Village and town industrial park industrial land performance evaluation method under view of city renewal

Abstract

The invention discloses a village and town industrial park industrial land performance evaluation method under the perspective of city updating, and relates to the technical field of performance evaluation, and the method comprises the following steps: dividing evaluation pattern spots of industrial lands according to collected industrial land data, constructing an industrial land performance evaluation index system based on the evaluation pattern spots, and selecting evaluation indexes; analyzing the selected evaluation index by using an analytic hierarchy process, and determining an evaluation index weight; and based on the evaluation index weight, evaluating the comprehensive performance of the industrial land, and making an implementation strategy according to an evaluation result. According to the method, by dividing the evaluation pattern spots of the industrial land, the specific condition and characteristics of each industrial land can be deeply known, so that the industrial land can be more accurately mastered, the pertinence and effectiveness of evaluation are ensured, the evaluation result is closer to the actual condition of the industrial land, and powerful support is provided for subsequent decision making.

Description

Technical Field

[0001] The present invention relates to the field of performance evaluation technology, and in particular to a performance evaluation method for industrial land in village and town industrial parks from the perspective of urban renewal. Background Art

[0002] Many scholars are gradually establishing an evaluation method based on a multi-dimensional indicator system to comprehensively evaluate the comprehensive spatial performance of cities. For example, for the performance evaluation of housing, a five-subsystem indicator system of urban spatial performance was constructed, and the relationship between industrial land use performance and differentiated land was studied in depth.

[0003] Urban low-efficiency land refers to those urban existing construction lands that are used for construction but have problems such as scattered layout, extensive use, unreasonable use, dilapidated buildings, etc., and whose ownership is clear and undisputed. In particular, low-efficiency industrial land refers to land in cities and towns that has failed to achieve its due efficiency due to problems in spatial layout, production efficiency, environmental protection and employment.

[0004] At present, the evaluation methods for land use performance mainly focus on the evaluation of intensive land use, such as the evaluation method and index system of urban land intensive use potential, and the urban land use performance evaluation index system at different spatial scales. However, these evaluation methods are still mainly at the macro level in terms of spatial scale and pertinence, and it is difficult to achieve the precise map requirements for urban renewal.

[0005] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0006] In response to the problems in the related technologies, the present invention proposes a performance evaluation method for industrial land in village and town industrial parks from the perspective of urban renewal to overcome the above-mentioned technical problems existing in the existing related technologies.

[0007] To this end, the specific technical solution adopted by the present invention is as follows:

[0008] A performance evaluation method for industrial land in village and town industrial parks from the perspective of urban renewal, the method comprises the following steps:

[0009] S1. Divide the industrial land evaluation plots according to the collected industrial land data, and build an industrial land performance evaluation index system based on the evaluation plots, and select evaluation indicators;

[0010] S2. Analyze the selected evaluation indicators using the analytic hierarchy process and determine the weights of the evaluation indicators;

[0011] S3. Evaluate the comprehensive performance of industrial land based on the evaluation index weights, and formulate implementation strategies based on the evaluation results.

[0012] Furthermore, according to the collected industrial land data, the industrial land evaluation plots are divided, and the industrial land performance evaluation index system is constructed based on the evaluation plots. The selection of evaluation indexes includes the following steps:

[0013] S11. Collect industrial land data, and divide the collected industrial land data into a number of assessment plots, wherein each assessment plot represents an independent statistical unit;

[0014] S12. Combine the assessment map with the land resource development needs to determine the comprehensive performance factors;

[0015] S13. Based on comprehensive performance factors and industrial land data, construct an industrial land performance evaluation index system, and select evaluation indicators from the industrial land performance evaluation index system.

[0016] Furthermore, the comprehensive performance factors include: economic benefits, site conditions and construction environment.

[0017] Further, the selected evaluation indicators are analyzed using the hierarchical analysis method, and the weights of the evaluation indicators are determined, including the following steps:

[0018] S21. Based on the industrial land performance evaluation index system, the evaluation indicators are divided into different levels, and the evaluation indicators of each level are numbered to construct a category judgment matrix;

[0019] S22, according to the constructed category judgment matrix, using the scaling method to score the evaluation indicators in the category judgment matrix;

[0020] S23, based on the scoring results, perform consistency check on each category judgment matrix;

[0021] S24, using mathematical software to calculate the maximum eigenvector of each category judgment matrix after the consistency test passes;

[0022] S25. Normalize the calculated maximum eigenvector to obtain the evaluation index weight.

[0023] Furthermore, the category judgment matrix includes: a secondary indicator judgment matrix, a tertiary indicator judgment matrix and a quaternary indicator judgment matrix.

[0024] Furthermore, based on the scoring results, the consistency check of each category judgment matrix includes the following steps:

[0025] S231, based on the scoring results, using mathematical software to calculate the maximum eigenvalue of each category judgment matrix;

[0026] S232, combining the maximum eigenvalue with the trace of the category judgment matrix, calculating the consistency index of the category judgment matrix, and obtaining the corresponding average random consistency index according to the consistency index;

[0027] S233, calculating the random consistency ratio based on the consistency index and the average random consistency index;

[0028] S234: Based on the random consistency ratio, the consistency of the category judgment matrix is ​​judged. If the random consistency ratio is less than the preset threshold, the category judgment matrix is ​​consistent. Otherwise, steps S231 to S233 are repeated until the category judgment matrix passes the consistency test.

[0029] Furthermore, the consistency index of the category judgment matrix is ​​calculated by combining the maximum eigenvalue with the trace of the category judgment matrix, and the calculation formula for obtaining the corresponding average random consistency index according to the consistency index is:

[0030]

[0031] In the formula, CI represents the consistency index;

[0032] λ max Represents the maximum eigenvalue of the category judgment matrix;

[0033] n represents the trace of the category judgment matrix.

[0034] Furthermore, based on the consistency index and the average random consistency index, the formula for calculating the random consistency ratio is:

[0035]

[0036] In the formula, CR represents the random consistency ratio value;

[0037] CI stands for consistency index;

[0038] RI stands for average random consistency index.

[0039] Furthermore, based on the weights of the evaluation indicators, the comprehensive performance of industrial land is evaluated, and implementation strategies are formulated according to the evaluation results, including the following steps:

[0040] S31. Based on the evaluation index weights, the comprehensive performance score of industrial land is calculated using multi-factor superposition analysis technology;

[0041] S32. Compare the calculated comprehensive performance score with the preset score to evaluate the comprehensive performance of the industrial land;

[0042] S33. Formulate implementation strategies based on the evaluation results of the comprehensive performance of industrial land.

[0043] Furthermore, the calculated comprehensive performance score is compared with the preset score, and the evaluation of the comprehensive performance of industrial land includes the following steps:

[0044] If the comprehensive performance score of industrial land is lower than the preset score, it means that the comprehensive performance of the industrial land development is poor;

[0045] If the comprehensive performance score of industrial land is higher than the preset score, it means that the comprehensive performance of the industrial land development is good.

[0046] The beneficial effects of the present invention are:

[0047] 1. By dividing the assessment plots of industrial land, the present invention can deeply understand the specific conditions and characteristics of each piece of industrial land, so as to achieve a more accurate grasp of them, ensure the pertinence and effectiveness of the assessment, make the assessment results closer to the actual conditions of the industrial land, and provide strong support for subsequent decision-making.

[0048] 2. The present invention can comprehensively evaluate the overall performance of industrial land by conducting a comprehensive performance evaluation, covering multiple aspects such as land use efficiency, economic benefits, and environmental benefits. It not only provides a solid data basis and reference materials for making future decisions, but also helps to improve the overall performance of industrial land and promote its sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 This is a flow chart of a method for evaluating the performance of industrial land in a village and town industrial park from the perspective of urban renewal according to an embodiment of the present invention;

[0051] Figure 2 It is a schematic diagram of an industrial land performance evaluation index system in a method for evaluating industrial land performance in a village and town industrial park from the perspective of urban renewal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments. They can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention.

[0053] According to an embodiment of the present invention, a method for evaluating the performance of industrial land in village and town industrial parks from the perspective of urban renewal is provided.

[0054] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to the performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to an embodiment of the present invention, the method includes the following steps:

[0055] S1. Divide the industrial land evaluation plots according to the collected industrial land data, and build an industrial land performance evaluation index system based on the evaluation plots, and select evaluation indicators.

[0056] It should be noted that the construction of the industrial land performance evaluation index system is not a simple combination and accumulation of certain evaluation indicators, but a comprehensive establishment of an index set that can reflect the performance of industrial land based on certain construction principles; the construction of the index system must strictly follow certain principles and processes, relevant logic and theoretical framework, and should adhere to general principles such as overall consistency, scientific accuracy, commonality and individuality, and the combination of standardization and operability, so as to meet the standards of scientific rationality, clear boundaries, and conformity to objective reality; at the same time, the following principles should be particularly emphasized:

[0057] (1) Principle of clarity and verifiability

[0058] The indicator design must have clear goal settings, clear division of responsibilities, clear time nodes, and statistically quantifiable results, and it must conform to the characteristics of evaluation indicators that can be divided into stages, quantified, and assessed.

[0059] (2) General comparability principle

[0060] The indicator design must meet the requirements of comparison between different periods and different objects, that is, vertical comparison and horizontal comparison; one is vertical comparison, that is, comparing the same object at different times, requiring the connotation and extension of the special work to remain stable in order to measure the reference values ​​(standard values) unchanged; the second is horizontal comparison, that is, comparing between different objects, finding common points, and designing evaluation content and standards.

[0061] (3) Goal-oriented principle

[0062] The indicator design should have the effect of guiding and encouraging regional work to develop in the established direction and towards the goal, and continuously approach the goal through effective control of the industrial land development and utilization efficiency evaluation process.

[0063] (4) Principle of avoidance

[0064] The evaluation of industrial land development and utilization efficiency is usually conducted through a joint meeting of various departments. Since they are only the makers of industrial land and planning, not the implementers, the official usually presides over the joint meeting and experts from all walks of life participate in the evaluation.

[0065] (5) Value neutrality principle

[0066] The principle of value neutrality is also known as the fact / value dichotomy principle, which requires a strict distinction between facts and values. This principle requires evaluators to respect facts, set industrial land development and utilization efficiency evaluation indicators according to the effect requirements in the project feasibility report and combined with the characteristic values ​​of the industry. At the same time, the evaluation conclusions should be based on facts, without any subjective value, so as not to affect the fairness of the evaluation results.

[0067] Specifically, according to the collected industrial land data, the industrial land evaluation plots are divided, and the industrial land performance evaluation index system is constructed based on the evaluation plots. The selection of evaluation indicators includes the following steps:

[0068] S11. Collect industrial land data, and divide the collected industrial land data into several evaluation plots, wherein each evaluation plot represents an independent statistical unit.

[0069] It should be noted that demarcating assessment plots is the basis for building an assessment system. According to the industrial land survey data of a certain area and the third national land survey data, there are 12,283 industrial land plots in the district, with a total area of ​​139.07 km2; among them, there are 6,902 industrial land plots at the street and town level and above, with a land area of ​​approximately 89.18 km2; there are 5,381 industrial land plots at the village level, with a land area of ​​approximately 44.89 km2; in order to unify the assessment dimensions and enhance the availability of statistical data sources, the study divides the statistical units at the "plot" scale, forming a total of 12,283 plots; all industrial enterprise data are entered into the ArcGIS platform according to the plot boundaries for analysis and statistics.

[0070] S12. Combine the assessment map with the land resource development needs to determine the comprehensive performance factors.

[0071] Specifically, the comprehensive performance factors include: economic benefits, site conditions and construction environment.

[0072] S13. Based on comprehensive performance factors and industrial land data, construct an industrial land performance evaluation index system, and select evaluation indicators from the industrial land performance evaluation index system.

[0073] It is necessary to add that, if Figure 2As shown, on the basis of clarifying the definition of industrial land, according to the development needs of land resources, the performance of industrial land should be evaluated. It is necessary not only to examine its quantity but also to analyze the quality contained therein; it is necessary to closely combine the nature and characteristics of industrial land, conduct a comprehensive analysis and research on the relevant fields involved, and scientifically and rationally analyze the "quantity" and "quality" of industrial land. By constructing an industrial land performance evaluation index system, a comprehensive and integrated analysis of the existing industrial land performance can be made, and industrial land can be identified for integration and improvement.

[0074] As shown in Table 1, the use of a multidimensional indicator system and a hierarchical analysis method that combines quantitative and qualitative methods is the basic method for land use performance evaluation, but targeted indicator selection and quantitative classification are crucial. In view of the main problems faced by urban renewal and the available data sources, an indicator system is constructed for industrial land survey data and supplementary third land survey data from three levels: economic benefits, site conditions, and construction environment.

[0075] Table 1 Industrial land performance evaluation index system

[0076]

[0077]

[0078] In addition, the indicator layer evaluation indicators belong to the evaluation level of the original data, which is the basis for the evaluation indicator system to achieve specific operations. It is necessary to explain the selection and definition of specific indicators:

[0079] 1) Economic Benefit A1

[0080] (1) Land output efficiency B1

[0081] C1 per-ha industrial output value refers to the ratio of the total income of industrial enterprises within the scope of the land to the area of ​​industrial land, with the unit of 10,000 yuan / ha. It reflects the output efficiency of industrial land and is a positive correlation indicator.

[0082] The calculation formula is: average land output value = total industrial output value of the plot / plot area.

[0083] C2 Average industrial profit and tax per unit area refers to the ratio of taxes paid by enterprises within the scope of the land per unit area to the area of ​​industrial land. Taxation is a direct reflection of economic development. Through taxation, we can directly understand the development of enterprises. Enterprises can also reflect their future development space and the output efficiency of industrial land through taxation. It is a positively correlated indicator.

[0084] The calculation formula is: Average industrial profit and tax per plot = total industrial fiscal revenue value of the plot / plot area.

[0085] (2) Land input intensity B2

[0086] C3 Infrastructure completeness refers to the degree of completeness of basic infrastructure such as roads, water supply, electricity, drainage, heat, telecommunications, gas and land leveling in the early stage of capital construction. It reflects the intensity of industrial land investment. In the quantification of indicators, the virtual variable method is used, which is a positively correlated indicator.

[0087] The statistical method is: three connections and one leveling is 1, five connections and one leveling is 3, and six connections and one leveling is 7.

[0088] C4, average number of employees per unit area, refers to the number of employees per unit area of ​​an enterprise. The number of employees in an enterprise can reflect the development level of the enterprise. Combined with other relevant indicators, it can effectively reflect the current economic development status and future development potential of the enterprise. It is a positively correlated indicator.

[0089] The calculation formula is: average number of employees per unit area = total number of employees / land area.

[0090] (3) Enterprise scale B3

[0091] C5 enterprises above designated size refers to the ratio of the number of enterprises above designated size within industrial land to the total number of enterprises above designated size in the city. It can reflect the economic development status of enterprises within the land. In the quantification of the indicator, the virtual variable method is used, which is a positive correlation indicator.

[0092] The statistical method is: 1 for non-scale enterprises and 9 for scale enterprises.

[0093] C6 Enterprise technological level refers to the number of high-tech enterprises per unit area of ​​land, reflecting the technological level of the enterprise. It is a positively correlated indicator. In the quantification of the indicator, the virtual variable method is used, which is a positively correlated indicator.

[0094] The statistical method is: the number of non-high-tech enterprises is 1, and the number of high-tech enterprises is 9.

[0095] 2) Land Condition A2

[0096] (1) Location suitability for development B4

[0097] The C7 land restriction condition refers to whether the enterprise's land use method is in line with the land use nature in the land use status planning and whether the enterprise's land use method meets the spatial control requirements such as ecological protection and land growth boundaries. It is divided according to the location of the assessment object. In the quantification of the indicator, the virtual variable method is used, which is a positive correlation indicator.

[0098] The statistical method is: industrial land outside the industrial protection line and outside the urban development boundary is assigned a value of 1; industrial land outside the industrial protection line and within the urban development boundary is assigned a value of 5; and industrial land within the industrial protection line is assigned a value of 9.

[0099] (2) Land use intensity B5

[0100] C8 Floor Area Ratio refers to the ratio of the total building area to the total land area within a plot. It reflects the total building area per unit area and comprehensively reflects the intensity of land use. The floor area ratio indicator can more intuitively reflect the development degree of the plot and is an important indicator for evaluating the degree of land use. Generally, the larger the floor area ratio, the better, but it must be within a reasonable limit. A floor area ratio that exceeds the limit will have a negative impact. Therefore, this indicator should be based on a reasonable limit.

[0101] The calculation formula is: Floor area ratio = total building area of ​​the plot / plot area.

[0102] C9 building density refers to the ratio of the total building base area to the land area within the built-up land, reflecting the plane utilization of the land. Generally speaking, the higher the building density, the better, but it must be within a reasonable limit. Building density exceeding the limit will have negative impacts. This indicator should be based on reasonable limits.

[0103] The calculation formula is: building density = building base area of ​​the plot / plot area.

[0104] C10 land use scale reflects the intensive and economical development of the land. It counts the size of the land and uses the dummy variable method to quantify the indicator, which is an interval indicator.

[0105] The statistical method is: less than 5 mu is 1, 5-10 mu is 3, 10-15 mu is 5, 15-20 mu is 7, and more than 20 mu is 9.

[0106] (3) Clarity of property rights B6

[0107] C11 Legality of land use procedures refers to the problem of failure to change the nature of land in a timely manner due to property rights changes and other reasons. It reflects the compliance of the land-using enterprises in handling procedures. It is mainly divided into three types: legally approved land use, less approval and more use, and use without approval. In the quantification of indicators, the dummy variable method is used, which is a reverse correlation indicator.

[0108] The statistical method is: legal approval is 7, less approval and more use is 5, and use before approval is 1.

[0109] C12 land ownership type is a general term for land ownership and the rights of land possession, use and income derived from it. It reflects the ownership status of land-using enterprises and is mainly divided into five types: villagers' groups, village collective economic organizations, township collective economic organizations, state-owned land use rights, and state-owned land use rights. In the quantification of indicators, the virtual variable method is used, which is a reverse correlation indicator.

[0110] The statistical method is: villagers' group is 1, village collective economic organization is 3, township collective economic organization is 5, state-owned land use right is 7, and state-owned land use right is 9.

[0111] 3) Construction environment A3

[0112] (1) Space environment B7

[0113] C13 The external environment of the building is the embodiment of the environmental features of the industrial land. In terms of the quantification of the indicator, it is assigned values ​​based on the cleanliness of the surrounding environment of the plot, as well as the degree of greening, social order, environmental pollution and damage. It is a positively correlated indicator.

[0114] Statistical method: Assign values ​​based on the cleanliness of the surrounding environment of the plot, as well as the degree of greening, social order, environmental pollution and damage.

[0115] C14 traffic conditions reflect the correlation between the land use and the spatial distribution of traffic lines. It counts the traffic line level of the area where the land is located. In the quantification of the indicator, the virtual variable method is used, which is an interval indicator.

[0116] The statistical method is: other roads are counted as 1, 500 meters around main roads are counted as 3, 800 meters around highways and expressways are counted as 5, 1000 meters around rail transit stations are counted as 7, and 2000 meters around planned railway stations are counted as 9.

[0117] (2) Construction quality B8

[0118] C15 Construction Year reflects the new and old conditions of industrial land construction. In terms of indicator quantification, it is assigned a value based on the specific year in which the land use behavior occurs, and is a positively correlated indicator.

[0119] The statistical method is: before 1995 is 1, 1995-2000 is 3, 2000-2005 is 5, 2005-2010 is 7, and after 2010 is 9.

[0120] C16 Building quality: Building quality reflects the actual use value of buildings in industrial land. In the quantification of indicators, the virtual variable method is used, which is a positive correlation indicator.

[0121] The statistical method is: 3 for non-high-standard factory buildings and 7 for high-standard factory buildings.

[0122] S2. Use the analytic hierarchy process to analyze the selected evaluation indicators and determine the weights of the evaluation indicators.

[0123] Specifically, the selected evaluation indicators are analyzed using the hierarchical analysis method, and the weights of the evaluation indicators are determined, including the following steps:

[0124] S21. Based on the industrial land performance evaluation index system, the evaluation indicators are divided into different levels, and the evaluation indicators of each level are numbered to construct a category judgment matrix.

[0125] Specifically, the category judgment matrix includes: a secondary indicator judgment matrix, a tertiary indicator judgment matrix and a quaternary indicator judgment matrix.

[0126] It should be noted that the industrial land performance evaluation index system is numbered, and then three types of judgment matrices are constructed, namely ab (secondary index), cd (third-level index) and ef (fourth-level index), as shown in Table 2, where each type of judgment matrix establishes a corresponding matrix based on specific indicators.

[0127] Table 2 Three types of judgment matrix

[0128]

[0129] S22. Based on the constructed category judgment matrix, the evaluation indicators in the category judgment matrix are scored using the scaling method.

[0130] It should be noted that, as shown in Table 3, after the judgment matrix is ​​constructed, each type of judgment matrix is ​​scored. The scoring principle is to score from 1 to 9 based on the comparative importance between the elements of each indicator. The larger the score between the two indicators, the more important the former is than the latter.

[0131] Table 3 Scaling method standards

[0132]

[0133] Among them, taking the secondary indicator judgment matrix in the category judgment matrix as an example, according to the identification of industrial land, economic benefits are used as the basis of plot conditions. When comparing the economic benefit b1 and the plot condition b2, b1 is more important than b2. Then, the number 5 is filled in the first column and second row of the ab matrix to indicate importance; and so on until the upper triangle in the secondary indicator judgment matrix is ​​filled, and the lower triangle is the corresponding opposite number and can be left blank.

[0134] S23. Based on the scoring results, a consistency check is performed on each category judgment matrix.

[0135] Specifically, based on the scoring results, the consistency check of each category judgment matrix includes the following steps:

[0136] S231. Based on the scoring results, use mathematical software to calculate the maximum eigenvalue of each category judgment matrix.

[0137] S232. Combining the maximum eigenvalue with the trace of the category judgment matrix, calculating the consistency index of the category judgment matrix, and obtaining the corresponding average random consistency index according to the consistency index.

[0138] Specifically, the consistency index of the category judgment matrix is ​​calculated by combining the maximum eigenvalue and the trace of the category judgment matrix, and the calculation formula for obtaining the corresponding average random consistency index according to the consistency index is:

[0139]

[0140] In the formula, CI represents the consistency index;

[0141] λ max Represents the maximum eigenvalue of the category judgment matrix;

[0142] n represents the trace of the category judgment matrix.

[0143] S233. Calculate the random consistency ratio based on the consistency index and the average random consistency index.

[0144] Specifically, based on the consistency index and the average random consistency index, the formula for calculating the random consistency ratio is:

[0145]

[0146] In the formula, CR represents the random consistency ratio value;

[0147] CI stands for consistency index;

[0148] RI stands for average random consistency index.

[0149] It should be noted that RI is the average random consistency index, which is used to measure whether the consistency of each order category judgment matrix is ​​reliable.

[0150] S234: Based on the random consistency ratio, the consistency of the category judgment matrix is ​​judged. If the random consistency ratio is less than the preset threshold, the category judgment matrix is ​​consistent. Otherwise, steps S231 to S233 are repeated until the category judgment matrix passes the consistency test.

[0151] It should be noted that when the hierarchical analysis method judges the importance of the matrix, contradictory results cannot occur; for example, a is more important than b and c, but according to the result, c is more important than a; when such contradictory results occur, it is necessary to perform a contradiction test on the category judgment matrix through a consistency test. If the category judgment matrix cannot pass the test, it is modified according to the feedback results until the category judgment matrix can pass the consistency test.

[0152] In addition, as shown in Table 4, the first-order or second-order judgment matrix generally has complete consistency. For the third-order and above judgment matrix, when its random consistency ratio CR is less than 0.1, it is considered that the consistency of the judgment matrix is ​​good; otherwise, it is necessary to adjust the judgment matrix until it passes the consistency test.

[0153] Table 4 Average random consistency index

[0154]

[0155] S24. Use mathematical software to calculate the maximum eigenvector of each category judgment matrix after the consistency test is passed.

[0156] S25. Normalize the calculated maximum eigenvector to obtain the evaluation index weight.

[0157] As shown in Table 5, the weights of the judgments are averaged to find the final weights of each indicator. Similarly, the corresponding weights of the third and fourth level indicators are obtained.

[0158] Table 5 Index weight table of industrial land performance evaluation index system

[0159]

[0160] S3. Evaluate the comprehensive performance of industrial land based on the evaluation index weights, and formulate implementation strategies based on the evaluation results.

[0161] Specifically, based on the weights of the evaluation indicators, the comprehensive performance of industrial land is evaluated, and the implementation strategy is formulated according to the evaluation results, including the following steps:

[0162] S31. Based on the evaluation index weights, use multi-factor overlay analysis technology to calculate the comprehensive performance score of industrial land.

[0163] S32. Compare the calculated comprehensive performance score with the preset score to evaluate the comprehensive performance of industrial land.

[0164] Specifically, the calculated comprehensive performance score is compared with the preset score, and the evaluation of the comprehensive performance of industrial land includes the following steps:

[0165] If the comprehensive performance score of industrial land is lower than the preset score, it means that the comprehensive performance of the industrial land development is poor;

[0166] If the comprehensive performance score of industrial land is higher than the preset score, it means that the comprehensive performance of the industrial land development is good.

[0167] S33. Formulate implementation strategies based on the evaluation results of the comprehensive performance of industrial land.

[0168] It should be noted that a single indicator can reflect a single sign of industrial land. After a multi-factor comprehensive analysis of the industrial land, industrial land with low comprehensive utilization efficiency will be transformed in the short term based on the analysis results, while industrial land with high or acceptable comprehensive efficiency will be transformed in the medium and long term.

[0169] As shown in Table 6, through the industrial land performance evaluation index system, 16 indicators were selected and classified and assigned weights, and the hierarchical analysis method was used to determine the comprehensive performance level of each evaluation plot.

[0170] Table 6 Multi-factor superposition analysis scores and weights

[0171]

[0172]

[0173] According to the current development of industrial land in a certain area and the future development trend of its location, a multi-factor superposition analysis was conducted using economic benefits, site conditions and construction environment to obtain a comprehensive evaluation map of industrial land development. The full score for industrial comprehensive performance is 100 points. The lower the score, the lower the comprehensive performance of industrial land development, and it is necessary to carry out transformation and improvement as soon as possible; the higher the score, the higher the comprehensive performance of industrial land development, and the industrial land needs to be retained and safeguard measures need to be taken.

[0174] In a specific embodiment, the method comprises:

[0175] 1. Economic Benefits

[0176] 1) Land output efficiency

[0177] (1) Industrial output per unit area

[0178] The overall industrial output value of a certain region is relatively low, and the differences in land use are large. In 2018, the total industrial output value reached 427 billion yuan. Based on the 13,406.96 hectares of industrial land that have been built, the average industrial output value per mu is about 1.9574 million yuan. Compared with other developed regions, there is still a certain gap and it has great potential for upgrading.

[0179] From the perspective of land use efficiency, industrial zones at or above the town level are more efficient, while scattered village-level industrial zones are less efficient, with serious problems such as two-tier differentiation. According to the survey, there are 2,048 industrial zones with an average industrial land output value of more than 2 million yuan per mu (approximately the average level of 1.9574 million yuan per mu in the whole region), covering an area of ​​about 3,140.98 hectares (accounting for about 23.43%), and their total industrial output value reached 335,190,645,000 yuan (accounting for 83.57%), and the average industrial output value per mu was as high as 6.9826 million yuan per mu; accordingly, there were 8,888 industrial zones with an average industrial land output value of less than 2 million yuan per mu, covering an area of ​​about 9,295.49 hectares (accounting for about 69.33%), and their total industrial output value was only 646,666,353.33 million yuan (accounting for 16.43%), and the average industrial output value per mu was only 463,800 yuan per mu, far below the average level of the whole region, as shown in Table 7.

[0180] Table 7 Statistics of average output value of industrial land by level

[0181]

[0182] According to the different levels of industrial zones, the land area of ​​industrial zones above town level is 8559.45 hectares (accounting for 63.84%), with an output value of 321350361400 yuan (accounting for 81.63%), and the average total output value per mu is about 2502900 yuan; the land area of ​​village-level industrial zones is 3877.00 hectares (accounting for 28.92%), with an output value of 72300939700 yuan (accounting for 18.37%), and the average total output value per mu is only 1243200 yuan, less than half of the town-level industrial zones, as shown in Table 8; it can be seen that a large number of village-level industrial zones have low land use efficiency, which seriously restricts the process of industrial upgrading in the whole region, and there is huge potential for the integration and redevelopment of industrial land.

[0183] Table 8 Statistics of average output value per industrial zone by grade

[0184]

[0185]

[0186] According to the situation of each town, the towns and streets with higher average industrial output value per mu are Jiangling Town and Qidu Town, both of which have reached 4 million yuan per mu; the next towns and streets with slightly higher average industrial output value per mu are Songling Town and Baqiao Town, both of which have reached 2 million yuan per mu, as shown in Table 9; the industrial enterprises in these towns and streets are large in scale, have good efficiency and less idle land, while other towns and streets have problems such as poor land use efficiency and more idle land.

[0187] Table 9 Statistics of average industrial output value per town

[0188]

[0189] From the perspective of spatial distribution, the average industrial output value per mu shows the concentration characteristics of three major industrial parks. Industrial zones with an average industrial output value per mu greater than 2 million yuan per mu are mostly concentrated in Jiangling Street, Shengze Town, and Lili Town. Most of them are distributed in a certain region's economic and technological development zones, high-tech industrial development zones, and high-tech industrial parks. The industrial enterprises in these parks are large in scale, have good efficiency, and less idle land. Other towns and streets have problems such as poor land use efficiency and more idle land.

[0190] (2) Average industrial profits and taxes per unit area

[0191] The overall taxation situation in a certain region is not ideal, and the industrial economic benefits are low. According to the survey, there are 2,028 industrial zones with an average industrial profit and tax of more than 75,000 yuan per mu (close to the average level of 78,700 yuan per mu in the whole region), covering an area of ​​about 3,089.84 hectares (accounting for about 23.05%), and their industrial profits and taxes reached 1,368,253,060 yuan (accounting for 86.50%), with an average industrial profit and tax of 295,200 yuan per mu. Correspondingly, there are 890 industrial zones with an average industrial profit and tax of less than 75,000 yuan per mu. There are 8 industrial zones with a total area of ​​about 9346.60 hectares (accounting for about 69.71%), and their industrial profits and taxes are only 213,561.52 million yuan (accounting for 13.50%), and the average industrial profits and taxes per mu is only 15,200 yuan / mu, that is, 23.05% of the land contributes nearly 86% of the industrial profits and taxes, and more than half of the industrial land has an average industrial profits and taxes of less than 75,000 yuan / mu. The polarization of industrial profits and taxes is serious, as shown in Table 10; in addition, it can be found from Table 10 that the larger the industrial profits and taxes of an industrial zone, the higher its average industrial profits and taxes, and the higher its economic benefits.

[0192] Table 10 Statistics of industrial profits and taxes per unit area of ​​industrial land by level

[0193]

[0194] From the perspective of industrial zones at different levels, the land area of ​​industrial zones above town level is 8559.44 hectares, the industrial profits and taxes are 1334863.15 million yuan, and the average industrial profits and taxes per land is about 104,000 yuan per mu; the land area of ​​village-level industrial zones is 3877.00 hectares, the industrial profits and taxes are 246951.43 million yuan, and the average industrial profits and taxes per land is only 42,500 yuan per mu, as shown in Table 11; it can be seen that industrial zones above town level are the dominant force in industrial profits and taxes, while most of the land in village-level industrial zones is not effectively utilized; from the perspective of spatial distribution, the distribution of average industrial profits and taxes per land is relatively scattered, and there are more lands with more than 75,000 yuan per mu and less than 25,000 yuan per mu in the three major industrial development zones; in addition, due to the overly scattered distribution, it is difficult to form a scale in the overall area.

[0195] Table 11 Statistics on average industrial profits and taxes per industrial zone and grade

[0196]

[0197]

[0198] 2) Land investment intensity

[0199] (1) Infrastructure completeness

[0200] The overall infrastructure construction in the district is in good condition, which is conducive to subsequent development; the supporting infrastructure in the district is mostly "five connections and one leveling", covering a total area of ​​12,206.44 hectares, accounting for 91.05% of the total land for infrastructure of different levels, of which Shengze Town and Lili Town account for more than 20%, and the supporting infrastructure is relatively complete, which can attract enterprises to settle in; followed by the infrastructure configuration of "three connections and one leveling", covering a total area of ​​970.52 hectares, accounting for about 7.24% of the total land for infrastructure of different levels, of which Lili Town and Pingwang Town account for a large proportion; while the facilities level of "six connections and one leveling" accounted for a small proportion, accounting for only 1.72%, mainly concentrated in Jiangling Street (accounting for 78.23%), while Baqie Street, Hengshan Street, Pingwang Town, Shengze Town, Zhenze Town, Qidu Town and Taoyuan Town did not meet the infrastructure standards of "six connections and one leveling", indicating that it is still necessary to focus on optimizing the infrastructure level in weak areas, as shown in Table 12.

[0201] Table 12 Statistics on land use for infrastructure level in each town

[0202]

[0203]

[0204] (2) Number of employees per location

[0205] The number of employees per industrial land in a certain region is relatively small, and the polarization phenomenon is extremely serious; the number of employees per land is mainly concentrated in 0-20 people / mu, and the number of industrial plots is 5,874, covering an area of ​​about 6,842.07 hectares, accounting for more than half of the total industrial land (51.03%); there are 5,062 plots of land with an average number of employees per land greater than 20 people / mu, covering an area of ​​about 5,594.37 hectares (accounting for 41.73%); among them, the proportion of industrial land with an average number of employees per land greater than 60 people / mu is relatively high (16.92%), mainly located in economic and technological development zones, as shown in Table 13; from the perspective of spatial distribution, industrial land with a high number of employees per land is mainly distributed in industrial parks and industrial agglomeration areas, among which the average number of employees per land in economic and technological development zones is generally higher, and scattered industrial land is characterized by a lower average number of employees per land.

[0206] Table 13 Statistics of the number of employees per area in a certain region

[0207]

[0208] Through the statistical analysis of the number of employees per land area and spatial distribution of industrial land in a certain area, it can be seen that the three major industrial parks have a large number of employees due to the industrial cluster effect, and the land use efficiency is relatively high, while the scattered industrial land in villages and towns is not intensive enough, and the number of employees per industrial land is relatively small; in order to increase the number of employees per land area in each town, the integration and upgrading of scattered industrial land in villages and towns should be accelerated to promote the industry's ability to attract talents.

[0209] 2. Land conditions

[0210] 1) Location suitability for development

[0211] The location of industrial areas in a certain region is highly suitable for development, which is conducive to subsequent renewal and construction. Due to differences in natural conditions and socio-economic conditions, the degree of suitability for development in different regions is also different; the urban development boundary is delineated based on factors such as topography, natural ecology, environmental capacity and basic farmland. The land within the urban development boundary is more suitable for urban renewal; as shown in Table 14, there are 4,802 industrial lands within the industrial protection line, covering an area of ​​7,089.29 hectares, accounting for more than half (52.88%); secondly, most of the land is located outside the industrial protection line and outside the urban development boundary, with an area of ​​4,312.31 hectares (accounting for 32.16%); the industrial land outside the industrial protection line and within the urban development boundary is relatively small, covering an area of ​​2,005.36 hectares (accounting for 14.96%).

[0212] Table 14 Statistics of the degree of suitability for development in different locations

[0213]

[0214] From the perspective of spatial distribution, the land within the security line is mostly located in the three major industrial parks and industrial zones at or above the town level, concentrated in large areas; while the land outside the industrial security line and outside the urban development boundary is mostly distributed in a linear manner along the main roads in village-level industrial zones; the industrial land outside the industrial security line and within the urban development boundary is scattered in Hengshan Street, Qidu Town, Shengze Town, Lili Town and other towns.

[0215] 2) Land use intensity

[0216] The overall land use efficiency in a certain area is relatively low, and the building density and the average floor area ratio are unbalanced; from the current industrial land development situation in various towns and streets, it can be seen that industrial land has not been well utilized; the total construction area of ​​the region is 10,403.8 hectares, and the average floor area ratio is relatively low, at 0.75; the average number of floors of industrial plants in the entire district is about 1.68 floors, and the overall utilization efficiency is low; on the contrary, the current industrial land building base area is 6,263.82 hectares, and the average building density is 44.89%; it can be seen that the industrial land use in the area is unreasonable, there is a lot of construction land but the construction intensity is weak, and the future should focus on improving the local land use efficiency.

[0217] (1) Floor area ratio

[0218] The floor area ratio is an important indicator to measure the intensity of construction land use. As shown in Table 15, the overall land use intensity in a certain region is relatively low and has a large room for improvement; the floor area ratio of most industrial land is 0.8-1.2, and the land area reaches 6561.51 hectares, accounting for nearly half (48.94%); the second is 0-0.8, with a land area of ​​about 6081.86 hectares, accounting for 45.36%, and the land space efficiency is relatively low; and the industrial land area with a floor area ratio above 1.2 is about 763.59 hectares, accounting for less than 6%, and the intensity of development and utilization of industrial construction land is insufficient, far lower than the level of the control cities.

[0219] Table 15 Statistics of land area by floor area ratio

[0220]

[0221] In terms of spatial distribution, there is less land with high floor area ratio in a certain area, and the distribution is unbalanced between the east and the west. The floor area ratio of industrial land in the east is relatively high and scattered, with relatively more in Jiangling Street. The floor area ratio in the range of 0.8-1.2 is most widely distributed in various towns, and most of them are distributed along main roads in scattered industrial areas in villages and towns. There are significant differences among the regions, and there is great potential for upgrading.

[0222] (2) Building density

[0223] Building density reflects the plane utilization of the land. The building density distribution in different areas of a certain region varies greatly, and the distribution of some industrial areas is unreasonable. From the statistical table of land area classified by building density, it can be seen that the building density is mostly between 25% and 70%, covering an area of ​​about 9773.68 hectares, accounting for about 72.90% of the industrial land area in the whole region; the industrial land area with a building density greater than 70% is about 1572.65 hectares (accounting for 11.73%), and the industrial land area with a building density less than 25% is 2060.63 hectares (accounting for 15.37%). The proportion of high-density and low-density industrial land is seriously polarized, as shown in Table 16.

[0224] Table 16 Statistics of land area by building density level

[0225]

[0226]

[0227] From the analysis of spatial layout, there are significant differences in building density in industrial areas throughout the region, showing an overall trend of higher in the south and lower in the north; among them, industrial land with a building density of less than 40% is mainly located in economic and technological development zones and high-tech industrial development zones, while industrial land with a building density greater than 70% is mostly distributed in the southern area, with a larger number in high-tech industrial parks. These lands will need to be regulated and optimized in the future.

[0228] (3) Land scale

[0229] The scale of industrial land in a certain area is relatively large, and most of the industrial land is concentrated in development. According to the survey, the current industrial land is about 13,406.96 hectares, accounting for about 38% of the total construction land in the district, the highest among all districts. As shown in Table 17, the current industrial land scale is mostly above 20 mu, covering an area of ​​about 8,888.27 hectares, accounting for more than 60%, and the scale of industrial land is relatively large; the second is the land scale between 5-20 mu, covering a total area of ​​about 3,716.33 hectares (accounting for 27.72%); and the proportion of industrial land with a scale of less than 5 mu is relatively small (5.98%), about 802.36 hectares (Table 4-19); it can be seen that the degree of agglomeration development of industrial land is relatively high, and most of the land is concentrated in development. In order to enhance the agglomeration effect of existing industries, relevant measures should be taken to strengthen the optimization and integration of small-scale fragmented land.

[0230] Table 17 Statistics of industrial land area by scale and grade

[0231]

[0232] From the overall distribution, there are many industrial built-up areas in a certain region and they are scattered, showing a high degree of fragmentation. Industrial land in most areas is scattered and the land use structure needs to be optimized. From the current industrial land development situation in various towns and streets, it can be seen that the land development intensity of Tongli Town and Jiangling Street is relatively high in the district, with a building density of only 34.58%, a floor area ratio of 0.83, and a number of building floors of 2.41, ranking first in the district; while the building density of Qidu Town, Shengze Town and Taoyuan Town is more than 50%, but the floor area ratio and number of building floors are not high, especially Taoyuan Town has only 1.12 building floors, which is the lowest level in the district. In the future, these places should focus on increasing their land development intensity and promoting intensive land use.

[0233] 3) Clarity of property rights

[0234] (1) Legality of land use procedures

[0235] The legality of land use procedures in a certain area is relatively high, and a few industrial lands in villages and towns need to be strengthened. According to the investigation, most of the industrial lands have been legally approved, and a very small number of lands are used without approval or used more than approved. As can be seen from the table below, there are about 12,418.24 hectares of industrial land that have been legally approved (accounting for 92.63%); there are about 18.20 hectares of industrial land that have been illegally approved (accounting for 0.14%), of which about 6.46 hectares of industrial land were used without approval (accounting for 0.05%), and about 11.74 hectares of industrial land were used more than approved (accounting for 0.09 hectares). There are still a small amount of illegal industrial land that needs to be strengthened, as shown in Table 18.

[0236] Table 18 Classification and statistics of the legality of land use procedures

[0237]

[0238] From the perspective of spatial distribution, a small amount of land that was used without approval or land that was used more than approved was distributed in municipal-level industrial clusters such as Lili Town, Jiangling Sub-district and Taoyuan Town, as well as scattered industrial areas in villages and towns. It can be seen that the scattered industrial areas in villages and towns have many land use problems due to the mixed interests of all parties, lax land use management and other problems, which is the main direction of future rectification.

[0239] (2) Type of land ownership

[0240] There are a lot of state-owned industrial land in a certain area, and the industrial space is highly concentrated. The construction of three major development zones has resulted in a high proportion of state-owned industrial land. According to the survey, the state-owned industrial land in the whole area is about 8928.97 hectares, accounting for 66.60%; the collective industrial land is about 4477.99 hectares, accounting for 33.40%. The state-owned industrial land is about twice the area of ​​collective industrial land. Among the state-owned industrial land, the state-owned land ownership industrial land is 616.47 hectares (accounting for about 6.90%), and the state-owned land use right industrial land is 8312.5 hectares (accounting for about 93.10%), and industrial land with state-owned land use rights accounts for a large proportion; among collective industrial land, village collective land accounts for about 2315.86 hectares (accounting for 51.72%), township collective land accounts for about 455.41 hectares (accounting for 10.17%), and villagers' group land accounts for about 1706.72 hectares (accounting for 38.11%); collective industrial land has many problems involving the interests of villagers, complex ownership, incomplete land use procedures, and too long lease period. In particular, the existence of a large number of collective transfer land makes integration and upgrading more difficult, as shown in Table 19.

[0241] Table 19 Industrial land ownership classification statistics

[0242]

[0243]

[0244] From the perspective of each town and street, the proportion of state-owned land in Jiangling Street, Lili Town and Shengze Town is relatively high, all close to 20%; collective land is mostly distributed in Shengze Town and Lili Town, of which Shengze Town accounts for more than 30%; while Songling Street, Hengshan Street, Baqie Street and Tongli Town have relatively less state-owned industrial land and collective land, accounting for no more than 3%; from the perspective of spatial distribution, state-owned land is mainly distributed in industrial zones at or above the town level, village collective industrial land is more concentrated in Jiangling Street, Lili Town and Shengze Town, and the others are scattered in village-level industrial land.

[0245] 3. Construction Environment

[0246] 1) Space environment

[0247] (1) External environment of the building

[0248] The overall land use style and appearance of a certain area is at a medium-to-high level, and the land use style and appearance of some land uses needs to be improved; according to the survey, there are about 11,898.74 hectares of industrial land with good and general land use style (accounting for 88.75%), and 1,508.22 hectares of industrial land with poor land use style (accounting for 11.25%). The overall land use style and appearance is good; from the perspective of each town, the land use with good land use style and appearance is mainly distributed in Jiangling Street and Shengze Town, covering a total area of ​​about 2,564.68 hectares, accounting for about 56.34%; the industrial land with poor land use style and appearance is mainly concentrated in Lili Town, covering an area of ​​about 495.07 hectares, accounting for more than 30%, as shown in Table 20.

[0249] Table 20 Statistics of land features distribution

[0250]

[0251] From the perspective of spatial distribution, land with better land appearance is concentrated in industrial land in municipal-level industrial clusters, especially economic and technological development zones and high-tech industrial parks; the land appearance in high-tech development zones is relatively poor and needs further optimization and remediation; from the perspective of development trends, the overall appearance of industrial land in industrial clusters is constantly improving and the overall quality is improving, while the appearance of scattered industrial land in villages and towns needs to be improved.

[0252] (2)Traffic conditions

[0253] The transportation resources in a certain area are relatively superior, which has a strong driving effect on industrial development. As shown in Table 21, most industrial land is distributed within 500 meters around the main roads, with about 4294 plots of land, covering an area of ​​4893.09 hectares (36.50%). Secondly, a large number of industrial land is distributed within 1000 meters around rail transit stations, covering an area of ​​about 2032.02 hectares (15.16%). There are also about 1468.58 hectares of industrial land within 800 meters around highways and expressways. hectares (10.95%) of industrial land; taking into account the impact of railway transportation on industry, about 505.87 hectares (3.77%) are distributed within 2000 meters around the proposed railway stations; it can be seen that industrial land is concentrated in locations with superior transportation conditions, with an area of ​​8899.56 hectares (66.38%), and 4507.40 hectares (33.62%) of industrial land are distributed in other areas. Transportation conditions have a greater impact on the distribution of industrial land.

[0254] Table 21 Traffic conditions classification statistics

[0255]

[0256] From the perspective of spatial distribution, most industrial land in a certain area is distributed linearly along the main traffic roads, and the overall distribution characteristics are "three verticals and two horizontals"; the "three verticals" are mainly industries along the Western Avenue, the Central Expressway and the Eastern Expressway, and the "three horizontals" are industries along the expressways and along the expressways; among them, the Economic and Technological Development Zone has superior transportation conditions such as rail transit stations, and the level of transportation infrastructure is relatively good, and industrial agglomeration development is achieved; while the rural and town areas lack major transportation arteries with strong transportation capacity, and the transportation development conditions are poor, and industrial development is restricted.

[0257] 2) Building quality

[0258] (1) Construction period

[0259] The construction of industrial zones in a certain region has roughly gone through three periods: from the beginning of the 21st century to 2005, bottom-up industrial development led to scattered land distribution, and the number of industrial land was relatively small, with only 1,440 plots covering an area of ​​about 1,409.21 hectares, which was the product of the initial bottom-up development of industry; the ten years from 2005 to 2015 were a period of rapid industrial development, with 9,022 new industrial land plots, covering an area of ​​about 10,120.79 hectares (accounting for 54.09%), of which 2010-2015 was the climax of industrial land construction, mostly scattered village-level industrial zones along the roads, which had a great impact on the current industrial land pattern; after 2015, the growth rate of industrial land slowed down, and most of the newly built industrial agglomeration areas at or above the municipal and town levels accounted for about 7.24% of the total industrial land, as shown in Table 22.

[0260] Table 22 Construction year distribution statistics

[0261]

[0262] From the distribution map of industrial zone construction years, it can be seen that the bottom-up industrial development path has caused the spatial dispersion of industrial land. The construction of concentrated industrial zones has played a major role in the formation of industrial space. The newly built industrial land is mainly distributed in three industrial parks, followed by urban industrial clusters; the old industrial land is scattered in the village and town areas. On the whole, the construction of industrial zones has shifted from dispersed to concentrated development.

[0263] (2) Construction quality

[0264] The quality of construction is the main factor affecting the appearance and use function of buildings. The overall quality of existing industrial buildings in a certain area is poor, and there are obvious differences in various regions. From the perspective of quantity distribution, the total land area with good construction quality in the whole area is about 1863.25 hectares (accounting for 13.90%), while the total land area with poor construction quality is about 11543.71 hectares (accounting for 86.10%), as shown in Table 23. Among them, the proportion of total land area with good construction quality in village-level industrial zones and industrial zones above town level is roughly the same as the proportion of total land area with poor construction quality, which are about 13% and 86% respectively. The area of ​​land with poor construction quality is 7 times that of land with good construction quality, and the construction quality in industrial zones is generally poor. It can be seen that the industrial area with poor construction quality is much higher than that of land with good construction quality, and the overall quality of buildings needs to be improved urgently. From the perspective of spatial distribution, industrial land with good construction quality is mainly distributed in three industrial parks, while the scattered industrial zones in villages and towns are generally of relatively poor construction quality due to lack of management and repair.

[0265] Table 23 Building quality classification statistics

[0266]

[0267] To sum up, with the help of the above-mentioned technical scheme of the present invention, by dividing the evaluation map of industrial land, it is possible to have an in-depth understanding of the specific conditions and characteristics of each piece of industrial land, so as to achieve a more accurate grasp of them, ensure the pertinence and effectiveness of the evaluation, and make the evaluation results closer to the actual situation of the industrial land, providing strong support for subsequent decision-making; through the comprehensive performance evaluation of industrial land, its overall performance can be comprehensively evaluated, covering land use efficiency, economic benefits and environmental benefits and other aspects, which not only provides a solid data basis and reference materials for making future decisions, but also helps to improve the overall performance of industrial land and promote its sustainable development.

[0268] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A performance evaluation method for industrial land in village and town industrial parks from the perspective of urban renewal, characterized by: The method comprises the following steps: S1. Divide the industrial land evaluation plots according to the collected industrial land data, and build an industrial land performance evaluation index system based on the evaluation plots, and select evaluation indicators; S2. Analyze the selected evaluation indicators using the analytic hierarchy process and determine the weights of the evaluation indicators; S3. Evaluate the comprehensive performance of industrial land based on the evaluation index weights, and formulate implementation strategies based on the evaluation results.

2. According to the method for evaluating the performance of industrial land in village and town industrial parks from the perspective of urban renewal in claim 1, it is characterized by: According to the collected industrial land data, the industrial land evaluation plots are divided, and the industrial land performance evaluation index system is constructed based on the evaluation plots. The selection of evaluation indexes includes the following steps: S11. Collect industrial land data, and divide the collected industrial land data into a number of assessment plots, wherein each assessment plot represents an independent statistical unit; S12. Combine the assessment map with the land resource development needs to determine the comprehensive performance factors; S13. Based on comprehensive performance factors and industrial land data, construct an industrial land performance evaluation index system, and select evaluation indicators from the industrial land performance evaluation index system.

3. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 2 is characterized by: The comprehensive performance factors include: economic benefits, site conditions and construction environment.

4. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 1 is characterized in that: The method of analyzing the selected evaluation indexes by using the analytic hierarchy process to determine the evaluation index weights comprises the following steps: S21. Based on the industrial land performance evaluation index system, the evaluation indicators are divided into different levels, and the evaluation indicators of each level are numbered to construct a category judgment matrix; S22, according to the constructed category judgment matrix, using the scaling method to score the evaluation indicators in the category judgment matrix; S23, based on the scoring results, perform consistency check on each category judgment matrix; S24, using mathematical software to calculate the maximum eigenvector of each category judgment matrix after the consistency test passes; S25. Normalize the calculated maximum eigenvector to obtain the evaluation index weight.

5. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 4 is characterized in that: The category judgment matrix includes: a secondary indicator judgment matrix, a tertiary indicator judgment matrix and a quaternary indicator judgment matrix.

6. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 5 is characterized by: Based on the scoring results, the consistency check of each category judgment matrix includes the following steps: S231, based on the scoring results, using mathematical software to calculate the maximum eigenvalue of each category judgment matrix; S232, combining the maximum eigenvalue with the trace of the category judgment matrix, calculating the consistency index of the category judgment matrix, and obtaining the corresponding average random consistency index according to the consistency index; S233, calculating the random consistency ratio based on the consistency index and the average random consistency index; S234: Based on the random consistency ratio, the consistency of the category judgment matrix is ​​judged. If the random consistency ratio is less than the preset threshold, the category judgment matrix is ​​consistent. Otherwise, steps S231 to S233 are repeated until the category judgment matrix passes the consistency test.

7. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 6 is characterized by: The calculation formula for combining the maximum eigenvalue with the trace of the category judgment matrix, calculating the consistency index of the category judgment matrix, and obtaining the corresponding average random consistency index according to the consistency index is: In the formula, CI represents the consistency index; λ max Represents the maximum eigenvalue of the category judgment matrix; n represents the trace of the category judgment matrix.

8. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 6 is characterized by: The formula for calculating the random consistency ratio based on the consistency index and the average random consistency index is: In the formula, CR represents the random consistency ratio value; CI stands for consistency index; RI stands for average random consistency index.

9. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 1 is characterized by: The method of evaluating the comprehensive performance of industrial land based on the evaluation index weights and formulating implementation strategies according to the evaluation results includes the following steps: S31. Based on the evaluation index weights, the comprehensive performance score of industrial land is calculated using multi-factor superposition analysis technology; S32. Compare the calculated comprehensive performance score with the preset score to evaluate the comprehensive performance of the industrial land; S33. Formulate implementation strategies based on the evaluation results of the comprehensive performance of industrial land.

10. The performance evaluation method of industrial land in village and town industrial parks from the perspective of urban renewal according to claim 9 is characterized in that: The calculated comprehensive performance score is compared with the preset score to evaluate the comprehensive performance of industrial land, including the following steps: If the comprehensive performance score of industrial land is lower than the preset score, it means that the comprehensive performance of the industrial land development is poor; If the comprehensive performance score of industrial land is higher than the preset score, it means that the comprehensive performance of the industrial land development is good.

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