Land greening intelligent planning method and system based on regional feature feedback

Abstract

This invention discloses a method and system for intelligent land greening planning based on regional feature feedback, belonging to the field of greening planning technology. The method includes acquiring planning area information, spatially dividing the planning area into functional areas and greenable areas, and filtering greenable areas based on functional areas to obtain the land greening planning area. This invention provides a precise geographic data foundation for subsequent spatial division of planning areas through spatialization and standardization of regional data. By formulating standardized quantitative assignment rules and combining them with the analytic hierarchy process (AHP) to determine indicator weights, it achieves the standardized construction of functional evaluation indicators for grid units. Through functional adaptability, it achieves the quantification and precision of functional area division. By extracting the boundary coordinates of functional areas to construct dual baselines and completing terrain adaptation curvature processing based on regional topography, it achieves the scientific setting of the greening planning area expansion benchmark.

Description

Technical Field

[0001] This invention relates to the field of greening planning technology, specifically to an intelligent land greening planning method and system based on regional feature feedback. Background Technology

[0002] Land greening is a core means of ecological environmental protection and restoration, and an important measure to optimize the spatial development pattern of the land and enhance the regional ecological carrying capacity. It can not only effectively conserve water and soil, regulate regional microclimate, purify air, and improve the natural ecological environment, but also enrich biodiversity and improve the quality of urban and rural living environments. As the core prerequisite for land greening implementation, the scientific nature, rationality, and accuracy of land greening planning directly determine the implementation effect, resource utilization efficiency, and ecological benefits of greening projects. Intelligent land greening planning technology based on regional characteristic feedback can deeply integrate the core characteristics of the planning area, such as geographical topography, ecological environment, and land management, to achieve precise matching between greening layout and regional development, avoiding resource waste caused by blind greening.

[0003] Currently, land greening planning suffers from several problems, including the inability to accurately delineate planning areas, the inability to select suitable greening areas based on regional delineation results, the lack of systematic integration of multi-dimensional regional characteristic data such as geographic spatial boundaries, control scope, land use types, and national land space control levels, a disconnect between planning schemes and actual regional development needs and ecological foundations, subjective division of functional and greening areas, a lack of quantitative indicator systems and scientific delineation methods, reliance on manual experience to determine functional and greening areas, vague delineation boundaries, and the potential for core functional areas to be encroached upon and inaccurate selection of greening areas. Greening areas are often roughly delineated based solely on green coverage requirements, lacking standardized spatial expansion and boundary marking methods, and ignoring the spatial connectivity between greening areas and functional areas. This can lead to scattered greening layouts and difficulty in achieving large-scale ecological benefits. Summary of the Invention

[0004] To address the aforementioned technical problems, this paper provides a land greening intelligent planning method and system based on regional feature feedback. This technical solution solves the problems mentioned in the background technology, such as the inability to accurately divide the planning area, the inability to select suitable greening areas based on the regional division results, the lack of systematic integration of multi-dimensional regional feature data such as geographic spatial boundaries, control scope, land use type, and national land space control level, the disconnect between the planning scheme and the actual development needs and ecological base of the region, the subjectivity of functional and greening area division, the lack of quantitative indicator system and scientific division method, the reliance on manual experience to determine functional areas and greening areas, the vague boundary division, the easy occurrence of core functional areas being squeezed out, the inaccurate selection of greening areas, the simple rough delineation of greening scope based on green coverage rate requirements, the lack of standardized spatial expansion and boundary marking methods, the neglect of the spatial connection between greening areas and functional areas, and the problem of scattered greening layout and difficulty in forming ecological benefits on a large scale.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A smart land greening planning method based on regional feature feedback includes: Obtain planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data; Based on the planning area information, the geospatial boundary coordinates, control scope, geographical topography and ecological environment data are integrated to form the original dataset; Based on the geospatial boundary coordinates, geospatial information of the planning area is obtained. The geospatial information of the planning area represents the geographic map corresponding to the planning area. The geographic map includes several grid cells. Spatial coordinate registration is performed on the original dataset to match all data to a unified geographic grid cell of the planning area, resulting in a spatially associated dataset, where each sub-item of the spatially associated dataset corresponds to each geographic grid cell. Based on the spatial association dataset, the planning area is spatially divided into functional areas and greenable areas. The functional areas include core functional areas for production, living and ecology, and the greenable areas are the greenable spaces within the planning area other than the functional areas. Based on functional zones, areas suitable for greening are screened to obtain land greening planning areas.

[0006] Preferably, the step of spatially dividing the planning area into functional areas and greenable areas based on the spatial association dataset specifically includes: The spatial correlation dataset is preprocessed to obtain a preprocessed dataset. All numerical indicators in the preprocessed dataset are normalized to obtain a standardized dataset; Based on a standardized dataset and in accordance with the principles of land and space planning, core indicators corresponding to each geographic grid unit are obtained. These core indicators include land use type and land and space control level. The weight coefficients for each core indicator are determined based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the natural breakpoint method and functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units. Based on the core functional units, the core functional units that are in contact with the regional boundaries are merged to obtain functional areas, clarify the geographical spatial range and control boundaries of each functional area, and form a spatial distribution map of functional areas. Based on the overall control scope of the planning area, the spatial scope of functional areas is eliminated, and the spatial areas that meet the conditions for greening are designated as greenable areas. The greenable conditions are non-construction land, non-permanent basic farmland, and land ecological base that can support vegetation growth. Spatial boundaries of greenable areas are marked to form a spatial distribution map of greenable areas. Spatial and attribute data of functional areas and green areas are linked and stored to construct a spatial division database of the planning area.

[0007] Preferably, the process of obtaining core indicators corresponding to each geographic grid unit based on a standardized dataset and in accordance with territorial spatial planning principles specifically includes: Based on the standardized dataset, the land use feature subset is obtained, which includes land use classification data, national land space land use status survey vector data, and land ownership registration data, thus obtaining the basic land use dataset. The land use types in the basic land use dataset are categorized into four levels: production function, living function, ecological function, and unused. A legal merging rule table for land use types is then developed, resulting in the legal merging rules. Based on the statutory merging rules, the original land use classification data in the land use basic dataset are batch merged to remove non-standard data with inconsistent classification standards, resulting in a standardized land use type vector dataset. Based on the geographic grid unit vector base map in the geographic map corresponding to the planning area, the standardized land use type vector dataset is spatially overlaid with the geographic grid unit to obtain the land use type proportion data of each grid unit, that is, the area proportion of each type of land in a single grid, forming a gridded land use proportion dataset. Based on the gridded land use proportion dataset, the main type determination rule is set: if the area proportion of a certain land use type in a certain grid cell exceeds half, the main land use type of the grid cell is determined to be that type; if no type has an area proportion exceeding half, it is determined to be a composite land use type, and the main land use type determination result of each grid cell is obtained. Based on land use analysis, ensure the quantitative assignment rules corresponding to each land use type; By directly assigning values ​​to mesh cells of a single primary type, initial values ​​for single-type quantization are obtained. For grid cells with composite land use types, a weighted average value is assigned based on the area proportion of each type to obtain the initial quantitative value of the composite grid. By integrating the initial quantitative values ​​of single-type grids and composite grids, the initial quantitative values ​​of land use types for all geographic grid units in the planning area are obtained. The initial values ​​of land use type quantification are bound to the unique identifiers of grid units to form a dataset of initial values ​​for land use type indicators.

[0008] Preferably, the step of obtaining the core indicators corresponding to each geographic grid unit based on a standardized dataset and in accordance with the principles of territorial spatial planning further includes: Based on the standardized dataset, the land use feature subset and the ecological environment feature subset are extracted and integrated to obtain the basic dataset of control level. This dataset includes three-line vector data, ecological control zoning data, and land development control data. Obtain spatial control planning information corresponding to the planning area, including Level 1 control, Level 2 control, Level 3 control, and the legally defined boundaries corresponding to each control level; Based on spatial control planning information, spatial integration is performed on the three-line data and ecological control zoning data in the basic data of control level, and spatially overlapping control boundaries are eliminated to form a unified statutory vector base map of land spatial control level; By performing precise spatial matching between the statutory vector base map of the land space control level and the geographic grid unit corresponding to the planning area, a preliminary result of the statutory control level corresponding to each grid unit is obtained; Based on the land development control data in the basic dataset of control levels, the preliminary results of the statutory control levels are checked for compliance with actual control, and the revised control level results are obtained. If the control level of the statutory vector base map of the land space control level corresponding to a certain grid unit is different from the control level in the land development control data, then the grid unit is marked as a check abnormal grid unit, and the check abnormal grid unit is manually reviewed and its level is corrected. Based on the preset control level quantification assignment rules, all grid cells in the corrected control level result are assigned values ​​to obtain the initial control level quantification value; If a grid cell is a cross-control level grid cell, then the initial value of the cross-control level grid is obtained by weighting the values ​​according to the area ratio of each control level in the grid. The cross-control level grid cell means that the grid cell is cut by the boundaries of two or more control levels. By integrating the initial quantitative values ​​of the control level and the initial quantitative values ​​of cross-level grids, the initial quantitative values ​​of the land space control level of all grid units in the planning area are obtained, and bound to the unique identifier of the grid unit to form a dataset of initial values ​​of land space control level indicators.

[0009] Preferably, the step of dividing the geographic grid units into core functional units and non-core functional units based on the natural breakpoint method and functional adaptability specifically includes: Based on the functional adaptability of each geographic grid unit, obtain the maximum and minimum functional adaptability values; Based on the maximum and minimum functional adaptability values, and using the functional adaptability corresponding to each geographic grid unit as a basis, the functional baseline adaptability is obtained based on data normalization. Based on the requirement of binary grouping, set the grouping threshold for fit; Based on the adaptation grouping threshold, geographic grid cells whose functional baseline adaptation exceeds the adaptation grouping threshold are taken as the first geographic grid cells, and the first grid cell group is obtained. Geographic grid cells whose functional baseline adaptation does not exceed the adaptation grouping threshold are used as second geographic grid cells to obtain the second grid cell group. Based on the first and second grid cell groups, the corresponding within-group variances are obtained; The sum of the within-group variance of the first grid cell group and the within-group variance of the second grid cell group is used as the data bias coefficient; The fitness grouping threshold is adjusted until the data deviation coefficient reaches the minimum value to obtain the fitness baseline threshold. Geographic grid units are divided according to the adaptation benchmark threshold. Geographic grid units whose functional benchmark adaptation exceeds the adaptation benchmark threshold are designated as core functional units, while geographic grid units whose functional benchmark adaptation does not exceed the adaptation benchmark threshold are designated as non-core functional units.

[0010] Preferably, the step of screening areas suitable for greening based on functional zones to obtain land greening planning areas specifically includes: Based on the needs of land greening, obtain the benchmark green coverage rate; Based on the planning area information, obtain the total area of ​​the planning area; The product of the total area of ​​the planned area and the benchmark green coverage rate shall be used as the greening requirement area; Based on the functional areas, obtain the standardized set of functional area boundary coordinates; Based on the standardized functional area boundary coordinate set, obtain the straight-line distance between any two points, take the two boundary points corresponding to the maximum straight-line distance as the endpoints of the first baseline, and the line connecting the two points is the initial line of the first baseline. Using the initial line of the first baseline as a reference, the standardized functional area boundary coordinates located on the same side of the initial line of the first baseline are divided into the same dataset to obtain the first coordinate set and the second coordinate set of the area boundary; Obtain the perpendicular distance from any point in the first coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum perpendicular distance as the first boundary point; Obtain the vertical distance from any point in the second coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum vertical distance as the second boundary point; Connect the first boundary point and the second boundary point to obtain the initial line of the second baseline; Based on the planning area information, a set of baseline terrain curvature rules is formulated; Based on the geospatial information of the planning area, obtain the size information of the geographic grid units; Based on the bending rule set and the geographic grid cell size information, the initial lines of the first and second baselines are subjected to terrain-adaptive bending processing to obtain the first and second baselines. The area is expanded along both sides of the first and second baselines until the area of ​​the expanded area that can be greened reaches the area required for greening. The area that can be greened at this point is then designated as the land greening planning area.

[0011] Furthermore, a land greening intelligent planning system based on regional feature feedback is proposed to implement the planning method described above, including: The main control module is used to determine the weight coefficients corresponding to each core indicator based on the analytic hierarchy process (AHP). Based on the core indicators and weight coefficients corresponding to each geographic grid unit, it obtains the functional adaptability of each geographic grid unit in the planning area by weighted summation. Based on the functional adaptability, it divides the geographic grid units into core functional units and non-core functional units according to the natural breakpoint method. It takes the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area. Based on the functional areas, it obtains the first baseline and the second baseline. Based on the first baseline and the second baseline, it obtains the land greening planning area. The information acquisition module is used to acquire planning area information. Based on the planning area information, it integrates geospatial boundary coordinates, control scope, geographic topography and ecological environment data to form an original dataset, and acquires geospatial information of the planning area based on the geospatial boundary coordinates. The evaluation module is used to perform spatial coordinate registration on the original dataset, match all data to the unified geographic grid unit of the planning area, and obtain a spatially associated dataset. Based on the standardized dataset, the core indicators corresponding to each geographic grid unit are obtained according to the national land spatial planning guidelines. The display module interacts with the main control module and is used to output the display function area, the greenable area, the first baseline and the second baseline, and the land greening planning area.

[0012] Optionally, the main control module specifically includes: The control unit is used to take the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area, obtain the first benchmark line and the second benchmark line according to the functional area, and obtain the land greening planning area according to the first benchmark line and the second benchmark line. An information receiving unit, which interacts with the information acquisition module and the evaluation module, is used to receive data and transmit it to the spatial partitioning unit; The spatial division unit is used to determine the weight coefficient corresponding to each core indicator based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units according to the natural breakpoint method.

[0013] Optionally, the information acquisition module specifically includes: The first acquisition unit is used to acquire planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data. The second acquisition unit is used to integrate geospatial boundary coordinates, control scope, geographic topography and ecological environment data to form an original dataset based on the planning area information, and to acquire geospatial information of the planning area based on the geospatial boundary coordinates.

[0014] Optionally, the evaluation module specifically includes: The first evaluation unit is used to perform spatial coordinate registration on the original dataset, matching all data to a unified geographic grid unit of the planning area to obtain a spatially associated dataset. The second evaluation unit is used to obtain the core indicators corresponding to each geographic grid unit based on a standardized dataset and in accordance with the principles of territorial spatial planning.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes a land greening intelligent planning method and system based on regional feature feedback. By spatializing and standardizing regional data, it provides a precise geographic data foundation for subsequent planning area spatial division. By formulating standardized quantitative assignment rules and combining them with the analytic hierarchy process to determine indicator weights, it realizes the standardized construction of grid unit functional evaluation indicators. Through functional adaptability, it achieves the quantification and precision of functional area division. By extracting functional area boundary coordinates to construct dual baselines and completing terrain adaptation curvature processing according to regional topography, it realizes the scientific setting of greening planning area expansion benchmarks, providing a spatial boundary foundation that fits regional characteristics for the subsequent precise expansion of greening areas. Attached Figure Description

[0016] Figure 1 This is a flowchart of an intelligent land greening planning method based on regional feature feedback proposed in this invention; Figure 2 This is a flowchart illustrating the process of obtaining functional areas and greenable areas in this invention. Figure 3 This is a flowchart illustrating the process of obtaining the initial value dataset for land use type indicators in this invention. Figure 4 This is a flowchart illustrating the process of obtaining the initial value dataset of the land space control level indicators in this invention. Figure 5 This is a structural block diagram of a land greening intelligent planning system based on regional feature feedback proposed in this invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 - Figure 4 As shown, an intelligent land greening planning method based on regional feature feedback in an embodiment of the present invention includes: Obtain planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data; Based on the planning area information, the geospatial boundary coordinates, control scope, geographical topography and ecological environment data are integrated to form the original dataset; Based on the geospatial boundary coordinates, geospatial information of the planning area is obtained. The geospatial information of the planning area represents the geographic map corresponding to the planning area. The geographic map includes several grid cells. Spatial coordinate registration is performed on the original dataset to match all data to a unified geographic grid cell of the planning area, resulting in a spatially associated dataset, where each sub-item of the spatially associated dataset corresponds to each geographic grid cell. Based on the spatial association dataset, the planning area is spatially divided into functional areas and greenable areas. The functional areas include core functional areas for production, living and ecology, and the greenable areas are the greenable spaces within the planning area other than the functional areas. Specifically, based on the spatial association dataset, the planning area is spatially divided into functional areas and greenable areas, including: The spatial correlation dataset is preprocessed to obtain a preprocessed dataset. All numerical indicators in the preprocessed dataset are normalized to obtain a standardized dataset; Based on a standardized dataset and in accordance with the principles of land and space planning, core indicators corresponding to each geographic grid unit are obtained. These core indicators include land use type and land and space control level. The weight coefficients for each core indicator are determined based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the natural breakpoint method and functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units. Based on the core functional units, the core functional units that are in contact with the regional boundaries are merged to obtain functional areas, clarify the geographical spatial range and control boundaries of each functional area, and form a spatial distribution map of functional areas. Based on the overall control scope of the planning area, the spatial scope of functional areas is eliminated, and the spatial areas that meet the conditions for greening are designated as greenable areas. The greenable conditions are non-construction land, non-permanent basic farmland, and land ecological base that can support vegetation growth. Spatial boundaries of greenable areas are marked to form a spatial distribution map of greenable areas. Spatial and attribute data of functional areas and green areas are linked and stored to construct a spatial division database of the planning area.

[0019] In this scheme, a standardized dataset is obtained by preprocessing the spatially correlated dataset and normalizing the numerical indicators. This eliminates the differences in dimensions between different indicators, data noise, and outlier interference, and solves the problems of disordered original data and lack of comparability of indicators. It provides unified, accurate, and comparable quantitative data support for subsequent core indicator extraction and functional adaptability calculation. The two core indicators of land use type and land space control level are extracted strictly in accordance with the land space planning guidelines, ensuring that the spatial division of the planning area fully conforms to the statutory planning requirements and regional land space control rules, thus guaranteeing the compliance and authority of the spatial division results. The weight coefficients of each core indicator are determined based on the analytic hierarchy process, and the quantitative weight allocation is carried out according to the actual importance of the indicators in the spatial functional division.

[0020] In this embodiment, when preprocessing the spatially correlated dataset, the following method is adopted: The principle is to remove outliers from numerical data, with the removal range being [missing information]. ,in The mean of the data. To normalize all numerical indicators in the preprocessed dataset, min-max normalization is used to map the indicators to the [0, 1] interval, with the standard deviation as the normalization value.

[0021] Land use type directly determines the greening suitability of grid units—the greening needs, suitability patterns, and ecological benefits of ecological, residential, and production land differ significantly (e.g., ecological land has the highest greening priority, while unused land has the lowest). This is a core dimension for calculating functional suitability and is directly related to the core objective of "precise selection of greening areas," making its impact more direct and critical. Land use type is standardized into index values ​​through "four-level merging - main type determination - quantitative assignment - weighted integration," covering all dimensions of production, residential, ecological, and unused land. The quantification granularity is finer (direct assignment for single types, weighted assignment for composite types), contributing more to the calculation of functional suitability and requiring higher weighting to reflect its dominant quantitative role.

[0022] In line with the principle of coordinated development of production, living and ecological spaces: The "Guidelines for the Compilation of the Overall Territorial Spatial Planning" clearly states the core requirement of "coordinated layout of production, living and ecological spaces". Land use type is the direct basis for dividing "production, living and ecological" spaces. Its weight ratio is higher than that of control level, which can ensure that the functional area division is more in line with the essence of spatial function and avoid deviating from the basic spatial attributes due to overemphasis on control constraints. Therefore, the weight coefficient of land use type is 0.55.

[0023] The land space control levels (Level 1 / Level 2 / Level 3) are determined by national, provincial, and municipal statutory plans (including the "three lines" control such as ecological protection red lines and permanent basic farmland). These levels are inviolable constraints on greening plans. For example, greening in Level 1 control areas must strictly adhere to the requirements for native vegetation protection, while greening in Level 3 control areas has greater flexibility. The constraints of these levels run through the entire planning process and must be given sufficient weight to ensure planning compliance. If the weight of the control level is too low, it may lead to the neglect of constraints such as legally prohibited greening areas and ecologically sensitive areas in the calculation of functional adaptability, causing conflicts between greening plans and land space control. Giving it a weight of 0.45 avoids excessive suppression of greening adaptability by control constraints while ensuring that the division of functional areas does not exceed the legal boundaries, achieving a balance of "adaptability first, compliance as a safety net".

[0024] Specifically, based on standardized datasets and in accordance with territorial spatial planning principles, core indicators corresponding to each geographic grid unit are obtained, including: Based on the standardized dataset, the land use feature subset is obtained, which includes land use classification data, national land space land use status survey vector data, and land ownership registration data, thus obtaining the basic land use dataset. The land use types in the basic land use dataset are categorized into four levels: production function, living function, ecological function, and unused. A legal merging rule table for land use types is then developed, resulting in the legal merging rules. Based on the statutory merging rules, the original land use classification data in the land use basic dataset are batch merged to remove non-standard data with inconsistent classification standards, resulting in a standardized land use type vector dataset. Based on the geographic grid unit vector base map in the geographic map corresponding to the planning area, the standardized land use type vector dataset is spatially overlaid with the geographic grid unit to obtain the land use type proportion data of each grid unit, that is, the area proportion of each type of land in a single grid, forming a gridded land use proportion dataset. Based on the gridded land use proportion dataset, the main type determination rule is set: if the area proportion of a certain land use type in a certain grid cell exceeds half, the main land use type of the grid cell is determined to be that type; if no type has an area proportion exceeding half, it is determined to be a composite land use type, and the main land use type determination result of each grid cell is obtained. Based on land use analysis, ensure the quantitative assignment rules corresponding to each land use type; By directly assigning values ​​to mesh cells of a single primary type, initial values ​​for single-type quantization are obtained. For grid cells with composite land use types, a weighted average value is assigned based on the area proportion of each type to obtain the initial quantitative value of the composite grid. By integrating the initial quantitative values ​​of single-type grids and composite grids, the initial quantitative values ​​of land use types for all geographic grid units in the planning area are obtained. The initial values ​​of land use type quantification are bound to the unique identifiers of grid units to form a dataset of initial values ​​for land use type indicators.

[0025] This solution precisely extracts land use characteristic subsets containing land use classification, current status survey vectors, and land ownership registration data from a standardized dataset, integrating them to form a basic land use dataset. This centralized collection of core land use-related data provides comprehensive and complete basic data support for subsequent classification, merging, and quantitative analysis. Legally mandated classification and merging are implemented, achieving standardized land use types merging at four levels: production, residential, ecological, and unused. A legally mandated merging rule table is established, and based on these rules, the original classification data is batch-merged and non-standard data is removed, ensuring that land use type classification aligns with national land spatial planning guidelines. This unifies classification standards and guarantees the compliance and uniformity of land use type analysis. The standardized land use type vector dataset is spatially overlaid with geographic grid units to obtain the land use type proportion data for each grid unit, achieving spatial grid-based quantification of land use types. This refines regional land use characteristics to the smallest planning unit, making the land use structure of each grid clear and quantifiable. Clear rules for determining the main type are established, enabling objective division of grid types. Rules specifying that a majority of types constitute a single main type, while those with less than half are composite types, standardize the determination of the main land use type for each grid unit.

[0026] It should be noted that in this scheme, the quantitative assignment rules for land use types are as follows: ecological land is assigned the highest value (10): it is in line with the core ecological goals of greening planning and has the highest planning priority. Ecological land (such as forest land, grassland, wetland, river and lake water surface, etc.) is the core carrier of the national land space ecological security pattern and the core matching area of ​​land greening planning. Its land base itself has good vegetation growth conditions. One of the core goals of greening planning is to consolidate the ecological function of ecological land, which is highly consistent with the core orientation of greening planning. At the same time, in national land space planning, ecological space is a rigid protection space, and its functional priority is higher than that of production and living space. Therefore, it is assigned the highest value of 10, which reflects its core weight ratio in the functional matching degree calculation. The value of residential land is second (9): matching the public service orientation of greening, the planning priority is second only to ecological residential land (such as urban residential land, public service land, rural homestead, etc.). It is the core area for optimizing the living environment. The core role of greening planning is to improve the quality of the living environment and improve the public service functions (such as landscape greening, leisure greening, noise reduction and dust reduction greening). It is an important service object of greening planning, and its planning priority is second only to ecological space. Moreover, the development and construction degree of residential land is relatively high. Greening needs to be accurately laid out as a supporting function. Its greening adaptability and planning importance are slightly lower than those of ecological land. Therefore, it is assigned a value of 9, forming a numerical level difference with ecological land, reflecting the gradient distinction of priority.

[0027] The value of production land is assigned again (8): following the principle of efficient use of production space, greening is a supporting protective function. The core function of production land (such as cultivated land, industrial and mining land, transportation and water conservancy facilities land, etc.) is production, construction and industrial development. In the land space planning, the principle of intensive and efficient production space is followed. Greening is only a supporting function (such as farmland shelterbelt, industrial and mining shelter greening, road green belt), and is not the core area of ​​greening planning. Its greening adaptability and planning priority are lower than ecological and living space. Therefore, the value is assigned 8, forming a numerical level difference with the living type, which not only reflects the planning positioning of production space, but also ensures the numerical differentiation of the three core land types.

[0028] The value of unused land is assigned to an extremely low value (1): This reflects its extremely poor greening adaptability and forms an extreme value distinction with the core land types. The ecological base of unused land (such as bare rock, sandy land, severely saline-alkali land, bare land, etc.) is extremely weak. The soil, hydrology, topography and other conditions cannot support the growth of conventional vegetation. It is a secondary area in greening planning and can only carry out ecological protection light greening according to the actual situation. Its greening adaptability and planning importance are far lower than the three core land types of production, life and ecology. Therefore, it is assigned an extremely low value of 1, forming a numerical level difference of 7-9 with the three core land types. The extreme value clearly reflects its low adaptability and can quickly distinguish non-core greening adaptability areas in the functional adaptability calculation.

[0029] Specifically, based on standardized datasets and in accordance with territorial spatial planning principles, the core indicators corresponding to each geographic grid unit are obtained, including: Based on the standardized dataset, the land use feature subset and the ecological environment feature subset are extracted and integrated to obtain the basic dataset of control level. This dataset includes three-line vector data, ecological control zoning data, and land development control data. Obtain spatial control planning information corresponding to the planning area, including Level 1 control, Level 2 control, Level 3 control, and the legally defined boundaries corresponding to each control level; Based on spatial control planning information, spatial integration is performed on the three-line data and ecological control zoning data in the basic data of control level, and spatially overlapping control boundaries are eliminated to form a unified statutory vector base map of land spatial control level; By performing precise spatial matching between the statutory vector base map of the land space control level and the geographic grid unit corresponding to the planning area, a preliminary result of the statutory control level corresponding to each grid unit is obtained; Based on the land development control data in the basic dataset of control levels, the preliminary results of the statutory control levels are checked for compliance with actual control, and the revised control level results are obtained. If the control level of the statutory vector base map of the land space control level corresponding to a certain grid unit is different from the control level in the land development control data, then the grid unit is marked as a check abnormal grid unit, and the check abnormal grid unit is manually reviewed and its level is corrected. Based on the preset control level quantification assignment rules, all grid cells in the corrected control level result are assigned values ​​to obtain the initial control level quantification value; If a grid cell is a cross-control level grid cell, then the initial value of the cross-control level grid is obtained by weighting the values ​​according to the area ratio of each control level in the grid. The cross-control level grid cell means that the grid cell is cut by the boundaries of two or more control levels. By integrating the initial quantitative values ​​of the control level and the initial quantitative values ​​of cross-level grids, the initial quantitative values ​​of the land space control level of all grid units in the planning area are obtained, and bound to the unique identifier of the grid unit to form a dataset of initial values ​​of land space control level indicators.

[0030] This scheme extracts land use and ecological environment characteristic subsets from standardized datasets and integrates them into a basic dataset for control levels. It fully covers core control data of territorial spatial planning, such as the three-line vector, ecological control zoning, and land development control, providing comprehensive and legally compliant basic data support for determining the control level of grid units. The three-line and ecological control zoning data are spatially fused and overlapping control boundaries are removed to form a unified legal vector base map of territorial spatial control levels. This ensures the legality, uniformity, and spatial accuracy of the determination of control levels of grid units. The unified legal control level vector base map is spatially precisely matched with geographic grid units, refining territorial spatial control levels to the smallest planning grid unit. This makes the legal control attributes of each grid unit clear and quantifiable, achieving a refined spatial representation of control levels.

[0031] It should be noted that in this scheme, the quantitative assignment rule for the control level is as follows: Level 1 control has the highest assignment value (10): it has the highest rigid control intensity and the strongest greening adaptability and planning constraint. The Level 1 control area is the core rigid control area in the territorial spatial planning, which mainly includes the ecological protection red line, permanent basic farmland, and the core construction area within the urban development boundary. Its control requirements are legally defined at the national and provincial levels. Development and utilization and greening construction must strictly follow the legal principles. Greening planning must prioritize adapting to its control requirements (such as greening within the ecological protection red line is mainly based on the protection of native vegetation, and greening within the permanent basic farmland is mainly based on farmland shelterbelts). Its control rigidity and greening planning constraint are the strongest, so it is assigned the highest value of 10, which reflects its core influence in the calculation of functional adaptability.

[0032] The secondary control area is assigned the value of 8: the intensity of key control is moderate, and greening is a supporting function with moderate adaptability. The secondary control area is the key control area in the land space planning, mainly including the general construction area, key agricultural development area, and general ecological control area within the urban development boundary. The control requirements are defined at the municipal and county levels. The development and utilization and greening construction have a certain degree of flexibility. The core role of greening planning is to support the core functions of the area (such as landscape greening in the general construction area of ​​the city and ecological protection greening in the key agricultural development area). Its control rigidity and greening adaptability are lower than those of the primary control area, so it is assigned the value of 8, forming two numerical levels with the primary control area, reflecting the gradient distinction of control intensity.

[0033] The third-level control is assigned the lowest value (6): the general control is the most flexible, and the greening adaptability and constraint are the weakest. The third-level control area is the general control area in the land space planning, which mainly includes the rural general area outside the urban development boundary, the non-core ecological control area, and scattered unused land. The control requirements are the most relaxed, and the development and utilization and greening construction are the most flexible. The greening plan can be flexibly laid out according to the regional characteristics and greening needs. It is the area for flexible adjustment of greening plan. Its control rigidity and greening plan constraint are the weakest. Therefore, it is assigned a value of 6, which forms two numerical level differences with the second-level control, matching the three-level gradient division of the control level.

[0034] Specifically, based on the natural breakpoint method and functional adaptability, geographic grid units are divided into core functional units and non-core functional units, including: Based on the functional adaptability of each geographic grid unit, obtain the maximum and minimum functional adaptability values; Based on the maximum and minimum functional adaptability values, and using the functional adaptability corresponding to each geographic grid unit as a basis, the functional baseline adaptability is obtained based on data normalization. Based on the requirement of binary grouping, set the grouping threshold for fit; Based on the adaptation grouping threshold, geographic grid cells whose functional baseline adaptation exceeds the adaptation grouping threshold are taken as the first geographic grid cells, and the first grid cell group is obtained. Geographic grid cells whose functional baseline adaptation does not exceed the adaptation grouping threshold are used as second geographic grid cells to obtain the second grid cell group. Based on the first and second grid cell groups, the corresponding within-group variances are obtained; The sum of the within-group variance of the first grid cell group and the within-group variance of the second grid cell group is used as the data bias coefficient; The fitness grouping threshold is adjusted until the data deviation coefficient reaches the minimum value to obtain the fitness baseline threshold. Geographic grid units are divided according to the adaptation benchmark threshold. Geographic grid units whose functional benchmark adaptation exceeds the adaptation benchmark threshold are designated as core functional units, while geographic grid units whose functional benchmark adaptation does not exceed the adaptation benchmark threshold are designated as non-core functional units.

[0035] In this scheme, the original fitness scores are normalized using the maximum and minimum values ​​to obtain a baseline fitness score. This eliminates the range differences and inconsistencies in the quantification scale of the original fitness scores, ensuring that the functional fitness of all geographic grid units within the planning area is on a uniform and comparable quantitative dimension. After grouping the grid units according to a threshold, the sum of the variances within two groups is used as the data deviation coefficient. This transforms the rationality of the grouping into a calculable and comparable quantitative indicator, freeing the functional unit grouping from vague empirical judgments and providing clear numerical criteria, thus ensuring the rigor and scientific nature of the grouping process. By repeatedly adjusting the fitness score grouping threshold and calculating the corresponding data deviation coefficient until the coefficient reaches its minimum value, the baseline fitness score threshold is determined. This achieves the optimal grouping effect, maximizing both intra-group similarity and inter-group differences after the division.

[0036] It should be noted that the fit grouping threshold is in the range [0, 1].

[0037] Based on functional zones, areas suitable for greening are screened to obtain land greening planning areas.

[0038] Specifically, based on functional zones, areas suitable for greening are screened to obtain land greening planning areas, including: Based on the needs of land greening, obtain the benchmark green coverage rate; Based on the planning area information, obtain the total area of ​​the planning area; The product of the total area of ​​the planned area and the benchmark green coverage rate shall be used as the greening requirement area; Based on the functional areas, obtain the standardized set of functional area boundary coordinates; Based on the standardized functional area boundary coordinate set, obtain the straight-line distance between any two points, take the two boundary points corresponding to the maximum straight-line distance as the endpoints of the first baseline, and the line connecting the two points is the initial line of the first baseline. Using the initial line of the first baseline as a reference, the standardized functional area boundary coordinates located on the same side of the initial line of the first baseline are divided into the same dataset to obtain the first coordinate set and the second coordinate set of the area boundary; Obtain the perpendicular distance from any point in the first coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum perpendicular distance as the first boundary point; Obtain the vertical distance from any point in the second coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum vertical distance as the second boundary point; Connect the first boundary point and the second boundary point to obtain the initial line of the second baseline; Based on the planning area information, a set of baseline terrain curvature rules is formulated; Based on the geospatial information of the planning area, obtain the size information of the geographic grid units; Based on the bending rule set and the geographic grid cell size information, the initial lines of the first and second baselines are subjected to terrain-adaptive bending processing to obtain the first and second baselines. The area is expanded along both sides of the first and second baselines until the area of ​​the expanded area that can be greened reaches the area required for greening. The area that can be greened at this point is then designated as the land greening planning area.

[0039] This plan determines the benchmark green coverage rate based on land greening needs, accurately calculates the required green area based on the total area of ​​the planning region, and ensures that the planned land greening area aligns with the actual needs of regional greening development. It constructs a dual benchmark line based on the standardized boundary coordinates of functional areas, ensuring that the delineation of greening planning areas always revolves around the spatial form of functional areas. This avoids spatial conflicts between greening areas and core functional areas of production, living, and ecology from a spatial benchmark perspective, ensuring the rationality of the national land space functional layout and achieving coordinated development of production, living, and ecological spaces. The first benchmark line is determined by extracting the extreme distance values ​​of the functional area boundary coordinates. The endpoints of the baselines are determined by the extreme values ​​of the vertical distances, and the initial lines of the two baselines are then used to determine the endpoints of the second baseline. This ensures that the initial lines of the two baselines accurately conform to the overall spatial outline of the functional area, forming a scientific spatial framework for the delineation of the green area. This lays a spatial foundation that conforms to the characteristics of the functional area for the orderly expansion of the green planning area. Based on the geographic information of the planning area, a set of baseline terrain curvature rules is formulated. Combined with the size of the geographic grid units, the initial baselines are subjected to terrain-adaptive curvature processing, transforming the baselines from a straight line into a form that conforms to the actual terrain and topography of the area. This ensures that the site selection of the green planning area conforms to the natural geographic characteristics of the area and improves the practicality of the planning scheme.

[0040] It should be noted that the specific set of rules for the curvature of the baseline is as follows: For gentle sections with terrain relief ≤15° and slope ≤25°: smooth curves are made along the terrain contour lines, with a curve fitting radius of curvature ≥50m to ensure the line is continuous without sharp angles; For slightly steep sections with a topographic relief of 15° to 30° and a slope of 25° to 35°: follow the topographic contour lines and make zigzag bends with a bend angle of ≤120° to avoid sharp bends; For steep slopes with terrain relief >30° and slope >35°: make local offset corrections to the baseline, shifting it 10-30m towards the flatter side of the terrain to avoid steep slope areas. When encountering natural waterways such as rivers and valleys: the baseline curves along the direction of the waterway, conforms to the natural terrain boundary, and preserves the space for connecting ecological corridors.

[0041] Reference Figure 5 As shown, further, combining the above-mentioned intelligent land greening planning method based on regional feature feedback, a land greening intelligent planning system based on regional feature feedback is proposed, including: The main control module is used to determine the weight coefficients corresponding to each core indicator based on the analytic hierarchy process (AHP). Based on the core indicators and weight coefficients corresponding to each geographic grid unit, it obtains the functional adaptability of each geographic grid unit in the planning area by weighted summation. Based on the functional adaptability, it divides the geographic grid units into core functional units and non-core functional units according to the natural breakpoint method. It takes the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area. Based on the functional areas, it obtains the first baseline and the second baseline. Based on the first baseline and the second baseline, it obtains the land greening planning area. The information acquisition module is used to acquire planning area information. Based on the planning area information, it integrates geospatial boundary coordinates, control scope, geographic topography and ecological environment data to form an original dataset, and acquires geospatial information of the planning area based on the geospatial boundary coordinates. The evaluation module is used to perform spatial coordinate registration on the original dataset, match all data to the unified geographic grid unit of the planning area, and obtain a spatially associated dataset. Based on the standardized dataset, the core indicators corresponding to each geographic grid unit are obtained according to the national land spatial planning guidelines. The display module interacts with the main control module and is used to output the display function area, the greenable area, the first baseline and the second baseline, and the land greening planning area.

[0042] The main control module specifically includes: The control unit is used to take the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area, obtain the first benchmark line and the second benchmark line according to the functional area, and obtain the land greening planning area according to the first benchmark line and the second benchmark line. An information receiving unit, which interacts with the information acquisition module and the evaluation module, is used to receive data and transmit it to the spatial partitioning unit; The spatial division unit is used to determine the weight coefficient corresponding to each core indicator based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units according to the natural breakpoint method.

[0043] The information acquisition module specifically includes: The first acquisition unit is used to acquire planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data. The second acquisition unit is used to integrate geospatial boundary coordinates, control scope, geographic topography and ecological environment data to form an original dataset based on the planning area information, and to acquire geospatial information of the planning area based on the geospatial boundary coordinates.

[0044] The evaluation module specifically includes: The first evaluation unit is used to perform spatial coordinate registration on the original dataset, matching all data to a unified geographic grid unit of the planning area to obtain a spatially associated dataset. The second evaluation unit is used to obtain the core indicators corresponding to each geographic grid unit based on a standardized dataset and in accordance with the principles of territorial spatial planning.

[0045] In summary, the advantages of this invention are as follows: by spatializing and standardizing regional data, it provides a precise geographic data foundation for subsequent planning of regional spatial division; by formulating standardized quantitative assignment rules and combining them with the analytic hierarchy process to determine indicator weights, it achieves the standardized construction of grid unit functional evaluation indicators; by achieving functional adaptability, it achieves the quantification and precision of functional area division; by extracting functional area boundary coordinates to construct dual baselines and completing terrain adaptation curvature processing based on regional topography, it achieves the scientific setting of greening planning area expansion benchmarks, providing a spatial boundary foundation that fits regional characteristics for the subsequent precise expansion of greening areas.

[0046] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A smart land greening planning method based on regional feature feedback, characterized in that, include: Obtain planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data; Based on the planning area information, the geospatial boundary coordinates, control scope, geographical topography and ecological environment data are integrated to form the original dataset; Based on the geospatial boundary coordinates, geospatial information of the planning area is obtained. The geospatial information of the planning area represents the geographic map corresponding to the planning area. The geographic map includes several grid cells. Spatial coordinate registration is performed on the original dataset to match all data to a unified geographic grid cell of the planning area, resulting in a spatially associated dataset, where each sub-item of the spatially associated dataset corresponds to each geographic grid cell. Based on the spatial association dataset, the planning area is spatially divided into functional areas and greenable areas. The functional areas include core functional areas for production, living and ecology, and the greenable areas are the greenable spaces within the planning area other than the functional areas. Based on functional zones, areas suitable for greening are screened to obtain land greening planning areas.

2. The intelligent land greening planning method based on regional feature feedback according to claim 1, characterized in that, The process of spatially dividing the planning area into functional zones and greenable zones based on the spatial association dataset specifically includes: The spatial correlation dataset is preprocessed to obtain a preprocessed dataset. All numerical indicators in the preprocessed dataset are normalized to obtain a standardized dataset; Based on a standardized dataset and in accordance with the principles of land and space planning, core indicators corresponding to each geographic grid unit are obtained. These core indicators include land use type and land and space control level. The weight coefficients for each core indicator are determined based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the natural breakpoint method and functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units. Based on the core functional units, the core functional units that are in contact with the regional boundaries are merged to obtain functional areas, clarify the geographical spatial range and control boundaries of each functional area, and form a spatial distribution map of functional areas. Based on the overall control scope of the planning area, the spatial scope of functional areas is eliminated, and the spatial areas that meet the conditions for greening are designated as greenable areas. The greenable conditions are non-construction land, non-permanent basic farmland, and land ecological base that can support vegetation growth. Spatial boundaries of greenable areas are marked to form a spatial distribution map of greenable areas. Spatial and attribute data of functional areas and green areas are linked and stored to construct a spatial division database of the planning area.

3. The intelligent land greening planning method based on regional feature feedback according to claim 2, characterized in that, Based on a standardized dataset and in accordance with territorial spatial planning principles, the core indicators corresponding to each geographic grid unit are obtained, specifically including: Based on the standardized dataset, the land use feature subset is obtained, which includes land use classification data, national land space land use status survey vector data, and land ownership registration data, thus obtaining the basic land use dataset. The land use types in the basic land use dataset are categorized into four levels: production function, living function, ecological function, and unused. A legal merging rule table for land use types is then developed, resulting in the legal merging rules. Based on the statutory merging rules, the original land use classification data in the land use basic dataset are batch merged to remove non-standard data with inconsistent classification standards, resulting in a standardized land use type vector dataset. Based on the geographic grid unit vector base map in the geographic map corresponding to the planning area, the standardized land use type vector dataset is spatially overlaid with the geographic grid unit to obtain the land use type proportion data of each grid unit, that is, the area proportion of each type of land in a single grid, forming a gridded land use proportion dataset. Based on the gridded land use proportion dataset, the main type determination rule is set: if the area proportion of a certain land use type in a certain grid cell exceeds half, the main land use type of the grid cell is determined to be that type; if no type has an area proportion exceeding half, it is determined to be a composite land use type, and the main land use type determination result of each grid cell is obtained. Based on land use analysis, ensure the quantitative assignment rules corresponding to each land use type; By directly assigning values ​​to mesh cells of a single primary type, initial values ​​for single-type quantization are obtained. For grid cells with composite land use types, a weighted average value is assigned based on the area proportion of each type to obtain the initial quantitative value of the composite grid. By integrating the initial quantitative values ​​of single-type grids and composite grids, the initial quantitative values ​​of land use types for all geographic grid units in the planning area are obtained. The initial values ​​of land use type quantification are bound to the unique identifiers of grid units to form a dataset of initial values ​​for land use type indicators.

4. The intelligent land greening planning method based on regional feature feedback according to claim 1, characterized in that, Based on standardized datasets and in accordance with territorial spatial planning principles, the method for obtaining core indicators corresponding to each geographic grid unit also includes: Based on the standardized dataset, the land use feature subset and the ecological environment feature subset are extracted and integrated to obtain the basic dataset of control level. This dataset includes three-line vector data, ecological control zoning data, and land development control data. Obtain spatial control planning information corresponding to the planning area, including Level 1 control, Level 2 control, Level 3 control, and the legally defined boundaries corresponding to each control level; Based on spatial control planning information, spatial integration is performed on the three-line data and ecological control zoning data in the basic data of control level, and spatially overlapping control boundaries are eliminated to form a unified statutory vector base map of land spatial control level; By performing precise spatial matching between the statutory vector base map of the land space control level and the geographic grid unit corresponding to the planning area, a preliminary result of the statutory control level corresponding to each grid unit is obtained; Based on the land development control data in the basic dataset of control levels, the preliminary results of the statutory control levels are checked for compliance with actual control, and the revised control level results are obtained. If the control level of the statutory vector base map of the land space control level corresponding to a certain grid unit is different from the control level in the land development control data, then the grid unit is marked as a check abnormal grid unit, and the check abnormal grid unit is manually reviewed and its level is corrected. Based on the preset control level quantification assignment rules, all grid cells in the corrected control level result are assigned values ​​to obtain the initial control level quantification value; If a grid cell is a cross-control level grid cell, then the initial value of the cross-control level grid is obtained by weighting the values ​​according to the area ratio of each control level in the grid. The cross-control level grid cell means that the grid cell is cut by the boundaries of two or more control levels. By integrating the initial quantitative values ​​of the control level and the initial quantitative values ​​of cross-level grids, the initial quantitative values ​​of the land space control level of all grid units in the planning area are obtained, and bound to the unique identifier of the grid unit to form a dataset of initial values ​​of land space control level indicators.

5. The intelligent land greening planning method based on regional feature feedback according to claim 1, characterized in that, Based on the natural breakpoint method and functional adaptability, the geographic grid units are divided into core functional units and non-core functional units, specifically including: Based on the functional adaptability of each geographic grid unit, obtain the maximum and minimum functional adaptability values; Based on the maximum and minimum functional adaptability values, and using the functional adaptability corresponding to each geographic grid unit as a basis, the functional baseline adaptability is obtained based on data normalization. Based on the requirement of binary grouping, set the grouping threshold for fit; Based on the adaptation grouping threshold, geographic grid cells whose functional baseline adaptation exceeds the adaptation grouping threshold are taken as the first geographic grid cells, and the first grid cell group is obtained. Geographic grid cells whose functional baseline adaptation does not exceed the adaptation grouping threshold are used as second geographic grid cells to obtain the second grid cell group. Based on the first and second grid cell groups, the corresponding within-group variances are obtained; The sum of the within-group variance of the first grid cell group and the within-group variance of the second grid cell group is used as the data bias coefficient; The fitness grouping threshold is adjusted until the data deviation coefficient reaches the minimum value to obtain the fitness baseline threshold. Geographic grid units are divided according to the adaptation benchmark threshold. Geographic grid units whose functional benchmark adaptation exceeds the adaptation benchmark threshold are designated as core functional units, while geographic grid units whose functional benchmark adaptation does not exceed the adaptation benchmark threshold are designated as non-core functional units.

6. The intelligent land greening planning method based on regional feature feedback according to claim 4, characterized in that, The process of selecting greenable areas based on functional zones to obtain land greening planning areas specifically includes: Based on the needs of land greening, obtain the benchmark green coverage rate; Based on the planning area information, obtain the total area of ​​the planning area; The product of the total area of ​​the planned area and the benchmark green coverage rate shall be used as the greening requirement area; Based on the functional areas, obtain the standardized set of functional area boundary coordinates; Based on the standardized functional area boundary coordinate set, obtain the straight-line distance between any two points, take the two boundary points corresponding to the maximum straight-line distance as the endpoints of the first baseline, and the line connecting the two points is the initial line of the first baseline. Using the initial line of the first baseline as a reference, the standardized functional area boundary coordinates located on the same side of the initial line of the first baseline are divided into the same dataset to obtain the first coordinate set and the second coordinate set of the area boundary; Obtain the perpendicular distance from any point in the first coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum perpendicular distance as the first boundary point; Obtain the vertical distance from any point in the second coordinate set of the region boundary to the initial line of the first baseline, and take the boundary point corresponding to the maximum vertical distance as the second boundary point; Connect the first boundary point and the second boundary point to obtain the initial line of the second baseline; Based on the planning area information, a set of baseline terrain curvature rules is formulated; Based on the geospatial information of the planning area, obtain the size information of the geographic grid units; Based on the bending rule set and the geographic grid cell size information, the initial lines of the first and second baselines are subjected to terrain-adaptive bending processing to obtain the first and second baselines. The area is expanded along both sides of the first and second baselines until the area of ​​the expanded area that can be greened reaches the area required for greening. The area that can be greened at this point is then designated as the land greening planning area.

7. A land greening intelligent planning system based on regional feature feedback, used to implement the planning method as described in any one of claims 1-6, characterized in that, include: The main control module is used to determine the weight coefficients corresponding to each core indicator based on the analytic hierarchy process (AHP). Based on the core indicators and weight coefficients corresponding to each geographic grid unit, it obtains the functional adaptability of each geographic grid unit in the planning area by weighted summation. Based on the functional adaptability, it divides the geographic grid units into core functional units and non-core functional units according to the natural breakpoint method. It takes the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area. Based on the functional areas, it obtains the first baseline and the second baseline. Based on the first baseline and the second baseline, it obtains the land greening planning area. The information acquisition module is used to acquire planning area information. Based on the planning area information, it integrates geospatial boundary coordinates, control scope, geographic topography and ecological environment data to form an original dataset, and acquires geospatial information of the planning area based on the geospatial boundary coordinates. The evaluation module is used to perform spatial coordinate registration on the original dataset, match all data to the unified geographic grid unit of the planning area, and obtain a spatially associated dataset. Based on the standardized dataset, the core indicators corresponding to each geographic grid unit are obtained according to the national land spatial planning guidelines. The display module interacts with the main control module and is used to output the display function area, the greenable area, the first baseline and the second baseline, and the land greening planning area.

8. The intelligent land greening planning system based on regional feature feedback according to claim 7, characterized in that, The main control module specifically includes: The control unit is used to take the product of the total area of ​​the planning area and the benchmark green coverage rate as the greening demand area, obtain the first benchmark line and the second benchmark line according to the functional area, and obtain the land greening planning area according to the first benchmark line and the second benchmark line. An information receiving unit, which interacts with the information acquisition module and the evaluation module, is used to receive data and transmit it to the spatial partitioning unit; The spatial division unit is used to determine the weight coefficient corresponding to each core indicator based on the analytic hierarchy process. Based on the core indicators and weight coefficients corresponding to each geographic grid unit, the functional adaptability of each geographic grid unit in the planning area is obtained by weighted summation. Based on the functional adaptability, the geographic grid unit is divided into core functional units and non-core functional units according to the natural breakpoint method.

9. The intelligent land greening planning system based on regional feature feedback according to claim 7, characterized in that, The information acquisition module specifically includes: The first acquisition unit is used to acquire planning area information, which includes geospatial boundary coordinates, control scope, geographic topography, and ecological environment data. The second acquisition unit is used to form an original dataset from geospatial boundary coordinates, control scope, geographic topography and ecological environment data based on the planning area information, and to acquire geospatial information of the planning area based on the geospatial boundary coordinates.

10. The intelligent land greening planning system based on regional feature feedback according to claim 7, characterized in that, The evaluation module specifically includes: The first evaluation unit is used to perform spatial coordinate registration on the original dataset, matching all data to a unified geographic grid unit of the planning area to obtain a spatially associated dataset. The second evaluation unit is used to obtain the core indicators corresponding to each geographic grid unit based on a standardized dataset and in accordance with the principles of territorial spatial planning.

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