Natural resource space planning management system based on territorial space element data

Abstract

The invention discloses a natural resource space planning management system based on territorial space element data, relates to the technical field of space planning, and provides high-quality data support for subsequent analysis by generating a standard space element data set Fstd with consistent structure specifications through unified structure conversion and standardization processing of original space data Draw; the attribute confrontation evaluation module constructs a function attribute vector Ex based on a standard space element data set Fstd, further calculates to obtain a tension matrix F, and realizes quantitative analysis of confrontation relationships among multiple types of space function types from the source; the spatial overlapping extraction module constructs a conflict unit set Cink and a spatial overlapping index vector Mw thereof through spatial geometric analysis, so that automatic identification of potential conflict areas and quantitative characterization of overlapping strength are ensured, full-dimension quantitative evaluation of spatial planning conflict strength is realized, and an automatically executed spatial conflict identification and mediation process is achieved.

Description

Technical Field

[0001] The present invention relates to the field of spatial planning technology, and in particular to a natural resource spatial planning management system based on national land space element data. Background Art

[0002] In the modern context of harmonious coexistence between human social development and natural ecology, spatial planning and resource allocation management have gradually become core components of national land space governance. As a technical tool for balancing resource allocation, ecological protection, and urban development, national land space planning is no longer just a map on paper; it becomes a complex system involving the coordinated processing, comprehensive analysis, and dynamic feedback of multiple types of spatial data. Within this system, national land space element data, such as land use types, ecological protection red lines, permanent basic farmland boundaries, and construction land expansion boundaries, form the underlying support for planning decisions and supervision.

[0003] Although many regions have established basic national land and spatial information platforms and integrated various spatial element data, in practice, identifying potential spatial functional conflicts between different elements still largely relies on traditional methods such as manual comparison and layer overlay analysis. These methods are not only inefficient but also highly dependent on the subjective judgment of professional technicians, which is prone to omissions and misjudgments.

[0004] Furthermore, most existing platforms only display static data layers and lack the ability to deeply analyze spatial logical relationships and functional attribute conflicts between data. For example, urban expansion trends conflict with permanent basic farmland protection zones, but current systems cannot effectively model and quantify these conflicts, let alone provide automated recommendations for conflict mediation or planning adjustments. The identification and measurement of spatial conflicts lacks systematic tool support. Therefore, the lack of a quantifiable, visual, and actionable spatial conflict index model has become a major bottleneck in improving the intelligent capabilities of current natural resource management platforms. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a natural resource spatial planning and management system based on national land space element data, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a natural resource spatial planning and management system based on national land spatial element data, including a multi-source spatial data integration module, an attribute confrontation evaluation module, a spatial overlap extraction module, a contradiction index fusion module and a contradiction level evaluation module;

[0007] The multi-source spatial data integration module is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, and then pre-process the original spatial data Draw to form a standard spatial feature dataset Fstd;

[0008] The attribute confrontation evaluation module analyzes multiple types of spatial elements based on the obtained standard spatial element dataset Fstd, establishes the functional attribute vector Ex, and calculates the confrontation tension Y between the elements of the functional attribute vector Ex to obtain the tension matrix F;

[0009] The spatial overlap extraction module performs spatial geometric intersection analysis on the standard spatial feature dataset Fstd, identifies pairs of features with overlapping relationships, and marks each overlapping area as a conflict unit C. It integrates all conflict units to obtain the conflict unit set Cunit, and then calculates the spatial overlap index W(C) for each conflict unit C to form a spatial overlap index vector Mw.

[0010] The contradiction index fusion module evaluates the adaptability gap of each conflict unit C based on the obtained conflict unit set Cunit, forms the mediation adaptability gap △C, and then fuses it with the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the conflict unit C;

[0011] The conflict level evaluation module evaluates the conflict level of each conflict unit C according to the obtained conflict scoring index SCI, and generates a level notification according to the conflict level.

[0012] Preferably, the multi-source spatial data integration module includes a data processing unit and a data conversion unit;

[0013] The data processing unit is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, including land classification and planning vector data Duec and grid remote sensing data Draster, and then perform vector data processing and remote sensing data processing on the original spatial data Draw;

[0014] The original spatial data Draw is specifically Draw = {Duec∪Draster};

[0015] Vector data processing is done by unifying the coordinates and clipping the spatial range of the land classes in the original spatial data Draw and the planning vector data Duec; remote sensing data processing is done by unifying the resolution, removing clouds and fog, selecting bands, and repairing the hole area interpolation of the grid remote sensing data in the original spatial data Draw; the hole area interpolation repair is repaired by using spatial interpolation and time series interpolation methods.

[0016] Among them, the land class and planning vector data Duec are specifically Due = {Duec(1), Duec(2)}, Duec(1) represents the current land use map, Duec(2) represents the planning boundary map, the current land use map is specifically used to identify the basic functional attributes of land, including urban land, farmland and forest land, and the planning boundary map is used to identify urban development boundaries, ecological red lines and permanent basic farmland;

[0017] The grid remote sensing data Draster is specifically Draster = {Draster(1), Draster(2), Draster(3), Draster(4)}, where Draster(1) represents terrain elevation data, Draster(2) represents multi-period remote sensing images, Draster(3) represents NDVI vegetation index, and Draster(4) represents slope map and water system and wetland distribution map.

[0018] Preferably, the data conversion unit preprocesses the acquired original spatial data Draw, wherein the preprocessing includes establishing a unified data field structure and function coding for the original spatial data Draw, and then uniformly converting the original spatial data Draw into a standard spatial element data set Fstd;

[0019] The establishment of a unified data field structure involves identifying the data type and function type in the original spatial data Draw, performing standard field extraction and structured encapsulation operations on each type of data, generating the kth spatial element unit f(k) with the same language format, and assigning a unified spatial function code to the kth spatial element unit f(k) by mapping the preset function type dictionary mapping table. All spatial element units f are integrated to obtain the standard spatial element dataset Fstd.

[0020] Standard spatial feature dataset Fstd = {Fstd(1), Fstd(2), ..., Fstd(k) | k∈n}, where n represents the length of the standard spatial feature dataset;

[0021] Spatial element unit f(k) = {ID, Geometry, Type, SourceTag, Area, Timestamp, tk};

[0022] In the spatial feature unit f(k), ID represents a unique identifier, which is generated by UUID; Geometry represents geometric data, which is specifically used for spatial overlay and overlap calculations and is obtained by extracting the original spatial data Draw that has been processed by vector data and remote sensing data; Type represents the feature type and is obtained by extracting the current land use map from the original spatial data Draw; SourceTag represents the data source identifier; Area represents the area of ​​the spatial feature and is obtained by calculating the geometry data Geometry; Timestamp represents the timestamp; tk represents the spatial function code and is obtained by matching the preset function type dictionary mapping table.

[0023] Preferably, the attribute adversarial evaluation module includes a function vector construction unit and an element calculation unit;

[0024] The function vector construction unit extracts the spatial element unit f with the same spatial function code tk based on the obtained standard spatial element dataset Fstd, and establishes a unique corresponding function attribute vector E(tk) for each spatial function code tk of the spatial element unit f. By integrating the function attribute vector E(tk) of each spatial function code tk, the attribute vector set M = {E(tk)|tk∈T} is obtained, where T represents the set of spatial function codes tk;

[0025] The functional attribute vector E(tk) is specifically E(tk) = {β(tk, 1), β(tk, 2), ..., β(tk, d)}; d represents the dimension of the functional attribute vector; β(tk, i) represents the score value on the i-th functional attribute dimension;

[0026] β(tk, i) is obtained by the following calculation formula:

[0027]

[0028] Where N(tk) represents the total number of spatial element units f with the same spatial function code tk, and P(j, i) represents the score of the j-th spatial element unit f in the i-th functional attribute dimension.

[0029] Preferably, the element calculation unit extracts different spatial function codes tx and spatial function codes ty from the set T, obtains the functional attribute vector E(tx) of the spatial function code tx and the functional attribute vector E(ty) of the spatial function code ty, calculates and obtains the functional antagonistic tension Y(tx, ty) between different spatial function codes, reflects the difference between the spatial function code tx and the spatial function code ty in spatial utilization and control objectives, and forms the tension matrix F of the spatial function code tk;

[0030] The tension matrix F is specifically The tension matrix F is a k*k square matrix, and each matrix element F(tx, ty) represents the functional opposition tension Y(tx, ty) between the spatial function code tx and the spatial function code ty;

[0031] The functional resistance tension Y (tx, ty) is obtained by the following calculation formula:

[0032]

[0033] where λ represents the tension adjustment coefficient, e represents the exponential function, and ||E(tx)-E(ty)|| represents the Euclidean distance between the functional attribute vector E(tx) of the spatial function code tx and the functional attribute vector E(ty) of the spatial function code ty.

[0034] Preferably, the spatial overlap extraction module includes a recognition unit and an overlap calculation unit;

[0035] The recognition unit performs spatial geometric intersection analysis on the standard spatial element dataset Fstd. The geometric intersection analysis calculates the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q) in the standard spatial element dataset Fstd, obtains the geometric shape G(p, q) of the intersection area, and compares it with the preset minimum recognition area threshold Gth to determine the overlapping relationship between the spatial element unit f(p) and the spatial element unit f(q). When an overlapping relationship is identified, the spatial element unit f(p) and the spatial element unit f(q) are marked as an overlapping spatial element pair, and each spatial element pair area with an overlapping relationship is marked as a conflict unit C. All conflict units C are integrated to obtain a conflict unit set Cunit.

[0036] The conflict unit C is specifically C={f(p), f(q), G(p, q), f(p, tk)), f(q, tk))}; wherein f(p, tk)) represents the spatial function code tk of the spatial element unit f(p), and f(q, tk)) represents the spatial function code tk of the spatial element unit f(q);

[0037] The geometric shape G(p,q) is obtained by the definition method of G(p,q)=Geom(f(p))∩Geom(f(q)), where Geom(f(p)) represents the spatial geometric area Geom of the spatial element unit f(p), Geom(f(q)) represents the spatial geometric area Geom of the spatial element unit f(q); ∩ represents the intersection symbol.

[0038] Preferably, the overlay calculation unit calculates the spatial overlay index W(C) of each conflict unit C based on the obtained conflict unit set Cunit, reflecting the overlap intensity in space, and integrates the spatial overlay index W(C) of each conflict unit C to obtain the spatial overlay index vector Mw;

[0039] The spatial superposition index W(C) is obtained by the following calculation formula:

[0040]

[0041] Where W(C(r)) represents the spatial overlap index W of the r-th conflict unit C, AG(f(p), f(q)) represents the intersection area of ​​the spatial element unit f(p) and the spatial element unit f(q), which is specifically obtained by calculating the geometric shape G(p, q), A(f(p)) represents the initial area of ​​the spatial element unit f(p), and A(f(q)) represents the initial area of ​​the spatial element unit f(q);

[0042] The intersection area AG(f(p), f(q)) is obtained by the calculation formula AG(f(p), f(q)) = Area(G(p,q)), where Area(G(p,q)) represents the area of ​​the spatial element, specifically the geometric shape G(p,q) of the intersection area obtained by the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q).

[0043] Preferably, the contradiction index fusion module includes an adaptability evaluation unit and an index fusion unit;

[0044] The adaptability evaluation unit extracts the r-th conflict unit C(r) based on the obtained conflict unit set Cunit to evaluate the adaptability gap △C(r) of the r-th conflict unit C(r), and obtains the mediation adaptability gap △C by integrating all conflict units in the conflict unit set Cunit;

[0045]

[0046] Where d represents the dimension of the functional attribute vector, and the subscript 1 in |E(tx)-E(ty)|1 represents the L1 norm used.

[0047] Preferably, the index fusion unit performs fusion processing based on the obtained mediation adaptability gap △C, the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the r-th conflict unit C(r);

[0048] The contradiction score index (SCI) is obtained by the following calculation formula:

[0049] SCI(C(r))=F(tx,ty)*W(C(r))*(1-ΔC(r));

[0050] Where SCI(C(r)) represents the contradiction score index of the r-th conflict unit C(r), and F(tx, ty) represents the functional antagonism tension between the spatial function code tx and the spatial function code ty.

[0051] Preferably, the contradiction level assessment module includes a decision generation unit;

[0052] The decision generation unit evaluates the conflict level of each conflict unit C according to the obtained conflict score index SCI. The conflict level is evaluated by comparing the conflict score index SCI with the preset upper threshold Smax and lower threshold Xmin of the conflict level, obtaining the conflict level L(C(r)) of the r-th conflict unit C(r), and generating a level notification according to the conflict level L(C(r)) of the r-th conflict unit C(r);

[0053] The contradiction level L(C(r)) is obtained by the following comparison method:

[0054] When the contradiction level L(C(r)) of the r-th conflict unit C(r) is greater than or equal to the upper threshold Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 3, indicating the third level, indicating that there is a planning conflict of the spatial function code tk, including expansion requirements and non-occupiable restrictions. A three-level notification is generated, and after extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning three-level notification template to notify the relevant departments and put them at the top of the pending task list for processing;

[0055] When the lower threshold value Xmin is less than the contradiction level L(C(r)) of the r-th conflict unit C(r) and less than the upper threshold value Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 2, indicating the second level, indicating that there is an inconsistency in the planning objectives of the spatial function code tk, a specific structural conflict but room for mediation, and a secondary notification is generated. After extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning secondary notification template and sent to the relevant department's pending task list for processing;

[0056] When the contradiction level L(C(r)) of the r-th conflict unit C(r) is less than the lower limit threshold Xmin, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 1, which indicates the first level, indicating that there is compatibility and superposition of spatial function code tk, and prompting for natural integration disposal, use superposition guidance, ecological construction coexistence design and flexible use empowerment suggestions through planning optimization. After extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), fill them into the preset spatial planning optimization template, and send a notification to the relevant departments to wait for optimization in the task list to be optimized.

[0057] The present invention provides a natural resource space planning and management system based on land space element data, which has the following beneficial effects:

[0058] (1) The unified structural transformation and standardization of the original spatial data Draw are realized through the multi-source spatial data integration module, and a standard spatial feature dataset Fstd with consistent structural specifications is generated, providing high-quality data support for subsequent analysis; the attribute confrontation assessment module constructs the functional attribute vector Ex based on the standard spatial feature dataset Fstd, and further calculates the tension matrix F, realizing the quantitative analysis of the confrontation relationship between multiple types of spatial functional types from the source; the spatial overlap extraction module constructs the conflict unit set Cunit and its spatial overlap index vector Mw through spatial geometric analysis, ensuring the automatic identification of potential conflict areas and the quantitative characterization of overlap intensity; the contradiction index fusion module fuses the tension matrix F, the spatial overlap index vector Mw and the mediation adaptability gap △C to form the contradiction score index SCI of the conflict unit, realizing a full-dimensional quantitative evaluation of the spatial planning conflict intensity; finally, the contradiction level assessment module realizes the hierarchical judgment of the conflict unit based on the contradiction score index SCI, and automatically generates level notifications, realizing responsive management of conflict situations and active mediation prompts, and achieving an automated spatial conflict identification and mediation process.

[0059] (2) By distinguishing and processing land use and planning vector data Duec and raster remote sensing data Draster, the consistency of multiple types of heterogeneous data such as land use status map, planning boundary map, remote sensing image, terrain elevation data, NDVI vegetation index, slope map and water system wetland distribution map in coordinate system, spatial range, resolution and time series is ensured. Furthermore, by reconstructing the unified data field structure and standardizing the functional coding of the original spatial data Draw, the system finally forms a standard spatial feature dataset Fstd with unified structure, consistent semantics, and standardized format. Each spatial feature unit f(k) in the dataset has complete data attribute fields, ensuring that the system has a clear and traceable data foundation and multi-dimensional spatial functional semantic support in subsequent attribute confrontation, spatial overlay, and contradiction fusion stages. It not only opens up a systematic fusion channel between remote sensing monitoring data and land use planning data, but also through the standardized structure of the spatial feature unit f(k) and the construction of a unified spatial functional code tk, the system has a high adaptability to spatial data of any time series and any region, significantly improving the data organization ability, semantic interpretation ability, and automatic processing efficiency of natural resource spatial planning, laying a key data foundation for building a global, dynamic, and scalable spatial planning management system.

[0060] (3) Based on the mediation adaptability gap △C, the tension matrix F, and the spatial overlay index vector Mw, index fusion processing is performed to automatically obtain the contradiction score index SCI(C(r)) of each conflict unit C(r). The decision generation unit dynamically compares the score index with the preset contradiction level upper threshold Smax and lower threshold Xmin to obtain the corresponding contradiction level L(C(r)) of the conflict unit. The system further extracts the spatial function code tk involved in the conflict based on the level classification rule of L(C(r)), fills tk and L(C(r)) into the spatial planning notification template of the corresponding level, automatically generates multi-level response notification content, and distributes it to the pending task list or pending optimization task list of the relevant department according to the level. This realizes the fully automatic connection between conflict level judgment and spatial planning response. Unlike the traditional method of relying on static reports and manual interpretation of conflicts one by one, it can trigger planning-level response notifications with semantic recognition capabilities and departmental docking structure, thereby greatly improving the timeliness, automation, and decision-making closed-loop capability of national land space planning management in the conflict handling link. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a schematic diagram of a natural resource space planning and management system based on land space element data according to the present invention;

[0062] Figure 2 This is a schematic diagram of the tension matrix F in a natural resource spatial planning and management system based on national land space element data of the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0064] Example 1

[0065] The present invention provides a natural resource space planning and management system based on land space element data. Figure 1 , including multi-source spatial data integration module, attribute confrontation evaluation module, spatial overlap extraction module, contradiction index fusion module and contradiction level evaluation module;

[0066] The multi-source spatial data integration module is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, and then pre-process the original spatial data Draw to form a standard spatial feature dataset Fstd;

[0067] The attribute confrontation evaluation module analyzes multiple types of spatial elements based on the obtained standard spatial element dataset Fstd, establishes the functional attribute vector Ex, and calculates the confrontation tension Y between the elements of the functional attribute vector Ex to obtain the tension matrix F;

[0068] The spatial overlap extraction module performs spatial geometric intersection analysis on the standard spatial feature dataset Fstd, identifies pairs of features with overlapping relationships, and marks each overlapping area as a conflict unit C. It integrates all conflict units to obtain the conflict unit set Cunit, and then calculates the spatial overlap index W(C) for each conflict unit C to form a spatial overlap index vector Mw.

[0069] The contradiction index fusion module evaluates the adaptability gap of each conflict unit C based on the obtained conflict unit set Cunit, forms the mediation adaptability gap △C, and then fuses it with the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the conflict unit C;

[0070] The conflict level evaluation module evaluates the conflict level of each conflict unit C according to the obtained conflict scoring index SCI, and generates a level notification according to the conflict level.

[0071] In this embodiment, the unified structure conversion and standardization processing of the original spatial data Draw are realized through the multi-source spatial data integration module, and a standard spatial element dataset Fstd with consistent structural specifications is generated, providing high-quality data support for subsequent analysis; the attribute confrontation evaluation module constructs the functional attribute vector Ex based on the standard spatial element dataset Fstd, and further calculates the tension matrix F, realizing the quantitative analysis of the confrontation relationship between multiple types of spatial functional types from the source; the spatial overlap extraction module constructs the conflict unit set Cunit and its spatial overlap index vector Mw through spatial geometric analysis, ensuring the automatic identification of potential conflict areas and the quantitative representation of overlap intensity; the contradiction index fusion module fuses the tension matrix F , the spatial overlay index vector Mw and the mediation adaptability gap △C are combined to form the conflict score index SCI of the conflict unit, realizing a full-dimensional quantitative assessment of the intensity of spatial planning conflicts; finally, the conflict level assessment module realizes the hierarchical judgment of the conflict units based on the contradiction score index SCI, and automatically generates level notifications to achieve responsive management of conflict situations and active mediation prompts, thus achieving an automated execution of spatial conflict identification and mediation process. Compared with the existing conflict discovery method based on manual interpretation, it not only significantly improves the objectivity, accuracy and comprehensiveness of conflict identification, but also provides a unified quantitative assessment standard and disposal basis for the demarcation of the "three zones and three lines", use optimization and spatial governance, which has practical value and promotion potential.

[0072] Example 2

[0073] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the multi-source spatial data integration module includes a data ,processing unit and a data conversion unit;

[0074] The data processing unit is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, including land classification and planning vector data Duec and grid remote sensing data Draster, and then perform vector data processing and remote sensing data processing on the original spatial data Draw;

[0075] The original spatial data Draw is specifically Draw = {Duec∪Draster};

[0076] Vector data processing is done by unifying the coordinates and clipping the spatial range of the land classes in the original spatial data Draw and the planning vector data Duec; remote sensing data processing is done by unifying the resolution, removing clouds and fog, selecting bands, and repairing the hole area interpolation of the grid remote sensing data in the original spatial data Draw; the hole area interpolation repair is repaired by using spatial interpolation and time series interpolation methods.

[0077] Among them, the land class and planning vector data Duec are specifically Due = {Duec(1), Duec(2)}, Duec(1) represents the current land use map, Duec(2) represents the planning boundary map, the current land use map is specifically used to identify the basic functional attributes of land, including urban land, farmland and forest land, and the planning boundary map is used to identify urban development boundaries, ecological red lines and permanent basic farmland;

[0078] The grid remote sensing data Draster is specifically Draster = {Draster(1), Draster(2), Draster(3), Draster(4)}, where Draster(1) represents terrain elevation data, Draster(2) represents multi-period remote sensing images, Draster(3) represents NDVI vegetation index, and Draster(4) represents slope map and water system and wetland distribution map.

[0079] The data conversion unit preprocesses the acquired original spatial data Draw. The preprocessing includes establishing a unified data field structure and function coding for the original spatial data Draw, and then uniformly converting the original spatial data Draw into a standard spatial feature dataset Fstd.

[0080] The establishment of a unified data field structure involves identifying the data type and function type in the original spatial data Draw, performing standard field extraction and structured encapsulation operations on each type of data, generating the kth spatial element unit f(k) with the same language format, and assigning a unified spatial function code to the kth spatial element unit f(k) by mapping the preset function type dictionary mapping table. All spatial element units f are integrated to obtain the standard spatial element dataset Fstd.

[0081] Standard spatial feature dataset Fstd = {Fstd(1), Fstd(2), ..., Fstd(k) | k∈n}, where n represents the length of the standard spatial feature dataset;

[0082] Spatial element unit f(k) = {ID, Geometry, Type, SourceTag, Area, Timestamp, tk};

[0083] In the spatial element unit f(k), ID represents a unique identifier, which is used for data traceability and index management and is generated by UUID; Geometry represents geometric data, which is specifically used for spatial overlay and overlap calculation and is obtained by extracting the original spatial data Draw that has been processed by vector data and remote sensing data, such as polygons (boundaries of plots and protected areas), polylines (water systems and boundary lines), points (monitoring points), and grids (remote sensing image blocks and DEMs); Type represents the feature type, which is used for functional classification identification and standardized coding field tk linkage and is obtained by extracting the land use status map in the original spatial data Draw, such as urban construction land, permanent basic farmland, ecological protection red lines and water resources. body; SourceTag represents the data source identifier, which is specifically used to identify the source platform and data batch of the element unit data; Area represents the area of ​​the spatial element, which is used for spatial contradiction calculation and is obtained through geometry data calculation; Timestamp represents the timestamp; tk represents the spatial function code, which is obtained by matching the preset function type dictionary mapping table, for example: spatial function code tk=LC101 represents urban construction land, spatial function code tk=LC201 represents permanent basic farmland, spatial function code tk=EC301 represents ecological protection red line, spatial function code tk=HY401 represents water body, and spatial function code tk=FL501 represents forest land.

[0084] In this embodiment, by distinguishing and processing land classification and planning vector data Duec and raster remote sensing data Draster, the consistency of multiple types of heterogeneous data such as land use status map, planning boundary map, remote sensing image, terrain elevation data, NDVI vegetation index, slope map and water system wetland distribution map in coordinate system, spatial range, resolution and time series is ensured. Furthermore, the data conversion unit completes the reconstruction of the unified data field structure and the standardization of the functional coding of the original spatial data Draw. The system finally forms a standard spatial feature dataset Fstd with unified structure, consistent semantics and standardized format. Each spatial feature unit f(k) in the dataset has complete data attribute fields, ensuring that the system has a clear and traceable data foundation and multi-dimensional spatial functional semantic support in subsequent attribute confrontation, spatial overlay and contradiction fusion stages. It not only opens up a systematic fusion channel between remote sensing monitoring data and land use planning data, but also through the standardized structure of the spatial feature unit f(k) and the construction of a unified spatial functional code tk, the system has a high adaptability to spatial data of any time series and any region, significantly improving the data organization ability, semantic interpretation ability and automatic processing efficiency of natural resource spatial planning, and laying a key data foundation for building a global, dynamic and scalable spatial planning management system.

[0085] Example 3

[0086] This embodiment is explained in Example 2, please refer to Figure 1 and Figure 2 ,Specifically: the attribute adversarial evaluation module includes a ,function vector construction unit and an element calculation unit;

[0087] The function vector construction unit extracts the spatial element unit f with the same spatial function code tk based on the obtained standard spatial element dataset Fstd, and establishes a unique corresponding function attribute vector E(tk) for each spatial function code tk of the spatial element unit f. By integrating the function attribute vector E(tk) of each spatial function code tk, the attribute vector set M = {E(tk)|tk∈T} is obtained, where T represents the set of spatial function codes tk;

[0088] The functional attribute vector E(tk) is specifically E(tk) = {β(tk, 1), β(tk, 2), ..., β(tk, d)}; d represents the dimension of the functional attribute vector; β(tk, i) represents the score value on the i-th functional attribute dimension;

[0089] β(tk, i) is obtained by the following calculation formula:

[0090]

[0091] Where N(tk) represents the total number of spatial element units f with the same spatial function code tk, and P(j, i) represents the score of the j-th spatial element unit f in the i-th functional attribute dimension.

[0092] The element calculation unit extracts different spatial function codes tx and spatial function codes ty from the set T, obtains the functional attribute vector E(tx) of the spatial function code tx and the functional attribute vector E(ty) of the spatial function code ty, calculates the functional antagonistic tension Y(tx, ty) between different spatial function codes, reflects the differences between the spatial function codes tx and ty in spatial utilization and control objectives, and forms the tension matrix F of the spatial function code tk;

[0093] The tension matrix F is specifically The tension matrix F is a k*k square matrix, and each matrix element F(tx, ty) represents the functional opposition tension Y(tx, ty) between the spatial function code tx and the spatial function code ty;

[0094] The functional resistance tension Y (tx, ty) is obtained by the following calculation formula:

[0095]

[0096] Where λ represents the tension adjustment coefficient, e represents the exponential function, and ||E(tx)-E(ty)|| represents the Euclidean distance between the functional attribute vector E(tx) of the spatial functional code tx and the functional attribute vector E(ty) of the spatial functional code ty;

[0097] Specific data example of the tension matrix F of the spatial function coding tk:

[0098] Set the spatial function code tk:

[0099] LC101 = urban construction land; AG201 = permanent basic farmland; EC301 = ecological protection red line; FL501 = forest land; HY401 = water body;

[0100] Based on the five set spatial function codes tk, a function attribute vector is generated, and the function antagonistic tension values ​​between each two are calculated to generate the tension matrix F of the spatial function code tk:

[0101]

[0102]

[0103] In this example, a functional attribute semantic modeling system centered around spatial function codes tk is constructed based on the standard spatial feature dataset Fstd. This module first clusters and categorizes spatial feature units f with the same spatial function code tk in Fstd. Based on a functional attribute dimension index system, it calculates the functional attribute vector E(tk) corresponding to each category tk and integrates all functional attribute vectors into a set of attribute vectors M = {E(tk)|tk∈T}. Furthermore, the element calculation unit performs pairwise combinations of spatial function codes tx and ty in the set T, calculates the degree of difference between their functional attribute vectors E(tx) and E(ty), and generates functional tension Y(tx,ty). Furthermore, a tension matrix F is constructed, using a k×k matrix structure to comprehensively characterize the objective conflict relationships between various spatial function codes tk. This achieves quantitative attribute modeling and mathematical representation of conflict and confrontation relationships between spatial functions, enabling the system to automatically identify the intensity of conflicts and confrontational trends between different spatial uses across multiple dimensions, such as control intensity, development suitability, and ecological sensitivity, without relying on subjective judgment. Compared with the traditional static conflict analysis method based on land type classification, this module conducts semantically driven attribute confrontation assessment based on the spatial function code tk in Fstd, constructs a quantifiable, adjustable, and dynamically evolving spatial use relationship tension expression mechanism, and provides interpretable and differentiated key parameter support for the subsequent spatial conflict index calculation and mediation path identification.

[0104] Example 4

[0105] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the spatial overlap extraction module includes a recognition unit and an ,overlap calculation unit;

[0106] The recognition unit performs spatial geometric intersection analysis on the standard spatial element dataset Fstd. The geometric intersection analysis calculates the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q) in the standard spatial element dataset Fstd, obtains the geometric shape G(p, q) of the intersection area, and compares it with the preset minimum recognition area threshold Gth to determine the overlapping relationship between the spatial element unit f(p) and the spatial element unit f(q). When an overlapping relationship is identified, the spatial element unit f(p) and the spatial element unit f(q) are marked as an overlapping spatial element pair, and each spatial element pair area with an overlapping relationship is marked as a conflict unit C. All conflict units C are integrated to obtain a conflict unit set Cunit.

[0107] The conflict unit C is specifically C={f(p), f(q), G(p, q), f(p, tk)), f(q, tk))}; wherein f(p, tk)) represents the spatial function code tk of the spatial element unit f(p), and f(q, tk)) represents the spatial function code tk of the spatial element unit f(q);

[0108] The geometric shape G(p,q) is obtained by the definition method of G(p,q)=Geom(f(p))∩Geom(f(q)), where Geom(f(p)) represents the spatial geometric area Geom of the spatial element unit f(p), Geom(f(q)) represents the spatial geometric area Geom of the spatial element unit f(q); ∩ represents the intersection symbol.

[0109] The overlay calculation unit calculates the spatial overlay index W(C) of each conflict unit C based on the obtained conflict unit set Cunit, reflecting the overlap intensity in space, and integrates the spatial overlay index W(C) of each conflict unit C to obtain the spatial overlay index vector Mw;

[0110] The spatial superposition index W(C) is obtained by the following calculation formula:

[0111]

[0112] Where W(C(r)) represents the spatial overlap index W of the r-th conflict unit C, AG(f(p), f(q)) represents the intersection area of ​​the spatial element unit f(p) and the spatial element unit f(q), which is specifically obtained by calculating the geometric shape G(p, q), A(f(p)) represents the initial area of ​​the spatial element unit f(p), and A(f(q)) represents the initial area of ​​the spatial element unit f(q);

[0113] The intersection area AG(f(p), f(q)) is obtained by the calculation formula AG(f(p), f(q)) = Area(G(p,q)), where Area(G(p,q)) represents the area of ​​the spatial element, specifically the geometric shape G(p,q) of the intersection area obtained by the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q).

[0114] This embodiment implements automatic identification of spatial geometric relationships and quantitative expression of overlap intensity based on a standard spatial element dataset Fstd. The recognition unit performs spatial geometric intersection analysis on the spatial element units f(p) and f(q) in Fstd, extracts the geometric shape G(p, q) of the intersection area, and compares it with the minimum identification area threshold Gth. It automatically determines whether a valid overlap relationship exists, then marks and generates conflicting units C, and integrates them into a set of conflicting units Cunit. Furthermore, the system calculates the spatial overlap index W(C) for each conflicting unit C through the overlap calculation unit. The overlap index is normalized by the intersection area AG(f(p), f(q)) and the original areas A(f(p)) and A(f(q)) to reflect the overlap intensity of the conflicting elements in their spatial distribution. This ultimately forms a spatial overlap index vector Mw. This breaks away from the previous approach of spatial planning conflict identification that relied on manual layer comparison. Instead, it establishes an automatic spatial overlap extraction mechanism based on spatial elements, using geometric intersection as the logical basis, and the spatial overlap index W(C) as a quantitative indicator. The system can quickly identify and quantitatively evaluate the geometric interaction relationship between spatial elements of any area and any functional code tk in a large-scale multi-source data environment, thereby improving the geometric accuracy, processing efficiency and degree of automation of conflict identification, providing solid spatial location information support for subsequent conflict index fusion and level assessment, and providing a clear geometric basis and indicator foundation for spatial utilization layout optimization and boundary adjustment.

[0115] Example 5

[0116] This embodiment is explained in Example 4. Please refer to Figure 1 Specifically: the index fusion unit performs a fusion process based on the obtained mediation adaptability gap △C, the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the r-th conflict unit C(r);

[0117] The contradiction score index (SCI) is obtained by the following calculation formula:

[0118] SCI(C(r))=F(tx,ty)*W(C(r))*(1-ΔC(r));

[0119] Where SCI(C(r)) represents the contradiction score index of the r-th conflict unit C(r), and F(tx, ty) represents the functional antagonism tension between the spatial function code tx and the spatial function code ty.

[0120] The contradiction level assessment module includes a decision generation unit;

[0121] The decision generation unit evaluates the conflict level of each conflict unit C according to the obtained conflict score index SCI. The conflict level is evaluated by comparing the conflict score index SCI with the preset upper threshold Smax and lower threshold Xmin of the conflict level, obtaining the conflict level L(C(r)) of the r-th conflict unit C(r), and generating a level notification according to the conflict level L(C(r)) of the r-th conflict unit C(r);

[0122] The contradiction level L(C(r)) is obtained by the following comparison method:

[0123] When the contradiction level L(C(r)) of the r-th conflict unit C(r) ≥ the upper threshold Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 3, indicating the third level, indicating that there is a planning conflict of the spatial function code tk, including expansion requirements and non-occupiable restrictions. For example, there is a land use conflict between the urban construction expansion demand and the permanent basic farmland protection target. A three-level notification is generated, and after extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning three-level notification template to notify the relevant departments to be placed at the top of the pending task list for disposal;

[0124] When the lower threshold value Xmin is less than the contradiction level L(C(r)) of the r-th conflict unit C(r) and less than the upper threshold value Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 2, indicating the second level, indicating that there is an inconsistency in the planning objectives of the spatial function code tk, a specific structural conflict but with room for mediation, for example: general cultivated land overlaps with urban secondary supporting construction areas and general forest land overlaps with industrial land, a second-level notification is generated, and after extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning second-level notification template and sent to the relevant department's pending task list for disposal;

[0125] When the contradiction level L(C(r)) of the r-th conflict unit C(r) is less than the lower limit threshold Xmin, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 1, which indicates the first level, indicating that there is compatibility and overlapping use of the spatial function code tk, and prompting suggestions for natural integration disposal, use overlapping guidance, ecological construction coexistence design and flexible use empowerment through planning optimization, for example: forest land and ecological restoration area overlap and water area and buffer green belt intersect. After extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), fill them into the preset spatial planning optimization template, and send a notification to the relevant departments in the optimization task list to wait for optimization.

[0126] In this embodiment, index fusion processing is performed based on the mediation adaptability gap △C, the tension matrix F and the spatial overlay index vector Mw to automatically obtain the contradiction score index SCI(C(r)) of each conflict unit C(r), and the decision generation unit dynamically compares the score index with the preset contradiction level upper limit threshold Smax and lower limit threshold Xmin to obtain the corresponding contradiction level L(C(r)) of the conflict unit. The system further extracts the spatial function code tk involved in the conflict based on the hierarchical classification rules of L(C(r)), fills tk and L(C(r)) into the spatial planning notification template of the corresponding level, automatically generates multi-level response notification content, and distributes it to the pending task list or pending optimization task list of the relevant department according to the level, realizing the fully automatic connection between conflict level judgment and spatial planning response. Unlike the traditional method of relying on static reports and manual interpretation of conflicts one by one, this module not only realizes the accurate quantification of spatial conflict levels, but also enables each conflict unit C(r) to trigger a planning-level response notification with semantic recognition capabilities and departmental docking structure on the basis of a clear level L(C(r)), thereby greatly improving the timeliness, automation and decision-making closed-loop capabilities of national land space planning management in the conflict handling link.

[0127] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A natural resource spatial planning and management system based on national land spatial element data, characterized by: It includes multi-source spatial data integration module, attribute confrontation evaluation module, spatial overlap extraction module, contradiction index fusion module and contradiction level evaluation module; The multi-source spatial data integration module is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, and then pre-process the original spatial data Draw to form a standard spatial feature dataset Fstd; The attribute confrontation evaluation module analyzes multiple types of spatial elements based on the obtained standard spatial element dataset Fstd, establishes the functional attribute vector Ex, and calculates the confrontation tension Y between the elements of the functional attribute vector Ex to obtain the tension matrix F; The spatial overlap extraction module performs spatial geometric intersection analysis on the standard spatial feature dataset Fstd, identifies pairs of features with overlapping relationships, and marks each overlapping area as a conflict unit C. It integrates all conflict units to obtain the conflict unit set Cunit, and then calculates the spatial overlap index W(C) for each conflict unit C to form a spatial overlap index vector Mw. The contradiction index fusion module evaluates the adaptability gap of each conflict unit C based on the obtained conflict unit set Cunit, forms the mediation adaptability gap △C, and then fuses it with the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the conflict unit C; The conflict level evaluation module evaluates the conflict level of each conflict unit C according to the obtained conflict scoring index SCI, and generates a level notification according to the conflict level.

2. The natural resource spatial planning and management system based on land and space element data according to claim 1 is characterized by: The multi-source spatial data integration module includes a data processing unit and a data conversion unit; The data processing unit is used to receive the original spatial data Draw transmitted by the natural resource platform and remote sensing monitoring system, including land classification and planning vector data Duec and grid remote sensing data Draster, and then perform vector data processing and remote sensing data processing on the original spatial data Draw; The original spatial data Draw is specifically Draw = {Duec∪Draster}; Vector data processing is done by unifying the coordinates and clipping the spatial range of the land classes in the original spatial data Draw and the planning vector data Duec; remote sensing data processing is done by unifying the resolution, removing clouds and fog, selecting bands, and repairing the hole area interpolation of the grid remote sensing data in the original spatial data Draw; the hole area interpolation repair is repaired by using spatial interpolation and time series interpolation methods. Among them, the land class and planning vector data Duec are specifically Due = {Duec(1), Duec(2)}, Duec(1) represents the current land use map, Duec(2) represents the planning boundary map, the current land use map is specifically used to identify the basic functional attributes of land, including urban land, farmland and forest land, and the planning boundary map is used to identify urban development boundaries, ecological red lines and permanent basic farmland; The grid remote sensing data Draster is specifically Draster = {Draster(1), Draster(2), Draster(3), Draster(4)}, where Draster(1) represents terrain elevation data, Draster(2) represents multi-period remote sensing images, Draster(3) represents NDVI vegetation index, and Draster(4) represents slope map and water system and wetland distribution map.

3. The natural resource spatial planning and management system based on national land spatial element data according to claim 2, characterized in that: The data conversion unit preprocesses the acquired original spatial data Draw. The preprocessing includes establishing a unified data field structure and function coding for the original spatial data Draw, and then uniformly converting the original spatial data Draw into a standard spatial feature dataset Fstd. The establishment of a unified data field structure involves identifying the data type and function type in the original spatial data Draw, performing standard field extraction and structured encapsulation operations on each type of data, generating the kth spatial element unit f(k) with the same language format, and assigning a unified spatial function code to the kth spatial element unit f(k) by mapping the preset function type dictionary mapping table. All spatial element units f are integrated to obtain the standard spatial element dataset Fstd. Standard spatial feature dataset Fstd = {Fstd(1), Fstd(2), ..., Fstd(k) | k∈n}, where n represents the length of the standard spatial feature dataset; Spatial element unit f(k) = {ID, Geometry, Type, SourceTag, Area, Timestamp, tk}; In the spatial feature unit f(k), ID represents a unique identifier, which is generated by UUID; Geometry represents geometric data, which is specifically used for spatial overlay and overlap calculations and is obtained by extracting the original spatial data Draw that has been processed by vector data and remote sensing data; Type represents the feature type and is obtained by extracting the current land use map from the original spatial data Draw; SourceTag represents the data source identifier; Area represents the area of ​​the spatial feature and is obtained by calculating the geometry data Geometry; Timestamp represents the timestamp; tk represents the spatial function code and is obtained by matching the preset function type dictionary mapping table.

4. The natural resource spatial planning and management system based on national land spatial element data according to claim 3 is characterized by: The attribute adversarial evaluation module includes a function vector construction unit and an element calculation unit; The function vector construction unit extracts the spatial element unit f with the same spatial function code tk based on the obtained standard spatial element dataset Fstd, and establishes a unique corresponding function attribute vector E(tk) for each spatial function code tk of the spatial element unit f. By integrating the function attribute vector E(tk) of each spatial function code tk, the attribute vector set M = {E(tk)|tk∈T} is obtained, where T represents the set of spatial function codes tk; The functional attribute vector E(tk) is specifically E(tk) = {β(tk, 1), β(tk, 2), ..., β(tk, d)}; d represents the dimension of the functional attribute vector; β(tk, i) represents the score value on the i-th functional attribute dimension; β(tk, i) is obtained by the following calculation formula: Where N(tk) represents the total number of spatial element units f with the same spatial function code tk, and P(j, i) represents the score of the j-th spatial element unit f in the i-th functional attribute dimension.

5. The natural resource spatial planning and management system based on national land spatial element data according to claim 4 is characterized by: The element calculation unit extracts different spatial function codes tx and spatial function codes ty from the set T, obtains the functional attribute vector E(tx) of the spatial function code tx and the functional attribute vector E(ty) of the spatial function code ty, calculates the functional antagonistic tension Y(tx, ty) between different spatial function codes, reflects the differences between the spatial function codes tx and ty in spatial utilization and control objectives, and forms the tension matrix F of the spatial function code tk; The tension matrix F is specifically The tension matrix F is a k*k square matrix, and each matrix element F(tx, ty) represents the functional opposition tension Y(tx, ty) between the spatial function code tx and the spatial function code ty; The functional resistance tension Y(tx, ty) is obtained by the following calculation formula: where λ represents the tension adjustment coefficient, e represents the exponential function, and ||E(tx)-E(ty)|| represents the Euclidean distance between the functional attribute vector E(tx) of the spatial function code tx and the functional attribute vector E(ty) of the spatial function code ty.

6. The natural resource spatial planning and management system based on national land spatial element data according to claim 1, characterized in that: The spatial overlap extraction module includes a recognition unit and an overlap calculation unit; The recognition unit performs spatial geometric intersection analysis on the standard spatial element dataset Fstd. The geometric intersection analysis calculates the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q) in the standard spatial element dataset Fstd, obtains the geometric shape G(p, q) of the intersection area, and compares it with the preset minimum recognition area threshold Gth to determine the overlapping relationship between the spatial element unit f(p) and the spatial element unit f(q). When an overlapping relationship is identified, the spatial element unit f(p) and the spatial element unit f(q) are marked as an overlapping spatial element pair, and each spatial element pair area with an overlapping relationship is marked as a conflict unit C. All conflict units C are integrated to obtain a conflict unit set Cunit. The conflict unit C is specifically C={f(p), f(q), G(p, q), f(p, tk)), f(q, tk))}; wherein f(p, tk)) represents the spatial function code tk of the spatial element unit f(p), and f(q, tk)) represents the spatial function code tk of the spatial element unit f(q); The geometric shape G(p,q) is obtained by the definition method of G(p,q)=Geom(f(p))∩Geom(f(q)), where Geom(f(p)) represents the spatial geometric area Geom of the spatial element unit f(p), Geom(f(q)) represents the spatial geometric area Geom of the spatial element unit f(q); ∩ represents the intersection symbol.

7. The natural resource spatial planning and management system based on national land spatial element data according to claim 6, characterized in that: The overlay calculation unit calculates the spatial overlay index W(C) of each conflict unit C based on the obtained conflict unit set Cunit, reflecting the overlap intensity in space, and integrates the spatial overlay index W(C) of each conflict unit C to obtain the spatial overlay index vector Mw; The spatial superposition index W(C) is obtained by the following calculation formula: Where W(C(r)) represents the spatial overlap index W of the r-th conflict unit C, AG(f(p), f(q)) represents the intersection area of ​​the spatial element unit f(p) and the spatial element unit f(q), which is specifically obtained by calculating the geometric shape G(p, q), A(f(p)) represents the initial area of ​​the spatial element unit f(p), and A(f(q)) represents the initial area of ​​the spatial element unit f(q); The intersection area AG(f(p), f(q)) is obtained by the calculation formula AG(f(p), f(q)) = Area(G(p,q)), where Area(G(p,q)) represents the area of ​​the spatial element, specifically the geometric shape G(p,q) of the intersection area obtained by the spatial geometric area Geom between the spatial element unit f(p) and the spatial element unit f(q).

8. The natural resource spatial planning and management system based on national land spatial element data according to claim 7, characterized in that: The contradiction index fusion module includes an adaptability assessment unit and an index fusion unit; The adaptability evaluation unit extracts the r-th conflict unit C(r) based on the obtained conflict unit set Cunit to evaluate the adaptability gap △C(r) of the r-th conflict unit C(r), and obtains the mediation adaptability gap △C by integrating all conflict units in the conflict unit set Cunit; Where d represents the dimension of the functional attribute vector, and the subscript 1 in |E(tx)-E(ty)|1 represents the L1 norm used.

9. The natural resource spatial planning and management system based on national land spatial element data according to claim 8, characterized in that: The index fusion unit performs a fusion process based on the obtained mediation adaptability gap △C, the tension matrix F and the spatial superposition index vector Mw to obtain the contradiction score index SCI of the r-th conflict unit C(r); The contradiction score index (SCI) is obtained by the following calculation formula: SCI(C(r))=F(tx,ty)*W(C(r))*(1-ΔC(r)); Where SCI(C(r)) represents the contradiction score index of the r-th conflict unit C(r), and F(tx, ty) represents the functional antagonism tension between the spatial function code tx and the spatial function code ty.

10. The natural resource spatial planning and management system based on national land spatial element data according to claim 1, characterized in that: The contradiction level assessment module includes a decision generation unit; The decision generation unit evaluates the conflict level of each conflict unit C according to the obtained conflict score index SCI. The conflict level is evaluated by comparing the conflict score index SCI with the preset upper threshold Smax and lower threshold Xmin of the conflict level, obtaining the conflict level L(C(r)) of the r-th conflict unit C(r), and generating a level notification according to the conflict level L(C(r)) of the r-th conflict unit C(r); The contradiction level L(C(r)) is obtained by the following comparison method: When the contradiction level L(C(r)) of the r-th conflict unit C(r) is greater than or equal to the upper threshold Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 3, indicating the third level, indicating that there is a planning conflict of the spatial function code tk, including expansion requirements and non-occupiable restrictions. A three-level notification is generated, and after extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning three-level notification template to notify the relevant departments and put them at the top of the pending task list for processing; When the lower threshold value Xmin is less than the contradiction level L(C(r)) of the r-th conflict unit C(r) and less than the upper threshold value Smax, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 2, indicating the second level, indicating that there is an inconsistency in the planning objectives of the spatial function code tk, a specific structural conflict but room for mediation, and a secondary notification is generated. After extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), they are filled into the preset spatial planning secondary notification template and sent to the relevant department's pending task list for processing; When the contradiction level L(C(r)) of the r-th conflict unit C(r) is less than the lower limit threshold Xmin, the contradiction level L(C(r)) of the r-th conflict unit C(r) is obtained as 1, which indicates the first level, indicating that there is compatibility and superposition of spatial function code tk, and prompting for natural integration disposal, use superposition guidance, ecological construction coexistence design and flexible use empowerment suggestions through planning optimization. After extracting the conflicting spatial function code tk and the contradiction level L(C(r)) of the r-th conflict unit C(r), fill them into the preset spatial planning optimization template, and send a notification to the relevant departments to wait for optimization in the task list to be optimized.

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