Urban stock space updating subdistrict demarcation method and system

Abstract

The application discloses a kind of urban stock space renewal district demarcation method and system, first, fusion night light and multi-source remote sensing data constructs construction land index, accurately extracts built-up area boundary and identifies inefficient land as update base;Second, construct the value evaluation system covering wisdom, flexibility, livable, civilized, innovation, green six dimensions, combined with farmland value model realizes the comparable quantification of update expected value and comprehensive cost;Then, determine the unit update priority through benefit-cost ratio model, and identify the leading function type according to multidimensional value gain;Finally, set eight sets of update scheme such as planning, innovation, respectively construct spatial equilibrium model to demarcate multi-level control boundary, form integrated scheme of hierarchical classification;The application breaks through the limitation of traditional experience judgment, realizes the whole process technology integration from space recognition, value accounting to decision-making, provides systematic and quantitative technical support for scientific promotion of urban renewal.

Description

Technical Field

[0001] This invention belongs to the field of land spatial planning and urban governance technology, and in particular relates to a method and system for delineating urban stock space renewal zones. Background Technology

[0002] Currently, my country's urbanization process has entered a high-quality development stage dominated by the renewal of existing spaces. With the urbanization rate surpassing 60%, urban development faces increasingly severe resource and environmental constraints, making the traditional extensive growth model reliant on large-scale incremental expansion unsustainable. Promoting the transformation of urban development from "incremental expansion" to "quality improvement of existing resources," and optimizing the spatial pattern of the land, improving urban functions, and enhancing the quality of the living environment through urban renewal, has become a core task of urban modernization in the new era. Against this backdrop, the scientific and precise delineation of urban renewal areas, serving as the basis for coordinating resource allocation, arranging implementation schedules, and implementing differentiated policies, plays a crucial role in improving urban governance capabilities and promoting the intensive and efficient use of space.

[0003] Currently, in urban renewal planning practice, the methods for delineating renewal areas mainly include the following: First, the simple overlay method based on administrative boundaries or existing roads, which directly adopts the administrative scope of street offices, communities, etc., or makes preliminary divisions based on main roads and natural geographical boundaries. Second, the boundary correction method based on single-item assessment results. This method usually first conducts an assessment of the current situation in one aspect, such as building quality, land use efficiency, or shortcomings in public service facilities, and then makes partial adjustments and mergers to the preliminary delineated area boundaries based on the assessment results. Third, the experience-driven expert judgment method, which organizes experts from multiple fields such as urban planning, sociology, and economics to conduct on-site surveys and discussions, and delineates the scope and boundaries of the renewal area based on the experts' knowledge and experience and by comprehensively considering various factors.

[0004] However, the aforementioned existing methods have significant limitations in practical application. First, delineation based on administrative boundaries often overlooks the continuity of urban spatial functions and the inherent correlation between renewal issues, easily leading to fragmented renewal projects and hindering the systematic improvement of areas. Second, methods based on single-item assessments place too much emphasis on a single objective, lacking comprehensive consideration of multi-dimensional values ​​such as economic, social, spatial, and environmental factors, resulting in delineation results that are difficult to adapt to the requirements of coordinated multi-objective urban renewal in the new era. Finally, while experience-based judgment methods can integrate information from multiple aspects, they are too subjective and lack unified, quantitative scientific basis, leading to significant differences in delineation results among different projects and making it difficult to accurately identify spatial differentiation of renewal value, thus failing to provide reliable support for differentiated renewal strategies. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a method and system for delineating urban stock space renewal zones, in order to solve the technical problems in the existing technology, such as fragmented delineation of renewal zones, single renewal objectives, and difficulty in achieving differentiated and precise policy implementation, caused by strong subjectivity, insufficient systematicity, and lack of comprehensive consideration of multi-dimensional values.

[0006] Technical solution: The method for delineating urban stock space renewal zones according to the present invention includes the following steps:

[0007] S1. Extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas for renewal, and spatially grid the potential areas for renewal to obtain multiple existing spatial units.

[0008] S2. Using the existing space unit as the basic evaluation unit, calculate the opportunity cost benchmark value of incremental development, and construct a value evaluation system containing multiple target dimensions. Calculate the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level.

[0009] S3. Calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension.

[0010] S4. Based on the update priority and the dominant update function type, set up a variety of multi-objective update schemes with different dominant objectives, construct a spatial equilibrium model for each scheme to delineate management boundaries at different levels, and integrate the boundaries under all schemes to form a hierarchical and classified management scheme for urban renewal.

[0011] This invention effectively solves the technical problems in existing technologies, such as fragmented delineation of urban renewal areas, singular renewal objectives, and difficulty in achieving differentiated and precise policies, caused by strong subjectivity, insufficient systematicity, and lack of comprehensive consideration of multi-dimensional values. By constructing a systematic delineation method for urban stock space renewal areas, this invention provides a systematic approach to delineating urban stock space renewal areas. This method first integrates scattered, inefficient land use into contiguous potential renewal areas and grids them through remote sensing-based objective identification and spatial clustering in step S1, thus avoiding the subjectivity and fragmentation of artificial delineation from the source. Second, the multi-dimensional value assessment system constructed in step S2 replaces single-dimensional experience-based judgments with quantified opportunity costs, expected values, and comprehensive costs, providing a scientific and comparable data foundation for subsequent decision-making. Then, step S3 calculates the benefit-cost ratio and identifies the dominant functions, achieving objective prioritization of renewal and precise positioning of unit functions, overcoming the problem of homogenization of renewal objectives. Finally, step S4 constructs a multi-objective spatial equilibrium model and integrates management and control schemes, integrating the dispersed unit values ​​into differentiated policy boundaries of hierarchical classification, thereby achieving a fundamental shift from localized and scattered renewal to overall planning, from single objectives to multi-objective collaboration, and from extensive policy implementation to precise management and control.

[0012] Preferably, step S1 includes:

[0013] S11. A construction land index (BI) is constructed by fusing and overlaying nighttime light data with remote sensing indices. The current boundary of the urban built-up area is extracted, and continuous pixel areas with a BI value greater than 0 are identified as existing spatial areas. The calculation formula for the construction land index BI is as follows:

[0014] Among them, NDBI is the Normalized Difference Building Index, used to characterize the distribution characteristics of built-up land; NDVI is the Normalized Difference Vegetation Index, used to characterize the degree of vegetation cover; and MNDWI is the Modified Normalized Difference Water Index, used to characterize the distribution characteristics of water bodies.

[0015] S12. Identify inefficient land use within the existing space area determined in S11, calculate the deviation of economic efficiency per unit area (UL) for each spatial unit, identify spatial units with GDP per unit area lower than a preset benchmark value as inefficient land use units, and spatially cluster the identified inefficient land use units to form contiguous potential areas for urban renewal, serving as the basis for urban existing space renewal; the formula for calculating the deviation of economic efficiency per unit area (UL) is:

[0016] in, It represents the regional GDP per unit area of ​​a spatial unit, used to characterize the current land use economic benefits of that unit; It serves as a benchmark for the regional GDP per unit area of ​​land with the same functional use as this spatial unit within the region, and is used to characterize the average or target economic benefit level of this type of land use.

[0017] By constructing a comprehensive objective identification system that extends from macro-level boundary extraction to micro-level unit identification, the scientific rigor and accuracy of urban stock space assessment have been significantly improved. This method first employs an innovative approach that integrates nighttime light data with remote sensing indices to construct a Construction Land Index (BI). Through multi-source data collaboration, interference from non-construction land such as vegetation and water bodies is effectively eliminated, achieving high-precision, automated extraction of urban built-up area boundaries. This avoids the subjectivity and boundary ambiguity inherent in traditional methods. Furthermore, the method introduces the Land Efficiency Deviation (UL) as a core quantitative indicator to accurately identify inefficient land units with economic output below the benchmark for similar functions. Spatial clustering then forms contiguous potential renewal areas, integrating previously scattered and isolated inefficient plots into a renewal base with economies of scale. This effectively solves the technical challenge of relying on qualitative judgments for inefficient land identification, which hinders the formation of contiguous and coordinated planning. This provides an objective and reliable spatial data foundation for subsequent systematic renewal.

[0018] Preferably, the benchmark value for calculating the opportunity cost of incremental development in step S2 includes:

[0019] A complete value model for farmland is used to calculate the comprehensive value of typical farmland outside the urban development boundary and within the planned expansion area, with this comprehensive value serving as the benchmark for opportunity cost. The complete value model for farmland includes economic value. Ecological value Social value ;

[0020] The economic value The calculation formula is: in, The agricultural added value per unit area of ​​the study area is calculated as the ratio of the agricultural added value of the study area to the actual cultivated land area at the end of the year. To restore the interest rate, the safe interest rate of the current year is used; The farmland scarcity correction factor is calculated using the following formula: in, The number of permanent residents in the study area. This represents the per capita demand for food crops in the study area. The yield of grain crops per unit cultivated land area in the study area. This represents the actual cultivated land area at the end of the year in the study area;

[0021] The ecological value The calculation formula is: in, The value of ecosystem services per unit area of ​​farmland after time-point correction; The regional correction factor is calculated using the following formula: in, This refers to the yield of grain crops per unit area of ​​cultivated land nationwide. The GDP of the study area The gross regional product (GRP) of the country;

[0022] The social value The calculation formula is: in, The value of farmland in ensuring livelihoods. The value of agricultural land for medical security. The value of farmland in ensuring employment;

[0023] The value of life security The calculation formula is: in, The average annual minimum living allowance for urban residents in the study area, The total rural population of the study area;

[0024] The value of medical insurance The calculation formula is: in, The study area represents the average annual per capita expenditure on healthcare and living expenses for rural households.

[0025] The value of employment security The calculation formula is: in, The average annual training cost per person, The study focuses on the rural labor force in the region.

[0026] By employing a complete farmland value model, a scientific and comprehensive quantitative benchmark is provided for the opportunity cost of urban incremental development, effectively addressing the bias in urban renewal decisions caused by the underestimation of the diverse values ​​of farmland in traditional methods. This model breaks through the single perspective of calculating only farmland economic output, systematically integrating economic, ecological, and social values ​​to construct a comprehensive value assessment system encompassing multiple functions such as agricultural production, ecological services, and social security. Furthermore, by introducing parameters such as scarcity and regional correction coefficients, the benchmark value is dynamically and locally adjusted for precision, ensuring that the final calculated opportunity cost benchmark truly reflects the actual comprehensive contribution level of farmland in different regional contexts. This technical approach provides an objective and comparable reference benchmark for the subsequent renewal value assessment of existing spatial units, ensuring the comprehensiveness and scientific nature of decision-making when balancing existing renewal with incremental expansion, and fundamentally avoiding resource allocation imbalances caused by inaccurate opportunity cost calculations.

[0027] Preferably, step S2, calculating the expected value of each existing spatial unit after updating in each target dimension, includes:

[0028] A value assessment system is constructed, encompassing six target dimensions: intelligence, innovation, livability, resilience, civilization, and green development. A multi-dimensional value gain model is used to calculate the expected value of each existing spatial unit after its update. The formula for the multi-dimensional value gain model is as follows:

[0029] in, The updated expected value, The benchmark land price before the update. This is a spatial location correction factor. For the value of the i-th target dimension, The weight coefficients are the weights corresponding to the i-th target dimension.

[0030] The models corresponding to the value assessment system for the six target dimensions are as follows:

[0031] Intelligent Dimension Value Model: in, Value in the dimension of wisdom For patent density, For mobile network coverage, Regarding the level of government data openness, , , For the corresponding weight coefficients, and ; Resilience Dimension Value Model: in, Value in the dimension of resilience For emergency resource density, The proportion of green space, To improve the coverage of emergency shelters, , , For the corresponding weight coefficients, and ; Livability Dimension Value Model: in, For the value of livability, For medical resource density, For the reachability of public service facilities, The noise pollution index, , , For the corresponding weight coefficients, and ; Civilization Dimension Value Model: in, For the value of civilization dimensions, For the preservation rate of cultural heritage, For the number of intangible cultural heritage items, Service radius of public cultural facilities , , For the corresponding weight coefficients, and ; Innovation Dimension Value Model: in, For the value of innovation dimensions, The number of high-tech enterprises, For the intensity of scientific research investment, The proportion of output value of high-tech products, , , For the corresponding weight coefficients, and ; Green Dimension Value Model: in, For the value of the green dimension, The percentage of days with good or excellent air quality. To improve the water environment monitoring compliance rate, For the proportion of renewable energy use, , , For the corresponding weight coefficients, and .

[0032] By constructing a value assessment system encompassing six target dimensions—intelligence, innovation, livability, resilience, civilization, and green development—and corresponding multi-dimensional value gain models, this method provides a comprehensive and refined quantitative assessment tool for the renewal potential of urban existing spatial units. This effectively overcomes the technical shortcomings of traditional methods, which often rely on a single value assessment dimension and fail to reflect comprehensive benefits. The method first deconstructs the diverse visions of urban development into six measurable dimensions and designs a quantitative model for each dimension, composed of core indicators. This ensures that the expected value after renewal comprehensively reflects the combined economic, social, environmental, and cultural benefits. Based on this, by introducing the pre-renewal benchmark land price and spatial location correction coefficients, the inherent value of the unit is organically combined with its spatial endowment. Then, through weighted coefficients, the values ​​of each dimension are systematically integrated, ultimately forming the expected value that reflects the unit's comprehensive gain potential. This technical solution realizes a shift from a single economic indicator to a comprehensive assessment paradigm based on multi-objective synergy, providing objective and detailed data support for the subsequent accurate identification of the renewal value composition of each unit and the scientific matching of dominant functional types.

[0033] Preferably, the method for calculating the comprehensive cost in step S2 includes:

[0034] Using a cost-plus approach, the comprehensive cost per unit area required for each existing space unit to reach the corresponding renewal standard is estimated for the six target dimensions. The calculation formula is as follows:

[0035]

[0036] in, The comprehensive cost per unit area required for each existing space unit to meet the corresponding renewal standards. The standard cost per unit area for implementing the benchmark update for this unit. Let be the cost adjustment factor for the i-th target dimension. For the value of the i-th target dimension, The theoretical maximum value of the i-th target dimension is set to 1.

[0037] By employing a cost-plus approach and a dynamic adjustment model, this method provides a scientific and precise quantitative means for calculating the comprehensive cost of urban existing space units, effectively solving the problem of cost inaccuracies caused by rigid standards and a lack of dynamic correlation with renewal goals in traditional cost estimation. This method first establishes a unified benchmark for cost accounting based on a baseline renewal cost. On this basis, it innovatively introduces a cost adjustment coefficient and models its correlation with the actual value and theoretical maximum value of each target dimension. This allows the comprehensive cost to be dynamically adjusted and differentiated based on the expected value gain of each unit in different dimensions such as intelligence, innovation, and livability. This technical solution transforms cost calculation from a static "one-size-fits-all" model to a dynamic "adjustable as needed" model, ensuring that high-value enhancement goals correspond to reasonable cost inputs. This provides a reliable financial basis for accurately calculating the renewal benefits of each unit and objectively determining the input-output efficiency.

[0038] Preferably, step S3 includes:

[0039] S31. Using a benefit-cost ratio model, calculate the renewal benefit-cost ratio R for each existing space unit; the formula for calculating the renewal benefit-cost ratio R is:

[0040]

[0041] in, The updated expected value calculated in step S2, The unit area comprehensive cost is calculated in step S2; existing space units with an R value greater than 1 are identified as units with good renewal efficiency, and the larger the R value, the higher the renewal efficiency of the unit.

[0042] S32. Based on the value gain of each existing space unit in the six target dimensions of intelligence, resilience, livability, civilization, innovation, and greenness, the dimension with the greatest value gain is determined as the dominant renewal function type of the unit; the value gain refers to the degree of improvement of the value of the unit in a certain target dimension relative to the level before the renewal.

[0043] S33. Sort all existing spatial units in the study area from largest to smallest according to their renewal benefit-cost ratio R to form a comprehensive renewal priority sequence. The comprehensive renewal priority sequence is used to guide the implementation schedule of urban renewal projects.

[0044] By constructing a complete decision-making chain from benefit quantification to functional positioning and time-series arrangement, this method provides a scientific and objective approach to prioritizing and determining functional orientation for urban stock space renewal. It effectively solves the problems of inefficient resource allocation and chaotic implementation timelines caused by ambiguous benefit assessments and mixed functional positioning in traditional renewal decisions. First, this method uses a benefit-cost ratio model to calculate the ratio between expected value and comprehensive cost. A clear quantitative threshold identifies units with genuine input-output benefits, and a gradient ranking reflecting renewal efficiency is formed based on the ratio, ensuring that fiscal and social capital flows preferentially to the areas with the highest benefits. On this basis, by analyzing the value gain characteristics of each unit across six target dimensions, its maximum potential for improvement is accurately identified, thus scientifically matching each unit with a dominant renewal function type, avoiding homogenization or mismatch in functional positioning. Finally, all units are integrated into a comprehensive renewal priority sequence, transforming scattered individual evaluations into a time-series guide for overall planning. This technical solution achieves progressive and precise decision-making from "where should it be renewed" to "for what purpose should it be renewed" to "when should it be renewed," significantly improving the systematicness, economy, and targeting of urban renewal actions.

[0045] Preferably, step S4 includes:

[0046] S41. Set up a multi-objective update scheme, including eight schemes: planning scheme, innovation scheme, civilization scheme, resilience scheme, smart scheme, livable I scheme, livable II scheme, and green scheme; and construct corresponding update boundary space equilibrium models for each of the eight schemes.

[0047] S42. In the ArcGIS geographic information system platform, spatial interpolation processing is performed on the parameters involved in the updated boundary spatial equilibrium model. Contour lines are extracted based on the boundary models corresponding to each scheme as the updated boundary under that scheme. All the updated boundaries extracted under the eight schemes are integrated to form a hierarchical and classified management scheme for urban renewal.

[0048] By constructing a technical framework integrating multi-objective scenario simulation and spatial boundaries, this method provides a flexible and systematic hierarchical and categorized management scheme for urban renewal. First, it establishes eight renewal schemes encompassing diverse development visions and constructs a corresponding spatial equilibrium model for each scheme, achieving a scientific simulation of the renewal boundary morphology under different policy objectives. Then, relying on a geographic information system platform, it performs spatial interpolation and contour line extraction on the parameters of each model, transforming the abstract multi-objective trade-off results into visualized concrete spatial boundaries. Finally, through the systematic integration of the boundaries of multiple schemes, a comprehensive scheme capable of finely delineating different renewal policy zones and management levels is formed. This technical approach effectively solves the problems of single objectives and rigid boundaries in traditional renewal planning, providing differentiated and operable precise policy implementation guidelines for urban renewal actions.

[0049] Secondly, the urban stock space renewal area delineation system of the present invention includes:

[0050] The existing space identification module is used to extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas to be updated, and spatially grid the potential areas to be updated to obtain multiple existing space units.

[0051] The value and cost accounting module is connected to the existing space identification module. It is used to calculate the opportunity cost benchmark value of incremental development with the existing space unit as the basic evaluation unit, and to construct a value evaluation system containing multiple target dimensions. It calculates the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level.

[0052] The priority and type determination module, connected to the value and cost accounting module, is used to calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost, so as to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension.

[0053] The control area delineation module is connected to the priority and type determination module. It is used to set multiple multi-objective update schemes with different dominant objectives based on the update priority and the dominant update function type. For each scheme, a spatial equilibrium model is constructed to delineate management boundaries at different levels. The boundaries under all schemes are integrated to form a hierarchical and classified urban renewal control scheme.

[0054] Thirdly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed by the method for delineating urban stock space renewal zones.

[0055] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for delineating urban stock space renewal zones.

[0056] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: 1. By clustering remote sensing data to form potential areas to be updated, and constructing a multi-dimensional value assessment system and benefit-cost ratio model, priority ranking and dominant function classification of existing spatial units are performed; furthermore, multi-objective schemes are set and spatial equilibrium models are constructed, and hierarchical classification and control schemes are formed by integrating multi-level management boundaries. This method replaces subjective judgment with systematic quantitative analysis, forming a complete closed loop from identification, assessment to control, solving the problems of strong subjectivity, insufficient systematicity, and lack of multi-dimensional comprehensive consideration in traditional methods; 2. Constructing a value assessment system containing multiple objective dimensions and calculating opportunity cost benchmarks, and realizing... The system achieves comparable quantification of the expected value and comprehensive cost after the update, solving the problem of traditional methods lacking multi-dimensional value comprehensive consideration and laying a data foundation for differentiated policy implementation; 3. It introduces an update benefit-cost ratio mechanism, which quantitatively evaluates units based on the ratio of value to cost to determine update priority, and identifies the dominant function type based on the magnitude of multi-dimensional value gain, providing an objective and transparent decision-making basis for rationally arranging the update sequence; 4. Based on priority and dominant function type, it sets up multi-objective update schemes and constructs a spatial equilibrium model. By integrating multi-level management boundaries under different schemes, it forms a hierarchical and classified control scheme, solving the technical problem that traditional methods are difficult to achieve differentiated and precise policy implementation. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0058] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0059] This invention provides a method for delineating urban stock space renewal zones. Addressing prominent issues in current urban stock renewal processes, such as inaccurate identification of renewal scope, insufficient multi-objective coordination, and an imperfect decision support system, this method offers a complete technical solution through a systematic and quantitative technical process for scientifically identifying the renewal base, assessing renewal potential, and formulating differentiated management strategies. The method mainly includes four core steps: First, accurate identification of stock space. This involves using a method that fuses nighttime light data with multi-source remote sensing indices to construct a construction land index, accurately extracting the current boundaries of the urban built-up area to define the scope of stock space, and identifying inefficient land use based on per-unit-area economic benefits to form contiguous potential renewal zones. Second, multi-dimensional renewal value and cost accounting. This involves determining the opportunity cost of incremental development based on a complete farmland value model, constructing a value gain assessment system and cost-plus model covering six dimensions: intelligence, resilience, livability, civilization, innovation, and green development, to realize the expected value and comprehensive cost after renewal. The first step is comparable quantification; the second step is updating the comprehensive assessment and priority determination, determining the economic efficiency of unit renewal by calculating the renewal benefit-cost ratio, identifying the dominant renewal function type based on multi-dimensional value gains, and forming a comprehensive renewal priority sequence; the third step is delineating multi-scenario differentiated management zones, setting eight renewal schemes (planning, innovation, civilization, resilience, intelligence, livable I, livable II, and green) based on multi-objective collaborative governance requirements, delineating multi-level management boundaries such as ideal, moderate, and extreme, extracting boundaries through spatial interpolation, and integrating the scope and orientation of differentiated renewal zones to form an operable and controllable hierarchical and classified renewal scheme. Figure 1 As shown, the specific steps include:

[0060] S1. Extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas for renewal, and spatially grid the potential areas for renewal to obtain multiple existing spatial units.

[0061] S2. Using the existing space unit as the basic evaluation unit, calculate the opportunity cost benchmark value of incremental development, and construct a value evaluation system containing multiple target dimensions. Calculate the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level.

[0062] S3. Calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension.

[0063] S4. Based on the update priority and the dominant update function type, set up a variety of multi-objective update schemes with different dominant objectives, construct a spatial equilibrium model for each scheme to delineate management boundaries at different levels, and integrate the boundaries under all schemes to form a hierarchical and classified management scheme for urban renewal.

[0064] Furthermore, step S1 includes:

[0065] S11: A method of fusion and overlay of nighttime light and remote sensing indices is adopted to extract the current boundary of the urban built-up area, and this boundary is used to define the scope of urban stock space. Specifically, the construction land index (BI) is used for extraction, and continuous pixel areas with BI>0 are identified as stock space. The calculation formula is as follows:

[0066]

[0067] Wherein: NDBI is the Normalized Difference Building Index, NDVI is the Normalized Difference Vegetation Index, and MNDWI is the Modified Normalized Difference Water Index.

[0068] S12: Identify inefficient land use in the existing space determined in S11, calculate the deviation of economic efficiency per unit area (UL) for each spatial unit, and identify spatial units with GDP per unit area lower than the benchmark value as inefficient land use units; spatially cluster these inefficient land use units to form contiguous potential areas for urban renewal, serving as the base of the urban existing space. The calculation formula is:

[0069]

[0070] Among them: GDP c GDP per unit area r It serves as the benchmark value for GDP per unit area of ​​land with similar functions in the region.

[0071] Further, step S2 includes:

[0072] S21: Determine the opportunity cost benchmark for incremental development, specifically using the full value model of farmland for calculation. The sum of the economic, social, and ecological values ​​of typical farmland outside the urban development boundary and within the planned expansion area is used as the opportunity cost benchmark value. The economic value model of farmland in step S2 is as follows:

[0073]

[0074]

[0075] Where: V a Let be the agricultural added value per unit area in the study area, which is the ratio of agricultural added value to the actual cultivated land area at the end of the year; r is the capitalization rate, which is the safe interest rate for the current year. F is the farmland scarcity correction coefficient, POP is the number of permanent residents in the study area, and F n F represents the per capita food crop demand in the study area. q Let A represent the yield of grain crops per unit cultivated land area in the study area, and let A represent the actual cultivated land area at the end of the year in the study area.

[0076] The ecological value model for farmland in step S2 is as follows:

[0077]

[0078]

[0079] Where: V c The value of farmland ecosystem services per unit area is adjusted for time point, where r is the rate of return, α1 is the farmland scarcity correction coefficient, α2 is the regionality correction coefficient, and F... q F represents the yield of grain crops per unit cultivated land area in the study area. Q This refers to the yield of grain crops per unit area of ​​cultivated land nationwide.

[0080] The social value model of farmland in step S2 is as follows:

[0081]

[0082] Where: V L V M V W The value of farmland in ensuring employment. This is a correction factor for farmland scarcity.

[0083] The subsistence value of farmland in step S2 is expressed as follows:

[0084]

[0085] Where: B represents the annual per capita minimum living allowance for urban residents in the study area, r represents the capitalization rate, and POP represents the return on investment. C A represents the total rural population of the study area, and A represents the actual cultivated land area of ​​the study area at the end of the year.

[0086] The medical insurance value of farmland in step S2 is expressed as follows:

[0087]

[0088] Where: C represents the annual per capita healthcare and living expenses of rural households in the study area, r is the capitalization rate, and POP is the percentage of income. C A represents the total rural population of the study area, and A represents the actual cultivated land area of ​​the study area at the end of the year.

[0089] The employment security value of farmland in step S2 is expressed as follows:

[0090]

[0091] Where: T is the average annual training cost per person, r is the capitalization rate, and POP is the average annual training cost per person. f A represents the rural labor force in the study area, and A represents the actual cultivated land area in the study area at the end of the year.

[0092] S22: Assess the post-renewal value of existing space under the target dimensions. Specifically, a multi-dimensional value gain model is used for calculation. The expected land value after renewal for each unit of existing space is calculated for each of the six target dimensions: smart, resilient, livable, civilized, innovative, and green. The calculation formula is as follows:

[0093]

[0094] Where: P r For the updated value, P b UV is the benchmark land price before the update. i For the value of the i-th target dimension, W i is the value weight coefficient for the i-th target dimension.

[0095] The value model for the S2 intelligent dimension is as follows:

[0096]

[0097] Among them: UV sma For the value of the intelligent dimension, S p For patent density, S m For mobile network coverage, S d Regarding the level of government data openness, , , For the corresponding weight coefficients, and .

[0098] The value model for the resilience dimension in step S2 is as follows:

[0099]

[0100] Among them: UV res As a value in the resilience dimension, R e For emergency resource density, R g R represents the percentage of green space. s To improve the coverage of emergency shelters, , , For the corresponding weight coefficients, and .

[0101] The value model for the livability dimension in step S2 is as follows:

[0102]

[0103] Among them: UV liv For the value of livability, L m For medical resource density, L d For the reachability of public service facilities, L n The noise pollution index, , , For the corresponding weight coefficients, and .

[0104] The S2 civilization dimension value model is as follows:

[0105]

[0106] Among them: UV cul For the value of the civilization dimension, C h For the preservation rate of cultural heritage, C i For the number of intangible cultural heritage items, C c Service radius of public cultural facilities , , These are the variable weight coefficients. .

[0107] The value model for the innovation dimension in step S2 is as follows:

[0108]

[0109] Among them: UV inn For the value of innovation dimensions, I h For the number of high-tech enterprises, I r For research investment intensity, I b Service radius of public cultural facilities , , For the corresponding weight coefficients, and .

[0110] The green dimension value model for step S2 is as follows:

[0111]

[0112] Among them: UV gre For the value of the green dimension, G a The percentage of days with good or excellent air quality, G w To improve the water environment monitoring compliance rate, G r For the proportion of renewable energy use, , , For the corresponding weight coefficients, and .

[0113] S23: Calculate the comprehensive cost required for the existing space to reach the target dimension update level. Specifically, a cost-plus method is used for estimation. For each of the six target dimensions, estimate the comprehensive cost per unit area required for each unit to reach the corresponding update standard. The calculation formula is:

[0114]

[0115] Where: C b The standard cost per unit area for implementing the benchmark update for this unit, UV i For the value of the i-th target dimension, UV i,max The theoretical maximum value of the i-th target dimension is set to 1.

[0116] Further, step S3 includes:

[0117] S31: Using the benefit-cost ratio model, calculate the renewal benefit-cost ratio of each existing space unit. An R value greater than 1 indicates that renewal is effective, and the larger the value, the higher the renewal efficiency.

[0118] S32: Based on the value gain of each unit in the six dimensions of intelligence, resilience, livability, civilization, innovation and green, the dimension with the greatest value gain is determined as the dominant update function type of the unit.

[0119] S33: All existing spatial units within the study area are ranked according to their renewal benefit-cost ratio to form a comprehensive renewal priority sequence, which is used to guide the implementation sequence of renewal projects.

[0120] Further, step S4 includes:

[0121] S41: Set up a multi-objective update scheme, including eight schemes: planning, innovation, civilization, resilience, intelligence, livability I, livability II, and green; construct an update boundary spatial equilibrium model for each of the eight schemes. Among them: (1) The planning scheme refers to the scenario of delineating the urban development boundary based on the current national land space plan, taking the scale of urban construction land in 2020 as the base, and controlling the expansion multiple within 1.3 times; (2) The innovation scheme refers to the scenario of delineating the ideal innovation boundary, the moderate innovation boundary, and the extreme innovation boundary according to the principle of optimal benefits, under the premise of improving regional innovation capacity as the primary objective; (3) The civilization scheme refers to the scenario of delineating the ideal civilization boundary, the moderate civilization boundary, and the extreme civilization boundary according to the premise of protecting and revitalizing historical culture as the primary objective; (4) The resilience scheme refers to the scenario of delineating the ideal resilience boundary, the moderate resilience boundary, and the extreme resilience boundary according to the premise of enhancing urban safety and disaster resistance capacity as the primary objective; (5) The intelligence scheme refers to the scenario of delineating the ideal resilience boundary, the moderate resilience boundary, and the extreme resilience boundary according to the premise of promoting digitalization and intelligence. Under the premise of transformation as the primary goal, the following governance scenarios are defined: ideal smart boundary, moderate smart boundary, and extreme smart boundary; (6) Livable I scheme refers to the governance scenarios defined for the ideal livable I boundary, moderate livable I boundary, extreme livable I boundary, and livable I-II boundary, based on the long-term improvement of the living environment in urban built-up areas and with the improvement of public services and living quality as the key strategic direction; (7) Livable II scheme refers to the governance scenarios defined for the carbon reduction boundary, natural boundary, and growth boundary of livable II, based on the sustainable development of rural areas and with the improvement of rural living conditions and preservation of local characteristics as the key direction; (8) Green scheme refers to the governance scenarios defined for the natural boundary, carbon reduction boundary, pollution reduction boundary, and growth boundary of green, with the goal of improving the stability of the ecosystem and the low carbon level.

[0122] S42: In ArcGIS, spatial interpolation is performed on the parameters involved in the model. Contour lines are extracted from the boundary model as update boundaries. All boundaries extracted from the eight schemes are integrated to form a hierarchical and categorized urban renewal management scheme. The formula is as follows:

[0123] ①Innovative solutions

[0124] Innovation Ideal Boundary: P r +UV inn =C d +MAP e +MAP c +MAP s

[0125] The appropriate boundary for innovation: P r +UV inn =C d +MAP e +MAP c

[0126] Innovation Limit Boundary: P r +UV inn =C d +MAP e

[0127] ② Civilization Plan

[0128] The Boundary of Civilizational Ideals: P r +UV cul =C d +MAP e +MAP c +MAP s

[0129] The Boundaries of Civilization: P r +UV cul =C d +MAP e +MAP c

[0130] The Boundary of Civilization: P r +UV cul =C d +MAP e

[0131] ③ Resilience Scheme

[0132] Ideal boundary of toughness: P r +UV res =C d +MAP e +MAP c +MAP s

[0133] The boundary of moderate toughness: P r +UV res =C d +MAP e +MAP c

[0134] Toughness limit boundary: P r +UV res =C d +MAP e

[0135] ④ Smart Solution

[0136] The Boundary of Wisdom and Ideals: P r +UV sma =C d +MAP e +MAP c +MAP s

[0137] The boundary of wisdom and moderation: P r +UV sma =C d +MAP e +MAP c

[0138] The Limit of Intelligence: P r +UV sma =C d +MAP e

[0139] ⑤ Livable Option I

[0140] Ideal boundary of livable environment I: P r +UV liv =C d +MAP e +MAP c +MAP s

[0141] Livable I Moderate Boundary: P r +UV liv =C d +MAP e +MAP c

[0142] Habitable I Limit Boundary: P r +UV liv =C d +MAP e

[0143] Habitable I-II Boundary: MAP e -MAP a =MP GDP

[0144] ⑥ Livable II Plan

[0145] Livability II Carbon Reduction Boundary: MAP e -MAP a =P r ′

[0146] Habitable II Natural Boundaries: MAP e -MAP a =P r

[0147] Livable Growth Boundary II: MAP e -MAP a =P rnew

[0148] ⑦ Green solutions

[0149] Green Natural Boundaries: MAPe +MAP c +MAP s +MAP g =P r

[0150] Green Carbon Reduction Boundary: MAP e +MAP c +MAP s +MAP g =P r ′

[0151] Green Pollution Reduction Boundary: MAP e +MAP c +MAP s +MAP g =P r "

[0152] Green Growth Frontier: MAP e +MAP c +MAP s +MAP g =P rnew

[0153] Where: MP GDP For construction land prices, MAP g The green value of farmland was calculated using the comprehensive assessment model of ecosystem service value proposed by Ke Xinli (2025), MAP. a For the cost of farmland pollution, P r ′ represents the updated value after carbon tax cost adjustment. The carbon tax cost is based on the average annual carbon market trading price in 2025 (62.36 yuan / ton). P r "Prnew" represents the updated value after adjusting for pollution costs and taking into account growth.

[0154] This method breaks through the limitations of traditional urban renewal delineation, which relies on experience-based judgment and has a single objective. It integrates multiple renewal objectives, including economic, social, cultural, and ecological ones. Through multi-scenario scheme design and multi-level boundary setting, it provides a systematic, quantitative, and diversified spatial decision-making reference system for urban renewal under different development orientations. It is applicable to urban renewal special planning, detailed land space planning, and the implementation of existing space optimization projects. It can provide scientific and transparent technical support for government departments, planning agencies, and relevant decision-makers.

[0155] Based on a similar inventive concept, embodiments of the present invention also provide an urban stock space renewal area delineation system corresponding to the urban stock space renewal area delineation method, comprising:

[0156] The existing space identification module is used to extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas to be updated, and spatially grid the potential areas to be updated to obtain multiple existing space units.

[0157] The value and cost accounting module is connected to the existing space identification module. It is used to calculate the opportunity cost benchmark value of incremental development with the existing space unit as the basic evaluation unit, and to construct a value evaluation system containing multiple target dimensions. It calculates the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level.

[0158] The priority and type determination module, connected to the value and cost accounting module, is used to calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost, so as to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension.

[0159] The control area delineation module is connected to the priority and type determination module. It is used to set multiple multi-objective update schemes with different dominant objectives based on the update priority and the dominant update function type. For each scheme, a spatial equilibrium model is constructed to delineate management boundaries at different levels. The boundaries under all schemes are integrated to form a hierarchical and classified urban renewal control scheme.

[0160] The present invention also discloses an electronic device.

[0161] Specifically, the electronic device can be a desktop computer, laptop computer, handheld computer, or cloud server, etc. This computer device may include, but is not limited to, a processor and memory. The processor and memory can be connected via a bus or other means. The processor can be a Central Processing Unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, graphics processing units (GPUs), embedded neural network processing units (NPUs) or other dedicated deep learning coprocessors, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0162] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor executes various functional applications and data processing by running non-transitory software programs, instructions, and modules stored in memory. Memory may include a program storage area and a data storage area. The program storage area may store the control unit and the application program required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, memory may include high-speed random access memory and non-transitory memory. In some embodiments, memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0163] The present invention also discloses a computer-readable storage medium.

[0164] Specifically, the computer-readable storage medium is used to store a computer program, which, when executed by a processor, implements the methods described in the above method implementation.

[0165] Those skilled in the art will understand that all or part of the processes in the methods described above can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

Claims

1. A method for delineating urban stock space renewal zones, characterized in that, Includes the following steps: S1. Extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas for renewal, and spatially grid the potential areas for renewal to obtain multiple existing spatial units. S2. Using the existing space unit as the basic evaluation unit, calculate the opportunity cost benchmark value of incremental development, and construct a value evaluation system containing multiple target dimensions. Calculate the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level. S3. Calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension. S4. Based on the update priority and the dominant update function type, set up a variety of multi-objective update schemes with different dominant objectives, construct a spatial equilibrium model for each scheme to delineate management boundaries at different levels, and integrate the boundaries under all schemes to form a hierarchical and classified management scheme for urban renewal.

2. The method according to claim 1, characterized in that, Step S1 includes: S11. A construction land index (BI) is constructed by fusing and overlaying nighttime light data with remote sensing indices. The current boundary of the urban built-up area is extracted, and continuous pixel areas with a BI value greater than 0 are identified as existing spatial areas. The calculation formula for the construction land index BI is as follows: Among them, NDBI is the Normalized Difference Building Index, used to characterize the distribution characteristics of built-up land; NDVI is the Normalized Difference Vegetation Index, used to characterize the degree of vegetation cover; and MNDWI is the Modified Normalized Difference Water Index, used to characterize the distribution characteristics of water bodies. S12. Identify inefficient land use within the existing space area determined in S11, calculate the deviation of economic efficiency per unit area (UL) for each spatial unit, identify spatial units with GDP per unit area lower than a preset benchmark value as inefficient land use units, and spatially cluster the identified inefficient land use units to form contiguous potential areas for urban renewal, serving as the basis for urban existing space renewal; the formula for calculating the deviation of economic efficiency per unit area (UL) is: in, It represents the regional GDP per unit area of ​​a spatial unit, used to characterize the current land use economic benefits of that unit; It serves as a benchmark for the regional GDP per unit area of ​​land with the same functional use as this spatial unit within the region, and is used to characterize the average or target economic benefit level of this type of land use.

3. The method according to claim 1, characterized in that, The benchmark value for calculating the opportunity cost of incremental development mentioned in step S2 includes: A complete value model for farmland is used to calculate the comprehensive value of typical farmland outside the urban development boundary and within the planned expansion area, with this comprehensive value serving as the benchmark for opportunity cost. The complete value model for farmland includes economic value. Ecological value Social value ; The economic value The calculation formula is: in, The agricultural added value per unit area of ​​the study area is calculated as the ratio of the agricultural added value of the study area to the actual cultivated land area at the end of the year. To restore the interest rate, the safe interest rate of the current year is used; The farmland scarcity correction factor is calculated using the following formula: in, The number of permanent residents in the study area. This represents the per capita demand for food crops in the study area. The yield of grain crops per unit cultivated land area in the study area. This represents the actual cultivated land area at the end of the year in the study area; The ecological value The calculation formula is: in, The value of ecosystem services per unit area of ​​farmland after time-point correction; The regional correction factor is calculated using the following formula: in, This refers to the yield of grain crops per unit area of ​​cultivated land nationwide. The GDP of the study area The gross regional product (GRP) of the country; The social value The calculation formula is: in, The value of farmland in ensuring livelihoods. The value of agricultural land for medical security. The value of farmland in ensuring employment; The value of life security The calculation formula is: in, The average annual minimum living allowance for urban residents in the study area, The total rural population of the study area; The value of medical insurance The calculation formula is: in, The study area represents the average annual per capita expenditure on healthcare and living expenses for rural households. The value of employment security The calculation formula is: in, The average annual training cost per person, The study focuses on the rural labor force in the region.

4. The method according to claim 1, characterized in that, Step S2, which involves calculating the expected value of each existing spatial unit after updating in each target dimension, includes: A value assessment system is constructed, encompassing six target dimensions: intelligence, innovation, livability, resilience, civilization, and green development. A multi-dimensional value gain model is used to calculate the expected value of each existing spatial unit after its update. The formula for the multi-dimensional value gain model is as follows: in, The updated expected value, The benchmark land price before the update. This is a spatial location correction factor. For the value of the i-th target dimension, The weight coefficients are the weights corresponding to the i-th target dimension. The models corresponding to the value assessment system for the six target dimensions are as follows: Intelligent Dimension Value Model: in, Value in the dimension of wisdom For patent density, For mobile network coverage, Regarding the level of government data openness, , , For the corresponding weight coefficients, and ; Resilience Dimension Value Model: in, Value in the dimension of resilience For emergency resource density, The proportion of green space, To improve the coverage of emergency shelters, , , For the corresponding weight coefficients, and ; Livability Dimension Value Model: in, For the value of livability, For medical resource density, For the reachability of public service facilities, The noise pollution index, , , For the corresponding weight coefficients, and ; Civilization Dimension Value Model: in, For the value of civilization dimensions, For the preservation rate of cultural heritage, For the number of intangible cultural heritage items, Service radius of public cultural facilities , , For the corresponding weight coefficients, and ; Innovation Dimension Value Model: in, For the value of innovation dimensions, The number of high-tech enterprises, For the intensity of scientific research investment, The proportion of output value of high-tech products, , , For the corresponding weight coefficients, and ; Green Dimension Value Model: in, For the value of the green dimension, The percentage of days with good or excellent air quality. To improve the water environment monitoring compliance rate, For the proportion of renewable energy use, , , For the corresponding weight coefficients, and .

5. The method according to claim 4, characterized in that, The method for calculating the comprehensive cost in step S2 includes: Using a cost-plus approach, the comprehensive cost per unit area required for each existing space unit to reach the corresponding renewal standard is estimated for the six target dimensions. The calculation formula is as follows: ;in, The comprehensive cost per unit area required for each existing space unit to meet the corresponding renewal standards. The standard cost per unit area for implementing the benchmark update for this unit. Let be the cost adjustment factor for the i-th target dimension. For the value of the i-th target dimension, The theoretical maximum value of the i-th target dimension is set to 1.

6. The method according to claim 1, characterized in that, Step S3 includes: S31. Using a benefit-cost ratio model, calculate the renewal benefit-cost ratio R for each existing space unit; the formula for calculating the renewal benefit-cost ratio R is: ;in, The updated expected value calculated in step S2, The unit area comprehensive cost is calculated in step S2; existing space units with an R value greater than 1 are identified as units with good renewal efficiency, and the larger the R value, the higher the renewal efficiency of the unit. S32. Based on the value gain of each existing space unit in the six target dimensions of intelligence, resilience, livability, civilization, innovation, and greenness, the dimension with the greatest value gain is determined as the dominant renewal function type of the unit; the value gain refers to the degree of improvement of the value of the unit in a certain target dimension relative to the level before the renewal. S33. Sort all existing spatial units in the study area from largest to smallest according to their renewal benefit-cost ratio R to form a comprehensive renewal priority sequence. The comprehensive renewal priority sequence is used to guide the implementation schedule of urban renewal projects.

7. The method according to claim 1, characterized in that, Step S4 includes: S41. Set up a multi-objective update scheme, including eight schemes: planning scheme, innovation scheme, civilization scheme, resilience scheme, smart scheme, livable I scheme, livable II scheme, and green scheme; and construct corresponding update boundary space equilibrium models for each of the eight schemes. S42. In the ArcGIS geographic information system platform, spatial interpolation processing is performed on the parameters involved in the updated boundary spatial equilibrium model. Contour lines are extracted based on the boundary models corresponding to each scheme as the updated boundary under that scheme. All the updated boundaries extracted under the eight schemes are integrated to form a hierarchical and classified management scheme for urban renewal.

8. A system for delineating urban stock space renewal zones, characterized in that, include: The existing space identification module is used to extract the current boundary of the urban built-up area based on remote sensing data, identify inefficient land use units within the boundary, spatially cluster the inefficient land use units to form contiguous potential areas to be updated, and spatially grid the potential areas to be updated to obtain multiple existing space units. The value and cost accounting module is connected to the existing space identification module. It is used to calculate the opportunity cost benchmark value of incremental development with the existing space unit as the basic evaluation unit, and to construct a value evaluation system containing multiple target dimensions. It calculates the expected value of each existing space unit after the update under each target dimension, as well as the comprehensive cost required to reach the update level. The priority and type determination module, connected to the value and cost accounting module, is used to calculate the update benefit-cost ratio of each existing space unit based on the expected value after the update and the comprehensive cost, so as to determine the update priority, and determine the dominant update function type of each unit based on the value gain of each target dimension. The control area delineation module is connected to the priority and type determination module. It is used to set multiple multi-objective update schemes with different dominant objectives based on the update priority and the dominant update function type. For each scheme, a spatial equilibrium model is constructed to delineate management boundaries at different levels. The boundaries under all schemes are integrated to form a hierarchical and classified urban renewal control scheme.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the urban stock space renewal area delineation method as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for delineating urban stock space renewal zones according to any one of claims 1 to 7.

Images