CN-122022534-A - Urban low-utility land identification and analysis method and system based on multivariate data

CN122022534ACN 122022534 ACN122022534 ACN 122022534ACN-122022534-A

Abstract

The invention discloses a method and a system for identifying and analyzing urban low-utility land based on multi-metadata, which relate to the technical field of urban land planning and comprise the steps of acquiring and preprocessing basic land data, extracting a target type land, and carrying out attribute association and space link with multi-source socioeconomic data; establishing a qualitative and quantitative low-utility land identification and evaluation index system, judging whether each type of land is a low-utility land by an expert weighting and comprehensive evaluation method to obtain a low-utility land preliminary identification result, carrying out multi-subject and multi-type field check on the preliminary identification result, integrating multi-source data to form a correction data set, carrying out fine screening and boundary correction on plots to generate a low-utility land final identification result layer, standardizing and warehousing the final identification result, establishing an annual data dynamic update mechanism, and carrying out iterative update on the existing final identification result set based on the latest multi-source data. The invention can greatly reduce human errors and improve the recognition efficiency and accuracy.

Inventors

XIE GUOJUN
TIAN YUNYU
ZHANG XIAOJIE
WANG LI
ZHANG PENGCHENG
ZHANG CHENGSONG
LIU SIYONG

Assignees

成都市市政工程设计研究院有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. A method for identifying and analyzing town low utility based on multivariate data, comprising: Step 1, acquiring and preprocessing basic land data, extracting a target type land from the preprocessed basic land data, collecting multi-source socioeconomic data, performing attribute association and space linking with the extracted target type land, and constructing a land-attribute integrated database; Step 2, constructing a qualitative and quantitative low-utility land identification evaluation index system for different types of land, adopting an expert weighting method to definitely weight each evaluation index, carrying out grading assignment, carrying out index scoring according to the low-efficiency degree of each land, calculating the comprehensive score of each land in a weighted summation mode, and judging whether each type of town land is a town low-utility land or not based on the comprehensive score to obtain a preliminary low-utility land identification result; Integrating the multisource data to form a correction data set, performing multidimensional space registration and comparison analysis on the correction data set and the low-utility land preliminary identification result, and performing man-machine cooperation to realize fine screening and boundary correction on land parcels to generate a final recognition result layer of the town low-utility land; And 4, standardizing final result of urban low-utility land after the correction of the inside-outside industry data into a library, constructing a data dynamic update mechanism, starting an update flow when the update condition is met by taking the natural year as a basic update period, and repeatedly executing the steps 1 to 4 on the acquired latest multi-source data, and iteratively updating the final result set of urban low-utility land according to the latest identification result.
2. The method for identifying and analyzing town low utility based on multivariate data according to claim 1, wherein the step 1 specifically comprises: the method comprises the steps of acquiring basic land data in an identification range, wherein the basic land data comprises annual land utilization change investigation data and town development boundary vector data, and the identification range is a current construction land area in a town development boundary; Using a cutting tool in ArcGIS software to cut the space of the annual land use change investigation data by taking the town development boundary as a cutting mask, extracting all map spots within the boundary range, and obtaining land use change investigation data within the town development boundary range; three target type land areas of living land, industrial and mining land and logistics storage land and business administration land are extracted in layers from land utilization change investigation data within the range of town development boundaries based on land codes or land property attributes through an attribute-based selection tool of ArcGIS software, so that three land type layers are formed; And collecting multisource socioeconomic data comprising department data, park data and town street data, associating the collected multisource socioeconomic data with vector data sets corresponding to three land type layers through an attribute connection tool of ArcGIS software, creating a field, updating associated attribute information into attribute tables of three land type layers of living land, industrial and mining and logistics storage land and business administration land by using a field calculator of the ArcGIS software, and constructing a land-attribute integrated database containing space geometry, land property, management attribute and statistical information to form a basic data result.
3. The method for identifying and analyzing town low utility based on multivariate data according to claim 1, wherein the step 2 specifically comprises: Constructing a qualitative and quantitative low-utility identification evaluation index system: the low-efficiency living land identification evaluation indexes are specifically divided into qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise stain discharge or pollution discharge sources, and the quantitative indexes comprise population density, dangerous old building occupancy rate, public service facility diversity, infrastructure coverage rate and external traffic connection degree; The low-efficiency industrial and mining and logistics storage land identification evaluation indexes are specifically divided into qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise industrial development types, environment protection requirement standard conditions and industrial or logistics storage management informatization levels, and the quantitative indexes comprise building coefficients and volume rates, construction progress, space idle rate of industrial land or logistics storage land, investment intensity or mu average tax, old production building or storehouse occupation ratio of industrial land or logistics storage land and external traffic connection degree; The evaluation indexes are specifically divided into qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise stain discharge or pollution discharge sources, and the quantitative indexes comprise construction progress, space free rate of the taking place of the business, low-end business state proportion of the taking place of the business, average business balance and external traffic connection degree; The method comprises the steps of determining the weight of each evaluation index by using a Delphi method, selecting 7-10 experts in the fields including urban planning, land planning, urban updating, industrial economy and ecological environment, carrying out 2-3 rounds of anonymous letter polling, and identifying practice experience by the experts in the first round in combination with towns in a low-utility mode to independently give weight; scoring land parcels in the basic data result based on the determined evaluation indexes to obtain index values of all evaluation indexes, and calculating comprehensive scores of all land parcels according to the following formula: In which, in the process, , An index value of the ith index of the target land parcel; And identifying the land with the comprehensive score of more than or equal to 6 points as a low-utility land, and obtaining a preliminary identification result of the low-utility land.
4. The urban low-utility land identification and analysis method based on multi-data according to claim 3, wherein the rule for scoring land plots in the basic data result based on the identification evaluation index is that each identification evaluation index is subjected to grading assignment, each index is divided into 4 grades according to land low-efficiency degree, 0 score, 3 score, 7 score and 10 score are correspondingly assigned, a quantitative index is based on an identification area corresponding index mean value, a threshold value is progressively set according to the low-efficiency degree, a qualitative index is subjected to definite grading standard according to the condition of meeting the low-efficiency condition, and index values of each evaluation index are obtained through calculation and assignment according to actual conditions.
5. The method for identifying and analyzing urban low-utility land based on multi-data according to claim 3, wherein the weights of pollution discharge points or pollution discharge sources, population density, dangerous old building ratio, public service facility diversity, infrastructure coverage rate and external traffic contact degree evaluation indexes of the low-efficiency living land are respectively 0.15, 0.3, 0.1, 0.2 and 0.1; The industrial development type of the low-efficiency industrial and mining area or logistics storage area, the environment-friendly requirement standard condition, the industrial or logistics storage management informatization level, the building coefficient and volume rate, the construction progress, the space free rate of the industrial area or logistics storage area, the investment intensity or mu average tax, the land danger old productive building or storehouse duty ratio of the industrial area or logistics storage area and the weight of the external traffic connection degree evaluation index are respectively 0.2, 0.1, 0.05, 0.1, 0.15, 0.1 and 0.05; the weights of the stain discharge or pollution discharge source, the construction progress, the space idle rate of the taking place of the low-efficiency manufacturer, the low-end business state proportion of the taking place of the manufacturer, the average business and the external traffic contact degree evaluation index are respectively 0.1, 0.25, 0.2, 0.15, 0.2 and 0.1.
6. A method for identifying and analyzing town low utility based on multivariate data according to claim 3, wherein the method for performing multi-subject, multi-type collaborative field check on the preliminary identification result by multivariate means specifically comprises: Based on the low utility ground preliminary identification result, collaborative field check is carried out on a multi-type main body, and a mode of integrating site survey, interview questionnaires and data cross validation is adopted to carry out systematic field check on five major core dimensions including firstly land actual utilization state including idle, low-efficiency utilization and normal utilization classification, secondly building integrity and layout suitability including dangerously old, old and sound grade judgment and space layout conflict check, thirdly business activity authenticity including actual business verification, empty rate measurement and production business activity assessment, fourthly facility matching and running conditions including infrastructure matching integrity, public service facility matching level and facility running stability and fault response capability, and fifthly rights compliance including land procedure completeness, mortgage sealing rights limit state and illegal land and illegal construction check, wherein the multi-type main body comprises enterprises, park or community management parties, typical residents or practitioners and governments.
7. The method for identifying and analyzing urban areas with low utility based on multivariate data according to claim 6, wherein the method for integrating the multisource data to form a corrected data set, performing multidimensional space registration and comparison analysis on the corrected data set and the primary identification result of the areas with low utility, and performing man-machine cooperation to realize fine screening and boundary correction on land areas to generate a final result layer of identification of the areas with low utility, specifically comprising: Collecting field verification data, and verifying the actual utilization state of land in the primary low-utility land identification result according to the actual use, building condition, facility matching, empty rate and field photo of the latest land in the data to form a field current situation verification layer with complete attribute; collecting land feature data, correcting the feature consistency of a land boundary according to land boundary lines, entitlement persons, areas, purposes and mortgage sealing states of the land in the data to form a land feature vector layer, collecting natural boundary data, extracting key geographic element information of mountain and river water systems in the data, checking whether the land boundary is reasonable to form a space constraint boundary layer, collecting control rule data, comparing a low-utility land primary identification result with constraint indexes of legal planning to form a planning index attribute table, wherein the constraint indexes comprise land property, volume rate and building density; Utilizing an intersecting tool of ArcGIS software to conduct multi-level spatial registration and comparison analysis on the correction data set obtained after the standardized pretreatment and the low-utility ground preliminary identification result, automatically finding contradiction and abnormal areas, and providing visual and quantitative basis for correction; Manually deleting land blocks with high-efficiency attribute of planning compliance, clear ownership or field verification from the low-efficiency land list after confirmation according to an attribute list of a preliminary identification result of the low-utility land, manually drawing and incorporating the land blocks with low-efficiency area with serious compliance conflict or field verification confirmed to be seriously low-efficiency area in a nesting analysis result, manually verifying the key attribute of each land block according to all evidence links, wherein the key attribute of each land block comprises identification of the low-efficiency type, the low-efficiency level and the dominant reconstruction direction by taking the land boundary line of the land-use attribute vector layer as legal basis in an ArcGIS editing environment and referring to a more accurate idle or break range in a field current verification layer; And integrating all correction operations to generate a final result-determining layer of the town low-utility land, wherein the layer has complete space geometric information and a verified attribute table, and the content comprises land location, land area, current land use type, use condition, determination reason, rights information, control rule index, land feature state, reconstruction suggestion and reconstruction-planning mode.
8. The method for identifying and analyzing town low utility based on multivariate data according to claim 7, wherein the intersecting tool of ArcGIS software is used to perform multi-level spatial registration and comparison analysis on the corrected dataset after standardized preprocessing and the preliminary identification result of low utility, and automatically find contradictory and abnormal areas, thereby providing visual and quantitative basis for correction, and the method specifically comprises the following steps: The method comprises the steps of carrying out superposition analysis on a map layer of a low-utility ground preliminary identification result and a map layer of a space constraint boundary, carrying out space verification on the boundary of a land block in the low-utility ground preliminary identification result and the key geographic element information boundary of a mountain and a river water system, comparing the current usage and the volume rate attribute of the land block with the corresponding planning usage and the specified volume rate in a planning index attribute table, verifying whether the land block meets space boundary management and legal planning requirements; The map spots which are seriously inconsistent with the land parcel boundary line are marked for the land parcel with abnormal rights and the map spots which are seriously inconsistent with the land parcel boundary line, whether the map spots are positioned in the characterized range or not is determined, and the specific areas which are not used are determined; The method comprises the steps of carrying out space association and visual examination on the low-utility ground primary identification result layer and the field current situation checking layer, specifically associating checking points, lines and facial information acquired by the field with pattern spots in the primary identification result layer, comparing the checking points, lines and facial information under the same view, identifying the places with evidence conflict, and providing a field investigation boundary for correcting the boundary obtained based on the field data.
9. The method for identifying and analyzing town low utility based on multivariate data according to claim 7, wherein said step 4 specifically comprises: The method comprises the steps of carrying out topological relation check, coordinate system unification and geometric correction on space elements of an achievement layer, unifying attribute information of each plot according to a standard attribute table structure, wherein the attribute information comprises identification numbers, identification time, identification reasons and boundary correction basis; Constructing a data dynamic updating mechanism, wherein the mechanism takes natural years as a basic updating period, and automatically triggers through preset updating time or manually starts an updating flow after updating the latest annual land utilization change survey data; The data dynamic updating process comprises the steps of data acquisition and preparation period, execution of acquisition and synchronization of latest multi-source data according to predefined interface standards and data standards, format standardization, spatial alignment and attribute structure matching of new and old data, establishment of a unified current annual work base map and a database, identification and correction processing period, acquisition of latest identification and correction results by carrying out intra-business data identification and intra-business data correction on the acquired latest multi-source data, result generation and verification period, corresponding addition, deletion, modification and verification operation on a final result library with low effectiveness according to the latest identification and correction results, generation of new-version low-effectiveness results and updated pattern spots, verification and confirmation of results by combining preset rules and manual review, and final realization of low-effectiveness result versions with independent annual update output and time stamps.
10. A multi-data-based town low utility identification and analysis system, comprising: the basic data processing module is used for acquiring basic land data and preprocessing, extracting a target type land from the preprocessed basic land data, collecting multi-source social and economic data, performing attribute association and space linking with the extracted target type land, and constructing a land-attribute integrated database; The internal data identification module is used for constructing a qualitative and quantitative low-utility land identification evaluation index system for different types of land, adopting an expert weighting method to definitely weight each evaluation index, carrying out grading assignment, carrying out index scoring according to the low-efficiency degree of each land, calculating the comprehensive score of each land in a weighted summation mode, and judging whether each type of town land is a town low-utility land or not based on the comprehensive score to obtain a preliminary low-utility land identification result; The system comprises an intra-field data correction module, a multi-source data generation module, a multi-dimensional space registration and comparison analysis module, a man-machine cooperation analysis module and a multi-source data generation module, wherein the multi-body multi-type collaborative field verification is carried out on the primary identification result by adopting a multi-element means; the data dynamic updating module is used for standardizing the final affirmed result of the town with low utility after the correction of the inside-outside industry data into a library, constructing a data dynamic updating mechanism, starting an updating flow when the updating condition is reached by taking the natural year as a basic updating period, and repeatedly calling the basic data processing module, the inside industry data identification module, the inside-outside industry data correction module and the data dynamic updating module for the acquired latest multi-source data, and carrying out iterative updating on the final affirmed result set of the existing town with low utility according to the latest identification result.

Description

Urban low-utility land identification and analysis method and system based on multivariate data Technical Field The invention relates to the technical field of urban land planning, in particular to a method and a system for identifying and analyzing urban low-utility land based on multivariate data. Background The urban low-utility land redevelopment is an important grip for utilizing the stock land by disc activity, improving the land utilization efficiency and promoting the urban and rural high-quality development. The urban low utility land identification is a premise of comprehensively finding low utility land numbers and efficiently comprehensively utilizing land resources, the existing urban low utility land identification technology is mainly developed around two types of technology paths, namely an efficiency evaluation model based on macroscopic statistical data is adopted in the method, a data envelopment analysis method (DEA) or an improved SBM-Undesirable model is generally adopted, macroscopic administrative areas such as provinces, cities and counties are used as research units, fixed asset investment, the number of practitioners and construction land scale are used as input elements, the production value and financial income of the two industries are used as output elements, land utilization efficiency is estimated through measuring and calculating input-output ratios, and the other method is based on a hierarchical analysis method of the land scale, wherein the method is used for determining each index weight through constructing a system comprising indexes such as volume rate, building density, land average tax, regional position condition and the like on a relative microscopic scale, land utilization efficiency score is calculated through the hierarchical analysis method, and then a 'low efficiency' threshold is defined by referring to national or local standards. However, the traditional low-utility identification method has the problems of single data source, insufficient economic and social attribute capture, macroscopic evaluation scale, weak refined identification capability, one-sided evaluation index, strong subjectivity, stiff standard, static technical method, lack of dynamic adaptation and intelligent decision making capability, low application efficiency, difficulty in supporting large-scale management practice and the like. It is needed to construct a set of intelligent recognition and analysis method for integrating multi-source data, breaking through the bottleneck of the traditional method, and meeting the actual demands of precise recognition and scientific research and judgment on low-utility land in the scenes of national space planning, city updating and the like. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide a method and a system for identifying and analyzing urban low-utility land based on multi-metadata, which improve the accuracy, scientificity and practicability of identifying the low-utility land. The aim of the invention is realized by the following technical scheme: In a first aspect, the present invention provides a method for identifying and analyzing town low-utility based on metadata, comprising: Step 1, acquiring and preprocessing basic land data, extracting a target type land from the preprocessed basic land data, collecting multi-source socioeconomic data, performing attribute association and space linking with the extracted target type land, and constructing a land-attribute integrated database; Step 2, constructing a qualitative and quantitative low-utility land identification evaluation index system for different types of land, adopting an expert weighting method to definitely weight each evaluation index, carrying out grading assignment, carrying out index scoring according to the low-efficiency degree of each land, calculating the comprehensive score of each land in a weighted summation mode, and judging whether each type of town land is a town low-utility land or not based on the comprehensive score to obtain a preliminary low-utility land identification result; Integrating the multisource data to form a correction data set, performing multidimensional space registration and comparison analysis on the correction data set and the low-utility land preliminary identification result, and performing man-machine cooperation to realize fine screening and boundary correction on land parcels to generate a final recognition result layer of the town low-utility land; And 4, standardizing final result of urban low-utility land after the correction of the inside-outside industry data into a library, constructing a data dynamic update mechanism, starting an update flow when the update condition is met by taking the natural year as a basic update period, and repeatedly executing the steps 1 to 4 on the acquired latest multi-source data, and iteratively updating the final result set of urban low-utility land accordin