A method and system for evaluating land use intensity based on highway construction projects

Abstract

The application discloses a kind of based on highway construction project's saving and intensive land evaluation method and system, method includes: obtaining the remote sensing image of the region corresponding to highway construction project, and extracting land information;With approval vector range and zoning standard, land information is interpreted to obtain functional zoning;According to the land use standard, the land control range of different functional zoning is calculated;Four-dimensional evaluation model is constructed to land increment, land stock, land structure and land potential, and based on four-dimensional evaluation model, respectively calculates each evaluation index;Based on evaluation index, above four quartiles and lower four quartiles are used as standard respectively, and the saving and intensive land of highway construction project is evaluated.Through the technical scheme of the application, the effect and potential of the saving and intensive land of the project can be objectively measured, quantitatively described and efficiently monitored, forming a land space saving and intensive use evaluation system, which realizes the precise description and monitoring of the intensive use of global land.

Description

Technical Field

[0001] This invention relates to the field of spatial planning technology, and in particular to a method and system for evaluating the economical and intensive use of land in highway construction projects. Background Technology

[0002] Currently, my country's research on the economical and intensive use of land space mainly focuses on extending the vertical dimension, improving space utilization, and reducing the actual land occupation of projects. In particular, the indicator constraints of major construction projects can assess the economical and intensive use of land space in a region from a regional perspective.

[0003] However, during project construction, there is a lack of assessment and monitoring of land-saving and intensive use for specific types of construction projects, making it difficult to effectively assess the land use of the project's construction content during the project construction phase.

[0004] Traditional methods rely primarily on field reconnaissance, topographic map analysis, and ground monitoring data, requiring significant time, manpower, and resources. In the process of functional zoning, the focus is often solely on the transportation function of highways, neglecting a comprehensive assessment of the ecological environment, land resource utilization, and socio-economic development. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a method and system for evaluating the economical and intensive use of land in highway construction projects. By dividing highway construction projects into functional zones and constructing a four-dimensional evaluation model to assess the economical and intensive use of land in these projects, the method objectively measures, quantitatively characterizes, and efficiently monitors the effectiveness and potential of land conservation and intensive use based on different functional zones. This forms a comprehensive and finely categorized evaluation system for the economical and intensive use of national land space, enabling precise characterization and monitoring of intensive land use across the entire region and providing a scientific basis for evaluating national land space utilization.

[0006] To achieve the above objectives, this invention provides a method for evaluating the economical and intensive use of land in highway construction projects, comprising:

[0007] Acquire remote sensing images of the area corresponding to the preset highway construction project, and extract the land use information of the highway construction project from the remote sensing images;

[0008] By combining the approved vector range and zoning standards, the land use information is interpreted to obtain the functional zoning of the highway construction project;

[0009] The land use control range for different functional zones of the highway construction project is calculated based on the project land use standards.

[0010] A four-dimensional assessment model is constructed to evaluate land use increment, land use stock, land use structure, and land use potential, and each evaluation index is calculated based on the four-dimensional assessment model.

[0011] Based on the evaluation index, the land-saving and intensive use of the highway construction project is assessed using the upper quartile and lower quartile as standards.

[0012] In the above technical solution, preferably, the land use information of the highway construction project is extracted from the remote sensing image, and the specific process includes:

[0013] By utilizing diverse remote sensing images, real-scene 3D images, real estate registration information, and socio-economic information, combined with big data analysis technology, a model for identifying production and construction activities is constructed.

[0014] Based on the aforementioned production and construction activity identification model, land use information, including the land area, occupied agricultural land area, and route length of the target project, is obtained from the remote sensing images of the highway construction project.

[0015] In the above technical solution, preferably, the land use information is interpreted to obtain the functional zoning of the highway construction project, and the specific process includes:

[0016] A training dataset was constructed using typical highway project samples with pre-annotated functional partitions and interpreted signs;

[0017] The preset machine learning algorithm is trained using the training dataset.

[0018] The land use information is input into the trained machine learning algorithm to interpret the functional zoning of the highway construction project;

[0019] The functional zones include roadbeds, bridges, tunnels, interchanges, and supporting facilities.

[0020] In the above technical solution, preferably, the process of constructing a four-dimensional evaluation model of land use increment, land use stock, land use structure, and land use potential, and calculating various evaluation indices based on the four-dimensional evaluation model, specifically includes:

[0021] A four-dimensional assessment model is constructed, comprising four dimensions: land use increment, land use stock, land use structure, and land use potential; among which,

[0022] The increase in land use = the difference between actual land use and existing land stock;

[0023] The land stock = (construction land + unused land) / total project land use;

[0024] The proportion of agricultural land is used as the land use structure, and the land use structure = agricultural land area / total project land area;

[0025] The land use potential is calculated using the savings rate as the land use potential, where the land use potential = actual land use of the construction project / land use index of the construction project = (area of ​​land use control scope - actual land use area) / area of ​​land use control scope * 100%.

[0026] Calculate the evaluation index of the four dimensions in the four-dimensional evaluation model.

[0027] In the above technical solution, preferably, the evaluation of the land-saving and intensive use of the highway construction project based on the evaluation index, using the upper quartile and lower quartile as standards respectively, specifically includes the following process:

[0028] Based on the calculated evaluation indexes of the four dimensions, the upper quartile and lower quartile are used as standards to assess the land-saving and intensive use of the highway construction project.

[0029] Inefficient land use projects were identified by screening out projects with land use increments greater than the upper quartile, land stock less than the lower quartile, agricultural land ratio greater than the upper quartile, and savings rate less than the lower quartile.

[0030] This invention also proposes a land-saving and intensive land-use assessment system for highway construction projects, applying the land-saving and intensive land-use assessment method for highway construction projects disclosed in any of the above technical solutions, including:

[0031] The image information extraction module is used to acquire remote sensing images of the area corresponding to the preset highway construction project, and extract the land use information of the highway construction project from the remote sensing images.

[0032] The functional zoning interpretation module is used to interpret the land use information by combining the approval vector range and zoning standards to obtain the functional zoning of the highway construction project;

[0033] The project scope calculation module is used to calculate the land control scope of different functional zones of the highway construction project based on the project land use standards.

[0034] The four-dimensional assessment calculation module is used to construct a four-dimensional assessment model of land use increment, land use stock, land use structure and land use potential, and to calculate various evaluation indices based on the four-dimensional assessment model.

[0035] The project land use assessment module is used to assess the land-saving and intensive use of the highway construction project based on the evaluation index, using the upper quartile and lower quartile as standards respectively.

[0036] In the above technical solution, preferably, the image information extraction module is specifically used for:

[0037] By utilizing diverse remote sensing images, real-scene 3D images, real estate registration information, and socio-economic information, combined with big data analysis technology, a model for identifying production and construction activities is constructed.

[0038] Based on the aforementioned production and construction activity identification model, land use information, including the land area, occupied agricultural land area, and route length of the target project, is obtained from the remote sensing images of the highway construction project.

[0039] In the above technical solution, preferably, the functional partition interpretation module is specifically used for:

[0040] A training dataset was constructed using typical highway project samples with pre-annotated functional partitions and interpreted signs;

[0041] The preset machine learning algorithm is trained using the training dataset.

[0042] The land use information is input into the trained machine learning algorithm to interpret the functional zoning of the highway construction project;

[0043] The functional zones include roadbeds, bridges, tunnels, interchanges, and supporting facilities.

[0044] In the above technical solution, preferably, the four-dimensional evaluation calculation module is specifically used for:

[0045] A four-dimensional assessment model is constructed, comprising four dimensions: land use increment, land use stock, land use structure, and land use potential; among which,

[0046] The increase in land use = the difference between actual land use and existing land stock;

[0047] The land stock = (construction land + unused land) / total project land use;

[0048] The proportion of agricultural land is used as the land use structure, and the land use structure = agricultural land area / total project land area;

[0049] The land use potential is calculated using the savings rate as the land use potential, where the land use potential = actual land use of the construction project / land use index of the construction project = (area of ​​land use control scope - actual land use area) / area of ​​land use control scope * 100%.

[0050] Calculate the evaluation index of the four dimensions in the four-dimensional evaluation model.

[0051] In the above technical solution, preferably, the project land assessment module is specifically used for:

[0052] Based on the calculated evaluation indexes of the four dimensions, the upper quartile and lower quartile are used as standards to assess the land-saving and intensive use of the highway construction project.

[0053] Inefficient land use projects were identified by screening out projects with land use increments greater than the upper quartile, land stock less than the lower quartile, agricultural land ratio greater than the upper quartile, and savings rate less than the lower quartile.

[0054] Compared with existing technologies, the beneficial effects of this invention are as follows: by dividing highway construction projects into functional zones and constructing a four-dimensional evaluation model to evaluate the land-saving and intensive use of highway construction projects, the effects and potential of land-saving and intensive use of projects are objectively measured, quantitatively characterized, and efficiently monitored based on different functional zones. This forms a comprehensive and finely categorized evaluation system for the economical and intensive use of national land space, achieving accurate characterization and monitoring of intensive land use across the entire region, and providing a scientific basis for evaluating national land space utilization. Attached Figure Description

[0055] Figure 1 This is a flowchart illustrating an embodiment of the land-saving and intensive use assessment method for highway construction projects disclosed in this invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] The present invention will now be described in further detail with reference to the accompanying drawings:

[0058] like Figure 1 As shown, a method for evaluating the economical and intensive use of land in highway construction projects according to the present invention includes:

[0059] Acquire remote sensing images of the area corresponding to the preset highway construction project, and extract the land use information of the highway construction project from the remote sensing images;

[0060] By combining the approved vector range and zoning standards, the land use information is interpreted to obtain the functional zoning of the highway construction project;

[0061] The land use control range for different functional zones of the highway construction project is calculated based on the project land use standards.

[0062] A four-dimensional assessment model is constructed to evaluate land use increment, land use stock, land use structure, and land use potential, and each evaluation index is calculated based on the four-dimensional assessment model.

[0063] Based on the evaluation index, the land-saving and intensive use of highway construction projects is assessed using the upper quartile and lower quartile as standards.

[0064] In this implementation, by dividing highway construction projects into functional zones and constructing a four-dimensional evaluation model to assess the land-saving and intensive use of highway construction projects, the effectiveness and potential of land-saving and intensive use of projects are objectively measured, quantitatively characterized, and efficiently monitored based on different functional zones. This forms a comprehensive and finely categorized evaluation system for the economical and intensive use of national land space, enabling precise characterization and monitoring of intensive land use across the entire region and providing a scientific basis for evaluating national land space utilization.

[0065] Specifically, by constructing a method for dividing highway projects into functional zones, different functional zones are defined according to the construction form and land use pattern of different highway construction projects, thereby assessing the economical and intensive use of land in each functional zone. By constructing an evaluation index system, the objective measurement challenge of accurately assessing its effects and potential is addressed, enabling precise characterization and monitoring of intensive land use across the entire region, and resolving the lack of quantitative characterization and efficient monitoring technologies for the effects of economical and intensive land use across the entire region.

[0066] To achieve the goals of intensive use of land space and value enhancement in highway construction projects, this invention proposes a theoretical algorithm for the economical and intensive use of land in highway construction projects. It proposes a four-dimensional evaluation index system encompassing land increment, stock, structure, and potential. This system enables the assessment of newly added construction land, ensuring the rational use of land for leading industries and major projects; the assessment of existing construction land, effectively monitoring the vitality of existing land; the assessment of structural adjustments, depicting the effects of changes in industrial land supply methods; and the assessment of potential tapping, identifying the potential of "technology for space" and the effectiveness of utilizing underground space. This theoretically proposed "four-dimensional evaluation model" for economical and intensive use provides direction for specific monitoring, evaluation, and data product development.

[0067] During implementation, a four-dimensional evaluation model is proposed, which can comprehensively measure the incremental, existing, structural, and potential land use of construction projects, forming a comprehensive and finely categorized evaluation system for the economical and intensive use of national land space. Intelligent monitoring technology for the economical and intensive use of national land space is established, which can quickly realize intelligent monitoring of land use for construction projects, idle land, and inefficient land use, and achieve quantitative monitoring of the scale, intensity, benefits, and structure of national land space use, thereby improving the efficient measurement of the economical and intensive use effects of human and natural factors.

[0068] This involves deeply integrating territorial spatial planning theory with advanced technologies such as Geographic Information Systems (GIS), spatiotemporal big data, and artificial intelligence algorithms to create an independent and controllable intelligent monitoring, analysis, and evaluation toolkit for territorial spatial conservation and intensive use. Under the premise of ensuring data security, it provides more reliable and high-performance big data processing, management, analysis, and visualization capabilities, enabling efficient monitoring, rapid analysis, high-precision simulation, and prediction of urban spatial structure and characteristics, and facilitating the rapid implementation of urban spatial governance capabilities, spatial pattern optimization, construction, and services.

[0069] In the above embodiments, preferably, the land use information of the highway construction project is extracted from remote sensing images, and the specific process includes:

[0070] By utilizing diverse remote sensing images, real-scene 3D images, real estate registration information, and socio-economic information, combined with artificial intelligence and big data analysis technology, an intelligent monitoring technology for economical and intensive use is established. This technology constructs a model for identifying production and construction activities, improves the efficiency of extracting production and construction activity plots, and enables the monitoring of economic savings rates in highway construction projects, intelligent identification of agricultural facility land, retrospective monitoring of idle land, and identification of inefficient land use.

[0071] Based on the production and construction activity identification model, land use information such as the land area, the area of ​​agricultural land occupied, and the route length of the target project are obtained from remote sensing images of highway construction projects.

[0072] During implementation, basic information such as the functional zoning and area of ​​the target project can be entered into the database, and sample data of the construction project can be entered into the database to form a sample database of different functional zoning for different types of projects.

[0073] In the above implementation method, preferably, the land use information is interpreted to obtain the functional zoning of the highway construction project. The specific process includes:

[0074] A training dataset was constructed using typical highway project samples with pre-annotated functional partitions and interpreted signs;

[0075] The preset machine learning algorithm is trained using a training dataset;

[0076] The land use information is input into the trained machine learning algorithm, which then interprets the functional zoning of the highway construction project.

[0077] The functional zones include roadbeds, bridges, tunnels, interchanges, and supporting facilities.

[0078] During implementation, interpretation markers for the functional zoning of highway construction projects can be pre-established based on different types and characteristics of functional zones. Typical samples can be pre-selected for training to construct a sample dataset and train machine learning algorithms. Land use information of completed construction projects is extracted from high-resolution remote sensing imagery. Combined with approved vector ranges, interpretation is performed through a combination of human experience and machine learning, dividing the target project into functional zones according to prescribed zoning standards. Based on the land use form and functional characteristics of highway projects, and in conjunction with interpretation markers, highway construction projects are divided into functional zones such as roadbed, bridges, tunnels, interchanges, and supporting facilities.

[0079] In the above implementation, preferably, the project land use standards are entered into a database (such as the "Construction Land Use Indicators for Highway Engineering Projects"). The relationship between the project's topographic zone (Class I, II, and III topographic zones), the construction length, width, height, and other factors of different functional zones and the project land use is included in the database, and relevant calculations can be performed in a certain way. For example, the land use index for a six-lane, 34.5-meter-wide highway is 7.8317 hectares / kilometer. From this, the land use control range of different functional zones for different types of projects can be obtained.

[0080] In the above implementation method, preferably, a four-dimensional assessment model is constructed, comprising land use increment, land use stock, land use structure, and land use potential. Based on this four-dimensional assessment model, various evaluation indices are calculated. The specific process includes:

[0081] Construct a four-dimensional assessment model that includes four dimensions: land use increment, land use stock, land use structure, and land use potential;

[0082] Calculate the evaluation index of the four dimensions in the four-dimensional evaluation model;

[0083] Wherein, the increase in land use = the difference between the actual amount of land used and the existing amount of land;

[0084] Land stock = (Construction land + Unused land) / Total project land use;

[0085] The proportion of agricultural land is used as the land use structure. The land use structure = agricultural land area / total project land area, where agricultural land includes arable land and permanent basic farmland.

[0086] The land saving rate is used as the land use potential. Land use potential = actual land use of the construction project / land use index of the construction project = (area of ​​land use control scope - actual land use area) / area of ​​land use control scope * 100%. The land saving rate index can be used to determine the rationality of the construction land index.

[0087] During implementation, the evaluation indicators for economical and intensive land use in highway construction projects can also be adopted as shown in the table below.

[0088]

[0089] During implementation, the calculation methods include:

[0090] (1) The j-index values ​​of each item are obtained by calculating the j-index values;

[0091] (2) Find the maximum value of the j-index for each item in all projects. max and minimum value j min ;

[0092] (3) Normalization operation yields the S values ​​of each component index. ij Value: S ij =(jj min ) / (j max -j min );

[0093] (4) Calculate the savings score for each item:

[0094] In the above implementation method, preferably, the land-saving and intensive use of highway construction projects is evaluated based on the evaluation index, using the upper quartile and lower quartile as standards respectively. The specific process includes:

[0095] Based on the calculated evaluation indexes of four dimensions, the upper quartile and lower quartile are used as standards to assess the land-saving and intensive use of highway construction projects.

[0096] By setting different search methods for different project indicators, inefficient land use projects with land use increment greater than the upper quartile, land use stock less than the lower quartile, agricultural land ratio greater than the upper quartile, and savings rate less than the lower quartile were screened out.

[0097] According to the above-described method for assessing the economical and intensive use of land in highway construction projects, the "artificial intelligence-driven intelligent monitoring technology for economical and intensive use" can significantly improve the efficiency of monitoring the economical rate of construction projects, comprehensive monitoring of existing land, retrospective monitoring of idle land, and intelligent identification of facility agricultural land, so as to ensure the stable operation of the economy and the efficient use of resources, and optimize the business environment.

[0098] The established "Case Study Database for Economical and Intensive Land Use" provides exemplary cases for economical and intensive land use in project construction and urban and rural development projects. It offers a "selection of the best" reference for economical and intensive land use management, including project land use pre-approval, agricultural land conversion approval, and planning permit approval, thus accelerating the implementation of construction projects and effective investments. On the one hand, it enables more scientific and rational planning of land resource utilization, achieving rational allocation of land resources, avoiding unreasonable land development and idleness, improving land development efficiency, and enhancing industrial economic benefits. On the other hand, based on static spatial value identification, it allows for dynamic, phased spatial value assessments, scientifically recognizing urban spatial value gaps and value change trends, thereby guiding subsequent urban development projects in site selection, implementation, and value realization, and providing real-time planning strategies and technical advice.

[0099] Among them, the "Four-Dimensional Evaluation Model for Economical and Intensive Use of Land Space" can establish a bridge between macro-level economical and intensive land use policies and micro-level project land use through innovation. It can provide objective monitoring and evaluation products for planning implementation monitoring, planning adjustment, and comprehensive land consolidation across the region. The relevant monitoring results can assist the government in macro-control of land resources, provide strong support for the balance between work and residence and the integration of industry and city within the area, and improve the quality of life of the people.

[0100] This invention also proposes a land-saving and intensive land-use assessment system for highway construction projects, applying the land-saving and intensive land-use assessment method for highway construction projects disclosed in any of the above embodiments, including:

[0101] The image information extraction module is used to acquire remote sensing images of the area corresponding to the preset highway construction project, and extract the land use information of the highway construction project from the remote sensing images.

[0102] The functional zoning interpretation module is used to interpret land use information by combining the approval vector range and zoning standards to obtain the functional zoning of highway construction projects;

[0103] The project scope calculation module is used to calculate the land control scope of different functional zones of a highway construction project based on the project land use standards.

[0104] The four-dimensional assessment calculation module is used to construct a four-dimensional assessment model of land use increment, land use stock, land use structure and land use potential, and calculate various evaluation indices based on the four-dimensional assessment model.

[0105] The project land use assessment module is used to evaluate the land-saving and intensive use of highway construction projects based on the evaluation index, using the upper quartile and lower quartile as standards respectively.

[0106] In the above embodiments, preferably, the image information extraction module is specifically used for:

[0107] By utilizing diverse remote sensing images, real-scene 3D images, real estate registration information, and socio-economic information, combined with big data analysis technology, a model for identifying production and construction activities is constructed.

[0108] Based on the production and construction activity identification model, land use information such as the land area, the area of ​​agricultural land occupied, and the route length of the target project are obtained from remote sensing images of highway construction projects.

[0109] In the above embodiments, preferably, the functional partition interpretation module is specifically used for:

[0110] A training dataset was constructed using typical highway project samples with pre-annotated functional partitions and interpreted signs;

[0111] The preset machine learning algorithm is trained using a training dataset;

[0112] The land use information is input into the trained machine learning algorithm, which then interprets the functional zoning of the highway construction project.

[0113] The functional zones include roadbeds, bridges, tunnels, interchanges, and supporting facilities.

[0114] In the above embodiments, preferably, the four-dimensional evaluation calculation module is specifically used for:

[0115] A four-dimensional assessment model is constructed, comprising four dimensions: land use increment, land use stock, land use structure, and land use potential; among which,

[0116] Increased land use = Difference between actual land use and existing land stock;

[0117] Land stock = (Construction land + Unused land) / Total project land use;

[0118] The proportion of agricultural land is used as the land use structure, and the land use structure = agricultural land area / total project land area;

[0119] The land use potential is calculated using the savings rate as the land use potential: Land use potential = Actual land use of the construction project / Land use index of the construction project = (Area of ​​land use control scope - Actual land use area) / Area of ​​land use control scope * 100%;

[0120] Calculate the evaluation index for each of the four dimensions in the four-dimensional evaluation model.

[0121] In the above embodiments, preferably, the project land use assessment module is specifically used for:

[0122] Based on the calculated evaluation indexes of four dimensions, the upper quartile and lower quartile are used as standards to assess the land-saving and intensive use of highway construction projects.

[0123] Inefficient land use projects were identified by screening out projects with land use increments greater than the upper quartile, land stock less than the lower quartile, agricultural land ratio greater than the upper quartile, and savings rate less than the lower quartile.

[0124] The land-saving and intensive land-use assessment system for highway construction projects disclosed in the above embodiments has modules whose functions correspond to the steps of the land-saving and intensive land-use assessment method for highway construction projects disclosed in the above embodiments. During implementation, the above embodiments are referred to for operation, and will not be repeated here.

[0125] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the saving and intensive land use based on a highway construction project, characterized in that, The method comprises the following steps: acquiring remote sensing images of a region corresponding to a preset highway construction project, and extracting land use information of the highway construction project from the remote sensing images; interpreting the land use information in combination with an approval vector range and a zoning standard to obtain a functional zoning of the highway construction project; calculating a land use control range of different functional zones of the highway construction project according to a project land use standard; constructing a four-dimensional evaluation model of land use increment, land use stock, land use structure and land use potential, and calculating evaluation indexes of each item based on the four-dimensional evaluation model, the specific process comprising: constructing a four-dimensional evaluation model including four dimensions of land use increment, land use stock, land use structure and land use potential; wherein, the land use increment = a difference between an actual land use amount and the land use stock; the land use stock = (construction land + unused land) / total project land use amount; using a proportion of agricultural land as the land use structure, the land use structure = agricultural land area / total project land use amount; using a saving rate as the land use potential, the land use potential = actual land use of the construction project / land use index of the construction project = (land use control range area - actual land use area) / land use control range area * 100%; calculating evaluation indexes of the four dimensions in the four-dimensional evaluation model; based on the evaluation indexes, evaluating a saving and intensive land use condition of the highway construction project by using the upper four quartiles and the lower four quartiles as standards, respectively.

2. The method for evaluating the saving and intensive land use based on the highway construction project according to claim 1, wherein, extracting the land use information of the highway construction project from the remote sensing images, the specific process comprising: applying multi-element remote sensing images, real scene three-dimensional images, real estate registration information and multi-element social and economic information, and combining big data analysis technology to construct a production and construction activity recognition model; based on the production and construction activity recognition model, acquiring land use information of a target project, including a land use area, an occupied agricultural land area and a route length from the remote sensing images of the highway construction project.

3. The method for evaluating the saving and intensive land use based on the highway construction project according to claim 1, wherein, interpreting the land use information to obtain the functional zoning of the highway construction project, the specific process comprising: constructing a training data set by using a pre-labeled functional zoning and a typical highway project sample of an interpretation sign; training a preset machine learning algorithm by using the training data set; inputting the land use information into the trained machine learning algorithm to interpret the functional zoning of the highway construction project; wherein the functional zoning includes a roadbed, a bridge, a tunnel, an interchanges and supporting facilities.

4. The highway construction project-based saving and intensive land use assessment method according to claim 1, characterized by, based on the evaluation indexes, evaluating a saving and intensive land use condition of the highway construction project by using the upper four quartiles and the lower four quartiles as standards, respectively, the specific process comprising: based on the calculated evaluation indexes of the four dimensions, evaluating a saving and intensive land use condition of the highway construction project by using the upper four quartiles and the lower four quartiles as standards, respectively; screening low-efficiency land use projects with a land use increment greater than the upper four quartiles, a land use stock less than the lower four quartiles, a proportion of agricultural land greater than the upper four quartiles and a saving rate less than the lower four quartiles.

5. A system for evaluating the saving and intensive land use based on a highway construction project, characterized by, application of the saving and intensive land use evaluation method based on a highway construction project according to any one of claims 1 to 4, comprising: An image information extraction module is configured to obtain remote sensing images of a region corresponding to a preset highway construction project, and extract land use information of the highway construction project from the remote sensing images; A functional zoning interpretation module is configured to interpret the land use information in combination with an approval vector range and zoning standards to obtain functional zoning of the highway construction project; A project range calculation module is configured to calculate land use control ranges of different functional zoning of the highway construction project according to project land use standards; A four-dimensional evaluation calculation module is configured to construct a four-dimensional evaluation model of land use increment, land use stock, land use structure and land use potential, and calculate evaluation indexes based on the four-dimensional evaluation model; A project land use evaluation module is configured to evaluate the land use of the highway construction project based on the evaluation indexes, with the upper quartile and the lower quartile as standards. The four-dimensional evaluation calculation module is specifically configured to: construct a four-dimensional evaluation model including four dimensions of land use increment, land use stock, land use structure and land use potential; wherein, the land use increment = the difference between the actual land use amount and the land use stock; the land use stock = (construction land + unused land) / total project land use amount; the land use structure = agricultural land area / total project land use amount, using the proportion of agricultural land as the land use structure; the land use potential = actual land use of the construction project / land use index of the construction project = (land use control range area - actual land use area) / land use control range area * 100%, using the saving rate as the land use potential; calculate evaluation indexes of the four dimensions in the four-dimensional evaluation model.

6. The highway construction project based saving and intensive land use assessment system according to claim 5, wherein, The image information extraction module is specifically configured to: use multi-element remote sensing images, real scene three-dimensional images, real estate registration information and social and economic multi-element information, and combine big data analysis technology to construct a production and construction activity recognition model; based on the production and construction activity recognition model, obtain land use information of the land use area, the occupied agricultural land area and the route length of the target project from the remote sensing images of the highway construction project.

7. The highway construction project based saving and intensive land use assessment system according to claim 5, wherein, The functional zoning interpretation module is specifically configured to: use pre-labeled functional zoning and typical highway project samples with interpretation signs to construct a training data set; train a preset machine learning algorithm using the training data set; input the land use information into the trained machine learning algorithm to interpret the functional zoning of the highway construction project; wherein the functional zoning includes roadbed, bridge, tunnel, interchanges and supporting facilities.

8. The highway construction project based saving and intensive land use assessment system according to claim 5, wherein, The project land use evaluation module is specifically configured to: based on the calculated evaluation indexes of the four dimensions, evaluate the land use of the highway construction project with the upper quartile and the lower quartile as standards; screen to obtain low-efficiency land use projects with land use increment greater than the upper quartile, land use stock less than the lower quartile, agricultural land proportion greater than the upper quartile and saving rate less than the lower quartile.

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