CN-121998452-A - Low-utility land intelligent identification and redevelopment potential evaluation method and system

CN121998452ACN 121998452 ACN121998452 ACN 121998452ACN-121998452-A

Abstract

The application discloses a method and a system for evaluating low-utility land intelligent recognition and redevelopment potential, wherein the method comprises the steps of obtaining land attribute data, carrying out nonlinear association analysis on the attribute data based on a multi-dimensional index system to identify the low-utility land, wherein the method comprises the steps of determining whether the low-utility land is preliminary recognition of the low-utility land, determining space units belonging to the low-utility land and optimizing recognition of the low-utility land, identifying fine recognition of low-efficiency subareas caused by minimum unit structure mismatch in the space units of the low-utility land, evaluating redevelopment potential by a construction potential evaluation index system in a quantized mode, analyzing redevelopment priority of the low-utility land through an entropy weight method and a multi-criterion decision, integrating a geographic information system platform, realizing visual display of the low-utility land, carrying out policy simulation based on the redevelopment priority, outputting simulation results and screening an optimal redevelopment mode. The application can realize accurate identification, classification evaluation and redevelopment potential dynamic analysis of low-utility places.

Inventors

CHEN GUODONG
JIANG JING
BAI ANQI
GUO JINGYI

Assignees

南京市市政设计研究院有限责任公司

Dates

Publication Date: 20260508
Application Date: 20260109

Claims (10)

1. A method for intelligently identifying and redevelopment potential of a low-utility site, comprising: acquiring multidimensional attribute data of a land block and preprocessing the multidimensional attribute data; The method comprises the steps of acquiring a multi-dimensional index system, acquiring a multi-dimensional index feature non-linear cluster of the space unit which is initially identified as the low-utility land, determining the space unit belonging to the low-utility land and the low-efficiency type, and performing fine identification, wherein the non-linear correlation analysis comprises three-level identification analysis, the preliminary identification comprises the steps of calculating a region entropy value, a coupling degree and a cooperative scheduling based on a region order model and a multi-dimensional index coupling cooperative model, dividing the space unit based on a Voronoi diagram, setting a threshold division and a feature combination to judge whether the divided space unit is the low-utility land; Constructing a potential evaluation index system to quantitatively evaluate the redevelopment potential of the land block with low utility, and analyzing the redevelopment priority of the land block with low utility through an entropy weight method and multiple criteria decision; And integrating the geographic information system platform, realizing visual display of the low-utility land, performing policy simulation based on the redevelopment priority, outputting a simulation result and screening an optimal redevelopment mode.
2. The low utility ground intelligent recognition and redevelopment potential assessment method of claim 1, wherein the primary recognition further comprises: The method comprises the steps of setting a dynamic zone level model to replace the zone level model, calculating the space integration degree of continuous years by adopting a time sequence space syntactic analysis algorithm and carrying out zone level division, calculating multi-scale zone level entropy aiming at each space unit, selecting the minimum scale zone level entropy from the multi-scale zone level entropy as final zone level entropy, wherein the multi-scale zone level entropy comprises a first scale entropy with a range of a single space unit, a second scale zone level entropy with a range of the single space unit and adjacent space units, a third scale zone level entropy with a range of the space unit in a administrative area where the single space unit is located, and judging zone level entropy thresholds with corresponding scales are arranged on different scale entropy, calculating the annual change rate of the corresponding scale zone level entropy, and adjusting the judging zone level entropy thresholds under the corresponding scales when the annual change rate of the zone level entropy is lower than the annual change rate of the preset zone level entropy.
3. The low utility ground intelligent recognition and redevelopment potential assessment method of claim 1, wherein the primary recognition further comprises: Based on the static index and the dynamic trend index of each dimension, the static nonlinear coupling degree and the dynamic nonlinear coupling degree are obtained by corresponding calculation, and the time sequence nonlinear coupling degree obtained by weighting calculation is used as the final coupling degree.
4. The low utility ground intelligent recognition and redevelopment potential assessment method of claim 1, wherein the optimized recognition further comprises: The method comprises the steps of carrying out multidimensional index feature nonlinear clustering on the space units which are preliminarily identified as low-utility land, adopting a DBSCAN clustering algorithm, carrying out multidimensional index feature standardization on the space units which are preliminarily identified as low-utility land candidate land, calculating attribute distances of non-spatial attributes among the space units based on a Markov distance algorithm, calculating the spatial distances among the space units by utilizing a Huffman distance algorithm, weighting calculation to obtain the mixed distance among the space units, constructing a mixed distance matrix, setting DBSCAN clustering parameters, traversing the space units, identifying core points, boundary points and noise points, carrying out space constraint verification, filtering the clustering of space discrete, and outputting the low-utility land with continuous space and the low-efficiency type thereof.
5. The method for evaluating the low utility land intelligent recognition and redevelopment potential according to claim 1, wherein the optimizing recognition further comprises constructing a heterogeneous time sequence chart attention network model, wherein node definition in the heterogeneous time sequence chart attention network model comprises the steps of taking a space unit as a core node, taking POIs and roads as auxiliary nodes, and edge definition comprises a space adjacent edge and a function associated edge, wherein the heterogeneous time sequence chart attention network model is provided with a space attention and feature attention mechanism, is embedded with an LSTM module to capture the time sequence trend of an input dynamic index, is generated through multi-dimensional index feature training corresponding to the space unit with history labeling inefficiency or not, inputs the multi-dimensional index feature corresponding to the space unit with preliminary recognition as the low utility land into the heterogeneous time sequence chart attention network model, and obtains whether the output space unit is a low utility land judgment result; The fine recognition further comprises the step of judging whether the output space unit is low-efficiency degree scoring, low-efficiency type and feature weight in the low-efficiency land judgment result, and the step of correcting and recognizing a preset minimum unit low-efficiency probability threshold and a minimum unit structure mismatch feature weight threshold in the low-efficiency subarea caused by the minimum unit structure mismatch in the space unit of the low-efficiency land so as to optimize the recognition result of the low-efficiency subarea caused by the minimum unit structure mismatch.
6. The method for intelligently identifying and evaluating redevelopment potential of a low-utility land according to claim 1, wherein the construction potential evaluation index system quantifies redevelopment potential evaluated low-utility land and evaluates redevelopment priority of a land parcel by entropy weight method and multi-criterion decision analysis comprises: Combining policy adaptation theory, a market benefit model and ecological constraint conditions, constructing a potential evaluation index system, acquiring potential evaluation indexes including economic force, social force and ecological force, and carrying out index standardization on each potential evaluation index; the entropy weight of each potential evaluation index is obtained by calculating the information entropy and the difference coefficient of each potential evaluation index through an entropy weight method; The method comprises the steps of constructing a weighted standardized matrix by utilizing a multi-criterion decision analysis algorithm, continuously adjusting the corresponding weight of potential evaluation indexes according to the identified low-efficiency type, determining an ideal solution, calculating Euclidean distance between a space unit and the ideal solution, calculating the closeness, comparing the closeness with a preset closeness threshold, determining a closeness corresponding range, judging a redevelopment priority according to the closeness range, carrying out dimensionality separation based on each potential evaluation index dimension, comparing the closeness of each dimensionality, and determining a redevelopment direction according to the largest dimensionality corresponding dimension.
7. The method for evaluating the low utility land intelligent recognition and redevelopment potential according to claim 1, wherein the policy simulation based on redevelopment priority, outputting the simulation result and screening the optimal redevelopment pattern comprises: Setting a redevelopment policy simulation engine, wherein a plurality of types of redevelopment modes are built in the redevelopment policy simulation engine, each redevelopment mode can simulate at least one policy effect of volume ratio rewarding policies, mixed land policies, ecological restoration policies and stock updating policies, the redevelopment priority of each space unit is divided into simulation resources and depths, the higher the redevelopment priority is, the higher the simulation resource occupation ratio is, the deeper the simulation hierarchy is, scene simulation is carried out based on each redevelopment mode, simulation results of each redevelopment mode are output, the closeness is recalculated, and the corresponding policy of the optimal redevelopment mode is screened.
8. A low utility smart identification and redevelopment potential assessment system, comprising: the data acquisition and preprocessing module is used for acquiring multidimensional attribute data of the land block and preprocessing the multidimensional attribute data; The low-utility land intelligent identification module is used for carrying out nonlinear association analysis on the collected data based on the multi-dimensional index system so as to identify the low-utility land; the nonlinear association analysis comprises three-level identification analysis, wherein the preliminary identification comprises the steps of calculating a region entropy value, a coupling degree and a co-scheduling based on a region order model and a multi-dimensional index coupling co-model, dividing space units based on a Voronoi diagram, setting threshold division and feature combination to judge whether the divided space units are low-utility grounds, the optimization identification comprises the steps of obtaining low-utility ground feature cluster groups by carrying out multi-dimensional index feature nonlinear clustering on the space units preliminarily identified as the low-utility grounds, and determining the space units and the low-efficiency types belonging to the low-utility grounds; the redevelopment potential dynamic evaluation module is used for constructing a potential evaluation index system to quantitatively evaluate the redevelopment potential in a low-utility manner and analyzing the redevelopment priority of the land parcels in the low-utility manner through an entropy weight method and multi-criterion decision analysis; The redevelopment decision simulation screening module is used for integrating the geographic information system platform, realizing the visual display of the low-utility land, performing policy simulation based on redevelopment priority, outputting a simulation result and screening an optimal redevelopment mode.
9. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the method according to any one of claims 1 to 7.
10. A computer device comprising a memory, a processor and a program stored and executable on the memory, which when executed by the processor performs the steps of the method according to any one of claims 1 to 7.

Description

Low-utility land intelligent identification and redevelopment potential evaluation method and system Technical Field The application relates to the technical field of land resource management, in particular to a method and a system for intelligently identifying low-utility land and evaluating redevelopment potential. Background In the technical fields of land resource management, urban updating and low-utility land redevelopment, the method can accurately identify and evaluate redevelopment potential of the low-utility land, and has important significance for reasonably planning land resources and improving urban development quality. Accurate identification and evaluation can help related departments to better understand land utilization conditions, and scientific and reasonable land policies and urban updating plans are formulated, so that land utilization efficiency is improved, and sustainable development of cities is promoted. In order to solve the problems of low-utility identification and redevelopment potential evaluation, the conventional means in the prior art mainly rely on linear weighted evaluation models, such as entropy weight method, analytic hierarchy process and the like. These methods evaluate whether the land is a low utility land and its redevelopment potential by weighting some economic, social, etc. metrics and then performing linear calculations. Meanwhile, some of the existing researches also adopt some simple threshold dividing methods, and the utilization efficiency of the land is judged according to the numerical value of some single indexes. The prior art has obvious defects. On one hand, the existing low-utility land identification method lacks consideration of nonlinear relation between land block attributes and low efficiency degree, is difficult to process multidimensional feature interaction effect, and cannot accurately reflect the real situation of land utilization. On the other hand, the existing research is still insufficient in explaining theoretical preset logic correlation of a redevelopment mode and summarizing and deducting a multi-factor interaction mechanism, and cannot fully consider the nonlinear relation between indexes and low-efficiency utilization degree, and neglects the excavation of high-value plots with synergistic effects. In addition, the existing low-utility land identification is mainly based on government land financial tax, consideration of comprehensive benefits of people is lacking, meanwhile, influence of regional condition difference on land utilization efficiency is usually ignored, and fine identification is difficult to realize. Disclosure of Invention In order to realize accurate identification, classification evaluation and redevelopment potential dynamic analysis of low-utility lands, the application provides a low-utility land intelligent identification and redevelopment potential evaluation method and system. In a first aspect, the present application provides a method for intelligently identifying and evaluating redevelopment potential with low utility, comprising: acquiring multidimensional attribute data of a land block and preprocessing the multidimensional attribute data; The method comprises the steps of acquiring a multi-dimensional index system, acquiring a multi-dimensional index feature non-linear cluster of the space unit which is initially identified as the low-utility land, determining the space unit belonging to the low-utility land and the low-efficiency type, and performing fine identification, wherein the non-linear correlation analysis comprises three-level identification analysis, the preliminary identification comprises the steps of calculating a region entropy value, a coupling degree and a cooperative scheduling based on a region order model and a multi-dimensional index coupling cooperative model, dividing the space unit based on a Voronoi diagram, setting a threshold division and a feature combination to judge whether the divided space unit is the low-utility land; Constructing a potential evaluation index system to quantitatively evaluate the redevelopment potential of the land block with low utility, and analyzing the redevelopment priority of the land block with low utility through an entropy weight method and multiple criteria decision; And integrating the geographic information system platform, realizing visual display of the low-utility land, performing policy simulation based on the redevelopment priority, outputting a simulation result and screening an optimal redevelopment mode. By adopting the scheme, the multi-attribute data of the land parcels are subjected to nonlinear association analysis by utilizing the multi-dimensional index system, the low-utility land is accurately identified through the three-level identification process, the quantitative redevelopment potential of the index system is constructed and the priority is evaluated, visual display and policy simulation are realized by means of the