Inefficient land identification method and system

Abstract

The present application discloses a method and system for identifying low-efficiency land, which includes: obtaining relevant data of an area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data; based on the land use data, identifying a first low-efficiency land in the area to be identified; based on a distance threshold and the first low-efficiency land, generating a plurality of fused patches, so as to identify a second low-efficiency land that is contiguous in the area to be identified according to the plurality of fused patches; based on the user equipment signaling data, geographic data, land use data and the second low-efficiency land, determining a to-be-developed area of ​​the low-efficiency land, wherein the to-be-developed area is used for site selection and construction related to the area to be identified, and can take into account both the identification accuracy and the identification range of the low-efficiency land, so as to accurately identify the to-be-developed area of ​​the low-efficiency land in the area to be identified, thereby improving the efficiency and effect of the construction and transformation carried out on the area to be identified.

Description

Technical Field

[0001] The present application relates to the technical field of land site selection, and in particular to a method and system for identifying inefficient land use. Background Art

[0002] At present, when it is necessary to construct or renovate a certain area, it is usually necessary to identify inefficient land with low development utilization rate in the area to provide guidance for construction and renovation, so as to improve the efficiency and effect of subsequent construction and renovation. In the prior art, when it is necessary to identify inefficient land in a certain area, the land use situation of the area is usually directly judged based on the public land survey data to determine whether the area has been fully utilized. If not, the area is judged as inefficient land. For example, it can be judged whether the area has been fully constructed based on whether the building density, volume ratio, etc. of the area meet the standards, and then it can be judged whether the area is inefficient land.

[0003] However, since the inefficient land identified by the existing technology is directly based on the land survey data, if the recognition accuracy needs to be pursued, the identified area needs to be limited to a very small range in order to directly use the land survey data, which means that it is difficult to ensure a balance between the recognition accuracy and the recognition range. Summary of the invention

[0004] In order to solve the above-mentioned technical problems, the embodiment of the present application proposes a method and system for identifying low-efficiency land, which can take into account both the recognition accuracy and recognition range of low-efficiency land, so as to accurately identify the undeveloped areas of low-efficiency land in the area to be identified, thereby improving the efficiency and effectiveness of the construction and reconstruction of the area to be identified.

[0005] In a first aspect, an embodiment of the present application provides a method for identifying inefficient land use, including:

[0006] Acquire relevant data of the area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data;

[0007] Based on the land use data, identifying a first inefficient land use in the to-be-identified area;

[0008] Based on the distance threshold and the first inefficient land, a plurality of fused image patches are generated, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused image patches;

[0009] Based on the user equipment signaling data, the geographic data, the land use data and the second inefficient land, an area of ​​inefficient land to be developed is determined, wherein the area to be developed is used for site selection and construction of land related to the area to be identified.

[0010] Furthermore, the generating of a plurality of fused patches based on the distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused patches, includes:

[0011] Taking the first low-efficiency land as a patch, and fusing the patches according to the distance threshold to obtain the plurality of fused patches, wherein each fused patch indicates a corresponding contiguous area;

[0012] Using the natural breakpoint method, the plurality of fused image patches are graded in descending order of the indicated contiguous areas to obtain a plurality of contiguous area grades;

[0013] Determine the land use range based on the contiguous areas corresponding to each fused image patch in the highest contiguous area level, wherein the land use range is composed of the maximum value and the minimum value of the contiguous areas corresponding to each fused image patch;

[0014] According to the land use scope, the second inefficient land use is identified in the area to be identified.

[0015] Furthermore, the determining of the to-be-developed area of ​​the low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes:

[0016] Expand the second low-efficiency land in a preset expansion manner to obtain various potential assessment areas;

[0017] Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an evaluation value of each potential assessment area;

[0018] Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

[0019] Further, the evaluating each potential assessment area based on the user equipment signaling data, the geographic data and the land use data to obtain the evaluation value of each potential assessment area includes:

[0020] Based on the user equipment signaling data, the geographic data and the land use data of each potential assessment area, the indicator calculation methods corresponding to the multiple development potential indicators are used to calculate and obtain multiple development potential indicator values ​​of each potential assessment area;

[0021] Normalizing the multiple development potential index values ​​of each potential assessment area to obtain a normalized development potential index value;

[0022] Determine the weights corresponding to the multiple development potential indicators by using the Delphi method;

[0023] Based on the weights corresponding to the multiple development potential indicators and the normalized development potential indicator value of each potential assessment area, a weighted calculation is performed to obtain the assessment value of each potential assessment area.

[0024] Furthermore, the step of identifying a first inefficient land in the to-be-identified area based on the land use data includes:

[0025] Using the indicator calculation methods corresponding to the multiple land use indicators, the land use indicator values ​​corresponding to the multiple land use indicators are calculated according to the land use data;

[0026] Dividing the area to be identified into a plurality of sub-areas;

[0027] For each sub-area, based at least on the land use index values ​​corresponding to each of the multiple land use indexes, a comprehensive score of each plot in the sub-area is calculated, and all plots in the sub-area whose comprehensive score is at the minimum score level are regarded as inefficient land in the sub-area;

[0028] The low-efficiency land in each of the several sub-areas is determined as the first low-efficiency land.

[0029] Furthermore, before calculating the comprehensive score of each plot in the sub-area based on the land use index values ​​corresponding to each of the multiple land use indexes, the method further includes:

[0030] Determine the weights corresponding to the multiple land use indicators;

[0031] The calculating of the comprehensive score of each plot in the sub-area based on at least the land use index values ​​corresponding to each of the multiple land use indexes comprises:

[0032] The multiple land use indicators are divided into positive indicators and negative indicators, and the land use indicator values ​​corresponding to the positive indicators and the land use indicator values ​​corresponding to the negative indicators are normalized to obtain normalized land use indicator values;

[0033] Based on the weights corresponding to the multiple land use indicators and the normalized land use indicator value, a weighted calculation is performed to obtain a comprehensive score for each plot in the sub-area.

[0034] Furthermore, the land use data is obtained after data cleaning, deduplication, spatial positioning and coordinate system processing of the initial land use data, wherein the initial land use data is obtained by performing OCR recognition on the land use information image.

[0035] Furthermore, the geographic data includes remote sensing image data, POI data and map panoramic data, wherein the map panoramic data is used to analyze the building facilities in the area to be identified.

[0036] In a second aspect, an embodiment of the present application provides a system for identifying inefficient land use, including:

[0037] A data acquisition module, used to acquire relevant data of the area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data;

[0038] A first identification module, configured to identify a first inefficient land in the to-be-identified area based on the land use data;

[0039] A second identification module is used to generate a plurality of fused image patches based on a distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused image patches;

[0040] The third identification module is used to determine the area to be developed of the inefficient land based on the user equipment signaling data, the geographic data, the land use data and the second inefficient land, wherein the area to be developed is used for the site selection and construction of land related to the area to be identified.

[0041] Furthermore, the determining of the to-be-developed area of ​​the low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes:

[0042] Expand the second low-efficiency land in a preset expansion manner to obtain various potential assessment areas;

[0043] Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an evaluation value of each potential assessment area;

[0044] Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

[0045] In summary, the embodiments of the present application have at least the following beneficial effects:

[0046] By adopting the embodiments of the present application, it is possible to take into account both the recognition accuracy and the recognition range of low-efficiency land, so as to accurately identify the undeveloped areas of low-efficiency land in the area to be identified, thereby improving the efficiency and effectiveness of the construction and reconstruction of the area to be identified. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of the method for identifying inefficient land use provided in an embodiment of the present application;

[0048] Figure 2A This is a partial schematic diagram of the low-efficiency land identification provided by the embodiment of the present application;

[0049] Figure 2B This is another partial schematic diagram of low-efficiency land identification provided by an embodiment of the present application;

[0050] Figure 3 It is a structural diagram of the low-efficiency land identification system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0052] In the description of the present application, the terms "first", "second", "third", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, features defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, the meaning of "multiple" is two or more. In the description of the present application, the term "including" and its variations are open inclusions, i.e., "including but not limited to". The term "based on" means "at least partially based on". The term "according to" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments".

[0053] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0054] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meaning as those commonly understood by those skilled in the art. The terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0055] First, see Figure 1 , shows a schematic flow chart of a method for identifying inefficient land use provided in an embodiment of the present application, the method comprising steps S101-S104, which are specifically as follows:

[0056] S101, obtaining relevant data of a to-be-identified area, wherein the relevant data includes land use data, geographic data and user equipment signaling data.

[0057] It should be noted that the user equipment signaling data refers to the signaling data generated by the user equipment when each user located in the to-be-identified area uses the user equipment, and the signaling data is called after the user's permission.

[0058] S102: Based on the land use data, identify a first inefficient land in the area to be identified.

[0059] S103: Generate a plurality of fused image patches based on a distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the area to be identified according to the plurality of fused image patches.

[0060] It is understandable that contiguous inefficient land can refer to large tracts of land that are continuously distributed and have low utilization efficiency. By taking a series of measures, such as replanning, infrastructure construction, and environmental governance, the utilization efficiency and value of these lands can be effectively improved, thereby promoting economic and social development.

[0061] S104, determining an area of ​​low-efficiency land to be developed based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land, wherein the area to be developed is used for site selection and construction of land related to the area to be identified.

[0062] In this embodiment, an initial identification is first performed in the area to be identified through land use data to obtain the first inefficient land to ensure the accuracy of identification, and then the range of the identified second inefficient land is adjusted by adjusting the distance threshold to ensure that the identification range can meet the user's requirements and obtain the second inefficient land. Finally, further processing is performed based on the user equipment signaling data, geographic data, land use data and the second inefficient land, so that the final area to be developed can take into account both the identification accuracy and the identification range.

[0063] Exemplarily, the land use data may include the data of industrial land, logistics and storage land, and commercial service facility land in the latest land change survey data. For example, in ArcMap software, import the land change survey data of the area to be identified, click "Select By Attributes", select the land parcels with the land class name attributes of industrial land, logistics and storage land, and commercial service facility land, and after selecting OK, right-click the latest land change survey data, select "Data", "Export Data", select "Selected Features" in the pop-up dialog box, and save it as a new vector file as land use data.

[0064] In an optional implementation, the generating of a plurality of fused patches based on the distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused patches, includes:

[0065] The first low-efficiency land is taken as a patch, and the patches are fused according to the distance threshold to obtain the plurality of fused patches, wherein each fused patch indicates a corresponding contiguous area; illustratively, the distance threshold may be 50m; the distance threshold may have an impact on industrial activities.

[0066] The natural breakpoint method is adopted to grade the plurality of fused image patches in the order of the indicated contiguous areas from large to small, so as to obtain a plurality of contiguous area grades.

[0067] The land use range is determined based on the contiguous areas corresponding to the fused patches in the highest contiguous area level, wherein the land use range is composed of the maximum and minimum values ​​of the contiguous areas corresponding to the fused patches.

[0068] According to the land use scope, the second inefficient land use is identified in the area to be identified.

[0069] In an optional implementation manner, determining the to-be-developed area of ​​the low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes:

[0070] The second low-efficiency land is expanded according to a preset expansion method to obtain various potential assessment areas.

[0071] Exemplarily, the second low-efficiency land is expanded according to a preset expansion method to obtain various potential assessment areas, which may include: if at least two pieces of second low-efficiency land are located within the same administrative area, then the administrative area is used as the potential assessment area obtained by expanding the at least two pieces of second low-efficiency land.

[0072] Exemplarily, the preset expansion method may include: expanding according to a preset expansion ratio.

[0073] Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an assessment value of each potential assessment area.

[0074] Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

[0075] Exemplarily, the natural breakpoint method can be used to grade the assessment values ​​of each potential assessment area (for example, into four levels: high, relatively high, relatively low, and low), and the potential assessment area with the highest graded result can be screened out from each potential assessment area as the area to be developed.

[0076] In an optional implementation, the evaluating each potential assessment area based on the user equipment signaling data, the geographic data and the land use data to obtain an evaluation value of each potential assessment area includes:

[0077] Based on the user equipment signaling data, the geographic data and the land use data of each potential assessment area, an indicator calculation method corresponding to a plurality of development potential indicators is adopted to perform calculations to obtain a plurality of development potential indicator values ​​for each potential assessment area.

[0078] The multiple development potential index values ​​of each potential assessment area are normalized to obtain a normalized development potential index value.

[0079] The Delphi method is used to determine the weights corresponding to the multiple development potential indicators.

[0080] Based on the weights corresponding to the multiple development potential indicators and the normalized development potential indicator value of each potential assessment area, a weighted calculation is performed to obtain the assessment value of each potential assessment area.

[0081] Exemplarily, multiple development potential indicators can be determined by socio-economic parameter dimensions and environmental parameter dimensions, for example, as shown in Table 1 below.

[0082] Table 1

[0083]

[0084] Specifically:

[0085] (1) Property rights complexity: Using real estate registration data and housing data, calculate the ratio of unregistered households to the total number of households in the area, which is used as the characteristic value of the property rights complexity of the area.

[0086] (2) Aggregation of inefficient plots: The aggregation of inefficient land in a region reflects the degree to which inefficient land in the region is clustered and connected. Its size is characterized by calculating the aggregation index, which is obtained by calculating the ratio of the common boundary length between plot pixels to the maximum common boundary length.

[0087] (3) Population density: The higher the population density in the area, the more people (including employment groups and residential groups) will be affected by the area transformation, accompanied by higher social costs (high communication costs) and economic costs (high compensation for suspension of work, compensation for demolition, etc.). The population data of the land is obtained through mobile phone signaling, and the population density is calculated using the formula "population density = plot population size / land area".

[0088] (4) Enterprise density: The higher the enterprise density in the area, the more enterprises will be affected during the transformation process, requiring more relocation compensation, and the shutdown of enterprises will also cause the economic contraction of the area. By using the business registration data of enterprises, the annual report addresses of enterprises are geocoded, and the enterprises are mapped to space. The enterprise density is calculated using the formula "enterprise density = number of enterprises in the plot / land area".

[0089] (5) Benchmark land price: Obtain the benchmark land price data from the land use data and calculate the realized land price level using the formula “realized land price level = commercial land price + industrial land price + residential land price”.

[0090] (6) Whether it involves historical and cultural protection: Investigate and obtain the protection scope of historical and cultural blocks and historical and cultural villages. If the area involves historical and cultural protection, the development potential is low, which is expressed by calculating the proportion of low-efficiency land included in the historical and cultural protection area to the total low-efficiency land in the area.

[0091] (7) Land transfer income: Calculate the average unit price of the same type of land transferred within the potential assessment area and the surrounding 3 km area in the past three years.

[0092] (8) Industrial tax revenue: Divide the fishing net into 500m*500m and calculate the total tax revenue within the fishing net. Use the spatial statistics tool - cluster distribution mapping - hot spot analysis (Getis-Ord Gi*) function in ArcMAP software, with the input field being the total tax revenue within the fishing net, to generate a new layer A. Based on the tax difference before and after the transformation, convert the analysis results in the new layer A into a score. The higher the score, the greater the potential for tax revenue increase after the transformation. Assign the converted score to the potential assessment area, which is the "industrial tax revenue".

[0093] (9) Infrastructure benefits: Divide the fishing net into 500m*500m, and calculate the number of transportation stations (bus stations), educational facilities (primary schools and kindergartens), medical institutions (hospitals, health centers, clinics, etc.), shopping facilities (supermarkets, convenience stores, canteens, etc.), and catering facilities (all catering facilities) within the fishing net. Use the spatial statistics tool - cluster distribution mapping - hot spot analysis (Getis-Ord Gi*) function in ArcMAP software, and input the fields of transportation stations, schools, medical institutions, shopping facilities, and catering facilities within the fishing net to generate a new layer A. According to the difference in the number of facilities before and after the transformation, the analysis results in the new layer A are converted into scores. The higher the score, the greater the potential for increasing the number of facilities after the transformation. The converted score is assigned to the potential assessment area, which is the "infrastructure benefit".

[0094] (10) Ecological land proportion: The proportion of the sum of the areas of forests, gardens, water areas and grasslands in the area to the total area of ​​the area is analyzed by remote sensing image data to obtain the ecological land proportion.

[0095] (11) Number of ancient and famous trees: Calculate the number of ancient and famous trees in the area using data on ancient and famous trees.

[0096] (12) Potential for urban environmental transformation: Using map panorama data and the visual image semantic segmentation technology of a deep learning fully convolutional network, we analyze the visible proportions of buildings, infrastructure and other elements in the street view images contained in the map panorama data, determine the degree of damage to building facades and infrastructure, and evaluate the street space environment order as the potential for urban environmental transformation.

[0097] In an optional implementation, the identifying a first inefficient land in the to-be-identified area based on the land use data includes:

[0098] Using the indicator calculation methods corresponding to the multiple land use indicators, the land use indicator values ​​corresponding to the multiple land use indicators are calculated according to the land use data.

[0099] The area to be identified is divided into a plurality of sub-areas.

[0100] For each sub-area, the comprehensive score of each plot in the sub-area is calculated based on at least the land use indicator values ​​corresponding to each of the multiple land use indicators, and all plots in the sub-area whose comprehensive score is at the minimum score level are regarded as inefficient land in the sub-area.

[0101] The low-efficiency land in each of the several sub-areas is determined as the first low-efficiency land.

[0102] For example, several sub-areas may be divided according to administrative divisions, for example, according to various counties in a city, and each county is a sub-area.

[0103] Exemplarily, the minimum score level refers to the comprehensive score of the plots that are in the last preset percentage after the comprehensive scores of the plots are arranged from large to small. For example, the 20% with the smallest scores can be used as the minimum score level.

[0104] Exemplarily, multiple land use indicators can be determined by four aspects: planning compliance, land use intensity, carrier conditions, and output efficiency. Among them, the indicators for commercial land in the area to be identified may be different from those for industrial land and logistics warehousing land, as shown in Table 2 below.

[0105] Table 2

[0106]

[0107] Specifically:

[0108] (1) Consistency of planned use: For example, if a plot of land is industrial land, and its planned use is commercial land and industrial land, the planned industrial land area / total plot area is calculated to obtain the proportion of land that is consistent with the planned and current status, which is the value of "consistency of planned use".

[0109] (2) Ownership status: Calculate the ratio of the number of structures with real estate ownership certificates to the total number of structures within the plot.

[0110] (3) Floor area ratio: In the house surface data, multiply the floor attribute by the building base area to obtain the building area, assign the building area to the land change survey data, and then divide the sum of the building areas in the plot by the plot area to obtain the plot’s floor area ratio.

[0111] (4) Building density: Assign the building surface area to the land change survey data, and then divide the sum of the building surface areas in the plot by the plot area to obtain the building density of the plot.

[0112] (5) Building age: Assign the average building age of the building surface to the land change survey data, and divide it according to the design service life and actual construction age of the building structure. The specific calculation method is shown in Table 3.

[0113] Table 3

[0114]

[0115] (6) Proportion of dangerous buildings: In the house surface data, multiply the floor attribute by the building base area to obtain the building area, assign the building structure and building area of ​​the house surface to the land change survey data, and calculate the proportion of the building area with the building structure of "E, shed, broken" on the plot to the total building area of ​​the plot to obtain the proportion of dangerous buildings on the plot. Among them, "E" represents a simple structure building.

[0116] (7) Infrastructure completeness: The value of “Infrastructure quantity” within the preset range is used as the infrastructure completeness.

[0117] (8) Average employed population per unit area / average operating income per unit area: Average employed population per unit area of ​​a community = number of employees in the community / community area; Average operating income per unit area = community operating income / community area.

[0118] (9) Tax per lot: Using vectorized corporate tax data, we screen out corporate data from the construction, manufacturing, and transportation industries based on their industry codes. We then assign the screened corporate tax data to the land change survey data to determine the total tax amount for the plot.

[0119] (10) Commercial property rental prices: The commercial and business building information data of each town and street after vectorization is used. Considering the incomplete coverage of the survey data and other factors, the commercial and business building information data of each town and street is processed by the Kriging interpolation method. In ArcMap software, click the Geostatistical Wizard button on the Geostatistical Analyst toolbar, select Kriging / Cokriging, select the commercial and business building information data of each town and street and the monthly rent (unit is RMB / square meter) attribute field, select the ordinary Kriging method, select the default parameters in the Semivariogram / Covariance Modeling dialog box, and click Finish to generate a new layer A. Assign the new layer A to the land change survey data through the spatialjoin function. The target features are the land change survey data, the join features are the new layer A, the join operation is "JOIN_ONE_TO_MANY", and the match option is "INTERSECT". In the field mapping of the join feature, right-click the monthly rent field - Merge Rules - Average, click OK to generate a new layer B. View the newly generated monthly rent field in the new layer B, and its value is the rental price of the commercial property of the plot.

[0120] (11) Conformity of industry orientation: Extract the highest revenue industry type from the current community's four economic census industry revenue data, which is the dominant industry type of the community. Use geocoding technology to vectorize it into the "current industry type" layer. The planned industry type is based on the industrial planning data. Perform the "Coverage" operation on the current industry type data and the planned industry type data in ArcMap, filter the attribute values ​​of the resulting layer, and retain the spots where the planned industry type is consistent with the current industry type. Then use the "Spatial Join" function in ArcMap, with the target features as the land change survey data, the join features as the spots filtered in the previous step, and the join operation as "JOIN_ONE_TO_MANY". In the field mapping of the join feature, right-click the "Land Type Area 2" attribute field, select "Merge Rule - Sum", select "INTERSECT" in the Match Option, and click OK to generate a new layer. Calculate the ratio of the "land type area 2" attribute value of the new layer to the "land type area" attribute value of the original land change survey data to obtain the value of industry orientation compliance.

[0121] (12) Scale status: Use the vectorized data of the four-level enterprises and assign them to the land change survey data. The target features are the land change survey data, the join features are the four-level enterprise data, the join operation is "JOIN_ONE_TO_MANY", select "INTERSECT" for the match option, click OK, and generate a new layer A. Check "JOIN_COUNT" in the new layer and change its name to "Scale status". Its value is the number of the four-level enterprises in the land.

[0122] (13) Technical level / development potential: Use the vectorized data of the four-level enterprises and the industrial and commercial registration enterprise data, select the high-tech enterprise and listed enterprise data according to the enterprise qualification label, and assign the high-tech enterprise / listed enterprise data to the land change survey data. The target features are the land change survey data, the join features are the high-tech enterprise / listed enterprise data, the join operation is "JOIN_ONE_TO_MANY", select "INTERSECT" for the match option, click OK, and generate a new layer A. View "JOIN_COUNT" in the new layer and change its name to "Technical level / development potential". Its value is the number of high-tech enterprises / listed enterprises in the land.

[0123] (14) Industry type: Use the vector data of industrial platforms and major innovation platforms at or above the municipal level, and assign them to the land change survey data. The target features are the land change survey data, and the join features are the vector data of industrial platforms and major innovation platforms at or above the municipal level. The join operation is "JOIN_ONE_TO_MANY", and the match option is "INTERSECT". Click OK to generate a new layer A. Check "JOIN_COUNT" in the new layer and rename it to "Industry type". If the value is not 0, it means that it is located within the industrial platforms and major innovation platforms at or above the municipal level. If it is 0, it means that it is located outside the industrial platforms and major innovation platforms at or above the municipal level.

[0124] In an optional implementation, before calculating the comprehensive score of each plot in the sub-area based at least on the land use index values ​​corresponding to each of the multiple land use indexes, the method further includes:

[0125] Determine the weights corresponding to each of the multiple land use indicators.

[0126] The calculating of the comprehensive score of each plot in the sub-area based on at least the land use index values ​​corresponding to each of the multiple land use indexes comprises:

[0127] The multiple land use indicators are divided into positive indicators and negative indicators, and the land use indicator values ​​corresponding to the positive indicators and the land use indicator values ​​corresponding to the negative indicators are normalized to obtain normalized land use indicator values.

[0128] Based on the weights corresponding to the multiple land use indicators and the normalized land use indicator value, a weighted calculation is performed to obtain a comprehensive score for each plot in the sub-area.

[0129] Alternatively, you can use GeoPandas in Python to read all the data containing land use indicator values, then use the merge() function of Pandas to merge all the land use indicator values, and then normalize the land use indicator values ​​according to the positive and negative indicators respectively.

[0130] In an optional embodiment, the land use data is obtained by performing data cleaning and deduplication processing, spatial positioning processing and coordinate system processing on the initial land use data, wherein the initial land use data is obtained by performing OCR recognition on the land use information image.

[0131] For example, see Figure 2A and Figure 2BFor the images of paper documents collected, OCR (Optical Character Recognition) technology is used to quickly identify and extract text. OCR technology refers to a technology that uses optical technology to recognize text. This technology obtains text information in the image, uses various pattern recognition algorithms to analyze the text morphological features, and then determines the standard encoding of the text, and stores it as a text file in a universal format, which is convenient for users to edit and process the information.

[0132] For example, see Figure 2 A and Figure 2B Data cleaning and deduplication processing can include the Simhash algorithm, which is a binary encoding algorithm that maps text data to a fixed length. After obtaining the Simhash value of the corresponding text, the Hamming distance can be used to measure the similarity between documents. Specifically, it includes the following steps:

[0133] a. Initialization: Input the text content to be recognized, generate a signature of length L and a set of L-dimensional vectors, and initialize the values ​​of the signature and vector to 0.

[0134] b. Word segmentation: Perform word segmentation on the keywords in the text content and count the number of times the segmented words appear in the text. This number is used as the weight value of the feature vector.

[0135] c. Hash: Calculate the hash value of the eigenvalue based on the hash function to obtain an L-dimensional signature value, which is a binary signature.

[0136] d. Weighting: Based on the binary signature, weight each position in the vector. If the i-th bit of the binary signature is 0, subtract the corresponding weight value obtained in step b from the i-th position of the vector. If the i-th bit of the binary signature is 1, add the corresponding weight value obtained in step b to the i-th position of the vector.

[0137] e. Dimensionality reduction: Finally, traverse the vector and set the values ​​of the corresponding bits in the signature initialized in step a for the bits in the vector that are greater than 0 to 1, otherwise set them to 0.

[0138] f. Output: Output the signature in step e as the final signature value. The difference between the final signature values ​​of two different documents is the Hamming distance.

[0139] For example, see Figure 2 A and Figure 2B In the spatial location processing, for non-vector data, such as corporate tax data, four-level enterprise data, factory survey data, etc., the geocoding technology in the map software can be used to spatialize the company registration or business address and factory address to achieve rapid spatial location of non-vector data.

[0140] In an optional implementation, the geographic data includes remote sensing image data, POI data and map panoramic data, wherein the map panoramic data is used to analyze the building facilities in the area to be identified.

[0141] On the second aspect, accordingly, the embodiments of the present application also provide a low-efficiency land identification system, which can implement all the processes of the low-efficiency land identification method provided in the above embodiments.

[0142] See also Figure 3 , showing a schematic diagram of the structure of the low-efficiency land identification system provided in an embodiment of the present application, including:

[0143] The data acquisition module 301 is used to acquire relevant data of the area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data.

[0144] The first identification module 302 is used to identify a first inefficient land in the area to be identified based on the land use data.

[0145] The second identification module 303 is used to generate a plurality of fused patches based on a distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the area to be identified according to the plurality of fused patches.

[0146] The third identification module 304 is used to determine the area to be developed of the low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land, wherein the area to be developed is used for the site selection and construction of land related to the area to be identified.

[0147] In an optional implementation, the generating of a plurality of fused patches based on the distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused patches, includes:

[0148] The first low-efficiency land is taken as a patch, and the patches are fused according to the distance threshold to obtain the plurality of fused patches, wherein each fused patch indicates a corresponding contiguous area.

[0149] The natural breakpoint method is adopted to grade the plurality of fused image patches in the order of the indicated contiguous areas from large to small, so as to obtain a plurality of contiguous area grades.

[0150] The land use range is determined based on the contiguous areas corresponding to the fused patches in the highest contiguous area level, wherein the land use range is composed of the maximum and minimum values ​​of the contiguous areas corresponding to the fused patches.

[0151] According to the land use scope, the second inefficient land use is identified in the area to be identified.

[0152] In an optional implementation manner, determining the to-be-developed area of ​​the low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes:

[0153] The second low-efficiency land is expanded according to a preset expansion method to obtain various potential assessment areas.

[0154] Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an assessment value of each potential assessment area.

[0155] Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

[0156] In an optional implementation, the evaluating each potential assessment area based on the user equipment signaling data, the geographic data and the land use data to obtain an evaluation value of each potential assessment area includes:

[0157] Based on the user equipment signaling data, the geographic data and the land use data of each potential assessment area, an indicator calculation method corresponding to a plurality of development potential indicators is adopted to perform calculations to obtain a plurality of development potential indicator values ​​for each potential assessment area.

[0158] The multiple development potential index values ​​of each potential assessment area are normalized to obtain a normalized development potential index value.

[0159] The Delphi method is used to determine the weights corresponding to the multiple development potential indicators.

[0160] Based on the weights corresponding to the multiple development potential indicators and the normalized development potential indicator value of each potential assessment area, a weighted calculation is performed to obtain the assessment value of each potential assessment area.

[0161] In an optional implementation, the identifying a first inefficient land in the to-be-identified area based on the land use data includes:

[0162] Using the indicator calculation methods corresponding to the multiple land use indicators, the land use indicator values ​​corresponding to the multiple land use indicators are calculated according to the land use data.

[0163] The area to be identified is divided into a number of sub-areas.

[0164] For each sub-area, the comprehensive score of each plot in the sub-area is calculated based on at least the land use indicator values ​​corresponding to each of the multiple land use indicators, and all plots in the sub-area whose comprehensive score is at the minimum score level are regarded as inefficient land in the sub-area.

[0165] The low-efficiency land in each of the several sub-areas is determined as the first low-efficiency land.

[0166] In an optional embodiment, the system further includes:

[0167] The first weight determination module is used to determine the weights corresponding to each of the multiple land use indicators before calculating the comprehensive score of each plot in the sub-area based at least on the land use indicator values ​​corresponding to each of the multiple land use indicators.

[0168] The calculating of the comprehensive score of each plot in the sub-area based on at least the land use index values ​​corresponding to each of the multiple land use indexes comprises:

[0169] The multiple land use indicators are divided into positive indicators and negative indicators, and the land use indicator values ​​corresponding to the positive indicators and the land use indicator values ​​corresponding to the negative indicators are normalized to obtain normalized land use indicator values.

[0170] Based on the weights corresponding to the multiple land use indicators and the normalized land use indicator value, a weighted calculation is performed to obtain a comprehensive score for each plot in the sub-area.

[0171] In an optional embodiment, the land use data is obtained by performing data cleaning and deduplication processing, spatial positioning processing and coordinate system processing on the initial land use data, wherein the initial land use data is obtained by performing OCR recognition on the land use information image.

[0172] In an optional implementation, the geographic data includes remote sensing image data, POI data and map panoramic data, wherein the map panoramic data is used to analyze the building facilities in the area to be identified.

[0173] In summary, the embodiments of the present application have at least the following beneficial effects:

[0174] By adopting the embodiments of the present application, it is possible to take into account both the recognition accuracy and the recognition range of low-efficiency land, so as to accurately identify the undeveloped areas of low-efficiency land in the area to be identified, thereby improving the efficiency and effectiveness of the construction and reconstruction of the area to be identified.

[0175] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary hardware platform, and of course, it can also be implemented entirely by hardware. Based on such an understanding, all or part of the contribution of the technical solution of the present application to the background technology can be embodied in the form of a software product, and the computer software product can be stored in a storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application or some parts of the embodiments.

[0176] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications are also considered to be within the scope of protection of the present application.

Claims

1. A method for identifying inefficient land use, characterized in that: include: Acquire relevant data of the area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data; Based on the land use data, identifying a first inefficient land use in the to-be-identified area; Based on the distance threshold and the first inefficient land, a plurality of fused patches are generated to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused patches, wherein the contiguous range of the identified second inefficient land is adjusted by adjusting the distance threshold; Determine a to-be-developed area of ​​the inefficient land based on the user equipment signaling data, the geographic data, the land use data and the second inefficient land, wherein the to-be-developed area is used for site selection and construction of land related to the area to be identified; The step of generating a plurality of fused image patches based on the distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused image patches, includes: Taking the first low-efficiency land as a patch, and fusing the patches according to the distance threshold to obtain the plurality of fused patches, wherein each fused patch indicates a corresponding contiguous area; Using the natural breakpoint method, the plurality of fused image patches are graded in descending order of the indicated contiguous areas to obtain a plurality of contiguous area grades; Determine the land use range based on the contiguous areas corresponding to each fused image patch in the highest contiguous area level, wherein the land use range is composed of the maximum value and the minimum value of the contiguous areas corresponding to each fused image patch; According to the land use scope, identifying the second low-efficiency land in the to-be-identified area; The step of identifying a first inefficient land in the to-be-identified area based on the land use data includes: Using the indicator calculation method corresponding to each of the multiple land use indicators, the land use indicator values ​​corresponding to each of the multiple land use indicators are calculated according to the land use data, wherein the multiple land use indicators include land use intensity and / or carrier conditions, the land use intensity includes volume ratio and / or building density, and the carrier conditions include building age, proportion of dilapidated buildings and / or completeness of infrastructure; Dividing the area to be identified into a plurality of sub-areas; For each sub-area, based at least on the land use index values ​​corresponding to each of the multiple land use indexes, a comprehensive score of each plot in the sub-area is calculated, and all plots in the sub-area whose comprehensive score is at the minimum score level are regarded as inefficient land in the sub-area; The low-efficiency land in each of the several sub-areas is determined as the first low-efficiency land.

2. The method for identifying inefficient land use according to claim 1, characterized in that: The determining of a to-be-developed area of ​​low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes: Expand the second low-efficiency land in a preset expansion manner to obtain various potential assessment areas; Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an evaluation value of each potential assessment area; Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

3. The method for identifying inefficient land use according to claim 2, characterized in that: The step of evaluating each potential assessment area based on the user equipment signaling data, the geographic data, and the land use data to obtain an assessment value of each potential assessment area includes: Based on the user equipment signaling data, the geographic data and the land use data of each potential assessment area, the indicator calculation methods corresponding to the multiple development potential indicators are used to calculate and obtain multiple development potential indicator values ​​of each potential assessment area; Normalizing the multiple development potential index values ​​of each potential assessment area to obtain a normalized development potential index value; Determine the weights corresponding to the multiple development potential indicators by using the Delphi method; Based on the weights corresponding to the multiple development potential indicators and the normalized development potential indicator value of each potential assessment area, a weighted calculation is performed to obtain the assessment value of each potential assessment area.

4. The method for identifying inefficient land use according to claim 1, wherein: Before calculating the comprehensive score of each plot in the sub-area based on at least the land use index values ​​corresponding to each of the multiple land use indexes, the method further includes: Determine the weights corresponding to the multiple land use indicators; The calculating of the comprehensive score of each plot in the sub-area based on at least the land use index values ​​corresponding to each of the multiple land use indexes comprises: The multiple land use indicators are divided into positive indicators and negative indicators, and the land use indicator values ​​corresponding to the positive indicators and the land use indicator values ​​corresponding to the negative indicators are normalized to obtain normalized land use indicator values; Based on the weights corresponding to the multiple land use indicators and the normalized land use indicator value, a weighted calculation is performed to obtain a comprehensive score for each plot in the sub-area.

5. The method for identifying low-efficiency land use according to any one of claims 1 to 4, characterized in that: The land use data is obtained after data cleaning, deduplication, spatial positioning and coordinate system processing are performed on the initial land use data, wherein the initial land use data is obtained by performing OCR recognition on the land use information image.

6. The method for identifying low-efficiency land use according to any one of claims 1 to 4, characterized in that: The geographic data includes remote sensing image data, POI data and map panorama data, wherein the map panorama data is used to analyze the building facilities in the area to be identified.

7. A system for identifying inefficient land use, characterized in that: include: A data acquisition module, used to acquire relevant data of the area to be identified, wherein the relevant data includes land use data, geographic data and user equipment signaling data; A first identification module, configured to identify a first inefficient land in the to-be-identified area based on the land use data; A second identification module is used to generate a plurality of fused patches based on a distance threshold and the first inefficient land, so as to identify the contiguous second inefficient land in the to-be-identified area according to the plurality of fused patches, wherein the contiguous range of the identified second inefficient land is adjusted by adjusting the distance threshold; a third identification module, configured to determine a to-be-developed area of ​​low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land, wherein the to-be-developed area is used for site selection and construction of land related to the to-be-identified area; The step of generating a plurality of fused image patches based on the distance threshold and the first inefficient land, so as to identify contiguous second inefficient land in the to-be-identified area according to the plurality of fused image patches, includes: Taking the first low-efficiency land as a patch, and fusing the patches according to the distance threshold to obtain the plurality of fused patches, wherein each fused patch indicates a corresponding contiguous area; Using the natural breakpoint method, the plurality of fused image patches are graded in descending order of the indicated contiguous areas to obtain a plurality of contiguous area grades; Determine the land use range based on the contiguous areas corresponding to each fused image patch in the highest contiguous area level, wherein the land use range is composed of the maximum value and the minimum value of the contiguous areas corresponding to each fused image patch; According to the land use scope, identifying the second low-efficiency land in the to-be-identified area; The step of identifying a first inefficient land in the to-be-identified area based on the land use data includes: Using the indicator calculation method corresponding to each of the multiple land use indicators, the land use indicator values ​​corresponding to each of the multiple land use indicators are calculated according to the land use data, wherein the multiple land use indicators include land use intensity and / or carrier conditions, the land use intensity includes volume ratio and / or building density, and the carrier conditions include building age, proportion of dilapidated buildings and / or completeness of infrastructure; Dividing the area to be identified into a plurality of sub-areas; For each sub-area, based at least on the land use index values ​​corresponding to each of the multiple land use indexes, a comprehensive score of each plot in the sub-area is calculated, and all plots in the sub-area whose comprehensive score is at the minimum score level are regarded as inefficient land in the sub-area; The low-efficiency land in each of the several sub-areas is determined as the first low-efficiency land.

8. The low-efficiency land identification system according to claim 7, characterized in that: The determining of a to-be-developed area of ​​low-efficiency land based on the user equipment signaling data, the geographic data, the land use data and the second low-efficiency land includes: Expand the second low-efficiency land in a preset expansion manner to obtain various potential assessment areas; Based on the user equipment signaling data, the geographic data and the land use data, each potential assessment area is evaluated respectively to obtain an evaluation value of each potential assessment area; Based on the evaluation values ​​of the various potential evaluation areas, the areas to be developed are identified in the various potential evaluation areas.

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