Land consolidation earthwork intelligent deployment method based on surveying and mapping big data
By constructing a three-dimensional digital foundation based on multi-source surveying and mapping big data, and combining it with land spatial planning and ecological protection models, the earthwork allocation was carried out using multi-objective optimization functions and genetic algorithms. This solved the problems of construction deviation and ecological damage during the earthwork allocation process, and achieved precise and ecological management of land consolidation projects.
Patent Information
- Application Number
- CN202611312545.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-27
- Publication Date
- 2026-11-06
AI Technical Summary
Existing earthwork allocation technologies fail to effectively integrate with land use planning and ecological restoration requirements, resulting in significant construction deviations and severe ecological damage. Furthermore, the lack of dynamic monitoring and iterative optimization mechanisms makes it impossible to achieve compliance and ecological goals for comprehensive land consolidation.
By constructing a three-dimensional digital base of multi-source surveying and mapping big data, embedding land spatial planning constraints, and combining topsoil and ecological landform protection models, earthwork allocation is carried out using multi-objective optimization functions and genetic algorithms. Combined with construction dynamic monitoring, the scheme is iterated and corrected to achieve intelligent and dynamic closed-loop control of earthwork scheduling.
This ensured the accuracy and compliance of the earthwork allocation plan, improved the economic and ecological aspects of land consolidation projects, and guaranteed that the construction process met the requirements of national land space planning and ecological protection.
Smart Images
Figure CN123050834A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the technical field of land consolidation and spatial planning, and in particular to an intelligent method for allocating earthwork in land consolidation based on surveying and mapping big data. Background Technology
[0002] Earthwork allocation is a core component of land consolidation projects, directly determining project costs, construction period, land leveling accuracy, and regional ecological restoration effectiveness. Currently, my country's comprehensive land consolidation, farmland quality improvement, and ecological restoration projects have an increasingly urgent need for refined and intelligent management of earthwork excavation, filling, transportation, and balanced scheduling. Earthwork allocation must also strictly comply with statutory planning requirements such as the overall national land space plan, farmland protection, and ecological management. However, existing land consolidation earthwork allocation technologies generally suffer from the following technical deficiencies.
[0003] Territorial spatial planning is the fundamental basis for comprehensive land consolidation. The optimization of the consolidation layout must be carried out within the framework of the "three zones and three lines" delineation. The stripping and reuse of topsoil from arable land is also an important measure to implement the strictest arable land protection system. However, existing earthwork allocation technologies only focus on the earthwork excavation and filling balance of a single plot, without linking with territorial spatial planning control rules, and without coordinating the three types of control boundaries: permanent basic farmland protection red line, ecological protection red line, and urban development boundary. At the same time, they ignore ecological restoration constraints and lack systematic technical arrangements for the special stripping, storage, backfilling, and reuse of topsoil in excavated areas. The earthwork allocation process is prone to damaging the original ecological landform and destroying the topsoil of arable land, which is out of touch with the requirements of integrated development of comprehensive territorial consolidation and ecological restoration.
[0004] Earthwork allocation faces challenges such as high dynamism, difficulty in multi-objective coordination, and complex environmental constraints. Although some studies have attempted to apply intelligent optimization methods such as genetic algorithms and ant colony algorithms to the field of earthwork allocation, existing methods are mostly single algorithms or simple combinations, failing to establish a multi-objective collaborative dynamic iterative optimization mechanism driven by surveying big data. These methods are unable to adapt to complex terrain, multi-plot linkage, and multi-constraint working conditions, nor can they achieve dynamic monitoring and iterative correction of the entire construction process. Static allocation schemes have poor adaptability and large construction deviations. Furthermore, existing technologies lack a standardized, parameterized quantitative calculation system; the core allocation logic relies on human experience and lacks clear formula support, making it impossible for those skilled in the art to accurately reproduce the allocation scheme. Summary of the Invention
[0005] The purpose of this invention is to provide an intelligent allocation method for land consolidation earthwork based on surveying and mapping big data, so as to achieve integrated intelligent management and control of precise empowerment of surveying and mapping data, rigid constraints of land planning, simultaneous implementation of ecological restoration, and overall optimal earthwork scheduling, thereby improving the compliance, economy, and ecology of land consolidation projects.
[0006] To achieve the above objectives, this invention provides a method for intelligent allocation of land consolidation earthwork based on surveying and mapping big data, comprising the following steps: S1. Collect multi-source surveying and mapping data and perform standardized fusion processing to construct a three-dimensional digital base for the entire land consolidation area; S2. Connect with the national land space planning and control system, divide the remediation area into constrained zones, and determine the rigid constraint threshold for earthwork allocation in each zone; S3. In conjunction with the requirements for regional ecological restoration and management, construct a dual constraint model for topsoil protection and original ecological landform restoration, and form an ecological constraint matrix for earthwork allocation; S4. Based on the topographic mapping data of the three-dimensional digital base, a precise earthwork volume calculation model is built, and the excavation volume, filling volume, usable earthwork volume and waste earthwork volume of each treatment unit are quantitatively calculated in combination with the preset earthwork evaluation parameters. S5. Based on the rigid constraints of planning, the ecological constraint matrix and the earthwork calculation results, a multi-objective optimization function is constructed, and the optimal earthwork allocation scheme for the whole region is obtained by solving it. S6. Establish a dynamic surveying and monitoring mechanism for the entire construction process and an iterative correction mechanism for the scheme, and dynamically optimize and allocate the scheme based on real-time updated surveying data.
[0007] Preferably, step S1 specifically includes the following steps: S11. Collect multi-source surveying and mapping data of the remediation area, including UAV aerial high-definition imagery, airborne LiDAR point cloud data, GNSS real-scene 3D model, 1:500 high-precision topographic and cadastral surveying and mapping data, routine remote sensing monitoring data and soil sampling and testing data. S12. Standardize the preprocessing of the collected multi-source surveying and mapping data, including point cloud denoising, image orthorectification, 3D model texture optimization, and coordinate system unification processing. The 2000 National Geodetic Coordinate System and the 1985 National Height Datum are uniformly adopted as the surveying and mapping datum. S13. Perform spatial registration and raster overlay fusion processing on the standardized preprocessed multi-source mapping data to generate a global DEM digital elevation model, a DSM digital surface model, a soil texture spatial distribution map and a surface feature classification map, and construct a global three-dimensional digital base for land consolidation with a resolution of 0.1m.
[0008] Preferably, step S2 specifically includes the following steps: S21. Obtain the data of the regional territorial spatial master plan and overlay it with a multi-layered control vector map layer of permanent basic farmland protection red line, ecological protection red line, urban development boundary, land use status classification and remediation project planning boundary; S22. Based on spatial intersection analysis of multi-layer control vector layers, the entire remediation area is divided into three types of constrained zones: rigid control zone, flexible remediation zone, and ecological restoration zone. S23. Set rigid constraint thresholds for earthwork allocation for each constrained zone. The rigid constraint thresholds include the maximum excavation depth, maximum soil pile height, upper limit of earthwork disturbance area, and set of prohibited earthwork transportation routes for each zone, forming a comprehensive planning rigid constraint system.
[0009] Preferably, step S3 specifically includes the following steps: S31. Construct a topsoil protection constraint model. Based on the soil stratification mapping data of the three-dimensional digital base, delineate the distribution range of the topsoil in the remediation area, set the topsoil protection thickness threshold, and set the area within the topsoil protection range as the earthwork excavation constraint zone. The excavation depth is limited by the bottom boundary elevation value of the constraint zone. The topsoil in the excavation area is stripped layer by layer, stored in a centralized manner, and the stripped soil is included in the soil source sequence of the earthwork allocation matrix. S32. Construct an ecological landform restoration constraint model. Based on the original topography, water system and vegetation distribution data of the three-dimensional digital base, set the spatial protection boundary of the original water system, micro-landform and vegetation distribution, set the ecological disturbance tolerance index, and limit the disturbance range and intensity of earthwork construction. S33. Integrate the constraints of topsoil protection and ecological landform restoration, and quantify them to form a standardized ecological constraint matrix for earthwork allocation.
[0010] Preferably, step S4 specifically includes the following steps: S41. Based on the global three-dimensional digital base, the treatment area is uniformly gridded to form a computational grid of equal size. S42. Collect the measured original elevation and the planned design elevation of each grid unit, calculate the elevation difference grid by grid, and sum the values according to the formula using the grid difference iteration method to obtain the total excavation volume and total fill volume of each treatment unit. S43. Retrieve soil texture, soil moisture content and zoning ecological attribute data of the remediation area, calculate the comprehensive usable earthwork coefficient, and combine it with the total excavation volume of each remediation unit to obtain the effective usable excavation volume of each remediation unit. S44. Calculate the difference between the unit fill demand and the effective available excavation volume to obtain the unit waste earthwork volume and the required external purchase earthwork volume, thus completing the quantitative calculation of earthwork parameters for the entire unit.
[0011] Preferably, in step S42, the formula for calculating the total fill volume of the remediation unit is: ; in, This refers to the total fill volume for a single remediation unit. , These represent the total number of rows and columns after the grid-based division of the rectification area. For the first unit in the rectification OK The difference between the design elevation and the measured original elevation of the grid. The area of a single grid cell; The formula for calculating the total excavation volume of the remediation unit is: ; in, This represents the total excavation volume for a single remediation unit.
[0012] Preferably, in step S43, the formula for calculating the comprehensive usable coefficient of earthwork is: ; in, The soil texture utilization coefficient is 0.85-1 for clay and loam, and 0.5-0.85 for sandy soil. This is the soil moisture content fit coefficient, which takes a value of 1 when the soil is in the optimal moisture content range, and decreases according to a linear rule after deviating from the optimal range. The ecological compliance coefficient for each zone is set at 0.6-0.8 for ecological restoration zones, 0.9-1 for flexible remediation zones, and a fixed value of 0 for rigid control zones.
[0013] Preferably, the specific formula for the multi-objective optimization function is as follows: ; in, The total cost of earthwork allocation, This represents the total transport distance for all earthwork. This represents the comprehensive loss value caused by ecological disturbance during earthwork construction. To ensure the compliance of the land use planning with the earthwork allocation plan, , , and These are the weighting coefficients.
[0014] Preferably, in step S6, the scheme iteration correction mechanism specifically includes the following: a preset standardized correction trigger threshold is set. When the actual terrain elevation deviation exceeds 0.05m or the earthwork supply and demand calculation deviation exceeds 3%, the model automatically restarts the multi-objective optimization iteration solution and dynamically adjusts the earthwork scheduling volume, transportation route and construction sequence of each remediation unit. When the deviation is within the threshold range, the existing optimal allocation scheme is maintained and executed stably.
[0015] Therefore, the present invention employs the above-mentioned intelligent allocation method for land consolidation earthwork based on surveying and mapping big data, which has the following advantages: (1) In this invention, by constructing a systematic fusion acquisition and standardized processing system of multi-source surveying and mapping big data (airborne LiDAR, UAV aerial survey, GNSS real-scene 3D, 1:500 high-precision topographic and cadastral surveying data, routine remote sensing monitoring data and soil sampling and testing data), a refined 3D digital base for the entire region is generated, realizing the accurate mapping of all elements of the terrain, soil, land features and spatial location of the remediation area, effectively solving the technical problems of single data support and large error in earthwork volume calculation in traditional technology.
[0016] (2) In this invention, by nesting the national land space planning and control system, the legal control layers such as the permanent basic farmland protection red line, ecological protection red line, and urban development boundary are directly embedded into the optimization model as hard constraints for earthwork allocation. Combined with the construction of the topsoil protection constraint model and the ecological landform restoration constraint model, the earthwork allocation scheme is rigidly controllable in terms of planning compliance and ecological protection.
[0017] (3) In this invention, by constructing a multi-objective optimization function for iterative solution, and in conjunction with the dynamic mapping and monitoring of the entire construction process and the scheme iteration correction mechanism, the intelligent scheduling and dynamic closed-loop management of the entire process of earthwork excavation, filling, transportation, disposal and reuse are realized, thereby improving the level of refined and standardized management of land consolidation projects.
[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description
[0019] Figure 1 This is a flowchart illustrating an intelligent allocation method for land consolidation earthwork based on surveying and mapping big data, according to the present invention. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Specific model specifications need to be selected and determined according to the actual specifications of the device, etc. The specific selection calculation method adopts existing technology in the art, and therefore will not be described in detail.
[0021] Example like Figure 1 As shown, this invention provides an intelligent allocation method for land consolidation earthwork based on surveying and mapping big data, comprising the following steps: S1. Collect multi-source surveying and mapping data and perform standardized fusion processing to construct a three-dimensional digital base for the entire land consolidation area; S11. Collect multi-source surveying and mapping data of the remediation area, including UAV aerial high-definition imagery, airborne LiDAR point cloud data, GNSS real-scene 3D model, 1:500 high-precision topographic and cadastral surveying and mapping data, routine remote sensing monitoring data and soil sampling and testing data. S12. Standardize the preprocessing of the collected multi-source surveying and mapping data, including point cloud denoising, image orthorectification, 3D model texture optimization, and coordinate system unification processing. The 2000 National Geodetic Coordinate System and the 1985 National Height Datum are uniformly adopted as the surveying and mapping datum. S13. Perform spatial registration and raster overlay fusion processing on the standardized preprocessed multi-source mapping data to generate a global DEM digital elevation model, a DSM digital surface model, a soil texture spatial distribution map and a surface feature classification map, and construct a global three-dimensional digital base for land consolidation with a resolution of 0.1m.
[0022] S2. Connect with the national land space planning and control system, divide the remediation area into constrained zones, and determine the rigid constraint threshold for earthwork allocation in each zone; S21. Obtain the data of the regional territorial spatial master plan and overlay it with a multi-layered control vector map layer of permanent basic farmland protection red line, ecological protection red line, urban development boundary, land use status classification and remediation project planning boundary; S22. Spatial intersection analysis based on multi-layered control vector maps: A spatial overlay analysis algorithm is used. Based on three layers of control maps—permanent basic farmland protection red line, ecological protection red line, and urban development boundary—overlay determination is performed according to legal control priorities. The entire remediation area is uniquely divided into three constrained zones: rigid control zone, flexible remediation zone, and ecological restoration zone. The control priorities, from highest to lowest, are: permanent basic farmland protection red line > ecological protection red line > urban development boundary. When multiple red lines overlap in any area, the area is uniquely classified according to the attribute of the highest priority red line. Areas without overlap or conflict are classified according to the attribute of a single layer. The specific determination rules are as follows: Rules for determining rigid control zones: Areas located within the permanent basic farmland protection red line, or overlapping areas of both permanent basic farmland and ecological protection red lines, are uniformly classified as rigid control zones; any earthwork excavation, loading, and transportation operations are prohibited in rigid control zones, and only in-situ leveling operations are allowed, strictly ensuring the priority of the permanent protection attributes of cultivated land; Rules for determining ecological restoration zones: Areas located within the ecological protection red line and not involving the permanent basic farmland red line are classified as ecological restoration zones; large-scale earthwork disturbance is prohibited in ecological restoration zones, and only ecologically adaptable earthwork fine-tuning operations are allowed to ensure the integrity of the area's ecological functions; Rules for determining flexible remediation zones: Areas that do not fall within the permanent basic farmland red line or the ecological protection red line, but are located only within the urban development boundary or in general agricultural or remediation-developable areas, are classified as flexible remediation zones; regular earthwork excavation, filling, and allocation operations are permitted in flexible remediation zones, which are the core implementation areas for optimized earthwork allocation.
[0023] S23. Set rigid constraint thresholds for earthwork allocation for each constrained zone. The rigid constraint thresholds include the maximum excavation depth, maximum soil pile height, upper limit of earthwork disturbance area, and set of prohibited earthwork transportation routes for each zone, forming a comprehensive planning rigid constraint system.
[0024] S3. In conjunction with the requirements for regional ecological restoration and management, construct a dual constraint model for topsoil protection and original ecological landform restoration, and form an ecological constraint matrix for earthwork allocation; S31. Construct a topsoil protection constraint model. Based on the soil stratification mapping data of the three-dimensional digital base, delineate the distribution range of the topsoil in the remediation area, set the topsoil protection thickness threshold, and set the area within the topsoil protection range as the earthwork excavation constraint zone. The excavation depth is limited by the bottom boundary elevation value of the constraint zone. The topsoil in the excavation area is stripped layer by layer, stored in a centralized manner, and the stripped soil is included in the soil source sequence of the earthwork allocation matrix. S32. Construct an ecological landform restoration constraint model. Based on the original topography, water system and vegetation distribution data of the three-dimensional digital base, set the spatial protection boundary of the original water system, micro-landform and vegetation distribution, set the ecological disturbance tolerance index, and limit the disturbance range and intensity of earthwork construction. S33. Integrate the constraints of topsoil protection and ecological landform restoration to quantify and form a standardized ecological constraint matrix for earthwork allocation. The ecological constraint matrix uses a spatial raster grid as the basic index unit. Each grid cell stores the corresponding location's partition category identifier, maximum allowable excavation depth, and ecological disturbance coefficient, realizing the rasterized, quantified, and standardized expression of the ecological constraints across the entire region. This serves as the ecological class input constraint parameter when solving the multi-objective optimization function in step S5, and is used to limit the solution boundary of earthwork allocation.
[0025] S4. Based on the topographic mapping data of the three-dimensional digital base, a precise earthwork volume calculation model is built, and the excavation volume, filling volume, usable earthwork volume and waste earthwork volume of each treatment unit are quantitatively calculated in combination with the preset earthwork evaluation parameters. S41. Based on the global three-dimensional digital base, the treatment area is uniformly gridded to form a computational grid of equal size. S42. Collect the measured original elevation and the planned design elevation of each grid unit, calculate the elevation difference grid by grid, and sum the values according to the formula using the grid difference iteration method to obtain the total excavation volume and total fill volume of each treatment unit. The formula for calculating the total fill volume of the remediation unit is: ; in, This refers to the total fill volume for a single remediation unit. , These represent the total number of rows and columns after the grid-based division of the rectification area. For the first unit in the rectification OK The difference between the design elevation and the measured original elevation of the grid. The area of a single grid cell; The formula for calculating the total excavation volume of the remediation unit is: ; in, This represents the total excavation volume for a single remediation unit.
[0026] S43. Retrieve soil texture, soil moisture content and zoning ecological attribute data of the remediation area, calculate the comprehensive usable earthwork coefficient, and combine it with the total excavation volume of each remediation unit to obtain the effective usable excavation volume of each remediation unit. The formula for calculating the comprehensive usability coefficient of earthwork is: ; in, The soil texture utilization coefficient is 0.85-1 for clay and loam, and 0.5-0.85 for sandy soil. This is the soil moisture content fit coefficient, which takes a value of 1 when the soil is in the optimal moisture content range, and decreases according to a linear rule after deviating from the optimal range. The ecological compliance coefficient for each zone is set at 0.6-0.8 for ecological restoration zones, 0.9-1 for flexible remediation zones, and a fixed value of 0 for rigid control zones.
[0027] The formula for calculating the effective usable excavation volume of each remediation unit is as follows: .
[0028] S44. Calculate the difference between the unit fill demand and the effective available excavation volume to obtain the unit waste earthwork volume and the required external purchase earthwork volume, thus completing the quantitative calculation of earthwork parameters for the entire unit.
[0029] S5. Based on the rigid constraints of planning, the ecological constraint matrix and the earthwork calculation results, a multi-objective optimization function is constructed, and the optimal earthwork allocation scheme for the whole region is obtained by solving it. The specific formula for the multi-objective optimization function is as follows: ; in, The total cost of earthwork allocation is optimized with the goal of minimizing the overall cost of earthwork transportation across the entire region, taking into account factors such as the volume of earthwork allocated, transportation distance, and unit transportation cost. The total earthwork transportation distance is calculated with the goal of minimizing the overall earthwork transportation distance across the entire region. The cumulative transportation mileage of all allocated earthwork is then weighted and statistically analyzed. The comprehensive ecological disturbance loss value generated by earthwork construction is calculated by quantifying the construction ecological loss based on the grid parameters of the ecological constraint matrix, and by weighting the allocated earthwork volume with the regional ecological disturbance coefficient. To assess the compliance of earthwork allocation plans with national land planning, the degree of alignment between the allocation plans and the rigid constraints of national land spatial planning and zoning is quantified. This is based on the calculation of the proportion of compliant earthwork construction grids across the entire region, which is the ratio of the area of construction grids that meet the zoning control thresholds and are free from illegal disturbances to the total area of earthwork construction grids across the entire region. , , and These are the weighting coefficients.
[0030] An improved genetic algorithm is used to iteratively solve the multi-objective optimization function, specifically including the following: Population initialization: Using the earthwork allocation volume and earthwork transportation route combination of each remediation unit as chromosome coding objects, the initial feasible solution population is randomly generated using real number coding. All individuals in the population must meet the following four constraints: Earthwork supply and demand balance constraint: The usable excavation output of a single unit ≤ the total usable excavation volume of the unit, and the fill input of a single unit ≥ the fill volume required by the unit; Land planning constraint: All earthwork allocation behaviors do not exceed the three types of spatial control boundaries and do not exceed the zoning earthwork disturbance threshold; Ecological restoration constraint: 100% of the topsoil is stripped and reused, and the ecological disturbance tolerance index does not exceed the preset threshold; Engineering construction constraint: The single earthwork transportation volume does not exceed the rated bearing capacity of the construction equipment, and the transportation route avoids control restricted areas. Fitness calculation: Substitute each individual in the population into the multi-objective optimization function to calculate the corresponding comprehensive objective function value F. The size of F is used as the evaluation standard for individual fitness. The smaller the F value, the better the comprehensive adaptability and optimization effect of the earthwork allocation scheme. Selection operation: A hybrid selection strategy combining elite retention and roulette wheel selection is adopted, directly retaining the elite individuals with the best fitness in the current population to the next generation, and retaining the remaining individuals based on their fitness proportion. Adaptive crossover and mutation operation: Adaptive crossover and adaptive mutation operations are performed on the individuals in the population that are retained after the selection operation, and the crossover probability and mutation probability are dynamically adjusted according to the weight parameters corresponding to the project type. Iterative convergence determination: A maximum number of iterations and a convergence fluctuation threshold are preset. When the fluctuation of the optimal objective function value of the population for several consecutive generations is less than the preset convergence threshold, or when the number of iterations reaches the maximum number of iterations, the algorithm is determined to have converged iteratively and the calculation is terminated. Optimal solution decoding output: Extract the optimal population individual after iterative convergence, decode to obtain the global standardized optimal earthwork allocation matrix, and output the earthwork scheduling volume, optimal transportation path and standardized construction sequence of each excavation unit, filling unit, compliant spoil disposal site and compliant borrow site.
[0031] S6. Establish a dynamic surveying and monitoring mechanism for the entire construction process and an iterative correction mechanism for the scheme, and dynamically optimize and allocate the scheme based on real-time updated surveying data.
[0032] The iterative correction mechanism includes the following: a pre-set standardized correction trigger threshold. When the actual terrain elevation deviation exceeds 0.05m or the earthwork supply and demand calculation deviation exceeds 3%, the model automatically restarts the multi-objective optimization iteration solution and dynamically adjusts the earthwork scheduling volume, transportation route and construction sequence of each remediation unit. When the deviation is within the threshold range, the existing optimal allocation plan is maintained and executed stably.
[0033] Therefore, this invention adopts the above-mentioned intelligent allocation method for land consolidation earthwork based on surveying and mapping big data. It constructs a three-dimensional digital base for the entire region by integrating multi-source surveying and mapping data, completes the constraint zoning by combining the priority of the national land planning red line, calculates earthwork parameters based on a refined earthwork calculation model, constructs a multi-objective optimization model by coupling multiple constraints, solves the optimal allocation scheme by using an improved genetic algorithm, and achieves iterative correction of the scheme by combining construction dynamic monitoring, effectively improving the accuracy, compliance and intelligence level of earthwork allocation.
[0034] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.
Claims
1. A method for intelligent allocation of land consolidation earthwork based on surveying and mapping big data, characterized in that: Includes the following steps: S1. Collect multi-source surveying and mapping data and perform standardized fusion processing to construct a three-dimensional digital base for the entire land consolidation area; S2. Connect with the national land space planning and control system, divide the remediation area into constrained zones, and determine the rigid constraint threshold for earthwork allocation in each zone; S3. In conjunction with the requirements for regional ecological restoration and management, construct a dual constraint model for topsoil protection and original ecological landform restoration, and form an ecological constraint matrix for earthwork allocation; S4. Based on the topographic mapping data of the three-dimensional digital base, a precise earthwork volume calculation model is built, and the excavation volume, filling volume, usable earthwork volume and waste earthwork volume of each treatment unit are quantitatively calculated in combination with the preset earthwork evaluation parameters. S5. Based on the rigid constraints of planning, the ecological constraint matrix and the earthwork calculation results, a multi-objective optimization function is constructed, and the optimal earthwork allocation scheme for the whole region is obtained by solving it. S6. Establish a dynamic surveying and monitoring mechanism for the entire construction process and an iterative correction mechanism for the scheme, and dynamically optimize and allocate the scheme based on real-time updated surveying data.
2. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data as described in claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Collect multi-source surveying and mapping data of the remediation area, including UAV aerial high-definition imagery, airborne LiDAR point cloud data, GNSS real-scene 3D model, 1:500 high-precision topographic and cadastral surveying and mapping data, routine remote sensing monitoring data and soil sampling and testing data. S12. Standardize the preprocessing of the collected multi-source surveying and mapping data, including point cloud denoising, image orthorectification, 3D model texture optimization, and coordinate system unification processing. The 2000 National Geodetic Coordinate System and the 1985 National Height Datum are uniformly adopted as the surveying and mapping datum. S13. Perform spatial registration and raster overlay fusion processing on the standardized preprocessed multi-source mapping data to generate a global DEM digital elevation model, a DSM digital surface model, a soil texture spatial distribution map and a surface feature classification map, and construct a global three-dimensional digital base for land consolidation with a resolution of 0.1m.
3. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 2, characterized in that: Step S2 specifically includes the following steps: S21. Obtain the data of the regional territorial spatial master plan and overlay it with a multi-layered control vector map layer of permanent basic farmland protection red line, ecological protection red line, urban development boundary, land use status classification and remediation project planning boundary; S22. Based on spatial intersection analysis of multi-layer control vector layers, the entire remediation area is divided into three types of constrained zones: rigid control zone, flexible remediation zone, and ecological restoration zone. S23. Set rigid constraint thresholds for earthwork allocation for each constrained zone. The rigid constraint thresholds include the maximum excavation depth, maximum soil pile height, upper limit of earthwork disturbance area, and set of prohibited earthwork transportation routes for each zone, forming a comprehensive planning rigid constraint system.
4. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 3, characterized in that: Step S3 specifically includes the following steps: S31. Construct a topsoil protection constraint model. Based on the soil stratification mapping data of the three-dimensional digital base, delineate the distribution range of the topsoil in the remediation area, set the topsoil protection thickness threshold, and set the area within the topsoil protection range as the earthwork excavation constraint zone. The excavation depth is limited by the bottom boundary elevation value of the constraint zone. The topsoil in the excavation area is stripped layer by layer, stored in a centralized manner, and the stripped soil is included in the soil source sequence of the earthwork allocation matrix. S32. Construct an ecological landform restoration constraint model. Based on the original topography, water system and vegetation distribution data of the three-dimensional digital base, set the spatial protection boundary of the original water system, micro-landform and vegetation distribution, set the ecological disturbance tolerance index, and limit the disturbance range and intensity of earthwork construction. S33. Integrate the constraints of topsoil protection and ecological landform restoration, and quantify them to form a standardized ecological constraint matrix for earthwork allocation.
5. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 4, characterized in that: Step S4 specifically includes the following steps: S41. Based on the global three-dimensional digital base, the treatment area is uniformly gridded to form a computational grid of equal size. S42. Collect the measured original elevation and the planned design elevation of each grid unit, calculate the elevation difference grid by grid, and sum the values according to the formula using the grid difference iteration method to obtain the total excavation volume and total fill volume of each treatment unit. S43. Retrieve soil texture, soil moisture content and zoning ecological attribute data of the remediation area, calculate the comprehensive usable earthwork coefficient, and combine it with the total excavation volume of each remediation unit to obtain the effective usable excavation volume of each remediation unit. S44. Calculate the difference between the unit fill demand and the effective available excavation volume to obtain the unit waste earthwork volume and the required external purchase earthwork volume, thus completing the quantitative calculation of earthwork parameters for the entire unit.
6. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 5, characterized in that: In step S42, the formula for calculating the total fill volume of the remediation unit is: ； in, This refers to the total fill volume for a single remediation unit. , These represent the total number of rows and columns after the grid-based division of the rectification area. For the first unit in the rectification OK The difference between the design elevation and the measured original elevation of the grid. The area of a single grid cell; The formula for calculating the total excavation volume of the remediation unit is: ； in, This represents the total excavation volume for a single remediation unit.
7. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data as described in claim 6, characterized in that: In step S43, the formula for calculating the comprehensive usability coefficient of earthwork is: ； in, The soil texture utilization coefficient is 0.85-1 for clay and loam, and 0.5-0.85 for sandy soil. This is the soil moisture content fit coefficient, which takes a value of 1 when the soil is in the optimal moisture content range, and decreases according to a linear rule after deviating from the optimal range. The ecological compliance coefficient for each zone is set at 0.6-0.8 for ecological restoration zones, 0.9-1 for flexible remediation zones, and a fixed value of 0 for rigid control zones.
8. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 7, characterized in that: The specific formula for the multi-objective optimization function is as follows: ； in, The total cost of earthwork allocation, This represents the total transport distance for all earthwork. This represents the comprehensive loss value caused by ecological disturbance during earthwork construction. To ensure the compliance of the land use planning with the earthwork allocation plan, , , and These are the weighting coefficients.
9. The intelligent allocation method for land consolidation earthwork based on surveying and mapping big data according to claim 8, characterized in that: In step S6, the scheme iteration correction mechanism specifically includes the following: a preset standardized correction trigger threshold is set. When the actual terrain elevation deviation exceeds 0.05m or the earthwork supply and demand calculation deviation exceeds 3%, the model automatically restarts the multi-objective optimization iteration solution and dynamically adjusts the earthwork scheduling volume, transportation route and construction sequence of each remediation unit. When the deviation is within the threshold range, the existing optimal allocation scheme is maintained and executed stably.