix reaches 98.6%, and the false positive rate of anomaly identification is controlled below 3%.

[0095] The system designs differentiated visualization schemes for different types of anomaly sub-matrices. The first type of anomaly displays the sequence of ownership changes in the form of a time axis, highlighting the plots with frequent changes; the second type of anomaly uses an ecological sensitivity heat map to represent the protection urgency of different areas with a color gradient. These visualization tools help managers quickly grasp the distribution of anomalies and improve decision-making efficiency. For example, the Natural Resources Bureau of a certain city discovered through the heat map that the land development anomalies were concentrated at the junction of two ecological corridors, and accordingly adjusted the regional replacement plan to avoid the fragmentation of the ecological network.

[0096] The anomaly handling workflow supports multi-department collaboration. When the system identifies a cross-administrative boundary anomaly cluster, it automatically creates a joint handling task and invites relevant regional managers to participate. The task tracking panel displays the completion status of each handling step, including data review, on-site investigation, consultation and decision-making, etc. In a cross-county case, the system completed the handling of 11 related anomalies involving three counties in 72 hours, significantly improving efficiency compared to the traditional paper document circulation method.

[0097] The incremental processing strategy is adopted for the update and maintenance of the resource space mapping matrix. In daily work, only the plots that have changed are recalculated for spatial relationships, and the full matrix reconstruction is scheduled at night when the system load is low. This strategy effectively reduces the performance impact on daily business operations while maintaining data timeliness. The running data of a provincial platform shows that incremental updating reduces the time consumption of daily data processing by 67% and the peak server resource occupancy by 41%.

[0098] Implementation cases show that this approach can effectively identify two key types of anomalies: 17 concentrated areas of cultivated land ownership anomalies were found in a certain eastern province, and 9 of them were found to have registration errors upon verification; 23 illegal development risk points were identified in a certain forest area in the west, successfully preventing the replacement plan of 6 important ecological areas. The anomaly analysis report generated by the system is included in the natural resources supervision clue library, providing data support for industry supervision. The entire implementation process embodies the technical route: through precise spatial correlation positioning, multi-dimensional feature classification of anomalies, and targeted handling based on domain knowledge, a management closed loop is formed for continuous optimization. This mode not only leverages the efficiency advantages of data-driven, but also maintains the core position of professional judgment, realizing the organic combination of technological innovation and institutional advantages.

[0099] In the process of modifying the replacement index accounting results, the dynamic correction unit first calls the minimum ecological protection ratio parameter specified in the replacement constraint conditions. This parameter is set by the provincial natural resources department based on regional ecological function orientation, and is usually expressed as the proportion of protected areas in forest land resources that must remain unchanged. After receiving the correction instruction, the system automatically retrieves the forest land resource plots involved in the current accounting results, calculates the ratio of the proposed replacement area to the total area for each plot, and compares it with the minimum ecological protection ratio. When the replacement ratio of a plot exceeds the allowed threshold, the system starts the compliance calibration program and reduces the replacement area of the plot by the difference ratio. The calibration process uses a stepwise adjustment strategy, preferentially reducing the replacement area of plots with lower ecological value coefficients to preserve the integrity of high ecological value areas.

[0100] Compliance calibration not only considers the replacement ratio of a single plot, but also assesses the ecological balance of the entire administrative region. The system aggregates the replacement of all forest land resources in the region, calculates the weighted average protection ratio, and automatically triggers a regional level protection warning when the overall protection ratio of some administrative units approaches the minimum requirement. This warning mechanism prompts the system to reevaluate the replacement weight distribution of plots in the region, and adjusts the replacement area of adjacent plots to meet local needs while ensuring overall ecological safety. The regional balance algorithm uses an iterative approximation method, recalculating the protection ratio after each adjustment until all administrative units meet the requirements. This hierarchical calibration mechanism ensures the rigid constraints of policy red lines while retaining the flexibility of resource allocation.

[0101] After the forest land resource replacement weight calibration is complete, the system immediately calculates the qualified rate of the associated cultivated land resource replacement area. The qualified rate indicator reflects the percentage of cultivated land resources that meet the ecological protection requirements in the modified replacement plan. The calculation process integrates multiple dimensional constraint conditions: whether the soil quality grade meets the cultivation standard, whether the slope is within the suitable range for cultivation, whether the buffer distance from the ecological protection zone is sufficient, whether the surrounding infrastructure meets agricultural needs, etc. Each condition sets a binary decision rule, and plots that meet all conditions are included in the qualified area. The system dynamically generates a qualified rate change curve to visually display the impact of each modification on the quality of the plan.

[0102] When the pass rate is detected to be lower than the preset threshold, the system sends a re-calculation request to the replacement scheme generation unit. The request contains detailed correction reason explanation and key parameter change record. The re-calculation process is not simply repeating the original process, but focusing on the problem area for targeted optimization. The system first locks the core factors that cause the decline in pass rate, such as the soil quality of a specific area not meeting the standard or the slope limit being too strict, and then adjusts the screening conditions or replacement rules of that area. For example, for soil quality problems, soil improvement feasibility assessment can be introduced to allow some improved land to be included in the replacement range; for slope limit, terracing engineering measures can be considered to appropriately relax the replacement threshold of steep slope land. This problem-oriented re-calculation mechanism effectively avoids the "one-size-fits-all" resource waste.

[0103] After the re-calculation scheme is generated, the system performs multi-version comparison analysis to highlight the main differences between the new and old schemes. The comparison dimensions include the increase and decrease of replacement area in each administrative region, the change of forest land resource protection ratio, and the distribution of cultivated land resource quality. Management personnel can intuitively understand the actual impact of the correction, especially the balance between ecological protection and resource development. The system also provides a difference reason tracing function, which allows users to view the specific parameter adjustment and calculation logic that led to the change by clicking on any change indicator. This transparent decision-making process greatly enhances the acceptability and execution efficiency of the scheme.

[0104] The interaction between the dynamic correction unit and the replacement scheme generation unit uses an asynchronous communication mechanism. The correction request is placed in a high-priority task queue, and the scheme generation unit returns the result through a callback interface after processing is completed. This design avoids direct coupling between the two units, ensuring stable operation of the system under high load. The communication content uses a structured message format, containing complete context information, so that interrupted tasks can be accurately resumed. All interaction records are stored persistently, forming a complete audit trail to support post-tracing and responsibility identification.

[0105] The system regularly evaluates the effectiveness of the correction mechanism, focusing on two indicators: correction response time and correction accuracy. Response time statistics from abnormal detection to completion of the whole process, and accuracy measures the degree of fit between the corrected scheme and actual management requirements. Evaluation data comes from two parts: system automatically recorded operation log, and manually filled satisfaction survey. The analysis results are used to optimize the parameter settings of the correction strategy, such as adjusting the trigger sensitivity of the pass rate threshold, improving the convergence speed of the regional balance algorithm, etc. This continuous self-optimization enables the system to adapt to changing policy environment and management requirements.

[0106] In a specific implementation case, a mountainous county found that the original replacement scheme involved 3 important water conservation forests. Through compliance calibration, the system reduced the replacement area from 125 hectares to 82 hectares, and supplemented 2 qualified farmland resource plots through re-calculation. The entire process took less than 4 hours, and the revised scheme not only met the demand for economic development land, but also ensured the integrity of the ecological function of the water source. Another revision case in a plain area shows that the system improved the regional qualification rate from 68% to 89% through three iterations, including optimizing soil detection sampling schemes and redefining ecological buffer distances.

[0107] The implementation of the dynamic revision unit fully considers the operation habits of users at different levels. Provincial managers can view macro revision statistics and trend analysis, municipal users focus on revision details and cross-regional coordination requirements within their jurisdiction, and county operators mainly handle specific land revision tasks. The system interface dynamically configures display content and operation permissions based on user roles to ensure that all types of users can efficiently complete their work. At the same time, the system provides detailed revision guidance documents and online training resources to help frontline personnel quickly master key operation points.

[0108] The design philosophy of the entire revision process is to take the ecological protection red line as a rigid constraint and the resource utilization efficiency as an optimization target, and to achieve scientific decision-making through data-driven dynamic adjustment. In terms of technology implementation, the adaptability and interpretability of algorithms are emphasized, and in terms of management process, the uniformity of standards and the convenience of operation are emphasized. This implementation method not only takes advantage of the automation of information systems, but also respects the complexity of natural resource management, and has shown strong practical value and promotion potential in practice. With the accumulation of system running time and the continuous optimization of algorithm models, the accuracy and efficiency of dynamic revision will be further improved, providing more intelligent support for farmland and forest resource replacement management.

[0109] It should be noted that in this document, relational terms such as first and second and the like can only be used to distinguish one entity or action from another entity or action, without necessarily requiring or implying any such actual relationship or order between or among the entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0110] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. An index dynamic accounting system for the replacement of cultivated resources and forest resources, characterized in that, The method comprises the following steps: a resource data acquisition unit acquires spatial distribution data of cultivated land resources, type and coverage range data of forest land resources, and replacement constraint condition data, and performs spatio-temporal alignment on the spatial distribution data, type and coverage range data, and replacement constraint condition data to generate a resource multidimensional data set; a replacement index accounting unit performs resource adaptability reconstruction processing based on the resource multidimensional data set, and separates out target resource data for replacement accounting and abnormal resource data for dynamic correction accounting; a replacement scheme generation unit generates a replacement index accounting result based on the target resource data, in combination with a preset cultivated land resource replaceable rate and a forest land resource developable rate, the replacement index accounting result comprising a cultivated land resource replacement area, a forest land resource replacement weight, and a replacement priority; the cultivated land resource replacement area is a non-single area, being a set of areas after multi-factor area conversion; a dynamic correction unit identifies an abnormal type in resource data updating based on the abnormal resource data, and corrects the replacement index accounting result in real time according to the abnormal type.

2. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 1, characterized in that, The replacement scheme generation unit performs the following operations: integrating cultivated land resource grades in the target resource data, forest land resource ecological value coefficients, and geographic overlay region data in the replacement constraint condition; calculating a matching relationship between the cultivated land resource replacement area and the forest land resource replacement weight according to the integrated data and a preset replacement rule, and outputting the replacement index accounting result.

3. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 1, characterized in that, The dynamic correction unit performs the following operations: monitoring the abnormal resource data, and locating a cultivated land resource change plot or forest land resource ownership change data that causes the abnormality; based on the monitoring result, re-evaluating the replacement priority and the replacement area affected, and correcting the cultivated land resource replacement area and the replacement priority in the replacement index accounting result.

4. The index dynamic accounting system for the replacement between the cultivated resources and the forest resources according to claim 3, characterized in that, The dynamic correction unit further performs the following operations: correlation analysis of cultivated land resource change reasons and forest land resource development restriction conditions corresponding to multiple abnormal resource data in the same administrative region, to determine whether a cross-regional replacement adjustment is triggered; if the cross-regional replacement adjustment is triggered, a multi-region replacement coordination strategy is executed to allocate standby cultivated land resource plots and update the replacement priority.

5. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 1, characterized in that, The replacement index accounting unit performs resource adaptability reconstruction processing, which comprises the following steps: converting the spatio-temporally aligned resource multidimensional data set into a resource adaptation matrix; decomposing the resource adaptation matrix to obtain a resource core matrix and a resource abnormal matrix; wherein the resource core matrix contains spatial matching characteristics of cultivated land resources and forest land resources, and the resource abnormal matrix identifies abnormal entries of plot ownership conflicts or ecological protection red line overlaps.

6. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 5, characterized in that, When the resource data acquisition unit generates the resource multidimensional data set, the plot coordinates of cultivated land resources, the boundary coordinates of forest land resources, and the administrative region boundaries in the replacement constraint condition are spatially overlaid to generate a resource space mapping matrix; The replacement index accounting unit further performs the following operations: based on the resource abnormal matrix, extracting abnormal entries and correlating the resource space mapping matrix, clustering the spatial characteristics of the abnormal entries to generate a first type of abnormal sub-matrix and a second type of abnormal sub-matrix; The first type of abnormal sub-matrix represents an abnormality caused by a change in the ownership of cultivated land resources, and the second type of abnormal sub-matrix represents an abnormality caused by ecological restrictions on forest land resources.

7. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 6, characterized in that, The clustering of the spatial features of the abnormal items by the replacement index accounting unit includes: adding a multi-dimensional feature vector to each abnormal record, the multi-dimensional feature vector including a time of change of the land plot, an administrative region code to which the land plot belongs, and an overlapping area of an ecological protection zone; configuring a weight for the multi-dimensional feature vector based on a development intensity threshold in the replacement constraint condition; grouping the multi-dimensional feature vectors according to spatial proximity to generate the first type of abnormal sub-matrix and the second type of abnormal sub-matrix.

8. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 5, characterized in that, The resource adaptability reconstruction processing performed by the replacement index accounting unit further includes: constructing a resource replacement coupling matrix to represent a supply of cultivated land resources and a demand for forest land resources across administrative regions; when the resource adaptation matrix is decomposed, introducing a cooperative constraint term of the resource replacement coupling matrix, combining resource abnormal matrices to iteratively solve, and identifying parallel abnormalities of cross-regional resource supply imbalance or ecological protection conflicts; when the supply-demand correlation degree of any two regions in the resource replacement coupling matrix exceeds a preset threshold, and the value of the corresponding abnormal item in the resource abnormal matrix is out of limit, triggering a multi-region replacement cooperative strategy.

9. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 1, characterized in that, When the replacement index accounting result is corrected by the dynamic correction unit, the minimum ecological protection ratio in the replacement constraint condition is called to calibrate the compliance of the corrected forest land resource replacement weight.

10. The index dynamic accounting system for the replacement between cultivated resources and forest resources according to claim 9, characterized in that, The dynamic correction unit also performs: based on the calibrated forest land resource replacement weight, recalculating the qualified rate of the cultivated land resource replacement area; when the qualified rate is lower than a preset threshold, triggering the replacement scheme generation unit to regenerate the replacement index accounting result.

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