Evaluation methods and related equipment for land consolidation and development based on GIS

Abstract

The invention relates to the technical field of land development, and specifically discloses a land consolidation and development evaluation method based on GIS and related equipment, wherein the land consolidation and development evaluation method based on GIS comprises the following steps: obtaining GIS information of a target area; respectively splitting and reorganizing GIS status data and GIS planning data to obtain a preparation data set and a planning data set; obtaining a total preparation cost according to the preparation data set and unit preparation costs of different land preparation methods, and obtaining a development investment cost and a predicted return curve about time according to the planning data set; comprehensively obtaining the total preparation cost, the development investment cost and the predicted return curve to obtain a profit and loss result of a target year for development evaluation; the method effectively solves the problems of low efficiency, low precision, and incomplete consideration of factors existing in traditional methods, and provides a more reliable and scientific basis for land consolidation and development decision-making.

Description

Technical Field

[0001] The present application relates to the field of land development technology, and in particular to a GIS-based land reclamation and development assessment method and related equipment. Background Art

[0002] With the rapid development of the country's economy and society, the rational use and allocation of land resources has become particularly important. As an effective way of land management, land consolidation and development aims to improve the utilization efficiency of land resources and alleviate the contradiction between land supply and demand through the integration, land clearing and preliminary development of scattered land. In the process of land consolidation and development, it is necessary to measure and evaluate the invested costs, which is of great significance to ensure the smooth progress of land consolidation and development, optimize resource allocation and improve economic benefits.

[0003] However, the current traditional land reclamation and development cost estimation methods are mostly based on manual statistics and calculations, which are inefficient and low in accuracy. There are problems such as unreasonable accounting methods, incomplete cost accounting, unscientific budget plans, inaccurate early cost accounting and long cost accounting cycles.

[0004] There is currently no effective technical solution to the above problems. Summary of the invention

[0005] The purpose of this application is to provide a GIS-based land consolidation and development assessment method and related equipment to improve the efficiency, accuracy, comprehensiveness and scientificity of land consolidation and development assessment.

[0006] In a first aspect, the present application provides a GIS-based land consolidation and development assessment method, the method comprising the following steps:

[0007] S1. Acquire GIS information of the target area, wherein the GIS information includes GIS status data and GIS planning data;

[0008] S2. Split and reorganize the GIS current status data and the GIS planning data respectively to obtain a preparation data set and a planning data set, wherein the preparation data set includes a plurality of local plots related to different land preparation methods;

[0009] S3. Obtain the total preparation cost based on the preparation data set and the unit preparation costs of different land preparation methods, and obtain the development input cost and the predicted return curve with respect to time based on the planning data set;

[0010] S4. Combining the total preparation cost, the development investment cost and the predicted profit curve, obtain the profit and loss result of the target year to conduct development evaluation.

[0011] The GIS-based land consolidation and development evaluation method of the present application utilizes GIS technology to automatically process spatial data, can efficiently process large amounts of complex spatial data, significantly improves data processing efficiency, and ensures the integrity and accuracy of calculations; secondly, the method can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast yield curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low accuracy, and incomplete consideration of factors existing in traditional methods, providing a more reliable and scientific basis for land consolidation and development decisions, and helping to improve the utilization efficiency and economic benefits of land resources.

[0012] The GIS-based land consolidation and development assessment method, wherein the GIS status data includes land ownership data, housing surveying and mapping data, and land use status data;

[0013] The steps to split and reorganize the GIS status data and obtain the prepared data set include:

[0014] Based on the land ownership data, the house surveying data and the land use status data, the land type information, ownership information and area information of each unit plot in the target area are obtained by splitting, wherein the area information includes: land area, building land area, building area and foundation area;

[0015] Allocate a land preparation method for each unit plot according to the land type information and ownership information;

[0016] Unit plots are combined according to the land preparation methods, and a plurality of local plots related to different land preparation methods are obtained to construct the preparation data set.

[0017] The GIS-based land consolidation and development assessment method of the present application effectively converts GIS status data into a consolidation data set containing local plot information of different land preparation methods. This conversion process takes into account the various characteristics of the plots, making the subsequent land consolidation and development assessment more accurate and reasonable, and providing a reliable data basis for the assessment of large-scale land consolidation projects. It more comprehensively considers various factors, such as land type, ownership, area, etc., thereby providing a more scientific and reasonable basis for subsequent consolidation work. The generated consolidation data set has good spatial correlation and visualization characteristics, which is conducive to decision makers to intuitively understand and analyze the consolidation plan.

[0018] In the GIS-based land consolidation and development assessment method, the unit land preparation costs of different land preparation methods in step S3 are determined based on the historical preparation costs of different land types in the surrounding areas of the target area.

[0019] The GIS-based land consolidation and development evaluation method of the present application utilizes the historical preparation cost data of the surrounding areas of the target area to determine the unit preparation costs of different land preparation methods, so as to more accurately reflect the local preparation cost level based on the actual historical data and avoid the errors that may be caused by arbitrary estimates. By considering the cost data of the surrounding areas, it can better adapt to the local economic environment and market conditions, making the cost estimation closer to reality. Therefore, different unit preparation costs determined based on historical preparation costs are used for different land types, which can more finely distinguish the preparation difficulty and cost differences of various land types, better reflect the actual cost level and changing trend of the local area, and improve the accuracy of cost estimation.

[0020] In the GIS-based land consolidation and development assessment method, the process of determining the unit land consolidation cost of different land consolidation methods includes:

[0021] According to the historical preparation costs of different land types in the surrounding areas of the target area, historical preparation information on different land preparation methods in the surrounding areas of the target area within the preset area is obtained;

[0022] Acquire a cost variation curve with respect to time according to the historical maintenance information;

[0023] The unit preparation costs of the different land preparation methods are predicted and obtained according to the expected preparation time and the cost change curve.

[0024] In the GIS-based land consolidation and development assessment method, the step of obtaining GIS planning data includes:

[0025] A planning scheme for the target area is obtained, and the GIS planning data is generated according to a building model corresponding to the planning scheme.

[0026] The GIS-based land consolidation and development assessment method, wherein the planning data set includes an engineering building data set and a revenue building data set;

[0027] The step of obtaining the development input cost and the predicted benefit curve about time according to the planning data set includes:

[0028] Acquire development input costs according to the engineering construction data set;

[0029] A predicted revenue curve for different development years is generated based on the revenue building data set and different building revenue methods.

[0030] The GIS-based land consolidation and development evaluation method, wherein the planning scheme includes a building scheme and a corresponding construction scheme, and the construction scheme includes construction sequence information about different buildings;

[0031] The step of obtaining the development investment cost according to the engineering construction data set comprises:

[0032] Acquire the basic investment costs of different buildings in the target area according to the engineering building dataset;

[0033] Acquire additional financing costs according to a financing model, wherein the financing model is generated by matching the investment and construction sequence information;

[0034] The development investment cost is obtained by combining the basic investment costs of different buildings and the additional financing costs.

[0035] In a second aspect, the present application also provides a GIS-based land consolidation and development assessment device, the device comprising:

[0036] An acquisition module is used to acquire GIS information of a target area, wherein the GIS information includes GIS current status data and GIS planning data;

[0037] A data reorganization module is used to split and reorganize the GIS current status data and the GIS planning data respectively to obtain a preparation data set and a planning data set, wherein the preparation data set includes a plurality of local plots related to different land preparation methods;

[0038] An estimation module is used to obtain the total preparation cost based on the preparation data set and the unit preparation costs of different land preparation methods, and to obtain the development input cost and the predicted return curve over time based on the planning data set;

[0039] An evaluation module is used to comprehensively consider the total preparation cost, the development investment cost and the predicted profit curve to obtain the profit and loss result of the target year for development evaluation.

[0040] The GIS-based land reclamation and development evaluation device of the present application utilizes GIS technology to automatically process spatial data, can efficiently process a large amount of complex spatial data, significantly improves data processing efficiency, and ensures the integrity and accuracy of calculations; secondly, the device can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast yield curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low accuracy, and incomplete consideration of factors existing in traditional methods, providing a more reliable and scientific basis for land reclamation and development decisions, and helping to improve the utilization efficiency and economic benefits of land resources.

[0041] In a third aspect, the present application further provides an electronic device, comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method provided in the first aspect are executed.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the method provided in the first aspect are executed.

[0043] From the above, it can be seen that the present application provides a GIS-based land consolidation and development evaluation method and related equipment, wherein the GIS-based land consolidation and development evaluation method utilizes GIS technology to automatically process spatial data, can efficiently process a large amount of complex spatial data, significantly improves data processing efficiency, and ensures the integrity and accuracy of calculations; secondly, the method can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast yield curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low precision, and incomplete consideration of factors existing in traditional methods, and provides a more reliable and scientific basis for land consolidation and development decisions, which is helpful for improving the utilization efficiency and economic benefits of land resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A flowchart of a GIS-based land consolidation and development assessment method provided in an embodiment of the present application.

[0045] Figure 2 A schematic diagram of the structure of a GIS-based land reclamation and development assessment device provided in an embodiment of the present application.

[0046] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0047] Reference numerals: 201, acquisition module; 202, data reorganization module; 203, estimation module; 204, evaluation module; 301, processor; 302, memory; 303, communication bus. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0049] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0050] First, please refer to Figure 1 Some embodiments of the present application provide a GIS-based land consolidation and development assessment method, the method comprising the following steps:

[0051] S1. Obtain GIS information of the target area, including GIS status data and GIS planning data;

[0052] S2, respectively splitting and reorganizing the GIS current status data and the GIS planning data to obtain a preparation data set and a planning data set, wherein the preparation data set includes multiple local plots related to different land preparation methods;

[0053] S3. Obtain the total preparation cost based on the preparation data set and the unit preparation costs of different land preparation methods, and obtain the development input cost and the predicted return curve with respect to time based on the planning data set;

[0054] S4. Comprehensive preparation total cost, development input cost and predicted profit curve to obtain the profit and loss results of the target years for development evaluation.

[0055] Specifically, GIS (Geographic Information System) is a computer system used to capture, store, check, analyze, manage, present and distribute all types of geographic data. GIS data generally contains spatial data and attribute data, which can be effectively organized, indexed and queried, and can serve as the data basis for subsequent splitting and reorganization for quick access and analysis. It combines multiple disciplines such as computer science, geography, cartography, remote sensing, and surveying, and provides users with functions such as query, analysis, simulation, and decision support for geospatial information by integrating geospatial data. In step S1, the target area is the land that needs to be evaluated for land reclamation and development, and the GIS information obtained includes two types of GIS status data and GIS planning data. Among them, the GIS status data is the current GIS data of the target area, which is geographic data actually collected through various means (such as satellite remote sensing images, drone aerial photography, field measurements, etc., or obtained from urban planning departments), edited and sorted, and can reflect the current status of the land, such as land ownership, topography, building distribution, etc.; GIS planning data is the GIS data of the target area after planning, which belongs to the GIS data of the planning model generated after simulated construction according to the planning scheme, and can be obtained by measuring the planning model.

[0056] More specifically, the splitting and reorganization of GIS status data is equivalent to data reorganization based on the land preparation method, wherein the splitting process can be to split the GIS status data into unit plots of a specific size to obtain the spatial data and attribute data of each unit plot, and then reorganize the unit plots based on the land preparation method applicable to each unit plot to obtain multiple local plots. All unit plots in each local plot adopt the same land preparation method to facilitate the subsequent calculation of the total preparation cost; it should be noted that the preparation data set is the reorganized GIS status data, and the local plots therein still have the corresponding spatial data and attribute data; the preparation data set is mainly used to calculate and analyze the cost required for the preparation target area, so it can be obtained by data reorganization based on the land preparation method.

[0057] More specifically, for the splitting and reorganization of GIS planning data, the planning data set is mainly used to calculate and analyze the development investment costs required to build the target area based on the prepared land to the development state corresponding to the planning model, as well as to predict the benefits generated after development. It does not need to consider changes in land ownership, but only needs to consider factors such as the number of buildings, building distribution, building scale and building function in the target area to obtain data reorganization.

[0058] More specifically, the preparation data set and the planning data set can be expressed in the form of tabular data or chart data or spatial maps. In the embodiment of the present application, since GIS data is surface data, the preparation data set and the planning data set are preferably organized in the form of spatial maps, that is, step S2 generates a current spatial map and a planning spatial map to represent the preparation data set and the planning data set, respectively. Both can display the differences in GIS data distribution by dividing the plots in the map. For example, the current spatial map displays multiple local plots of different sizes occupying different areas. These local plots are divided based on the land preparation method and are still accompanied by corresponding spatial data and attribute data. This processing method can intuitively and accurately reflect the distribution characteristics of GIS data, which is convenient for users to make corrections.

[0059] More specifically, land preparation refers to a new land management model that integrates scattered land, conducts land clearance and pre-development. Land preparation methods generally include reclaiming land use rights, house expropriation and demolition, land acquisition, handling of historical issues left over from land expropriation and transfer, and land reclamation. Different preparation methods have different processing costs. Therefore, step S3 needs to combine the spatial data (such as building area) and attribute data (land nature) of the local plots in the preparation data set with the unit preparation cost corresponding to the land preparation method to calculate the preparation cost of each local plot, and then calculate the total preparation cost of the entire target area based on these preparation costs. For example, the unit preparation cost of converting agricultural land to construction land may be 500 yuan / square meter, while the unit preparation cost of old city renovation may be 2,000 yuan / square meter. These unit maintenance costs are combined with the area information in the maintenance data set to calculate the total maintenance cost; the unit maintenance cost can be a calculation base input by the user, or a calculation base automatically generated by the system collecting surrounding historical data. The former can estimate the total maintenance cost based on the user's considerations, and the latter can estimate the total maintenance cost based on the actual field of view environment.

[0060] It should be noted that the total preparation cost is the preparation cost of calculating the target area from the current status to a state without buildings.

[0061] More specifically, the development input cost is the capital investment cost required to build the target area after preparation to the expected state of the planning scheme. The planning data set clarifies the construction status of the planning scheme, so cost calculation and prediction can be performed based on general construction engineering estimation models to obtain the development input cost, such as estimating the construction cost of residential land based on building density and floor area ratio, or considering infrastructure investment in commercial land.

[0062] More specifically, the predicted revenue curve is actually a revenue forecast for buildings with revenue functions in the planning scheme, such as commercial buildings, paid sports venues, shops, etc. These buildings will generate time-related revenue, such as the sales rate and selling price of commercial buildings over time, the rental revenue and rental changes of commodities over time, etc. For buildings with different revenue functions, different revenue models can be used to simulate the corresponding data such as the number of buildings and area size to obtain corresponding independent revenue curves. By superimposing these independent revenue curves, a predicted revenue curve that can comprehensively reflect the overall revenue changes of the target area over time can be obtained; among them, buildings with different revenue functions can be extracted and distinguished through the planning data set.

[0063] It should be noted that the independent revenue curve should be predicted and obtained in conjunction with the planning scheme to determine the time when the corresponding building with revenue function starts to generate revenue.

[0064] More specifically, after determining the cost and benefit related data, step S4 can combine these data to obtain the profit and loss data of the target area with respect to time changes, so that the user can set the target year to obtain the profit and loss result of the target area at the corresponding development time, wherein the profit and loss result can be a monetary profit and loss value, profit and loss rate, profit and loss rate range, etc., which is convenient for users to view the profit and loss situation under different target years and evaluate the planning scheme of the target area.

[0065] It should be noted that the profit and loss results can also be estimated to reflect the time to break even in the target area or the time to reach a specific rate of return on investment, etc.

[0066] More specifically, the GIS-based land reclamation and development evaluation method of the embodiment of the present application can be used to conduct development evaluation on different planning schemes for a target area, so as to provide users with profit and loss results of different planning schemes, thereby facilitating users to evaluate and make decisions on planning schemes. It can also be used to conduct development evaluation on the same or similar planning schemes for different target areas, so as to provide users with profit and loss results of different target areas, thereby facilitating users to evaluate and make decisions on target areas.

[0067] Traditional land consolidation and development assessment methods usually rely on empirical estimates and simple spreadsheet calculations, which are difficult to handle complex spatial information and prone to omissions or repeated calculations. The GIS-based land consolidation and development assessment method of the embodiment of the present application uses GIS technology to automatically process spatial data, which can efficiently process a large amount of complex spatial data, significantly improve data processing efficiency, and ensure the integrity and accuracy of calculations; secondly, the method can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast yield curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low precision, and incomplete consideration of factors existing in traditional methods, providing a more reliable and scientific basis for land consolidation and development decisions, and helping to improve the utilization efficiency and economic benefits of land resources.

[0068] In some preferred implementations, the GIS status data includes land ownership data, house surveying and mapping data, and land use status data;

[0069] The steps to split and reorganize the GIS status data and obtain the prepared data set include:

[0070] Based on the land ownership data, house surveying and mapping data and land use status data, the land type information, ownership information and area information of each unit plot in the target area are obtained. The area information includes: land area, building land area, building area and foundation area;

[0071] Configure land preparation methods for each unit plot based on land type information and ownership information;

[0072] Unit plots are combined according to the land preparation methods, and multiple local plots related to different land preparation methods are obtained to construct a preparation dataset.

[0073] Specifically, land ownership data, housing surveying and mapping data, and land use status data are all surface data in GIS format. Among them, land ownership data include information such as land owner, ownership type, ownership area, ownership certificate number, etc. Housing surveying and mapping data include information such as building area, construction area, land area, floor area ratio, number of floors, floor height, etc. Land use status data include control detailed planning, control lines (blue line, green line, yellow line, purple line and other urban control lines) and other data.

[0074] More specifically, the GIS-based land consolidation and development assessment method of the embodiment of the present application obtains a preparation data set by splitting and reorganizing the GIS status data. The specific steps are as follows: First, use land ownership data, house mapping data, and land use status data to obtain detailed information on each unit plot in the target area, including land type, ownership, and area. This step provides basic data for the subsequent configuration of land preparation methods. Then, according to the acquired land type information and ownership information, an appropriate land preparation method is configured for each unit plot. This step takes into account the characteristics of the plot and ensures the rationality of the preparation method. Finally, according to the configured land preparation method, the unit plots are combined into multiple local plots to form a preparation data set. This step integrates plots with similar preparation methods to facilitate subsequent preparation work and cost evaluation.

[0075] More specifically, the unit plot is the smallest area division unit for dividing the target area or a unit for division based on building forms.

[0076] More specifically, when splitting and obtaining relevant information of unit plots, spatial analysis techniques, such as overlay analysis, buffer zone analysis, etc., can be used to ensure the accuracy and completeness of the information.

[0077] More specifically, the acquisition of land type information can be verified based on the current land use data combined with the results of remote sensing image interpretation. The acquisition of ownership information mainly relies on land ownership data, and field surveys may be required to update and verify the accuracy of the data. The calculation of area information can be corrected by using the area calculation function of GIS software combined with field measurement data.

[0078] More specifically, the process of configuring land preparation methods for unit plots can be adaptively matched based on a pre-constructed pairing table of land type information, ownership information, and land preparation methods, or a decision matrix can be established to comprehensively consider factors such as land type, ownership, and area. For example, for plots with a high proportion of building land area, it may be tempting to choose a preparation method of demolition and reconstruction, while for green spaces or agricultural land, it may be more appropriate to adopt a preparation method of land leveling or ecological restoration.

[0079] More specifically, when combining unit plots to form local plots, a cluster analysis algorithm can be used to group adjacent plots with similar preparation methods. In this process, a maximum local plot area, such as 1 hectare, can be set to ensure that each local plot is of moderate size for easy management and implementation.

[0080] It should be noted that the preparation data set obtained after reorganization can still include the area information corresponding to the unit plots corresponding to the local plots, and can also include comprehensive area information about different local plots generated based on the comprehensive area information corresponding to these unit plots, so as to facilitate the subsequent steps to quickly calculate and obtain the total preparation cost, wherein the data type contained in the comprehensive area information corresponds to the data type contained in the area information.

[0081] More specifically, there are certain differences in the cost calculation objects of different land preparation methods. Therefore, the area information obtained by the GIS-based land consolidation and development evaluation method in the embodiment of the present application includes at least land area, building land area, building area and foundation area, which can be used as the basis for subsequent calculation of the preparation costs of different land preparation methods to ensure accurate calculation of the total preparation cost.

[0082] More specifically, in a further embodiment, the area information also includes the number of building floors and the average floor area ratio to assist in adjusting the unit preparation cost and improve the calculation accuracy of the total preparation cost.

[0083] More specifically, the GIS-based land consolidation and development assessment method of the embodiment of the present application effectively converts GIS status data into a preparation data set containing local plot information of different land preparation methods. This conversion process takes into account the various characteristics of the plots, making the subsequent land consolidation and development assessment more accurate and reasonable, and providing a reliable data basis for the assessment of large-scale land consolidation projects. It more comprehensively considers various factors, such as land type, ownership, area, etc., thereby providing a more scientific and reasonable basis for subsequent preparation work. The generated preparation data set has good spatial correlation and visualization characteristics, which is conducive to decision makers to intuitively understand and analyze the preparation plan.

[0084] In some preferred embodiments, the method further comprises the following steps performed between step S1 and step S2:

[0085] SA, corrects GIS status data based on topological relationships, geometric relationships and spatial consistency.

[0086] Specifically, the GIS-based land consolidation and development assessment method of the embodiment of the present application improves data quality by adding a data correction step between obtaining GIS information and splitting and reorganizing data, and corrects GIS status data based on topological relationships, geometric relationships, and spatial consistency, thereby correcting possible errors or inconsistencies in the data and ensuring that the data used in subsequent analysis is more accurate and reliable; among them, the correction of topological relationships ensures the correct logical relationship between spatial elements and reduces errors in subsequent analysis; the correction of geometric relationships corrects the shape and position errors of spatial elements and improves the accuracy of spatial analysis; the correction of spatial consistency ensures the coordination and consistency between different data layers and provides a reliable basis for the comprehensive analysis of multi-layer data.

[0087] More specifically, during the implementation process, corrections based on topological relationships can include multiple methods. For example, boundary overlaps or gaps between adjacent plots can be checked and corrected to ensure that the connection relationship between the plots is correct. Another way is to verify the connectivity of the road network and correct possible broken or hanging nodes. Corrections based on geometric relationships can include correcting the distortion of the shape of the plot, such as eliminating sharp corners or slender protrusions to make the shape of the plot more regular. The location of the building can also be corrected to match the actual geographical location. Spatial consistency corrections can include unifying the coordinate systems of different data layers to ensure the spatial superposition accuracy of each layer of data.

[0088] More specifically, these correction steps are closely related to the aforementioned GIS information acquisition and data splitting and reorganization steps. By making corrections in the early stages of data processing, the propagation and amplification of erroneous data in subsequent analysis can be effectively avoided. At the same time, the corrected building location data can be better matched with the planning scheme, thereby improving the reliability of development evaluation.

[0089] The GIS-based land consolidation and development assessment method of the embodiment of the present application effectively solves the quality problems that may exist in the original GIS data by adding a correction step for the GIS status data, thereby significantly improving the accuracy and reliability of the entire assessment process.

[0090] In some preferred embodiments, the unit preparation costs of different land preparation methods in step S3 are determined based on the historical preparation costs of different land types in the surrounding areas of the target area.

[0091] Specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application utilizes the historical preparation cost data of the surrounding areas of the target area to determine the unit preparation costs of different land preparation methods, so as to more accurately reflect the local preparation cost level based on the actual historical data, and avoid the errors that may be caused by estimates out of thin air. By considering the cost data of the surrounding areas, it can better adapt to the local economic environment and market conditions, making the cost estimation closer to reality. Therefore, different unit preparation costs determined based on historical preparation costs are used for different land types, which can more finely distinguish the preparation difficulty and cost differences of various land types, can better reflect the actual cost level and changing trend of the local area, and improve the accuracy of cost estimation.

[0092] In some preferred embodiments, the process of determining the unit land preparation cost of different land preparation methods includes:

[0093] According to the historical preparation costs of different land types in the surrounding areas of the target area, historical preparation information on different land preparation methods in the surrounding areas of the target area within the preset area is obtained;

[0094] Obtain the cost change curve over time based on historical maintenance information;

[0095] The unit preparation cost of different land preparation methods is predicted based on the expected preparation time and cost change curve.

[0096] Specifically, the historical maintenance information may be a historical average unit maintenance cost or include the scale of the maintenance object and the corresponding historical maintenance cost.

[0097] More specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application obtains historical consolidation information of the surrounding areas of the target area, establishes a cost change curve, and predicts the unit consolidation cost of different land consolidation methods in combination with the expected consolidation time. This method takes into account the time factor and regional characteristics and can more accurately reflect the actual situation.

[0098] More specifically, the historical preparation costs of different land types in the surrounding areas of the target area can be obtained through various channels, such as government public data, historical records of land management departments, or professional databases. The historical preparation information should include cost data of different land preparation methods, such as demolition compensation costs, land leveling costs, infrastructure construction costs, etc. The preset area range can be flexibly set according to actual conditions, for example, it can be within 5 kilometers around the target area, or similar plots in the same administrative area.

[0099] In practical applications, this application can achieve the determination of unit preparation costs of different land preparation methods through the following methods:

[0100] First, a preset area can be set, such as a circular area with a radius of 10 kilometers centered on the target area. Within this area, the cost data of all completed land preparation projects in the past 3-5 years are collected. This data can be obtained from local land management departments, developers or related institutions.

[0101] Secondly, the collected historical land preparation cost data is classified according to different land preparation methods. Common land preparation methods may include: demolition and resettlement, land leveling, infrastructure construction, etc. For each preparation method, it can also be subdivided according to land type (such as residential land, commercial land, industrial land, etc.).

[0102] Then, the historical preparation cost data of each preparation method is statistically analyzed. The historical average unit preparation cost of each preparation method in different periods and different land types can be calculated, and then the cost change curve about time change can be constructed for different land preparation methods based on these historical average unit preparation costs; among them, the cost change curve can be fitted by a variety of mathematical models, such as linear regression model, polynomial regression model or exponential smoothing model. Selecting a suitable model requires considering the characteristics and change trends of historical data. For example, if the historical data shows an obvious linear growth trend, a linear regression model can be used; if there are cyclical fluctuations, a time series analysis method can be considered.

[0103] Finally, combined with the expected maintenance time, this cost change curve is used to predict the future unit maintenance cost. The expected maintenance time can be determined based on project planning and actual conditions. By substituting the expected maintenance time into the cost change curve, the corresponding predicted cost value can be obtained as the unit maintenance cost; in addition, the process of obtaining the predicted cost value adopts statistical methods such as weighted average method and trend extrapolation method, and an expert evaluation mechanism can also be introduced to give the final unit maintenance cost after comprehensively considering various factors.

[0104] It should be noted that there are certain differences in the preparation time of local plots under different land preparation methods. Therefore, the above steps can also configure different expected preparation times according to different land preparation methods to predict the corresponding unit preparation costs, so as to more accurately estimate the total preparation cost.

[0105] More specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application can dynamically consider the impact of time factors on costs to predict unit preparation costs to achieve estimation of total preparation costs, making cost predictions closer to actual conditions, and making predictions separately for different land preparation methods, which can more finely and accurately reflect the cost differences of various preparation methods. In addition, the prediction process also takes into account regional characteristics. By analyzing historical data of surrounding areas, the prediction results are closer to actual conditions, which can help decision makers better evaluate the feasibility and economic benefits of projects, reduce investment risks, and optimize resource allocation.

[0106] In some preferred embodiments, the method further comprises the following steps performed between step S3 and step S4:

[0107] SB, adjust the total cost of preparation and / or predict the benefit curve based on policy planning information compensation.

[0108] Specifically, the main function of this step is to make compensatory adjustments to the total preparation cost and / or predicted benefit curve based on policy planning information, thereby taking into account policy factors that may affect land consolidation and development, improving the accuracy of the evaluation results, and enhancing the applicability and flexibility of the method, such as electricity subsidies, interest-free loans and other policies, to improve the accuracy of the total preparation cost and predicted benefit curve.

[0109] More specifically, in practical applications, the compensation and adjustment of policy planning information can be achieved in a variety of ways. For example, the weighted coefficient method can be used to assign different weights to the various components of the total preparation cost and the predicted benefit curve according to the importance and impact of different policies. Another method is to use the correction coefficient to directly correct the total preparation cost and the predicted benefit curve according to the degree of impact of the policy on various costs and benefits; in addition, a policy impact model can be established to analyze historical data and policy implementation effects, and to construct a relationship model between policy and cost and benefit, so as to more accurately predict the impact of policy changes on the total preparation cost and the predicted benefit curve. These methods can be flexibly selected and combined according to specific circumstances to achieve the best compensation and adjustment effect.

[0110] More specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application introduces step SB, which can more comprehensively consider the various factors affecting land consolidation and development, including not only GIS data and economic factors, but also policy factors. This comprehensive consideration makes the evaluation results closer to the actual situation and provides a more reliable basis for land consolidation and development decisions.

[0111] In specific implementation, the following steps can be used to compensate and adjust policy planning information:

[0112] 1. Collect and analyze relevant policy and planning information, including but not limited to land use policies, urban planning policies, environmental protection policies, etc.

[0113] 2. Evaluate the potential impact of these policies on the total cost of maintenance and the predicted benefit curve, which can be done through expert evaluation or data analysis methods.

[0114] 3. Establish a quantitative model for policy impact and convert policy impact into quantifiable parameters. For example, you can set a policy impact coefficient ranging from 0.8 to 1.2, where 1 means no impact, less than 1 means reduced costs or benefits, and greater than 1 means increased costs or benefits.

[0115] 4. Adjust the total cost of preparation based on the quantitative model. For example, if a policy is expected to increase the cost of preparation by 10%, the original total cost of preparation can be multiplied by 1.1.

[0116] 5. Similarly, make adjustments to the forecasted benefit curve. For example, if the policy is expected to reduce benefits by 5% in the first three years but increase benefits by 8% starting in the fourth year, the benefit curve can be adjusted accordingly.

[0117] 6. Finally, the adjusted total maintenance cost and predicted benefit curve are used for subsequent evaluation calculations.

[0118] In this way, the method of this application can more accurately reflect the impact of policy changes on land consolidation and development, and improve the reliability and practicality of the evaluation results.

[0119] In some preferred implementations, the step of obtaining GIS planning data includes:

[0120] Obtain the planning scheme of the target area and generate GIS planning data based on the building model corresponding to the planning scheme.

[0121] Specifically, the planning scheme is an expected engineering plan for the target area, which may include information such as building distribution, building scale, supporting facilities, land use nature, and volume ratio. It is an engineering plan that can be used to assist in completing the construction of a complete building model. More specifically, in some other implementations, the planning scheme may be a virtual building model itself established on a large map such as the target area, and the corresponding GIS planning data may be directly extracted by analyzing the building model itself.

[0122] More specifically, based on the foregoing, it can be seen that the GIS-based land reclamation and development evaluation method of the embodiment of the present application can be used to conduct development evaluation on different planning schemes for a target area and can be used to conduct development evaluation on the same or similar planning schemes for different target areas. The latter can be achieved by calculating and comparing corresponding profit and loss results based on the same or similar planning schemes for different target areas, and the former can be achieved by providing more than two planning schemes for the same target area and calculating and comparing corresponding profit and loss results. It is worth mentioning that in the former implementation mode, the planning scheme can be a planning scheme directly input by the user, or it can be a plurality of planning schemes automatically generated by professional planning and design software that meet some user-defined indicator requirements.

[0123] More specifically, when generating GIS planning data based on the building model corresponding to the planning scheme, the following steps can be adopted:

[0124] First, you can use 3D modeling software (such as SketchUp, Revit, etc.) to create building models based on the planning scheme. These models should contain attribute information such as the building's geometry, height, area, etc.

[0125] Secondly, the building model can be integrated with the GIS system by using BIM (Building Information Modeling) technology. The BIM model contains rich building information and can be directly converted into GIS data format.

[0126] Thirdly, you can use specialized GIS software (such as ArcGIS, QGIS, etc.) to import and convert the building model into GIS planning data. During this process, it is necessary to ensure that the spatial reference system of the building model is consistent with the GIS system to ensure the accuracy of the data.

[0127] Finally, automated tools can be developed to achieve batch conversion of building models into GIS planning data. This approach is particularly suitable for large-scale urban planning projects and can significantly improve data processing efficiency.

[0128] More specifically, in the process of generating GIS planning data, it is necessary to pay attention to retaining the key attribute information of the building model, such as building type, height, area, volume ratio, etc. This information is crucial for the subsequent land consolidation and development assessment. At the same time, it is also necessary to consider incorporating public space information such as roads and green spaces into the GIS planning data for a more comprehensive assessment; the GIS planning data obtained in this way provides a reliable data basis for the subsequent land consolidation and development assessment.

[0129] More specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application generates GIS planning data by directly using planning schemes and building models, which greatly improves the efficiency of data acquisition. Compared with traditional manual creation or complex data conversion processes, this method can quickly generate a large amount of accurate GIS planning data; secondly, since the GIS planning data is generated based on the actual planning scheme and building model, it can accurately reflect the planning intention and building characteristics, significantly reducing data errors. This high accuracy is crucial for subsequent land consolidation and development evaluation and can provide a more reliable basis for decision-making. Thirdly, the generated GIS planning data can be directly used for subsequent land consolidation and development evaluation, including calculating development input costs and predicting yield curves. This seamless connection greatly improves the efficiency and accuracy of the entire evaluation process. In addition, by converting the planning scheme into GIS data, the planning results can be more intuitively displayed, which is convenient for decision makers and relevant personnel to understand and evaluate the planning scheme. This visualization advantage is particularly important in complex land consolidation projects, which can help all parties better understand and evaluate the feasibility and potential impact of the planning scheme. Finally, when the planning scheme changes, new GIS planning data can be quickly generated by updating the building model to ensure the timeliness of the data. This flexibility and updatability are very valuable for long-term land consolidation project management, as it can reflect planning changes in a timely manner and support dynamic decision-making.

[0130] In some preferred embodiments, the planning dataset includes an engineering building dataset and a revenue building dataset;

[0131] The steps to obtain the development input cost and the predicted benefit curve over time based on the planning data set include:

[0132] Obtain development input costs based on engineering and construction datasets;

[0133] Generate forecasted revenue curves for different development years based on the revenue building dataset and different building revenue methods.

[0134] Specifically, the GIS-based land consolidation and development evaluation method of the embodiment of the present application obtains a planning data set including an engineering construction data set and a revenue building data set according to GIS planning data, and uses the two types of data sets to respectively calculate the development input cost and the predicted revenue curve, which can more accurately reflect the economic situation of the land consolidation and development project; it should be noted that the engineering construction data set and the revenue building data set are not different data sets. The engineering construction data set is used to calculate the development input cost, and contains information such as the type, scale, material, etc. of all buildings in the target area. This information directly affects the estimation of the development cost. The revenue building data set is used to generate predicted revenue curves for different development years in combination with different building revenue methods, and the buildings with revenue functions involved are actually also present in the engineering construction data set.

[0135] More specifically, the engineering construction data set may include information such as the type of building (such as residential, commercial, office, etc.), building area, floor height, structure type (such as reinforced concrete, steel structure, etc.), decoration standards, etc. This information can be imported through a building information model (BIM) or a computer-aided design (CAD) system. Based on this information, the bill of quantities method or parameter estimation method can be used in combination with additional cost parameters such as development cycle, labor cost, and tax cost to calculate the development input cost; the income building data set may include information such as the purpose of the building, rentable or saleable area, expected rent or selling price, occupancy rate or sales progress, etc. Different building income methods may include sale, rental, self-operation, etc. The GIS-based land consolidation development evaluation method of the embodiment of the present application can generate multi-year predicted income curves for each type of building by combining market research data and economic forecasting models.

[0136] More specifically, the land preparation dataset is used to calculate the land preparation cost, while the engineering construction dataset and the benefit building dataset are used to evaluate the costs and benefits of the development phase. This comprehensive data usage makes the evaluation results more accurate and reliable.

[0137] More specifically, in practical applications, the GIS-based land consolidation development evaluation method of the embodiment of the present application can be implemented by the following steps: First, the engineering construction data and the income building data are extracted from the planning scheme and stored as the engineering construction data set and the income building data set respectively. Then, the development input cost is calculated by using the engineering construction data set in combination with the local construction cost index and market price information. This process may need to consider the cost differences of different building types, as well as the material and labor costs that change over time. Next, the income building data set is used to generate a multi-year predicted income curve for each type of building in combination with market research data and economic forecasting models. This process needs to consider the income characteristics of different building types, such as the sales cycle of residential buildings, the rental growth trend of commercial real estate, etc. Finally, the development input cost and the predicted income curve are combined to derive the cash flow forecast of the project at different time points, thereby evaluating the economic feasibility of the project; this method not only takes into account the cost, but also takes into account the income that changes over time, which helps users better understand the long-term economic performance of the project.

[0138] More specifically, in a further embodiment, the revenue building data set includes the starting revenue time corresponding to different buildings (which can be determined based on the expected building completion time in the planning scheme), so that the aforementioned independent revenue curve should be combined with the planning scheme to determine the starting time for generating revenue for the corresponding building with revenue function.

[0139] In some preferred embodiments, the step of generating a forecasted revenue curve for different development years based on the revenue building data set and different building revenue modes includes:

[0140] Obtain benchmark yield curves per unit size for different types of buildings with yield functions;

[0141] Obtain independent yield curves corresponding to different types of buildings with yield functions in the target area according to the benchmark yield curve and the yield building dataset;

[0142] All independent yield curves are combined to obtain the forecasted yield curve for different development years.

[0143] Specifically, in this embodiment, the benchmark revenue curve is a revenue curve representing the time changes of the unit scale of the corresponding type of building with revenue function, which can characterize the changes in revenue generated by a certain type of building with a unit scale (such as 10 square meters); combined with the building data of the revenue building data set, independent revenue curves corresponding to different types of buildings with revenue functions in the target area can be calculated and obtained, and then these independent revenue curves can be combined to conveniently derive a predicted revenue curve that can accurately characterize the revenue situation of the target area, so as to improve the accuracy of revenue prediction.

[0144] More specifically, the benchmark yield curve can be preset by the user or obtained based on market research; in an embodiment of the present application, the benchmark yield curve per unit scale of different types of buildings with revenue functions is determined based on the yield curve per unit scale of different types of buildings with revenue functions in the surrounding areas of the target area.

[0145] Specifically, the GIS-based land reclamation and development evaluation method of the embodiment of the present application utilizes the unit-scale revenue curves of different types of buildings with revenue functions in the surrounding areas of the target area to determine a benchmark revenue curve, so as to more accurately reflect the local level of revenue changes based on actual historical data, thereby avoiding errors that may be caused by estimates out of thin air. By considering the revenue data of the surrounding areas, it can better adapt to the local economic environment and market conditions, making the revenue estimation closer to reality, and being able to more finely distinguish the revenue generated by various types of buildings, which can better reflect the local actual revenue level and changing trends, thereby improving the accuracy of revenue estimation.

[0146] In some preferred implementations, the planning scheme includes a building scheme and a corresponding construction scheme, and the construction scheme includes construction sequence information about different buildings;

[0147] The steps to obtain development input costs based on the engineering and construction dataset include:

[0148] Obtain the basic investment costs of different buildings in the target area based on the engineering building dataset;

[0149] Obtain additional financing costs based on the financing model, which is generated by matching the investment and construction sequence information;

[0150] The development input cost is obtained by combining the basic input costs and financing additional costs of different buildings.

[0151] Specifically, the construction plan represents the specific scale and distribution of different types of buildings in the target area, and is used to calculate the basic investment costs of different types of buildings. The basic investment costs may include basic development costs and tax costs. The basic development costs may include unit area costs, material costs, labor costs, etc. The investment and construction plan represents the construction development schedule, which may include the start time, construction period and completion time of each building, so it includes information on the investment and construction sequence of different buildings, which can be sorted and generated through project management software.

[0152] More specifically, the financing model can be one or more. In an implementation mode where there is only one financing model, the additional financing cost is the additional cost generated under the current financing model strategy, which can improve the cost accounting accuracy when combined with the development investment cost. In an implementation mode where there are multiple financing models, the GIS-based land reclamation development evaluation method of the embodiment of the present application can generate different additional financing costs according to different financing models to generate different development investment costs, so as to allow users or decision makers to evaluate the advantages and disadvantages of different financing models.

[0153] More specifically, the GIS-based land reclamation and development evaluation method of the embodiment of the present application preferably generates a financing model that meets the user's preset needs based on the matching of investment and construction sequence information, and realizes automatic recommendation of the most suitable financing model. The user's preset needs can be one or more of the lowest financing additional cost, the minimum number of financing times, the minimum financing amount, the nature of the financing party, etc.; wherein, the financing model can be batch financing, one-time financing, cross-cooperation partner financing, etc. For example, for large-scale projects developed in phases, a batch financing model may be adopted; while for small-scale projects that are built quickly, one-time financing may be more suitable; the calculation of the financing additional cost needs to consider multiple factors such as interest rate, financing period, and repayment method.

[0154] More specifically, when combining basic input costs and additional financing costs, the time value can be introduced. For example, the net present value method can be used to convert costs in different periods to the same point in time, which can more accurately reflect the actual cost structure of the project.

[0155] The GIS-based land reclamation and development evaluation method of the embodiment of the present application not only takes into account the cost differences of different building types, but also takes into account the investment sequence and financing costs, thereby obtaining a more accurate and comprehensive cost estimation result.

[0156] More specifically, in some other embodiments, the financing model can also be generated using a pre-trained deep learning model based on investment and construction sequence information, cash flow, and building plan decisions to output a combination of multiple financing models with the lowest additional cost.

[0157] More specifically, the additional financing costs mainly include loan interest.

[0158] In some preferred implementations, the basic investment costs of different buildings include infrastructure costs, costs of public areas such as greening, relocation costs, and commercial building construction costs.

[0159] Specifically, the cost of public areas such as greening takes into account the investment in environmental beautification and public space construction. The cost of relocation and resettlement reflects the cost of resettling residents that may be involved in the land reclamation process. The cost of commercial building construction is directly related to the main construction investment of the development project. This cost breakdown method helps to more accurately evaluate the actual investment of each construction project, thereby improving the accuracy of the overall land reclamation and development assessment. The GIS-based land reclamation and development assessment method of the embodiment of the present application can more comprehensively reflect the economic feasibility of the development project by taking these specific cost items into consideration, providing a more reliable reference for decision makers.

[0160] More specifically, infrastructure costs can be further subdivided into sub-projects such as road engineering, water supply and drainage engineering, power engineering, and communication engineering. For example, road engineering may include the construction costs of main roads, secondary roads, and branch roads; water supply and drainage engineering may involve the laying costs of tap water pipe networks, rainwater pipe networks, and sewage pipe networks. The costs of public areas such as greening can include the costs of different types of greening projects such as park green spaces, street greening, and greening within communities, as well as the configuration costs of public facilities such as fitness equipment and rest seats. The cost of relocation and resettlement may involve multiple aspects such as temporary resettlement costs, long-term resettlement housing construction costs, and relocation compensation costs. The cost of commercial building construction can be subdivided into the costs of multiple stages such as foundation treatment, main structure, decoration engineering, and equipment installation.

[0161] More specifically, in practical applications, this detailed cost classification is organically combined with the aforementioned GIS data processing and evaluation methods. The precise geographic information and planning data obtained through the GIS system can provide a basis for the accurate calculation of various costs.

[0162] In specific implementation, the following methods can be used: First, based on the current land use data and planning data in the GIS system, determine the specific areas and scales that require infrastructure construction, greening, relocation and resettlement, and commercial building construction. Then, for infrastructure costs, the road length, pipe network length, etc. can be calculated based on the terrain data and planned road network data in the GIS system, and then multiplied by the unit cost to get the total cost. For greening costs, they can be calculated based on the planned green area and type (such as parks, street greening, etc.), combined with local greening standards and unit costs. Relocation and resettlement costs can be estimated based on the existing building area and population data in the GIS system, combined with local resettlement compensation standards. The cost of commercial building construction can be calculated based on the planned building area and type, combined with the local construction market conditions.

[0163] Second, please refer to Figure 2 Some embodiments of the present application also provide a GIS-based land consolidation and development assessment device, the device comprising:

[0164] The acquisition module 201 is used to acquire GIS information of the target area, where the GIS information includes GIS current status data and GIS planning data;

[0165] The data reorganization module 202 is used to split and reorganize the GIS current data and the GIS planning data to obtain a preparation data set and a planning data set, wherein the preparation data set includes a plurality of local plots related to different land preparation methods;

[0166] An estimation module 203 is used to obtain the total preparation cost according to the preparation data set and the unit preparation costs of different land preparation methods, and to obtain the development input cost and the predicted return curve with respect to time according to the planning data set;

[0167] The evaluation module 204 is used to comprehensively consider the total preparation cost, development input cost and predicted yield curve to obtain the profit and loss result of the target period for development evaluation.

[0168] The GIS-based land reclamation and development evaluation device of the embodiment of the present application utilizes GIS technology to automatically process spatial data, can efficiently process a large amount of complex spatial data, significantly improves data processing efficiency, and ensures the integrity and accuracy of calculations; secondly, the device can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast profit curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low accuracy, and incomplete considerations in traditional methods, providing a more reliable and scientific basis for land reclamation and development decisions, and helping to improve the utilization efficiency and economic benefits of land resources.

[0169] In some preferred embodiments, the GIS-based land consolidation and development assessment device of the embodiment of the present application is used to execute the GIS-based land consolidation and development assessment method provided in the first aspect above.

[0170] Third, please refer to Figure 3 Some embodiments of the present application also provide a structural diagram of an electronic device. The present application provides an electronic device, including: a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other through a communication bus 303 and / or other forms of connection mechanisms (not marked). The memory 302 stores computer-readable instructions executable by the processor 301. When the electronic device is running, the processor 301 executes the computer-readable instructions to execute the method in any optional implementation of the above embodiments.

[0171] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method in any optional implementation of the above embodiment is executed. The computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0172] In summary, the embodiments of the present application provide a GIS-based land consolidation and development evaluation method and related equipment, wherein the GIS-based land consolidation and development evaluation method utilizes GIS technology to automatically process spatial data, can efficiently process a large amount of complex spatial data, significantly improves data processing efficiency, and ensures the integrity and accuracy of calculations; secondly, the method can also simulate different plans and evaluate their impacts, and can also consider time factors to generate dynamic forecast yield curves, which is helpful for evaluating long-term economic benefits, and effectively solves the problems of low efficiency, low accuracy, and incomplete considerations in traditional methods, providing a more reliable and scientific basis for land consolidation and development decisions, and helping to improve the utilization efficiency and economic benefits of land resources.

[0173] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0174] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0175] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0176] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0177] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A GIS-based land consolidation and development assessment method, characterized in that: The method comprises the following steps: S1. Acquire GIS information of the target area, wherein the GIS information includes GIS current status data and GIS planning data, wherein the GIS current status data includes land ownership data, house surveying and mapping data, and land use current status data; SA, modify GIS status data based on topological relationships, geometric relationships and spatial consistency; S2. Split and reorganize the GIS current status data and the GIS planning data respectively to obtain a preparation data set and a planning data set, wherein the preparation data set includes a plurality of local plots related to different land preparation methods; S3. Obtain the total preparation cost based on the preparation data set and the unit preparation costs of different land preparation methods, and obtain the development input cost and the predicted return curve with respect to time based on the planning data set; S4, comprehensively analyzing the total preparation cost, the development investment cost and the predicted profit curve to obtain the profit and loss result of the target period for development evaluation; The steps to split and reorganize the GIS status data and obtain the prepared data set include: Based on the land ownership data, the house surveying data and the land use status data, the land type information, ownership information and area information of each unit plot in the target area are obtained by splitting, wherein the area information includes: land area, building land area, building area and foundation area; Allocate a land preparation method for each unit plot according to the land type information and ownership information; Combining unit plots according to the land preparation methods, obtaining a plurality of local plots related to different land preparation methods to construct the preparation data set; The unit preparation costs of different land preparation methods in step S3 are determined according to the historical preparation costs of different land types in the surrounding areas of the target area; The process of determining the unit land preparation cost of different land preparation methods includes: According to the historical preparation costs of different land types in the surrounding areas of the target area, historical preparation information on different land preparation methods in the surrounding areas of the target area within the preset area is obtained; Acquire a cost variation curve with respect to time according to the historical maintenance information; The unit preparation costs of the different land preparation methods are predicted and obtained according to the expected preparation time and the cost change curve.

2. The GIS-based land consolidation and development assessment method according to claim 1, characterized in that: The steps to obtain GIS planning data include: A planning scheme for the target area is obtained, and the GIS planning data is generated according to a building model corresponding to the planning scheme.

3. The GIS-based land consolidation and development assessment method according to claim 2, characterized in that: The planning data set includes an engineering building data set and a revenue building data set; The step of obtaining the development input cost and the predicted benefit curve about time according to the planning data set includes: Acquire development input costs according to the engineering construction data set; A predicted revenue curve for different development years is generated based on the revenue building data set and different building revenue methods.

4. The GIS-based land consolidation and development assessment method according to claim 3 is characterized in that: The planning scheme includes a building scheme and a corresponding construction scheme, and the construction scheme includes construction sequence information about different buildings; The step of obtaining the development investment cost according to the engineering construction data set comprises: Acquire the basic investment costs of different buildings in the target area according to the engineering building dataset; Acquire additional financing costs according to a financing model, wherein the financing model is generated by matching the investment and construction sequence information; The development investment cost is obtained by combining the basic investment costs of different buildings and the additional financing costs.

5. A GIS-based land consolidation and development assessment device, characterized in that: The device comprises: An acquisition module is used to acquire GIS information of a target area, wherein the GIS information includes GIS current data and GIS planning data, and the GIS current data is corrected based on topological relationships, geometric relationships and spatial consistency, wherein the GIS current data includes land ownership data, house surveying and mapping data, and land use current data; A data reorganization module is used to split and reorganize the GIS current status data and the GIS planning data respectively to obtain a preparation data set and a planning data set, wherein the preparation data set includes a plurality of local plots related to different land preparation methods; An estimation module is used to obtain the total preparation cost based on the preparation data set and the unit preparation costs of different land preparation methods, and to obtain the development input cost and the predicted return curve over time based on the planning data set; An evaluation module, for obtaining a profit and loss result of a target year by comprehensively considering the total preparation cost, the development investment cost and the predicted yield curve to perform development evaluation; The steps to split and reorganize the GIS status data and obtain the prepared data set include: Based on the land ownership data, the house surveying data and the land use status data, the land type information, ownership information and area information of each unit plot in the target area are obtained by splitting, wherein the area information includes: land area, building land area, building area and foundation area; Allocate a land preparation method for each unit plot according to the land type information and ownership information; Combining unit plots according to the land preparation methods, obtaining a plurality of local plots related to different land preparation methods to construct the preparation data set; The unit preparation costs of different land preparation methods are determined based on the historical preparation costs of different land types in the surrounding areas of the target area; The process of determining the unit land preparation cost of different land preparation methods includes: According to the historical preparation costs of different land types in the surrounding areas of the target area, historical preparation information on different land preparation methods in the surrounding areas of the target area within the preset area is obtained; Acquire a cost variation curve with respect to time according to the historical maintenance information; The unit preparation costs of the different land preparation methods are predicted and obtained according to the expected preparation time and the cost change curve.

6. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1 to 4 are executed.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are executed.

Images