A land resource use assessment method and system based on intensive and low-carbon orientation

Abstract

This invention relates to the field of land resource evaluation technology, and discloses a method and system for evaluating land resource utilization based on intensive and low-carbon orientation. The method includes: dividing the area to be evaluated into initial evaluation units according to a preset first regional division strategy; determining the land intensive utilization results and low-carbon emission results corresponding to the initial evaluation units based on the evaluation dataset of the area to be evaluated, and analyzing the intensive and low-carbon correlation results corresponding to the initial evaluation units; updating the first regional division strategy based on the intensive and low-carbon correlation results when the preset strategy update trigger condition is met, obtaining a second regional division strategy, and determining re-evaluation units based on the second regional division strategy; and determining the optimal allocation result of land resources based on the re-evaluation units. This invention can solve the technical problems in related technologies where the connection between land intensive utilization evaluation and low-carbon emission evaluation is insufficient, and the fixed regional division method is difficult to adapt to the differentiated governance needs within industrial functional zones.

Description

Technical Field

[0001] This invention relates to the field of land resource evaluation technology, and in particular to a land resource utilization assessment method and system based on intensive and low-carbon orientation. Background Technology

[0002] In related technologies, the assessment of land resource utilization in industrial functional zones, industrial parks, and industrial-led core start-up areas is usually based on administrative boundaries, planning boundaries, or plot boundaries, and the level of intensive land use is determined based on factors such as land development intensity, economic output status, and inefficient idle status.

[0003] However, as industrial functional zones transform towards green, low-carbon, and high-quality development, simply evaluating based on land intensification is insufficient to reflect the differences in energy consumption, carbon dioxide emissions, and low-carbon transformation potential of industrial land; and evaluating based solely on carbon dioxide emissions is insufficient to reflect land resource carrying capacity efficiency and industrial output status.

[0004] Furthermore, the evaluation units in related technologies are mostly fixed boundaries, and once determined, they are not adjusted based on the evaluation results. When different intensive and low-carbon states exist within the same evaluation unit, or when adjacent evaluation units share energy facilities, fixed boundaries can easily lead to the averaging or fragmentation of evaluation results, thereby reducing the accuracy and feasibility of the land resource optimization allocation results. Summary of the Invention

[0005] The main purpose of this application is to provide a land resource utilization assessment method and system based on intensive and low-carbon orientation, which aims to solve the technical problems in related technologies such as insufficient connection between land intensive use assessment and low-carbon emission assessment, and the difficulty of adapting fixed area division methods to the differentiated governance needs within industrial functional zones.

[0006] To achieve the above objectives, this invention provides a land resource use assessment method based on intensive and low-carbon principles, the method comprising: According to the preset first area division strategy, the area to be evaluated is divided into initial evaluation units; Based on the assessment dataset of the area to be assessed, the land intensive use results and low carbon emission results corresponding to the initial evaluation unit are determined. The land intensive use results include land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low carbon emission results include per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting. Based on the results of intensive land use and low carbon emissions, analyze the intensive and low carbon correlation results corresponding to the initial evaluation unit; When the preset strategy update trigger condition is met, the first region division strategy is updated based on the intensive low-carbon association result to obtain the second region division strategy, and the re-evaluation unit is determined based on the second region division strategy. Based on the re-evaluation unit, the optimal allocation result of land resources is determined.

[0007] Furthermore, to achieve the above objectives, the present invention also provides a land resource use assessment system based on intensive and low-carbon orientation, comprising: The initial division module is used to divide the area to be evaluated into initial evaluation units according to the preset first area division strategy; The result determination module is used to determine the land intensive use result and low carbon emission result corresponding to the initial evaluation unit based on the evaluation dataset of the area to be evaluated. The land intensive use result includes land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low carbon emission result includes per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting. The correlation analysis module is used to analyze the intensive and low-carbon correlation results corresponding to the initial evaluation unit based on the intensive land use results and the low-carbon emission results. The strategy update module is used to update the first region division strategy based on the intensive low-carbon association result when the preset strategy update trigger condition is met, to obtain the second region division strategy, and to determine the re-evaluation unit based on the second region division strategy. The configuration determination module is used to determine the optimal allocation result of land resources based on the re-evaluation unit.

[0008] One or more technical solutions proposed in this application have at least the following technical effects: Compared with the separation of land intensive use evaluation and low-carbon emission evaluation in related technologies, this application can simultaneously determine the results of land intensive use and low-carbon emission within the same evaluation unit, and determine the results of optimal allocation of land resources through the correlation between intensive and low-carbon results, thereby improving the comprehensiveness of the evaluation results.

[0009] Compared with the fixed evaluation units in related technologies, this application updates the first region division strategy to obtain the second region division strategy when the preset strategy update trigger conditions are met. This enables the evaluation units to be split, merged or buffered according to changes in intensive low-carbon status, thereby improving the matching degree between the evaluation boundary and the actual governance object.

[0010] Compared with the simple allocation of carbon dioxide emissions based on land area in related technologies, this application writes energy emission data into the corresponding evaluation unit through spatial binding relationship, first low-carbon verification window and public emission allocation rules, which can reduce the assessment bias caused by enterprise relocation, energy metering mismatch and unclear public emission attribution.

[0011] Compared with the difficulty in translating evaluation results into management actions in related technologies, this application transforms evaluation results into differentiated land resource optimization allocation results through inefficient high-carbon remediation schemes, efficient high-carbon carbon reduction schemes, inefficient low-carbon cultivation schemes, and efficient low-carbon demonstration schemes. This is conducive to forming a land resource allocation mechanism that is both emission reduction and output-oriented. Attached Figure Description

[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart illustrating the first embodiment of the land resource utilization assessment method based on intensive and low-carbon orientation in this application.

[0015] Figure 2 This is a schematic diagram illustrating the standardization and spatial binding processing of the evaluation dataset for the region to be evaluated in this application.

[0016] Figure 3 This is a schematic diagram showing the positional relationship between the first low-carbon verification window and the second low-carbon verification window in this application.

[0017] Figure 4 This is a schematic diagram illustrating the principle of updating the first region partitioning strategy to the second region partitioning strategy in this application.

[0018] Figure 5 This is a schematic diagram illustrating the relationship generated by the optimized allocation of land resources in this application.

[0019] Figure 6 This is a schematic diagram illustrating the analysis that forms the basis for generating the optimal allocation results of land resources in this application.

[0020] Figure 7 This is a schematic diagram of the structure of the land resource utilization assessment system based on intensive and low-carbon orientation provided in this application, which is a second embodiment.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The main solution of this application embodiment is as follows: Based on a preset first regional division strategy, the area to be evaluated is divided into initial evaluation units; based on the evaluation dataset of the area to be evaluated, the land intensive use results and low-carbon emission results corresponding to the initial evaluation units are determined, wherein the land intensive use results include land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low-carbon emission results include per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting processing; based on the land intensive use results and the low-carbon emission results, the intensive and low-carbon correlation results corresponding to the initial evaluation units are analyzed; when a preset strategy update trigger condition is met, the first regional division strategy is updated based on the intensive and low-carbon correlation results to obtain a second regional division strategy, and a re-evaluation unit is determined based on the second regional division strategy; based on the re-evaluation unit, the land resource optimization allocation result is determined.

[0025] In related technologies, land resource utilization assessment typically uses fixed administrative boundaries, fixed planning boundaries, or fixed plot boundaries as assessment units. However, the lack of a feedback and update relationship between the assessment unit and the assessment results means that, given significant differences in land use structure, industrial activities, and low-carbon governance needs within industrial functional zones, fixed boundaries can easily lead to inaccurate assessment results.

[0026] After forming the initial evaluation unit, this application further conducts a correlation analysis between the results of intensive land use and low carbon emissions, and updates the regional division strategy when the preset strategy update trigger conditions are met. This allows the evaluation boundary to be transformed from a simple management boundary into a re-evaluation unit boundary that better reflects the actual governance needs, thereby improving the accuracy of the evaluation results and their management application value.

[0027] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, spatial analysis, layer management, and result output functions, or it can be a land resource utilization assessment system capable of performing the above functions. The following description uses a land resource utilization assessment system as an example to illustrate this embodiment and the subsequent embodiments.

[0028] Example 1: Based on this, embodiments of this application provide a land resource use assessment method based on intensive and low-carbon principles. (Refer to...) Figure 1 , Figure 1 This is a flowchart illustrating Example 1 of the land resource utilization assessment method based on intensive and low-carbon orientation in this application.

[0029] In this embodiment, the land resource utilization assessment method includes steps S100 to S500: Step S100: According to the preset first region division strategy, the region to be evaluated is divided into initial evaluation units.

[0030] It should be noted that the area to be evaluated can be an industrial functional zone, industrial park, development zone, core start-up area, or other spatial area where industrial land is the primary carrier. The first area division strategy is a preset strategy used to form the initial evaluation units at the start of the evaluation.

[0031] Understandably, the pre-defined first-zone delineation strategy is primarily used to provide stable initial evaluation boundaries, enabling the assessment system to perform the first land resource utilization assessment within the existing management framework. Specifically, this first-zone delineation strategy forms initial evaluation units based on pre-defined boundary elements, and then determines whether an update is needed based on subsequent intensive low-carbon correlation results and pre-defined strategy update trigger conditions.

[0032] The first zoning strategy is based on pre-defined boundary elements. These pre-defined boundary elements include management boundary elements, planning boundary elements, and land parcel boundary elements. Management boundary elements are used to ensure the evaluation results are consistent with administrative or park management systems; planning boundary elements are used to ensure the evaluation results are consistent with industrial functional zone planning, regulatory planning, and land use control requirements; and land parcel boundary elements are used to ensure the evaluation results are consistent with ownership management, land transfer, land use renewal, and enterprise land occupation status.

[0033] In one feasible implementation, the land resource utilization assessment system first reads the boundary layer of the area to be assessed and overlays the management boundary elements, planning boundary elements, and plot boundary elements in the boundary layer. The system performs a topological check on the overlaid spatial objects to eliminate duplicate boundaries, gap boundaries, and intersecting boundaries. Subsequently, the system forms candidate evaluation units according to the processing order of prioritizing plot boundaries, correcting planning boundaries, and aggregating management boundaries.

[0034] It should be noted that "plot boundary priority" means that the system prioritizes the plot area determined by the current land ownership or construction land status, avoiding the forced merger of plots with different land ownership or different actual use status; "planning boundary correction" means that the system uses planning boundaries to determine whether candidate evaluation units cross different planning functions; and "management boundary aggregation" means that the system assigns candidate evaluation units to the corresponding management areas, so that the subsequent evaluation results can serve the decomposition of management responsibilities.

[0035] In one feasible implementation, the system determines whether each plot of land meets the independent evaluation criteria. If a plot of land has at least two of the following: independent ownership, independent industry, and independent energy metering, the system identifies that plot as an independent initial evaluation unit. Through this process, the system can evaluate plots of land with independent production, independent metering, or independent ownership separately, avoiding the dilution of their evaluation results by adjacent plots.

[0036] In another feasible implementation, if multiple adjacent plots share the same dominant industry identifier and the same management zone identifier, the system merges these adjacent plots into a single initial evaluation unit. This process reduces the fragmentation of evaluation results caused by overly detailed plot division and enables land resources with similar industry functions within the same management zone to be evaluated holistically.

[0037] Specifically, if there are three adjacent plots, A1, A2, and A3, within the area to be evaluated, where A1 and A2 both belong to the electronic equipment industry zone and are managed by the same park management agency, and A3 belongs to the logistics and warehousing zone, then the system, according to the first regional division strategy, will merge A1 and A2 into one initial evaluation unit and use A3 as another initial evaluation unit. In this way, the initial evaluation units retain the existing management logic while avoiding unnecessary splitting of adjacent plots with consistent industrial functions.

[0038] In this embodiment, the initial evaluation unit is formed based on the preset first region division strategy, which can ensure that the initial evaluation results have a stable spatial basis and provide a comparable benchmark boundary for the dynamic update of the subsequent second region division strategy.

[0039] Step S200: Based on the assessment dataset of the area to be assessed, determine the land intensive use results and low carbon emission results corresponding to the initial evaluation unit. The land intensive use results include land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data. The low carbon emission results include per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting.

[0040] It should be noted that the assessment dataset for the area to be assessed is a collection of data corresponding to that area. This dataset can be retrieved by the system before the assessment begins, or imported from external databases, survey systems, or spatial information platforms. The assessment dataset for the area to be assessed includes basic spatial data, industrial activity data, and energy emission data. Basic spatial data is used to characterize land boundaries, spatial location, planning attributes, and construction status; industrial activity data is used to characterize enterprise production, output carrying capacity, and industry type; and energy emission data is used to characterize information related to energy use, energy metering, and carbon dioxide emissions.

[0041] In one feasible implementation, basic spatial data may include plot identifiers, plot boundaries, planned uses, management zones, construction status, and building object identifiers; industrial activity data may include enterprise identifiers, leading industry identifiers, production status, output carrying capacity status, and actual production space records; energy emission data may include energy metering object identifiers, energy type, metering entity, metering location, and metering time. The above data do not need to originate from the same data system, but they require unified processing after entering the assessment system.

[0042] Before determining the results of intensive land use and low-carbon emissions, the system standardizes the assessment dataset for the area to be evaluated. Standardization includes data encoding, temporal caliber processing, spatial coordinate processing, and statistical caliber processing. Data encoding ensures that enterprise objects, land parcel objects, building objects, and energy metering objects can be uniformly identified; temporal caliber processing ensures that land evaluation data, industrial activity data, and energy emission data are within the same assessment period; spatial coordinate processing allows for the overlay of various data layers; and statistical caliber processing ensures that data from different sources can be aggregated into the same evaluation unit.

[0043] Understandably, if the basic spatial data uses an annual update caliber while the energy emission data uses a monthly measurement caliber, the system can aggregate the energy emission data according to the assessment cycle and match the aggregated energy emission data with the land use status within the same assessment cycle. If different layers use different coordinate systems, the system first converts each layer to the same coordinate benchmark before performing spatial overlay and object binding.

[0044] Reference Figure 2 The system establishes spatial binding relationships after standardization. These spatial binding relationships characterize the correspondence between enterprise objects, land parcel objects, building objects, and energy metering objects. Specifically, the system first reads the production address field and land ownership field corresponding to the enterprise object based on its enterprise identifier, and then binds the enterprise object to the corresponding land parcel object. The system then binds the energy metering object to the corresponding enterprise object or building object based on its metering location field and metering subject field.

[0045] If the production address field of a business entity does not correspond to the metering location field of an energy metering object, it indicates an inconsistency between the business registration information, the actual production space, or the energy metering attribution. In this case, the system reads the actual production space records of the business entity, such as on-site survey records, factory usage records, or questionnaire verification records, and updates the binding relationship between the business entity and the land parcel based on these records. Simultaneously, the system migrates the energy records corresponding to the energy metering object to the updated land parcel object, preventing incorrect energy emissions from being written to the land parcel where the registered address is located.

[0046] Specifically, enterprise object QY-01 is registered at plot DK-01, but its actual production space records show that its production equipment and energy metering points are located at plot DK-02. When establishing the spatial binding relationship, the system first identifies the mismatch between the registered address field and the metering location field, then reads the actual production space records to confirm that QY-01's production space is located at DK-02. Subsequently, QY-01 is bound to DK-02, and the energy records corresponding to this enterprise object are migrated to DK-02. Through this process, plot DK-01 will not be mistakenly included in the enterprise object's energy emissions, and plot DK-02 can accurately reflect its corresponding low-carbon emission results. Table 1 shows an exemplary field organization method for the assessment dataset of the area to be assessed.

[0047] Table 1. Example of the evaluation dataset for the region to be evaluated. ; It should be noted that the examples in Table 1 are only used to illustrate the organization of the assessment dataset for the area to be assessed, and do not limit the field names or number of fields in the actual application of this application. In practical applications, as long as land objects, industry objects, and energy objects can be bound to the corresponding evaluation units, they can be used as the assessment dataset in this application.

[0048] When determining the results of intensive land use, the system extracts the intensive evaluation data corresponding to the initial evaluation unit from the standard assessment dataset. The intensive evaluation data includes land use intensity data and land output carrying capacity data. Land use intensity data reflects the development and utilization status of the evaluation unit, while land output carrying capacity data reflects the status of the evaluation unit in terms of industrial output, tax contribution, or industrial carrying capacity.

[0049] The system determines the land use intensity level based on land use intensity data. In one example, the system can classify the initial evaluation unit as high, medium, or low land use intensity based on its construction carrying capacity, factory building usage status, and land development status. If the initial evaluation unit's construction carrying capacity meets the preset construction target, and its factory building usage status meets the preset usage target, the system determines the initial evaluation unit as high land use intensity. If the initial evaluation unit only partially meets the above targets, the system determines it as medium land use intensity. If the initial evaluation unit does not meet the above targets, the system determines it as low land use intensity.

[0050] The system determines the output carrying capacity level based on land output carrying capacity data. In one example, the system can classify the initial evaluation unit as high, medium, or low output carrying capacity level based on unit output, tax contribution status, and industrial carrying capacity status. If the unit output of the initial evaluation unit meets the output target set by the industrial functional zone, and the industrial carrying capacity status is consistent with the leading industry positioning, the system determines it as high output carrying capacity level; if the unit output does not meet the target but the industrial carrying capacity status is consistent with the leading industry positioning, it is determined as medium output carrying capacity level; if both unit output and industrial carrying capacity status fail to meet the target, it is determined as low output carrying capacity level.

[0051] Furthermore, the system determines land intensive use efficiency based on utilization intensity level and output carrying capacity level. It should be noted that the land intensive use efficiency in this embodiment can be a level result, a scoring result, or a labeling result, and is not limited to a fixed mathematical expression. In practical applications, the system pre-establishes level conversion rules. These rules include utilization intensity level conversion rules, output carrying capacity level conversion rules, and comprehensive judgment rules; specifically, high, medium, and low utilization intensity levels are converted into high, medium, and low utilization intensity values, respectively, and high, medium, and low output carrying capacity levels are converted into high, medium, and low output carrying capacity values, respectively. Within the same evaluation period, the system converts the two levels to the same comparison caliber according to the same level conversion rules, and determines the land intensive use efficiency based on the combination of utilization intensity value and output carrying capacity value.

[0052] For example, when using the scoring results as land intensive use efficiency, the system can synthesize the use intensity value and output carrying capacity value into a land intensive use efficiency score according to a preset contribution relationship. The preset contribution relationship can be a proportional contribution relationship or a differentiated contribution relationship set according to the management objectives of industrial functional zones; the contribution relationship remains unchanged within the same evaluation period. The system compares the synthesized land intensive use efficiency score with a preset intensive threshold. If it is not lower than the preset intensive threshold, a high land intensive label is generated; if it is lower than the preset intensive threshold, a low land intensive label is generated.

[0053] For example, when using non-scoring results as land intensive use efficiency, the system can directly generate tags according to the combination of levels: if both the utilization intensity level and the output carrying capacity level are not lower than the preset target level, a high land intensive tag is generated; if either level is lower than the preset target level, a low land intensive tag or a tag to be improved is generated.

[0054] It should be noted that the system also generates a first constraint list based on land intensive use efficiency. The first constraint list is used to record at least one of the following: inefficient land use markers, idle land use markers, and insufficient output markers.

[0055] Furthermore, the first constraint list is generated in the order of evaluation level identification, constraint item writing, and constraint source recording. The system first reads the utilization intensity level and output carrying capacity level, and writes the initial evaluation units with a utilization intensity level lower than the preset utilization level threshold into the insufficient development intensity mark; writes the initial evaluation units with an output carrying capacity level lower than the preset output level threshold into the insufficient output mark; and writes the initial evaluation units in the standard evaluation dataset with idle status field, shutdown / semi-shutdown field, or inefficient factory building field into idle land mark or inefficient land mark.

[0056] The first constraint list includes at least the initial evaluation unit identifier, trigger field, constraint marker, constraint source, and verification status. The trigger field records land use intensity data or land output carrying capacity data that triggers the constraint; the constraint source records whether the constraint originates from plot boundary data, enterprise output data, questionnaire verification data, or management ledger data; and the verification status indicates whether the constraint is in a directly confirmed state or a state requiring supplementary verification. In this way, the first constraint list not only records whether the initial evaluation unit is inefficient but also the reasons for the inefficiency judgment, facilitating subsequent cross-verification with the second constraint list.

[0057] For example, if the initial evaluation unit P4's construction carrying capacity does not meet the preset construction target, and its unit land output does not meet the output target of similar industries, the system will record insufficient development intensity and insufficient output as markers, respectively. If the questionnaire verification results also show that P4 has long-term vacant factory buildings, then an inefficient land use marker will be added. Thus, the first constraint list corresponding to P4 is recorded as a land use constraint item triggered by insufficient development intensity, insufficient output, and inefficient factory buildings.

[0058] When determining low-carbon emission results, the system sets up a first low-carbon verification window. This first low-carbon verification window is located before the carbon dioxide emission inventory is generated and is used to verify the consistency of the subject field, time field, and spatial field in the energy emission data. The subject field represents the energy user, the time field represents the assessment period to which the energy use belongs, and the spatial field represents the location of the land parcel, building, or enterprise corresponding to the energy metering object.

[0059] Specifically, the system reads energy emission data line by line. If the metering entity field in the energy emission data matches the enterprise identifier, and that enterprise identifier is already bound to the corresponding land parcel object, then the energy emission data passes the entity consistency verification. If the metering time in the energy emission data is within the current assessment period, then the energy emission data passes the time consistency verification. If the metering location field in the energy emission data matches the actual production space record of the enterprise object, then the energy emission data passes the spatial consistency verification.

[0060] For energy emission data that passes consistency verification, the system generates individual carbon dioxide emission records. Individual carbon dioxide emission records that can be directly matched with enterprise or land parcel identifiers are directly written into the corresponding initial evaluation unit. Individual carbon dioxide emission records that cannot be directly matched with enterprise or land parcel identifiers are identified as public emission records. For public emission records, the system splits them according to public emission allocation rules and writes them into the corresponding initial evaluation unit.

[0061] The public emissions allocation rules are determined based on public allocation factors. These factors include energy supply occupancy factors, building usage factors, and beneficiary factors. The energy supply occupancy factor reflects the service relationship between public energy facilities and each assessment unit; the building usage factor reflects the building usage and occupancy status of public facilities by each assessment unit; and the beneficiary factor reflects the actual benefit received by enterprises within each assessment unit from public facilities. This approach avoids attributing all public emissions to the land where public facilities are located, and also avoids simply allocating emissions equally based on area.

[0062] Furthermore, when quantifying the public allocation factor, the system first determines the public facility service recipients corresponding to the public emission records. Service recipients can be determined through energy pipeline connections, contractual energy supply relationships, metering ledgers, lists of beneficiary enterprises, or on-site survey records. For public facilities where service recipients cannot be directly determined, the system uses the spatial overlay result of the public facility's designed service scope and the evaluation unit boundary as candidate service recipients, and marks this candidate relationship as pending verification.

[0063] The system generates the energy supply occupancy ratio, building usage ratio, and beneficiary ratio respectively. The energy supply occupancy ratio is determined based on the occupancy of each evaluation unit in the total energy supply, energy supply duration, or metering interface capacity of the public facilities; the building usage ratio is determined based on the proportion of the actual used building area, production building area, or building area connected to the public facilities in each evaluation unit to the total beneficiary building area; and the beneficiary ratio is determined based on the number of enterprises actually using the public facilities in each evaluation unit, the number of major production enterprises, or the proportion of the production load of the beneficiary to the total beneficiary.

[0064] After obtaining the above proportions, the system determines the public emission allocation proportions according to a preset combination order. If the energy supply metering data is complete, the energy supply occupancy proportion is used as the primary proportion, and then corrected using the building usage proportion and the beneficiary proportion. If the energy supply metering data is incomplete but the building usage record is complete, the building usage proportion is used as the primary proportion, and then corrected using the beneficiary proportion. If both the energy supply metering data and the building usage record are incomplete, the beneficiary proportion is used as the provisional primary proportion, and the corresponding public emission allocation record is marked as pending review. The system ensures that the total allocation proportions of all evaluation units corresponding to the same public emission record constitute a complete allocation relationship, thereby avoiding duplicate or omitted allocations.

[0065] Based on the aforementioned public emission allocation ratio, the system performs spatial weighting on public emission records, that is, it writes public emission records into the corresponding evaluation units according to the spatial service relationship and beneficiary relationship of each evaluation unit. Simultaneously, for enterprise emission records that span multiple evaluation units, the system determines spatial weights based on actual production space, energy metering location, and building usage scope, and writes the emission records into multiple evaluation units accordingly. The spatial weights are the spatial allocation ratios jointly defined by energy service relationship, building usage relationship, and beneficiary relationship.

[0066] Specifically, a centralized energy supply station is located in the initial evaluation unit P1, but it simultaneously serves P1, P2, and P3. The system does not write all public emission records corresponding to this energy supply station into P1. Instead, it determines the allocation portions for P1, P2, and P3 according to the public emission allocation rules. If the building use factor and beneficiary factor of P2 are both higher than those of P1, then the public emission allocation record for P2 can be higher than that for P1. Through this process, the per-site CO2 emission efficiency can more closely approximate the correlation between actual benefits and actual emissions.

[0067] The system aggregates individual carbon dioxide emission records written to the same initial evaluation unit to obtain the total carbon dioxide emissions corresponding to that initial evaluation unit. Then, based on the total carbon dioxide emissions and the land use carrying capacity data corresponding to the initial evaluation unit, the system determines the carbon dioxide emission efficiency per unit area. Land use carrying capacity data may include industrial land use carrying capacity data and building carrying capacity data; this embodiment does not limit their specific form.

[0068] In one feasible implementation, when determining the per-region CO2 emission efficiency, the system first determines the total CO2 emissions involved in the calculation. This total CO2 emissions includes individual CO2 emission records directly written into the initial evaluation unit, as well as public emission allocation records written into the initial evaluation unit according to public emission allocation rules. Subsequently, the system reads the land use carrying capacity data corresponding to the initial evaluation unit. If the land use carrying capacity data only includes industrial land carrying capacity area, then the industrial land carrying capacity area is used as the land use carrying capacity base; if the land use carrying capacity data includes both industrial land carrying capacity area and building carrying capacity correction data, then the corrected land carrying capacity base is first determined based on preset building carrying capacity correction rules, and then the per-region CO2 emission efficiency is determined based on the total CO2 emissions and the land use carrying capacity base.

[0069] Furthermore, when generating land use carrying capacity data, the system first reads the industrial land boundary, actual construction boundary, and building object boundary of the initial evaluation unit, and removes roads, water areas, public green spaces, and supporting spaces that do not participate in industrial production carrying capacity to obtain the industrial land carrying capacity area. If there are phased construction, idle factory buildings, production stoppage areas, or temporary construction areas within the evaluation unit, the system will mark the corresponding areas as carrying capacity correction objects.

[0070] When generating building carrying capacity correction data, the system adjusts the data according to the building's construction status, usage status, and production-related status. Buildings already constructed and used for industrial activities such as production, R&D, pilot testing, and warehousing are identified as actual carrying capacity buildings. Buildings that are not yet constructed, not in use, long-term idle, or used only as non-productive temporary spaces are not considered actual carrying capacity buildings, or are included in the carrying capacity base according to their actual usage ratio. Based on the land area occupied by the actual carrying capacity buildings, the system corrects the industrial land carrying capacity area to obtain the corrected land carrying capacity base.

[0071] When determining the carbon dioxide emission efficiency per unit area, the system first determines the total emissions that should be included in the evaluation unit through spatial weighting, and then performs unit land carrying capacity conversion based on the corrected land carrying capacity base.

[0072] For example, assuming that the initial evaluation unit P5 has a direct CO2 emission record of 860 tons and a public emission allocation record of 140 tons during an evaluation period, the system will summarize the total CO2 emissions corresponding to P5 as 1,000 tons. If the industrial land carrying capacity area corresponding to P5 is 50 mu (approximately 3.3 hectares), and the building carrying capacity correction data was not used in this round of evaluation, the system will convert the 1,000 tons to the carrying capacity per unit land area of ​​50 mu (approximately 3.3 hectares), resulting in a CO2 emission efficiency of 20 tons per mu (approximately 13 tons per hectare) for P5.

[0073] If the total carbon dioxide emissions corresponding to the same initial evaluation unit P6 are 900 tons, and the industrial land carrying capacity area is 30 mu (approximately 2 hectares), but the building carrying capacity correction data indicates that 10 mu (approximately 6.7 hectares) of this area is undeveloped and not actually carrying production activities, then the system, according to the preset building carrying capacity correction rules, determines the actual land area participating in the carrying capacity to be 20 mu (approximately 1.3 hectares), and accordingly obtains the per-mu carbon dioxide emission efficiency of P6 as 45 tons per mu (approximately 2.3 tons per hectare). Through the above processing, the system can distinguish between nominal land area and actual carrying capacity area, avoiding the underestimation of per-mu carbon dioxide emission efficiency due to an excessively large land area during the construction phase.

[0074] It should be noted that the carbon dioxide emission efficiency per unit area in this application is used to characterize the carbon dioxide emission level under the unit land carrying capacity condition. If the carbon dioxide emission efficiency per unit area is higher than the preset emission threshold, it indicates that the evaluation unit has high carbon emission pressure at the unit land carrying capacity level; if the carbon dioxide emission efficiency per unit area is not higher than the preset emission threshold, it indicates that the evaluation unit has not exceeded the low-carbon control requirements at the unit land carrying capacity level.

[0075] Furthermore, the second constraint list is generated in the order of emission efficiency assessment, carbon constraint item writing, and allocation source record. The system compares the per-regional carbon dioxide emission efficiency with the preset emission threshold; if the per-regional carbon dioxide emission efficiency is higher than the preset emission threshold, a high-carbon emission marker is written; if the proportion of fossil energy use in total energy use in energy emission data is higher than the preset energy structure threshold, an energy structure constraint marker is written; if there are public emission allocation records in the total carbon dioxide emissions, a public emission allocation marker is written, and the corresponding public facility identifier, beneficiary unit identifier, and allocation basis are recorded.

[0076] The second constraint list includes at least the initial evaluation unit identifier, per-acre carbon dioxide emission efficiency, emission threshold comparison results, energy structure constraint results, public emission allocation results, and low-carbon verification status. The low-carbon verification status indicates whether the low-carbon emission results of the initial evaluation unit require further verification. For example, if the per-acre carbon dioxide emission efficiency of initial evaluation unit P5 is 20 tons per acre, and the preset emission threshold is 15 tons per acre, the system will write a high-carbon emission marker. If the total carbon dioxide emissions of P5 include public emission allocation records from centralized energy supply stations, then a public emission allocation marker will be written, and the centralized energy supply station identifier and allocation basis will be recorded. Thus, the second constraint list can indicate whether the high-carbon source of the initial evaluation unit is its own direct emissions, energy structure factors, or public emission allocation factors.

[0077] In one feasible implementation, the system can save the land intensive use results and low-carbon emission results for each assessment cycle at the end of that cycle, and use them as a historical reference for determining whether the zoning strategy needs to be updated in the next assessment cycle. Through this process, the system can not only output the current assessment results, but also identify whether a certain initial assessment unit continues to have inefficiencies or high-carbon problems throughout consecutive assessment cycles.

[0078] Step S300: Based on the results of intensive land use and low carbon emissions, analyze the intensive and low carbon correlation results corresponding to the initial evaluation unit.

[0079] It should be noted that the intensive and low-carbon correlation results are used to characterize the combined state between land use efficiency and low-carbon emission efficiency of the initial evaluation unit. By correlating land use efficiency and low-carbon emission efficiency, the governance type of the initial evaluation unit under the guidance of intensive and low-carbon is determined.

[0080] Reference Figure 3 The system sets up a second low-carbon verification window. This second low-carbon verification window is located after the per-land CO2 emission efficiency is determined, and is used to cross-verify the first and second constraint lists. The first constraint list is derived from intensive land use results, and the second constraint list is derived from low-carbon emission results.

[0081] In one feasible implementation, the second low-carbon verification window reads the first and second constraint lists one by one according to the evaluation unit. If the first constraint list contains inefficient land use markers and the second constraint list also contains high-carbon emission markers, the system determines the initial evaluation unit as an inefficient high-carbon type; if the first constraint list does not contain inefficient land use markers and the second constraint list does not contain high-carbon emission markers, the system determines the initial evaluation unit as an efficient low-carbon type. Through this process, the system can simultaneously consider land use status and low-carbon emission status within the same evaluation unit.

[0082] If the same initial assessment unit simultaneously possesses both a high land-use efficiency marker and a high carbon emission marker, the system generates a high-efficiency, high-carbon marker. A high land-use efficiency marker indicates that land-use efficiency is not lower than a preset threshold, while a high carbon emission marker indicates that per-unit carbon dioxide emission efficiency exceeds a preset threshold. This type of assessment unit indicates that land-use efficiency has reached its target, but carbon dioxide emission pressure exceeds control requirements. Therefore, direct relocation is not advisable; instead, priority should be given to carbon reduction and retrofitting.

[0083] If the same initial evaluation unit simultaneously possesses both a low land-use efficiency label and a low-carbon emission label, the system generates an inefficient low-carbon label. A low land-use efficiency label indicates that land-use efficiency is below a preset threshold, while a low-carbon emission label indicates that per-unit carbon dioxide emission efficiency is not higher than a preset emission threshold. This type of evaluation unit indicates that emission pressure has not exceeded control requirements, but land use efficiency is insufficient, making it suitable for subsequent low-carbon industry introduction, revitalization of idle factory buildings, or optimization of land use structure.

[0084] If the same initial assessment unit simultaneously has both low land-use efficiency and high carbon emission labels, the system generates an inefficient high-carbon label. Such assessment units indicate insufficient land use efficiency and emission pressures exceeding control requirements, making them suitable for subsequent remediation pathways for inefficient and high-carbon practices.

[0085] If the same initial assessment unit simultaneously possesses both high land-use efficiency and low-carbon emission labels, the system generates an efficient low-carbon label. This type of assessment unit indicates that land use efficiency has met targets and emission pressures have not exceeded control requirements, making it suitable for subsequent demonstration and promotion pathways.

[0086] In one feasible implementation, the second low-carbon verification window is also used to identify whether spatial binding relationships need to be corrected. For example, if an initial assessment unit is marked as high-carbon emitting, but there are no energy metering objects within that unit, and its high carbon emissions originate from adjacent public facilities, the system will generate an external impact label for that unit instead of directly identifying it as a high-carbon emitting site. As another example, if a business is registered in initial assessment unit B1, but its actual production space records show that its main production activities are located in initial assessment unit B2, the system will rebind the business to B2 and migrate the relevant energy records to B2.

[0087] Understandably, the second low-carbon verification window serves a different purpose than the first. The first low-carbon verification window primarily verifies whether energy emission data can be accurately entered into the evaluation unit before low-carbon emission results are generated; the second low-carbon verification window primarily verifies whether the combination of land intensive use results and low-carbon emission results conforms to spatial logic after low-carbon emission results are generated. Through the division of labor between the two verification windows, the system can separately control data input errors and result correlation errors.

[0088] In one feasible implementation, if the second low-carbon verification window identifies that the intensive low-carbon type of an initial evaluation unit is inconsistent with the type of its internal land parcels, the system further reads the labeling results of each land parcel within that initial evaluation unit. If at least two land parcels have different intensive low-carbon types, the system generates a boundary differentiation marker. This boundary differentiation marker serves as the triggering basis for subsequent updates to the first region delineation strategy.

[0089] Through the above processing, the intensive low-carbon correlation results are not only used to generate evaluation types, but also to determine whether data binding and evaluation boundaries need to be adjusted, thus providing a basis for subsequent updates to the first region division strategy.

[0090] Step S400: When the preset strategy update trigger condition is met, the first region division strategy is updated based on the intensive low-carbon association result to obtain the second region division strategy, and a re-evaluation unit is determined based on the second region division strategy.

[0091] It should be noted that the preset strategy update trigger conditions include periodic trigger conditions and status trigger conditions. Periodic trigger conditions are triggered when a preset evaluation cycle is reached, such as quarterly, semi-annually, or annually. Status trigger conditions are when the initial evaluation unit has a boundary-internal differentiation marker, a cross-boundary homogeneity marker, or an external influence marker.

[0092] Understandably, the periodic trigger condition is used to ensure that the system can review the evaluation boundary according to a fixed evaluation cycle, avoiding the long-term use of the old boundary; the state trigger condition is used to ensure that the system can promptly initiate strategy updates when there is obvious spatial differentiation or cross-boundary correlation, avoiding the need to wait for the next cycle to adjust the evaluation unit.

[0093] Internal boundary differentiation is indicated by the presence of at least two land parcels with different intensive low-carbon types within the same initial evaluation unit. For example, an initial evaluation unit C1 may contain three land parcels: C1-1 is of high-efficiency low-carbon type, C1-2 is of low-efficiency high-carbon type, and C1-3 is of low-efficiency high-carbon type. Because different governance types exist within the same initial evaluation unit, the system generates internal boundary differentiation markers and splits the initial evaluation unit into multiple sub-evaluation units along the land parcel boundaries during policy updates.

[0094] Cross-boundary homogeneous markers are those adjacent initial evaluation units that share the same dominant industry identifier and the same energy facility identifier. For example, initial evaluation units D1 and D2, although belonging to different management sub-zones, both belong to the biopharmaceutical industry and share the same centralized heating facility. The system generates cross-boundary homogeneous markers and deletes the common evaluation boundary between D1 and D2 during strategy updates, generating merged evaluation units. This process enables regions sharing emission reduction facilities to participate in subsequent optimization configurations as a whole.

[0095] External impacts are identified when the primary beneficiaries in the public emissions sharing record are located outside the initial assessment unit. For example, an energy center may be located in the initial assessment unit E1, but its primary service recipients are located in E2 and E3. If all emissions pressures are attributed to E1, it would distort the assessment of E1. After identifying this situation, the system generates an external impact marker and creates associated buffer units based on the service scope of the energy center, establishing a low-carbon governance linkage between E1, E2, and E3.

[0096] Furthermore, the primary beneficiaries are determined by the system based on the intensity of benefit. If the public emission allocation ratio corresponding to an initial evaluation unit is the highest among all benefit evaluation units, or if it exceeds a preset benefit ratio threshold for multiple consecutive evaluation periods, then the system identifies that initial evaluation unit as the primary beneficiary. If the allocation ratios of multiple evaluation units are close and all exceed the preset benefit ratio threshold, then the system identifies these multiple evaluation units collectively as the primary beneficiaries. Thus, the system can determine the main governance responsibilities and related governance targets for public emissions.

[0097] In one feasible implementation, this application proposes a dual-trigger update mechanism. This mechanism includes a first trigger path and a second trigger path. The first trigger path is a periodic trigger path, used to ensure that the evaluation system can review the region division strategy when the preset evaluation period arrives, even if no significant state change occurs. The second trigger path is a state trigger path, used to ensure that when the initial evaluation unit experiences internal boundary differentiation, cross-boundary homogeneity, or external influences, the strategy update can be initiated in advance without waiting for the next evaluation period.

[0098] Specifically, after each intensive low-carbon correlation analysis, the system first determines whether a preset assessment period has been reached. If the preset assessment period has been reached, the system generates a periodic update task and reads the intensive low-carbon correlation results of all initial evaluation units within this period. If the preset assessment period has not been reached, the system continues to determine whether there are state triggering conditions. If state triggering conditions exist, the system generates a state update task; if no state triggering conditions exist, the system only saves the assessment results for this round and does not update the regional division strategy.

[0099] Furthermore, the periodic update task and the status update task can have different processing scopes. The periodic update task can cover the entire area to be evaluated, used to comprehensively verify whether the first area division strategy is still applicable; the status update task can only cover the initial evaluation unit with the trigger marker and its adjacent evaluation units, used to reduce unnecessary global re-division. Through this design, this application avoids both the instability of results caused by re-dividing the area for each evaluation and the problem that fixed periodic updates cannot respond to changes in industry activities in a timely manner.

[0100] In another feasible implementation, this application also proposes a boundary update intensity grading mechanism. The system configures an update intensity for each trigger marker. If the trigger marker is an internal boundary differentiation marker, and at least two plots within the same initial evaluation unit have different intensive low-carbon types, the system performs a splitting process; if the trigger marker is a cross-boundary homogeneous marker, and adjacent initial evaluation units share the same energy facility identifier, the system performs a merging process; if the trigger marker is an external impact marker, the system does not directly change the original evaluation boundary, but instead generates associated buffer units. By assigning different update intensities to different trigger markers, the same regional adjustment action can be avoided for all triggering situations, thereby improving the precision of the regional division strategy update.

[0101] Reference Figure 4 When updating the first region division strategy based on the intensive low-carbon correlation results, the system can perform three types of actions: splitting, merging, and correlation buffering. If the initial evaluation unit has an internal boundary differentiation marker, the system uses the land parcel boundary within the initial evaluation unit as the splitting boundary to generate a split evaluation unit. If adjacent initial evaluation units have cross-boundary homogeneous markers, the system deletes the common evaluation boundary between adjacent initial evaluation units and generates a merged evaluation unit. If the initial evaluation unit has an external impact marker, the system generates a correlation buffer unit based on the service range of the corresponding public facility.

[0102] Furthermore, the associated buffer unit is an associated management unit superimposed on the original evaluation unit. When generating an associated buffer unit, the system first reads the public facility identifier, facility location, pipeline or service path, service object list, and public emission allocation record; then, it determines the buffer benchmark based on the service scope of the public facility. If the service scope has a clearly defined pipeline, energy supply boundary, or contract service scope, the system uses that scope as the buffer benchmark; if the service scope lacks a clearly defined boundary, the system generates candidate buffer ranges centered on the location of the public facility, combined with a preset service radius, road corridor, or pipeline direction.

[0103] The system overlays the candidate buffer range with the boundary of the initial evaluation unit, extracts evaluation units that intersect with the candidate buffer range and have public emission sharing records, major beneficiary markers, or energy facility sharing markers, and forms associated buffer units. If an associated buffer unit overlaps with the original initial evaluation unit, the system does not delete the boundary of the original initial evaluation unit, but instead writes the associated buffer identifier, public facility identifier, beneficiary identifier, and public emission sharing ratio into the layer attributes; if the associated buffer unit only covers a part of the original evaluation unit, the system writes that part as the associated impact range into the strategy update record and generates collaborative governance requirements in the subsequent configuration results.

[0104] When a related buffer unit needs to participate in a re-evaluation, the system only uses the related buffer unit for matters related to public emissions, shared facilities, and collaborative governance; the efficiency of intensive land use is still determined by re-aggregating the land parcels, buildings, and industrial activities it covers. In this way, the related buffer unit can express the impact of public facilities on external evaluation units without causing logical conflicts between the original evaluation boundaries and ownership and management boundaries.

[0105] It should be noted that splitting evaluation units, merging evaluation units, and associating buffer units are not mutually exclusive. Within the same update cycle, the system can perform splitting processing on one area while simultaneously performing merging processing on another area, and can also generate associating buffer units around public facilities. The system writes these update actions into the policy update record and generates a second area division policy.

[0106] The system incorporates at least one of the following into the second regional division strategy: splitting evaluation units, merging evaluation units, and associating buffer units. The evaluation units corresponding to the second regional division strategy are then designated as re-evaluation units. These re-evaluation units are used to subsequently re-execute object binding, data migration, emission aggregation, carrying capacity baseline correction, land intensive use efficiency recalculation, and per-unit carbon dioxide emission efficiency recalculation.

[0107] Specifically, after completing the evaluation in the first quarter, a certain industrial park used a first-zone division strategy to create 10 initial evaluation units. In the second quarter evaluation, the system identified two of these initial evaluation units with internal boundary differentiation markers, one group of adjacent initial evaluation units with cross-boundary homogeneity markers, and one initial evaluation unit with an external impact marker. Based on this, the system performed two splits, one merge, and one correlation buffering process, resulting in 12 re-evaluation units. The number of these re-evaluation units was not simply increased or decreased, but dynamically formed according to actual governance needs.

[0108] In one feasible implementation, after generating the second region division strategy, the system can also perform consistency verification on the evaluation units before and after the update. Consistency verification includes boundary closure verification, spatial overlap verification, and data migration verification. Boundary closure verification confirms that the boundaries of the re-evaluation units can form closed spaces; spatial overlap verification confirms that there is no unreasonable overlap between re-evaluation units; and data migration verification confirms that the enterprise objects, land parcel objects, building objects, and energy metering objects within the original initial evaluation units have been migrated or bound to the corresponding re-evaluation units.

[0109] If the consistency check fails, the system retains the first region division strategy as the current valid strategy and writes the reason for the failure into the strategy update record. If the consistency check passes, the system sets the second region division strategy as the current valid strategy and proceeds to the subsequent land resource optimization allocation result determination process based on the re-evaluation unit. This process avoids distortion of subsequent configuration results due to boundary errors or data migration errors during the strategy update process.

[0110] Step S500: Based on the re-evaluation unit, determine the optimal allocation result of land resources.

[0111] like Figure 5 As shown, it should be noted that after determining the re-evaluation unit, the system re-executes data collection and result calculation based on the re-evaluation unit, and determines the land resource optimization allocation result at the re-evaluation unit level.

[0112] Specifically, for split evaluation units, the system re-establishes spatial binding relationships based on the split land parcels, buildings, enterprises, and energy metering objects. It migrates land use intensity data, land output carrying capacity data, and individual carbon dioxide emission records from the original initial evaluation units to the corresponding split evaluation units, and recalculates land intensive use efficiency, the first constraint list, total carbon dioxide emissions, per-unit carbon dioxide emission efficiency, and the second constraint list. For merged evaluation units, the system aggregates data objects from multiple original initial evaluation units into the merged evaluation unit, re-summarizes emission records and land carrying capacity data, and regenerates land intensive use results and low-carbon emission results based on the merged data. For associated buffer units, the system retains the basic evaluation results of the original evaluation units, while writing public facility emission allocation records, major beneficiary markers, and shared energy facility identifiers into the associated buffer units. When collaborative governance of public facilities is involved, the system recalculates the public emission allocation relationship within the associated scope.

[0113] After recalculation, the system executes the second low-carbon verification window again to cross-verify the first and second constraint lists of the re-evaluation unit, and uses the verified high-efficiency high-carbon, low-efficiency high-carbon, low-efficiency low-carbon, or high-efficiency low-carbon types as the direct basis for the land resource optimization allocation results.

[0114] Reference Figure 6 The results of land resource optimization include inefficient and high-carbon remediation plans, efficient and high-carbon carbon reduction plans, inefficient and low-carbon development plans, and efficient and low-carbon demonstration plans.

[0115] If the land use efficiency of a re-evaluation unit is lower than a preset intensive use threshold, but the per-unit carbon dioxide emission efficiency is higher than a preset emission threshold, the system determines an inefficient and high-carbon remediation plan. This plan may include inefficient space cleanup, industrial access restrictions, and prioritizing the timing of energy system upgrades and renewals. This plan is used to address re-evaluation units with insufficient land use efficiency and emission pressures exceeding control requirements.

[0116] In one example, the land intensive use efficiency of re-evaluation unit F1 is 62 points, lower than the preset intensive use threshold of 70 points; the per-acre carbon dioxide emission efficiency is 3.10 tons / acre, higher than the preset emission threshold of 2.80 tons / acre. The system identifies F1 as an inefficient and high-carbon remediation target and generates an inefficient and high-carbon remediation plan. This plan may include including F1 in the near-term remediation list, restricting the introduction of new high-energy-consuming projects, prioritizing the verification of the usage status of inefficient factory buildings, and simultaneously proposing energy system transformation requirements.

[0117] If the land use efficiency of the re-evaluation unit is not lower than the preset intensive threshold, and the carbon dioxide emission efficiency per unit area is higher than the preset emission threshold, then the system determines an efficient and high-carbon reduction scheme. This efficient and high-carbon reduction scheme may include energy substitution, process emission reduction, sharing of public emission reduction facilities, and enhanced carbon emission monitoring. This scheme is used to address re-evaluation units where land use efficiency meets the target but emission pressure exceeds control requirements.

[0118] In one example, the land intensive use efficiency of re-evaluation unit F2 is 82 points, higher than the preset intensive use threshold of 70 points; the per-acre carbon dioxide emission efficiency is 3.25 tons / acre, higher than the preset emission threshold of 2.80 tons / acre. The system identifies F2 as a high-efficiency, high-carbon reduction target and generates a high-efficiency, high-carbon reduction plan. This plan prioritizes its connection to low-carbon energy sources, the adoption of energy-saving technologies, and increased frequency of carbon emission monitoring.

[0119] If the land use efficiency of the re-evaluation unit is lower than the preset intensive threshold, and the per capita carbon dioxide emission efficiency is not higher than the preset emission threshold, the system determines an inefficient low-carbon development plan. This plan can include the introduction of low-carbon industries, revitalization of idle factory buildings, improvement of development intensity, and optimization of land use structure. This plan is used to address re-evaluation units where emission pressure does not exceed control requirements but land use efficiency is insufficient.

[0120] In one example, the land intensive use efficiency of re-evaluation unit F3 is 58 points, lower than the preset intensive threshold of 70 points; the per-acre carbon dioxide emission efficiency is 1.90 tons / acre, not higher than the preset emission threshold of 2.80 tons / acre. The system identifies F3 as an inefficient low-carbon development target and generates an inefficient low-carbon development plan. This plan can prioritize the introduction of low-carbon R&D, pilot-scale, or light manufacturing projects and revitalize idle factory buildings to improve land use efficiency while maintaining a low-carbon status.

[0121] If the land use efficiency of the re-evaluation unit is not lower than the preset intensive use threshold, and the per-unit carbon dioxide emission efficiency is not higher than the preset emission threshold, then the system determines a high-efficiency, low-carbon demonstration scheme. The high-efficiency, low-carbon demonstration scheme may include spatial guarantees, demonstration and promotion, policy incentives, and long-term monitoring. This scheme is used to handle re-evaluation units where land use efficiency has reached the target and emission pressure has not exceeded control requirements.

[0122] In one example, the land intensive use efficiency of re-evaluation unit F4 is 88 points, higher than the preset intensive use threshold of 70 points; the carbon dioxide emission efficiency per unit area is 2.10 tons / mu, not higher than the preset emission threshold of 2.80 tons / mu. The system identifies F4 as a high-efficiency and low-carbon demonstration object and generates a high-efficiency and low-carbon demonstration plan. This plan may include preserving existing industrial space, summarizing low-carbon land use patterns, using it as a demonstration unit in the park, and setting a long-term monitoring period.

[0123] In one feasible implementation, the system can also output the land resource optimization allocation results as layer results, list results, and record results. The layer results are used to display the spatial location and configuration scheme of each re-evaluation unit; the list results are used to display the evaluation type, trigger markers, and configuration measures of each re-evaluation unit; and the record results are used to display the process of updating the first regional division strategy to the second regional division strategy.

[0124] Therefore, this embodiment enables land resource utilization assessment to be transformed from static evaluation to dynamic evaluation, and can form land resource allocation results that are oriented towards both emission reduction and output.

[0125] Example 2: Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment described above can be referred to the above description, and will not be repeated hereafter.

[0126] This application also provides a land resource use assessment system based on intensive and low-carbon principles; please refer to... Figure 7 The land resource use assessment system based on intensive and low-carbon orientation includes: The initial division module 10 is used to divide the area to be evaluated into initial evaluation units according to the preset first area division strategy. The result determination module 20 is used to determine the land intensive use result and low carbon emission result corresponding to the initial evaluation unit based on the evaluation dataset of the area to be evaluated. The land intensive use result includes land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low carbon emission result includes per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting. The correlation analysis module 30 is used to analyze the intensive and low-carbon correlation results corresponding to the initial evaluation unit based on the intensive land use results and the low-carbon emission results. The strategy update module 40 is used to update the first region division strategy based on the intensive low-carbon association result when the preset strategy update trigger condition is met, to obtain a second region division strategy, and to determine a re-evaluation unit based on the second region division strategy. The configuration determination module 50 is used to determine the optimal allocation result of land resources based on the re-evaluation unit.

[0127] The land resource utilization assessment system based on intensive and low-carbon principles provided in this application, employing the land resource utilization assessment method based on intensive and low-carbon principles described in the above embodiments, can solve the technical problems of insufficient connection between land intensive assessment and low-carbon emission assessment in land resource utilization assessment, and the difficulty of using fixed regional division methods to support differentiated governance. Compared with the prior art, the beneficial effects of the land resource utilization assessment system provided in this application are the same as those of the land resource utilization assessment method provided in the above embodiments, and will not be repeated here.

[0128] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the land resource utilization assessment method and system based on intensive and low-carbon orientation. Equivalent substitutions or conventional transformations based on the technical concept of this application should be included within the scope of protection of this application.

[0129] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A land resource use assessment method based on intensive and low-carbon orientation, characterized in that, The method includes: According to the preset first area division strategy, the area to be evaluated is divided into initial evaluation units; Based on the assessment dataset of the area to be assessed, the land intensive use results and low carbon emission results corresponding to the initial evaluation unit are determined. The land intensive use results include land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low carbon emission results include per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting. Based on the results of intensive land use and low carbon emissions, analyze the intensive and low carbon correlation results corresponding to the initial evaluation unit; When the preset strategy update trigger condition is met, the first region division strategy is updated based on the intensive low-carbon association result to obtain the second region division strategy, and the re-evaluation unit is determined based on the second region division strategy. Based on the re-evaluation unit, the optimal allocation result of land resources is determined.

2. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 1, characterized in that, The steps for dividing the area to be evaluated into initial evaluation units according to the preset first area division strategy include: Based on preset boundary elements, the first area division strategy is determined, wherein the preset boundary elements include one or more combinations of management boundary elements, planning boundary elements, and land parcel boundary elements; According to the first regional division strategy, the land parcels that meet the independent evaluation conditions are identified as independent initial evaluation units, wherein the independent evaluation conditions are that the land parcel has at least two of the following: independent ownership identification, independent industry identification, and independent energy metering identification. According to the first regional division strategy, adjacent plots that meet the merging evaluation conditions are merged into an initial evaluation unit, wherein the merging evaluation conditions are that the adjacent plots have the same dominant industry identification and the same management area identification.

3. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 1, characterized in that, Before determining the land intensive use results and low carbon emission results corresponding to the initial evaluation unit based on the evaluation dataset of the area to be evaluated, the following steps are included: Obtain the assessment dataset of the region to be assessed, wherein the assessment dataset of the region to be assessed includes basic spatial data, industrial activity data, and energy emission data; The evaluation dataset of the region to be evaluated is standardized to obtain a standard evaluation dataset. The standardization process includes data encoding, time-based processing, spatial coordinate processing, and statistical processing. Based on the standard evaluation dataset, spatial binding relationships are established, wherein the spatial binding relationships are used to characterize the correspondence between enterprise objects, land parcel objects, building objects, and energy metering objects.

4. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 3, characterized in that, The steps to establish a spatial binding relationship include: Based on the enterprise identifier of the enterprise object, determine the production address field and land ownership field corresponding to the enterprise object; Based on the production address field and the land ownership field, the enterprise object is bound to the corresponding land parcel object; Based on the metering location field and metering subject field of the energy metering object, the energy metering object is bound to the corresponding enterprise object or building object; If the production address field of the enterprise object does not correspond to the metering location field of the energy metering object, then based on the actual production space record of the enterprise object, the binding relationship between the enterprise object and the land parcel object is updated, and the energy record corresponding to the energy metering object is migrated to the updated land parcel object.

5. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 3, characterized in that, The steps for determining the land intensive use results corresponding to the initial evaluation unit include: Extract the intensive evaluation data corresponding to the initial evaluation unit from the standard evaluation dataset, wherein the intensive evaluation data includes land use intensity data and land output carrying capacity data; Based on the land use intensity data, the use intensity level corresponding to the initial evaluation unit is determined; Based on the land output carrying capacity data, the output carrying capacity level corresponding to the initial evaluation unit is determined; Based on the utilization intensity level and the output carrying capacity level, the land intensive use efficiency corresponding to the initial evaluation unit is determined, and a first constraint list is generated, wherein the first constraint list is used to record at least one of inefficient land use markers, idle land use markers, and insufficient output markers.

6. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 3, characterized in that, The steps for determining the low-carbon emission results corresponding to the initial evaluation unit include: Set up a first low-carbon verification window, and within the first low-carbon verification window, perform consistency verification on the main field, time field, and spatial field of the energy emission data; A single carbon dioxide emission record is generated based on energy emission data that has passed consistency verification; Individual carbon dioxide emission records that can be directly matched with enterprise or land parcel identifiers will be written into the corresponding initial evaluation unit. Individual carbon dioxide emission records that cannot be directly matched with enterprise or land parcel identifiers are split according to the public emission allocation rules and written into the corresponding initial evaluation units. The public emission allocation rules are determined based on public allocation factors, which include energy supply occupancy factors, building use factors, and beneficiary factors. The individual carbon dioxide emission records written into the same initial evaluation unit are aggregated to determine the total carbon dioxide emission corresponding to the initial evaluation unit. Based on the total carbon dioxide emission and the land use carrying capacity data corresponding to the initial evaluation unit, the per-land carbon dioxide emission efficiency is determined.

7. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 6, characterized in that, Based on the results of intensive land use and low carbon emissions, the steps for analyzing the intensive and low carbon correlation results corresponding to the initial evaluation unit include: Based on the per capita carbon dioxide emission efficiency, a second constraint list is generated, wherein the second constraint list is used to record at least one of high carbon emission markers, energy structure constraint markers, and public emission sharing markers; Set up a second low-carbon verification window, and cross-verify the first constraint list and the second constraint list within the second low-carbon verification window; If the same initial evaluation unit has both a high land intensification marker and a high carbon emission marker, then an efficient high carbon marker is generated. The high land intensification marker is that the land intensification efficiency is not lower than a preset intensification threshold, and the high carbon emission marker is that the per capita carbon dioxide emission efficiency is higher than a preset emission threshold. If the same initial evaluation unit has both a low land intensification label and a low carbon emission label, an inefficient low carbon label is generated. The low land intensification label means that the land intensification efficiency is lower than the preset intensification threshold, and the low carbon emission label means that the per capita carbon dioxide emission efficiency is not higher than the preset emission threshold. If the same initial evaluation unit has both a low land intensification label and a high carbon emission label, then an inefficient high carbon label is generated. If the same initial evaluation unit has both a high land intensification label and a low carbon emission label, then an efficient low carbon label is generated.

8. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 7, characterized in that, The preset strategy update triggering conditions include periodic triggering conditions and state triggering conditions; The periodic trigger condition is reaching a preset evaluation period; The state triggering condition is that the initial evaluation unit has a boundary internal differentiation mark, a cross-boundary homogeneous mark, or an external influence mark. The boundary differentiation marker is the presence of at least two land parcels with different intensive low-carbon types within the same initial evaluation unit; the cross-boundary homogeneity marker is the presence of adjacent initial evaluation units with the same dominant industry identifier and sharing the same energy facility identifier; and the external impact marker is the presence of the main beneficiary in the public emission sharing record located outside the initial evaluation unit.

9. The land resource use assessment method based on intensive and low-carbon orientation as described in claim 8, characterized in that, Based on the intensive low-carbon correlation results, the first region division strategy is updated to obtain a second region division strategy, and the step of determining the re-evaluation unit based on the second region division strategy includes: If the initial evaluation unit has a boundary internal differentiation mark, then the land parcel boundary within the initial evaluation unit is used as the split boundary to generate a split evaluation unit; If adjacent initial evaluation units have homogeneous cross-boundary markers, then delete the common evaluation boundary between adjacent initial evaluation units and generate a merged evaluation unit; If the initial evaluation unit has an external impact marker, then an associated buffer unit is generated based on the service range of the corresponding public facility; Based on at least one of the split evaluation unit, the merge evaluation unit, and the associated buffer unit, a second region partitioning strategy is generated, and the evaluation unit corresponding to the second region partitioning strategy is determined as a re-evaluation unit.

10. A land resource use assessment system based on intensive and low-carbon principles, characterized in that, The system includes: The initial division module is used to divide the area to be evaluated into initial evaluation units according to the preset first area division strategy; The result determination module is used to determine the land intensive use result and low carbon emission result corresponding to the initial evaluation unit based on the evaluation dataset of the area to be evaluated. The land intensive use result includes land intensive use efficiency obtained based on land use intensity data and land output carrying capacity data, and the low carbon emission result includes per-unit carbon dioxide emission efficiency obtained based on carbon dioxide emission inventory and spatial weighting. The correlation analysis module is used to analyze the intensive and low-carbon correlation results corresponding to the initial evaluation unit based on the intensive land use results and the low-carbon emission results. The strategy update module is used to update the first region division strategy based on the intensive low-carbon association result when the preset strategy update trigger condition is met, to obtain the second region division strategy, and to determine the re-evaluation unit based on the second region division strategy. The configuration determination module is used to determine the optimal allocation result of land resources based on the re-evaluation unit.

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