Project planning and site selection method based on available land analysis and land development cost estimation

Abstract

The invention discloses a project planning and site selection method based on available land analysis and land development cost estimation, and the method comprises the steps: carrying out the land current situation analysis of land parcels to be selected one by one, i.e., carrying out the spatial overlay analysis of the screened land parcels to be selected meeting conditions and the land utilization current situation data of adjacent years, analyzing the land current situation of each land parcel, and carrying out the calculation of the land development cost of each land parcel; comprising the following steps: further analyzing the areas and proportions of cultivated land and forest land for the agricultural land, estimating the land cost based on the land current situation analysis result of a to-be-selected land parcel, and calculating the land cost according to the agricultural land area, the cultivated land area, the forest land area and the current policy. According to the method, cultivated land purchase indexes and capital costs required for land acquisition compensation are estimated, land parcels to be selected are sorted according to different dimensions such as occupied cultivated land areas, land capital costs, landforms and the like, government departments can conveniently check land element input-output ratios and land performance evaluation, and the pertinence of investment attraction and the efficiency and accuracy of project planning and site selection are improved.

Description

Technical Field

[0001] This invention relates to a project planning and site selection method, and in particular to a project planning and site selection method based on available land analysis and land development cost estimation, belonging to the technical field of project planning and site selection methods. Background Technology

[0002] Traditional project planning and site selection mostly rely on human experience. Due to the lack of complete data and information asymmetry among investment promotion personnel regarding planning, land, construction, and investment attraction across departments, traditional planning and site selection is inefficient, inaccurate, and unable to estimate investment costs, making it difficult to meet the diversified project site selection requirements of investors. Summary of the Invention

[0003] The main objective of this invention is to provide a project planning and site selection method based on available land analysis and land development cost estimation.

[0004] The objective of this invention can be achieved by adopting the following technical solution: The project planning and site selection method based on available land analysis and land development cost estimation includes the following steps: Step 1: Collect and organize spatial element data and policy and regulatory data related to planning and site selection, and establish a project site selection database; Step 2: Establish a land availability analysis model to dynamically calculate the available land within this administrative region; Step 3: Based on the client's needs, input the planning site selection conditions and calculate the proposed site selection. Step 4: Consistency analysis between the two plans involves overlaying the analysis results from Step 3 with the overall land use plan, and specially marking the proposed site plots that do not conform to the overall land use plan to reduce their scores; Step 5: Site selection land use status analysis, which involves spatially overlaying the analysis results of Step 3 with the land use status data of adjacent years to analyze the area and proportion of construction land, agricultural land and unused land for each proposed site. Agricultural land is further analyzed to include the area and proportion of cultivated land and forest land. Step Six: Estimate the cost of land development funds. Based on the analysis results of Step Five, estimate the costs of purchasing farmland quotas, land acquisition compensation, and forest vegetation restoration according to the current land use area, cultivated land area, and forest land area. Step 7: The proposed sites are ranked comprehensively based on factors such as the area of ​​cultivated land occupied, land development costs, consistency with urban planning regulations, and topography, for investment promotion personnel to select and recommend. Step 8: Establish a dynamic data element update mechanism to dynamically update the project site selection database from Step 1, improve data timeliness, and ensure the accuracy of analysis results.

[0005] Preferably, the spatial element data related to site selection in step one mainly includes: territorial spatial planning, regulatory detailed planning, land supply, planning conditions, construction land planning permit, construction project planning permit, scope of selected project sites, unusable land parcels, inefficient land use, idle land, land acquired and stored, other usable land, overall land use planning, land change survey, prohibited construction areas, restricted construction areas, permanent basic farmland, historical and cultural blocks / historical buildings, contaminated sites, transportation facilities, supporting facilities, and zoning scope. The data format is spatial vector data. Policy and regulatory data mainly includes: planned construction land space scale, annual land use plan, land consolidation and upgrading, adjustment price of cultivated land occupation and compensation balance indicators, comprehensive land price of expropriated areas, compensation standards for attachments and seedlings on expropriated land, and collection standards for forest vegetation restoration fees, etc. All of the above data are stored in a relational database.

[0006] Preferably, the formula for calculating available land is: Available Land = Controlled Detailed Planning Land - Land Supply - Land Planned but Not Implemented - Construction Land Planning Permit - Construction Project Planning Permit - Selected Project Scope - Unusable Plots + Land Acquired + Other Usable Land + Inefficient Land + Idle Land. Among these, other usable land and unusable plots with disputes need to be investigated and measured by a third-party agency.

[0007] Preferably, the planning site selection conditions include, but are not limited to, land use nature, land area, site selection area, and surrounding supporting facilities, and select suitable proposed site plots from the available land. Meanwhile, advanced site selection conditions can be set to allow adjacent available land parcels to be merged for site selection, and two rules can be selected: area priority and land use priority. The selected area refers to administrative divisions, functional zones, industrial parks, and user-defined site selection ranges, while surrounding facilities include public amenities such as transportation, medical care, commerce, and education.

[0008] Preferably, step four, after the approval and implementation of the China Land Spatial Planning, can be omitted.

[0009] Preferably, in step five, the area and proportion of cultivated land and forest land need to be further analyzed.

[0010] Preferably, the spatial element data format related to planning and site selection is spatial vector data. The specific algorithm adopts the minimum distance method, which includes the following steps: Suppose that each object can be represented as a point in a feature space, which is usually multidimensional, with each dimension representing a feature.

[0011] Preferably, a dynamic time-dimensional factor and a machine learning prediction model are introduced into the original formula for calculating available land: Dynamic available land formula: S 动态可用地= (Controlled detailed planning land use - ∑ occupied land + ∑ revitalizable land) × δ(t) where δ(t) is the time decay factor (predicted by an LSTM model trained on historical land development rates, reflecting the land supply trend in the next 1-3 years). By analyzing satellite remote sensing imagery using convolutional neural networks (CNNs), inefficient land use and idle land boundaries can be automatically identified, replacing traditional manual surveys and improving data acquisition efficiency (accuracy ≥ 90%).

[0012] Preferably, a single-factor evaluation matrix R is constructed using expert scoring, and the comprehensive cost level (low / medium / high) is output by combining the principle of maximum membership.

[0013] Step 7 Extension: Multi-objective genetic algorithm sorting Design a comprehensive location selection index (LSI) that integrates multi-dimensional constraints: ; : Construction land ratio score (higher is better, weight α=0.4); Cost grade score (lower is better, weight β=0.3); Consistency score between the two regulations (compliance is 100 points, weight γ=0.2); : Terrain slope score (<5° is 100 points, weight δ=0.1).

[0014] Beneficial technical effects of the present invention: This invention provides a project planning and site selection method based on available land analysis and land development cost estimation. Addressing the shortcomings of traditional planning and site selection methods, such as low efficiency, poor accuracy, and difficulty in estimating investment costs, this method utilizes a GIS spatial analysis model to quickly and accurately screen available land parcels according to customer needs and estimate the investment cost of each site selection option. This significantly improves the efficiency of project planning and site selection, providing land resource support for the implementation of investment projects. The technical solution adopted by this invention to solve its technical problems is as follows: Collect and organize spatial element data and policy and regulatory data related to planning and site selection, and store them in a relational database.

[0015] Using a GIS spatial analysis model, the available land within this administrative region is dynamically calculated as a candidate site for investment promotion planning and site selection.

[0016] Based on the client's needs, input the planning site selection conditions, including but not limited to land use nature, land area, site selection area, surrounding supporting facilities, etc., and filter the available land for the proposed site selection that meets the conditions; at the same time, the advanced site selection conditions can be set to allow adjacent available land plots to be combined for site selection, and two rules can be selected: area priority and land use nature priority.

[0017] A land use status analysis was conducted for each of the proposed site selection plots. This involved spatially overlaying the selected plots with land use status data from adjacent years to analyze the current land use status of each plot, including the area and proportion of three major categories of land: construction land, agricultural land, and unused land. Further analysis of the area and proportion of cultivated land and forest land was also required for agricultural land.

[0018] Based on the analysis of the current land use status of the proposed site, land costs are estimated. According to the area of ​​agricultural land, cultivated land, and forest land, as well as current policies, the required capital costs for purchasing cultivated land quotas, land acquisition compensation, and forest vegetation restoration are estimated.

[0019] The proposed sites are ranked according to different dimensions such as the area of ​​cultivated land occupied, land capital cost, consistency between planning and landform, and topography, so as to facilitate government departments in calculating the input-output ratio of land elements and evaluating land use performance, thereby improving the targeting of investment promotion and the efficiency and accuracy of project planning and site selection. Attached Figure Description

[0020] Figure 1 This is a system diagram of a preferred embodiment of the project planning and site selection method based on available land analysis and land development cost estimation according to the present invention. Detailed Implementation

[0021] To enable those skilled in the art to understand the technical solution of the present invention more clearly, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0022] Step S1 involves collecting and organizing spatial element data and policy and regulatory data related to planning and site selection to establish a project site selection database. The spatial element data related to planning and site selection mainly includes: territorial spatial planning, detailed control planning, land supply, planning conditions, construction land planning permits, construction project planning permits, the scope of selected project sites, unusable land parcels, inefficient land use, idle land, land acquired and stored, other usable land, overall land use planning, land change surveys, prohibited construction areas, restricted construction areas, permanent basic farmland, historical and cultural blocks / historical buildings, contaminated sites, transportation facilities, supporting facilities (education, medical, commercial, etc.), zoning scope, etc., in spatial vector data format. Policy and regulatory data mainly includes: the spatial scale of planned construction land, annual land use plans, farmland occupation and compensation balance indicators and fees, and policies related to land consolidation and land use quotas. All of the above data are stored in a relational database.

[0023] Step S2: Establish a land availability analysis model to dynamically calculate the available land within the administrative region. The formula for calculating available land is: Available Land = Controlled Detailed Planning Land - Land Supply - Planned but Not Implemented Land - Construction Land Planning Permit - Construction Project Planning Permit - Selected (Investment-Attracted) Project Scope - Unusable Plots (with Disputes, etc.) + Land Acquired + Other Usable Land + [Inefficient Land + Idle Land]. Among these, other usable land and unusable plots with disputes need to be investigated and measured by a third-party agency. The land within [ ] can be selected and calculated according to the specific circumstances of each region.

[0024] Step S3: Based on the client's needs, input the planning site selection conditions, including but not limited to land use nature, land area, site selection area, surrounding supporting facilities, etc., and filter the available land for suitable proposed site selection plots. Simultaneously, advanced site selection conditions can be set to allow the merging of adjacent available land plots, with two rules available: area priority and land use nature priority. The site selection area refers to administrative divisions, functional zones, industrial parks, user-defined site selection areas (uploaded by the user or drawn online), etc. Surrounding facilities include public amenities such as transportation, medical care, commerce, and education.

[0025] Step S4, the consistency analysis between the two plans, involves overlaying the analysis results of step S3 with the overall land use plan. Proposed sites that do not conform to the overall land use plan are specially marked and their scores are reduced. This step can be omitted after the land use plan is approved and implemented.

[0026] Step S5, Site Selection Land Use Status Analysis, involves spatially overlaying the analysis results from Step S3 with land use status data from adjacent years to analyze the area and proportion of construction land, agricultural land, and unused land for each proposed site. Further analysis of the area and proportion of arable land and forest land is required for agricultural land.

[0027] Step S6: Estimate the cost of land development funds. Based on the analysis results of step S5, estimate the cost of purchasing farmland quotas, land acquisition compensation, and forest vegetation restoration according to the current land use area, cultivated land area, and forest land area.

[0028] Step S7: The proposed site selection plots are comprehensively ranked according to factors such as the area of ​​cultivated land occupied, land development capital costs, consistency with the two planning regulations, and topography, for investment promotion personnel to select and recommend.

[0029] Step S8: Establish a dynamic update mechanism for data elements, dynamically update the project site selection database from Step S1, improve data timeliness, and ensure the accuracy of analysis results.

[0030] In this invention, an AI dynamic prediction and intelligent optimization module is introduced; Upgrade the available land analysis model; A dynamic time-dimensional factor and a machine learning prediction model are introduced into the original formula for calculating available land: Dynamic available land formula: S 动态可用地 = (Controlled detailed planning land use - ∑ occupied land + ∑ revitalizable land) × δ(t) where δ(t) is the time decay factor (predicted by an LSTM model trained on historical land development rates, reflecting the land supply trend in the next 1-3 years).

[0031] Data-driven optimization: By analyzing satellite remote sensing imagery through convolutional neural networks (CNN), inefficient land use and idle land boundaries can be automatically identified, replacing traditional manual surveys and improving data acquisition efficiency (accuracy ≥ 90%).

[0032] Cost estimation incorporates fuzzy comprehensive evaluation to construct a fuzzy evaluation model for land development costs, integrating uncertainties such as policy, location, and market fluctuations. Set of cost influencing factors: ; Fuzzy weight matrix: The weight vector W = [0.3, 0.25, 0.2, 0.15, 0.1] is determined using the Analytic Hierarchy Process (AHP). Fuzzy evaluation matrix: A single-factor evaluation matrix R is constructed using expert scoring, and the comprehensive cost level (low / medium / high) is output by combining the principle of maximum membership.

[0033] Step 7 Extension: Multi-objective genetic algorithm sorting Design a comprehensive location selection index (LSI) that integrates multi-dimensional constraints: ; : Construction land ratio score (higher is better, weight α=0.4); Cost grade score (lower is better, weight β=0.3); Consistency score between the two regulations (compliance is 100 points, weight γ=0.2); : Terrain slope score (<5° is 100 points, weight δ=0.1).

[0034] By optimizing land parcel combinations through genetic algorithms, it supports the generation of clustered site selection schemes (such as industrial clusters, commercial complexes, etc.) and improves the efficiency of intensive land use.

[0035] By storing land status data and cost accounting processes on the blockchain, and using smart contracts to automatically trigger policy compliance verification (such as automatic cancellation of farmland occupation and compensation balance indicators), the data is ensured to be tamper-proof, thereby enhancing the credibility of government decision-making.

[0036] Intelligent matching function: Customers submit site selection requirements through blockchain nodes, and the system automatically matches eligible plots and generates an unalterable site selection report, realizing on-chain management of the entire process of "requirement-site selection-approval".

[0037] Digital Twin Site Selection Sand Table 3D visualization model: Based on the Unity engine, a digital twin of the proposed site area is constructed, integrating spatial elements such as terrain, transportation, and supporting facilities, and supporting interactive query of land parcel information (such as rotation, scaling, and attribute pop-ups).

[0038] Dynamic simulation function: After inputting the project type (such as industrial, residential, commercial), the system automatically simulates the economic indicators (such as GDP contribution, number of jobs) and environmental impacts (such as carbon emissions, land use efficiency) after the land is developed, to assist decision-makers in comparing and selecting alternatives.

[0039] Formula Innovation: Land Use Performance Evaluation Model Design a formula for the Land Input-Output Ratio (LIOR) to quantify the economic benefits of site selection schemes: ; Annual output value of land use category i (e.g., 800,000 yuan / mu for industrial land and 2,000,000 yuan / mu for commercial land). Land use type weight (set according to local industrial policies, such as strategic emerging industries λ = 1.2); Location correction factor (1.5 for city center, 1.0 for suburbs). When LIOR>1, it indicates that the development revenue of the land parcel covers the costs and has a surplus, and it is given priority recommendation; By using LIOR ranking, the government can quickly identify high-value land parcels and formulate differentiated investment attraction policies (such as providing tax incentives for land parcels with LIOR>2).

[0040] The above description is merely a further embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope disclosed in the present invention, based on the technical solution and concept of the present invention, shall fall within the scope of protection of the present invention.

Claims

1. A project planning and site selection method based on available land analysis and land development cost estimation, characterized by: Includes the following steps: Step 1: Collect and organize spatial element data and policy and regulatory data related to planning and site selection, and establish a project site selection database; Step 2: Establish a land availability analysis model to dynamically calculate the available land within this administrative region; Step 3: Based on the client's needs, input the planning site selection conditions and calculate the proposed site selection. Step 4: Consistency analysis between the two plans involves overlaying the analysis results from Step 3 with the overall land use plan, and specially marking the proposed site plots that do not conform to the overall land use plan to reduce their scores; Step 5: Site selection land use status analysis, which involves spatially overlaying the analysis results of Step 3 with the land use status data of adjacent years to analyze the area and proportion of construction land, agricultural land and unused land for each proposed site. Agricultural land also needs further analysis of the area and proportion of cultivated land and forest land. Step Six: Estimate the cost of land development funds. Based on the analysis results of Step Five, estimate the cost of purchasing farmland quotas and land acquisition compensation funds according to the current land use area, cultivated land area, forest land area, and unused land area. Step 7: The proposed sites are ranked comprehensively according to the area of ​​cultivated land occupied, land development capital costs, consistency with the two plans, and topography, for investment promotion personnel to select and recommend. Step 8: Establish a dynamic update mechanism for planning and site selection data elements, and dynamically update the project site selection database from Step 1 to improve data timeliness and ensure the accuracy of analysis results.

2. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 1, characterized in that: The spatial element data related to site selection in step one mainly includes: territorial spatial planning, regulatory detailed planning, land supply, planning conditions, construction land planning permit, construction project planning permit, scope of selected project sites, unusable land parcels, inefficient land use, idle land, land acquired and stored, other usable land, overall land use planning, land change survey, prohibited construction areas, restricted construction areas, permanent basic farmland, historical and cultural blocks / historical buildings, contaminated sites, transportation facilities, supporting facilities, and zoning scope. The data format is spatial vector data. The spatial vector data must be referenced using the CGCS2000 geographic coordinate system. Policy and regulatory data include, but are not limited to: the scale of planned construction land space, annual land use plans, land consolidation and upgrading, adjustment prices of cultivated land occupation and compensation indicators, comprehensive land prices of expropriated areas, compensation standards for attachments and seedlings on expropriated land, and policy documents on forest vegetation restoration fee collection standards. All of the above data are stored in a relational database.

3. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 2, characterized in that: The formula for calculating available land is: Available land = Controlled detailed planning land - Land supply - Land that has been planned but not implemented - Construction land planning permit - Construction project planning permit - Scope of selected project site - Unusable land + Land acquired and stored + Other usable land + Inefficient land + Idle land. Among them, other usable land and unusable land with disputes need to be investigated and measured by a third-party agency. Spatial overlay analysis algorithm is used: PostGIS space overlay st_collect(), PostGIS spatial clipping st_difference().

4. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 3, characterized in that: Planning site selection conditions include, but are not limited to, land use nature, land area, site selection area, and surrounding supporting facilities, and selecting suitable site plots from available land. Meanwhile, advanced site selection conditions can be set to allow adjacent available land parcels to be merged for site selection, and two rules can be selected: area priority and land use priority. Among them, the site selection area refers to the administrative division, functional area, industrial park, and user-defined site selection range, and the surrounding facilities include transportation, medical, commercial, and educational public facilities; The query for nearby facilities uses PostGIS's minimum distance calculation function ST_DistanceSphere(), with the unit being meters.

5. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 4, characterized in that: Step four can be omitted after the approval and implementation of the China Land Spatial Planning.

6. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 5, characterized in that: Step five further analyzes the area and proportion of cultivated land and forest land in agricultural land.

7. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 6, characterized in that: The spatial overlay analysis algorithm is used to calculate the area and proportion of construction land, agricultural land, and unused land for each proposed site. Further analysis of agricultural land reveals the area and proportion of arable land and forest land. Postgis space overlay st_collect(); Land development cost calculation: The cost of purchasing farmland quotas is calculated based on the local farmland compensation balance quota adjustment price. The cost of land acquisition is calculated based on the area of ​​agricultural land, construction land, and unused land. Compensation costs are calculated based on local standards for compensation for attachments and crops on the land acquired during land expropriation. The cost of occupying forest land is calculated based on the local forest vegetation restoration fee collection standards. The above-mentioned costs combined constitute the land development cost of the proposed site for this invention. The compensation standard policy documents are stored in the database for easy updating and dynamic maintenance, and the cost calculation model can dynamically calculate land development costs based on the policy.

8. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 7, characterized in that: A dynamic time-dimensional factor and a machine learning prediction model are introduced into the original formula for calculating available land: Dynamic available land formula: S 动态可用地 = (Controlled detailed planning land use - ∑ occupied land + ∑ revitalizable land) × δ(t) where δ(t) is the time decay factor (predicted by an LSTM model trained on historical land development rates, reflecting the land supply trend in the next 1-3 years). By analyzing satellite remote sensing imagery using convolutional neural networks (CNNs), inefficient land use and idle land boundaries can be automatically identified, replacing traditional manual surveys and improving data acquisition efficiency (accuracy ≥ 90%).

9. The project planning and site selection method based on available land analysis and land development cost estimation according to claim 7, characterized in that: A single-factor evaluation matrix R is constructed using expert scoring, and the comprehensive cost level (low / medium / high) is output by combining the principle of maximum membership. Step 7 Extension: Multi-objective genetic algorithm sorting Design a comprehensive location selection index (LSI) that integrates multi-dimensional constraints: ; : Construction land ratio score (higher is better, weight α=0.4); Cost grade score (lower is better, weight β=0.3); Consistency score between the two regulations (compliance is 100 points, weight γ=0.2); : Terrain slope score (<5° is 100 points, weight δ=0.1).

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