A spatial distribution prediction method based on ecological environment influence

Abstract

The application discloses a space distribution prediction method based on ecological environment influence, and through the management type and management scale of each position point in a target region, the initial space distribution is determined by using different weight values, the space-time deduction space distribution is obtained by considering the influence of influence factors on the position points, and the accurate final space distribution prediction is obtained by considering the overlap of pollution spaces of different position points and dividing according to the ratio, so as to solve the technical problem that the existing technology cannot accurately predict the space distribution of pollution generated by production and consumption in the target region by artificial experience judgment; the space distribution of pollution generated by production and consumption in the target region can be accurately predicted, so that the subsequent workers can obtain accurate data for supporting work in the process of pollution treatment or responsibility division.

Description

Technical Field

[0001] This invention relates to the field of big data processing technology, and in particular to a method for predicting the spatial distribution of ecological and environmental impacts. Background Technology

[0002] Human production and consumption activities have triggered serious ecological and environmental problems, leading to severe environmental pressure. Globalization has resulted in the increasing geographical separation of production and consumption, leading to unprecedented cross-regional environmental pollution problems caused by trade. To analyze the environmental pollution generated during the production process and the environmental pollution generated during the consumption process, it is desirable to spatially classify the environmental pollution generated during production and consumption. This would enable effective and targeted environmental improvement efforts and provide strong data support for improving the ecological environment.

[0003] Existing technologies often rely on human judgment based on experience when classifying the spatial distribution of environmental pollution. This makes it impossible to accurately predict the spatial distribution of pollution generated by production and consumption in the target area. Consequently, subsequent staff cannot obtain accurate data to support their work in the process of pollution control or responsibility allocation.

[0004] As ecological and environmental issues receive increasing attention, it is crucial to spatially divide the ecological and environmental conditions caused by production and consumption. Therefore, there is an urgent need for a spatial distribution prediction strategy based on ecological and environmental impacts to address the technical problem that existing technologies, which rely on human experience, cannot accurately predict the spatial distribution of pollution generated by production and consumption in target areas. Summary of the Invention

[0005] This invention provides a spatial distribution prediction method based on ecological and environmental impacts, which can accurately predict the spatial distribution of pollution generated by production and consumption in target areas, so that subsequent staff can obtain accurate data to support their work in the process of pollution control or responsibility allocation.

[0006] To address the aforementioned technical problems, embodiments of the present invention provide a method for predicting the spatial distribution of ecological and environmental impacts, comprising:

[0007] Obtain urban planning layout data for the target area, determine the locations for production and consumption in the target area based on the urban planning layout data, and determine the business type and scale of each location.

[0008] Based on the business type and scale of each location, the ecological pollution type and ecological pollution range of the location are determined, and the weight value of the location is determined based on the ecological pollution type. The initial spatial distribution of the location is determined based on the weight value and the ecological pollution range.

[0009] Identify the influencing factors that affect the ecological pollution changes at the location point, and use a preset time period as the prediction duration to perform a spatiotemporal extrapolation of the location point to obtain the extrapolated spatial distribution of the location point after the preset time period.

[0010] In the target region, identify two locations where the extrapolated spatial distribution overlaps, and determine the overlapping spatial distribution of the two locations;

[0011] Based on the ratio of the inferred spatial distributions of the two location points, the overlapping spatial distributions are divided according to the ratio to obtain the final spatial distribution prediction.

[0012] As a preferred embodiment, the steps of acquiring urban planning layout data of the target area, determining the locations for production and consumption in the target area based on the urban planning layout data, and determining the business type and scale of each location specifically include:

[0013] Based on the urban planning layout data of the target area, areas with production and operation attributes and consumption and operation attributes are extracted as the starting points for production and consumption.

[0014] The production and consumption quantities of each initial point within a preset period are statistically analyzed, and the top n types of goods with the highest production and consumption quantities are selected as the main products of the initial point. When it is determined that any one of the main products has ecological pollution properties, the initial point is determined as the location point.

[0015] The production and consumption of the main products with ecological pollution characteristics at the location point within a preset period shall be taken as the operating scale of the location point.

[0016] The business type of each location is determined by the proportion of the production and consumption of its main products with ecological pollution characteristics within a preset period to the total production and consumption of that location.

[0017] As a preferred embodiment, the step of determining the type and scope of ecological pollution at each location based on its business type and scale specifically includes:

[0018] Based on the business type of the location, determine the main products and their technological processes for the location;

[0019] When it is determined that the main product has ecological pollution characteristics, the main product is taken as the ecological pollution type of the location point;

[0020] Based on the technological process of the main product, determine the amount of pollution generated when producing and consuming one unit of the main product, determine the total amount of pollution generated at the location point based on the business scale, and determine the ecological pollution range of the location point based on the total amount of pollution.

[0021] As a preferred embodiment, the step of determining the weight value of the location point according to the type of ecological pollution, and determining the initial spatial distribution of the location point according to the weight value and the range of ecological pollution, specifically includes:

[0022] A first initial value is set for the location point based on the type of ecological pollution at the location point;

[0023] Calculate the spatial distance between the location point and surrounding location points. When the ecological pollution range of the location point and surrounding location points overlaps, select the surrounding location point with the smallest spatial distance value. Calculate the product of the spatial distance value of the surrounding location point and the first initial value, and use it as the weight value of the location point.

[0024] The inscribed circle of the ecological pollution range of the location point is determined, and the inscribed circle is expanded outward by a multiple of the weight value to obtain the initial spatial distribution of the location point.

[0025] As a preferred embodiment, the step of determining the influencing factors affecting the ecological pollution changes at the location point, using a preset time period as the prediction duration, and performing spatiotemporal extrapolation on the location point to obtain the extrapolated spatial distribution of the location point after the preset time period specifically includes:

[0026] Based on the main products of the location and its surrounding locations, determine the benign and malignant influencing factors that affect the ecological pollution changes at the location.

[0027] A cellular automaton model is established, with the benign and malignant influencing factors used as the influencing conditions of the cellular automaton model. A preset time period is used as the inference time of the cellular automaton model. The cellular automaton model is controlled to execute the inference development mode until the inference development time reaches the inference time. The output spatial scale is used as the inference spatial distribution of the location points.

[0028] As a preferred embodiment, the step of determining two overlapping location points in the target region based on the extrapolated spatial distribution, and determining the overlapping spatial distribution of the two location points, specifically includes:

[0029] Based on the spatial distribution of each location point, two location points in the target area whose spatial distributions overlap are identified.

[0030] Choose the location point that first completes the spatial distribution of the deduced equation from the two location points, and use the edge of its spatial distribution as the first red line;

[0031] Choose the location point from the two locations where the spatial distribution of the deduction is finally completed, and use the edge of its spatial distribution as the second red line.

[0032] The intersection range defined by the first red line and the second red line is taken as the overlapping spatial distribution of the two location points.

[0033] As a preferred embodiment, the step of dividing the overlapping spatial distribution according to the ratio of the inferred spatial distributions of the two location points to obtain the final spatial distribution prediction specifically includes:

[0034] Choose the location point that first completes the spatial distribution of the deduced model from the two location points, and define the range of the intersection between its spatial distribution and the second red line as the first value;

[0035] Choose the location point from the two locations where the spatial distribution of the deduction is finally completed, and define the range of the spatial distribution of the deduction intersecting with the first red line as the second value;

[0036] Calculate the ratio of the first value to the second value, and divide the overlapping spatial distribution into a first distribution region and a second distribution region according to the ratio.

[0037] The first distribution area is merged with the inference spatial distribution corresponding to the location point that first completes the inference spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that first completes the inference spatial distribution.

[0038] The second distribution area is merged with the spatial distribution corresponding to the last completed spatial distribution location to obtain the final spatial distribution prediction corresponding to the last completed spatial distribution location.

[0039] Accordingly, another embodiment of the present invention also provides a spatial distribution prediction system based on ecological and environmental impacts, including: a location determination module, an initial spatial module, a deduced spatial module, an overlapping spatial module, and a distribution prediction module;

[0040] The location determination module is used to acquire urban planning layout data of the target area, determine the location points for production and consumption in the target area based on the urban planning layout data, and determine the business type and business scale of each location point.

[0041] The initial spatial module is used to determine the type and scope of ecological pollution of each location point based on its business type and scale, determine the weight value of each location point based on the type of ecological pollution, and determine the initial spatial distribution of the location points based on the weight value and the scope of ecological pollution.

[0042] The extrapolation space module is used to determine the influencing factors that affect the ecological pollution changes at the location point, and to perform spatiotemporal extrapolation on the location point with a preset time period as the prediction duration, so as to obtain the extrapolated spatial distribution of the location point after the preset time period.

[0043] The overlapping space module is used to identify two locations in the target region where the inference space distribution overlaps, and to determine the overlapping spatial distribution of the two locations.

[0044] The distribution prediction module is used to divide the overlapping spatial distribution according to the ratio of the inferred spatial distribution of the two location points, so as to obtain the final spatial distribution prediction.

[0045] As a preferred embodiment, the location determination module is specifically used for: extracting areas with production and consumption attributes as initial points for production and consumption based on urban planning layout data of the target area; statistically analyzing the production and consumption quantities of each initial point within a preset period, selecting the top n types of goods with the highest production and consumption quantities as the main products of the initial point; determining the initial point as a location point when any one of the main products is determined to have ecological pollution characteristics; using the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period as the operating scale of the location point; and proportionally setting the operating type of the location point according to the proportion of the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period to the total production and consumption quantities of the location point.

[0046] As a preferred embodiment, the initial space module is used to determine the type and scope of ecological pollution of each location based on its business type and scale. Specifically, this includes: determining the main product and its production process of each location based on its business type; when the main product is determined to be ecologically polluting, classifying it as the type of ecological pollution of the location; determining the amount of pollution generated when producing and consuming one unit of the main product based on its production process; determining the total amount of pollution generated by the location based on its business scale; and determining the scope of ecological pollution of the location based on the total amount of pollution.

[0047] As a preferred embodiment, the initial spatial module is used to determine the weight value of the location point according to the type of ecological pollution, and to determine the initial spatial distribution of the location point according to the weight value and the range of ecological pollution. Specifically, this includes: setting a first initial value for the location point according to the type of ecological pollution; calculating the spatial distance between the location point and surrounding location points; when the ecological pollution ranges of the location point and surrounding location points overlap, selecting the surrounding location point with the smallest spatial distance value; calculating the product of the spatial distance value of the surrounding location point and the first initial value as the weight value of the location point; determining the inscribed circle of the ecological pollution range of the location point; and expanding the inscribed circle outward by a multiple of the weight value to obtain the initial spatial distribution of the location point.

[0048] As a preferred embodiment, the extrapolation space module is specifically used for: determining the benign and malignant influencing factors affecting the ecological pollution changes at the location point based on the main products of the location point and its surrounding locations; establishing a cellular automaton model, using the benign and malignant influencing factors as the influencing conditions of the cellular automaton model, using a preset time period as the extrapolation time of the cellular automaton model, controlling the cellular automaton model to execute the extrapolation development mode until the extrapolation development time reaches the extrapolation time, and using the output spatial scale as the extrapolation spatial distribution of the location point.

[0049] As a preferred embodiment, the overlapping space module is specifically used for: determining two locations in the target area where the extrapolated spatial distribution overlaps, based on the extrapolated spatial distribution of each location point; selecting the location point that completes the extrapolated spatial distribution first, and using the edge of its extrapolated spatial distribution as a first red line; selecting the location point that completes the extrapolated spatial distribution last, and using the edge of its extrapolated spatial distribution as a second red line; and using the intersection range defined by the first red line and the second red line as the overlapping spatial distribution of the two location points.

[0050] As a preferred embodiment, the distribution prediction module is specifically used for: selecting the location point that first completes the deduced spatial distribution from two location points, and defining the range where its deduced spatial distribution intersects with the second red line as a first value; selecting the location point that last completes the deduced spatial distribution from two location points, and defining the range where its deduced spatial distribution intersects with the first red line as a second value; calculating the ratio of the first value to the second value, and dividing the overlapping spatial distribution into a first distribution region and a second distribution region according to the ratio; merging the first distribution region with the deduced spatial distribution corresponding to the location point that first completes the deduced spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that first completes the deduced spatial distribution; merging the second distribution region with the deduced spatial distribution corresponding to the location point that last completes the deduced spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that last completes the deduced spatial distribution.

[0051] This invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the spatial distribution prediction method based on ecological and environmental impact as described in any of the preceding embodiments.

[0052] This invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the spatial distribution prediction method based on ecological and environmental impact as described in any of the preceding embodiments.

[0053] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0054] This invention addresses the technical problem of existing technologies that rely on human experience to accurately predict the spatial distribution of pollution generated from production and consumption within a target area. This allows for precise prediction of the spatial distribution, enabling subsequent pollution control and responsibility allocation based on accurate data. Attached Figure Description

[0055] Figure 1: A flowchart illustrating the steps of a spatial distribution prediction method based on ecological and environmental impacts provided in an embodiment of the present invention;

[0056] Figure 2 : A schematic diagram of the structure of a spatial distribution prediction system based on ecological and environmental impacts provided in an embodiment of the present invention;

[0057] Figure 3 : A schematic diagram of the structure of one embodiment of the terminal device provided in this invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] Example 1

[0060] Please refer to Figure 1 The flowchart of a spatial distribution prediction method based on ecological and environmental impact provided by an embodiment of the present invention includes steps 101 to 105, each step being as follows:

[0061] Step 101: Obtain urban planning layout data of the target area, determine the location points for production and consumption in the target area based on the urban planning layout data, and determine the business type and business scale of each location point.

[0062] In this embodiment, step 101 specifically includes: Step 1011, extracting areas with production and consumption attributes as initial points for production and consumption based on urban planning layout data of the target area. Step 1012, statistically analyzing the production and consumption quantities of each initial point within a preset period, selecting the top n types of goods with the highest production and consumption quantities as the main products of the initial point, and determining the initial point as a location point when any one of the main products is determined to have ecological pollution characteristics. Step 1013, using the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period as the operating scale of the location point. Step 1014, setting the operating type of the location point according to the proportion of the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period to the total production and consumption quantities of the location point.

[0063] Specifically, to determine the ecological and environmental impacts of production and consumption processes on the local area, we first need to identify regions with both production and consumption attributes. Within a pre-defined statistical period, we collect statistics on the production and consumption quantities within these regions, identifying the most abundant product categories as the region's main products. Based on these main products, we can create a pre-existing table of product pollution levels on environmental websites, allowing us to determine whether these main products possess ecological pollution characteristics. If the main products produced and consumed in this region are determined to be ecologically polluting, the production and consumption quantities in this region are used as the operating scale. Furthermore, considering that a region at the same location may contain multiple main products, to better profile that region, we construct corresponding operating types based on the proportion of different main products in the total quantity, using the same proportion for each main product, to better distinguish between different locations.

[0064] Step 102: Determine the ecological pollution type and ecological pollution range of each location point based on its business type and scale, determine the weight value of each location point based on its ecological pollution type, and determine the initial spatial distribution of the location points based on its weight value and ecological pollution range.

[0065] Specifically, this step involves two aspects. First, how to determine the type and scope of ecological pollution based on the business type and scale obtained in the previous step; second, how to determine the initial spatial distribution of pollution caused at this location. The specific execution process of this step will be explained in detail below, dividing it into these two aspects.

[0066] In the first aspect of this embodiment, step 102, which involves determining the type and scope of ecological pollution at each location based on its business type and scale, specifically includes: Step 10211, determining the main product and its production process of the location based on its business type; Step 10212, when the main product is determined to have ecological pollution characteristics, classifying the main product as the type of ecological pollution at the location; Step 10213, based on the production process of the main product, determining the amount of pollution generated when producing and consuming one unit of the main product, determining the total amount of pollution generated by the location based on its business scale, and determining the scope of ecological pollution at the location based on the total amount of pollution.

[0067] Specifically, after determining the business type of a location, analyzing the business type reveals the main product, and the corresponding production process for that main product can be found online. First, we need to determine the eco-pollution nature of this main product to identify the location as eco-friendly. The obtained production process allows us to determine the pollution generated when producing and consuming one unit of the main product, thus defining the scope of eco-pollution.

[0068] In the second aspect of this embodiment, step 102, which involves determining the weight value of the location point based on the type of ecological pollution and determining the initial spatial distribution of the location point based on the weight value and the ecological pollution range, specifically includes: Step 10221, setting a first initial value for the location point based on the type of ecological pollution. Step 10222, calculating the spatial distance between the location point and surrounding location points; when the ecological pollution ranges of the location point and surrounding location points overlap, selecting the surrounding location point with the smallest spatial distance value, and calculating the product of the spatial distance value of the surrounding location point and the first initial value as the weight value of the location point. Step 10223, determining the inscribed circle of the ecological pollution range of the location point, and expanding the inscribed circle outward by a multiple of the weight value to obtain the initial spatial distribution of the location point.

[0069] Specifically, different initial weight values, or first initial values, are first assigned to different types of ecological pollution. Considering that the closer the spatial distance, the greater the probability of pollution overlap between the current location and surrounding locations, the nearest surrounding location is selected as a reference. Research shows that the minimum spatial distance between the current location and the nearest surrounding location is often directly proportional to the spatial distribution of ecological pollution. Using the product of the spatial distance value and the first initial value as the weight value, and expanding the inscribed circle of the ecological pollution area outwards by multiples of this weight value, the initial spatial distribution of the location points can be obtained.

[0070] Step 103: Determine the influencing factors affecting the ecological pollution changes at the location point, and perform spatiotemporal extrapolation on the location point using a preset time period as the prediction duration to obtain the extrapolated spatial distribution of the location point after the preset time period.

[0071] In this embodiment, step 103 specifically includes: Step 1031, determining the benign and malignant influencing factors affecting the ecological pollution changes at the location point based on the main products of the location point and its surrounding locations. Step 1032, establishing a cellular automaton model, using the benign and malignant influencing factors as the influencing conditions of the cellular automaton model, using a preset time period as the deduction time of the cellular automaton model, controlling the cellular automaton model to execute a deduction development mode until the deduction development time reaches the deduction time, and using the output spatial scale as the deduction spatial distribution of the location point.

[0072] Specifically, cellular automata are discrete-time, spatial, and state-based grid dynamics models where spatial interactions and temporal causality are localized, possessing the ability to simulate the spatiotemporal evolution of complex systems. Scientists often utilize cellular automata models to extrapolate processes such as urban and ecological issues. This step involves constructing a cellular automata model using conventional methods. During construction, benign and malignant influencing factors affecting ecological pollution changes at a given location are used as construction conditions. The preset time period mentioned in this step is actually the development period. The cellular automata model can extrapolate the extent of ecological pollution within this preset time period. The specific construction process is not detailed here but can be achieved using conventional construction methods.

[0073] Step 104: Identify two locations in the target region where the extrapolated spatial distribution overlaps, and determine the overlapping spatial distribution of the two locations.

[0074] In this embodiment, step 104 specifically includes: Step 1041, determining two overlapping location points in the target area based on the extrapolated spatial distribution of each location point. Step 1042, selecting the location point that completes the extrapolated spatial distribution first from the two location points, and using the edge of its extrapolated spatial distribution as the first red line. Step 1043, selecting the location point that completes the extrapolated spatial distribution last from the two location points, and using the edge of its extrapolated spatial distribution as the second red line. Step 1044, defining the intersection range defined by the first red line and the second red line as the overlapping spatial distribution of the two location points.

[0075] Specifically, during the spatial distribution extrapolation process, the extrapolation results between any two locations may overlap. To ensure greater data accuracy, two red lines will appear sequentially during the extrapolation process. The first line represents the extrapolation range of the location whose extrapolation is completed first, and the second line represents the extrapolation range of the location whose extrapolation is completed later. We first define the extrapolation range that is completed first, i.e., the edge of the extrapolated spatial distribution, as the first red line, forming a circle. Then, the extrapolation range that is completed last will form another circle. The intersection of these circles is considered the overlapping portion. Since the overlapping portion is actually calculated repeatedly at both locations, we determine the overlapping portion in this step to more accurately define the region, facilitating precise segmentation later.

[0076] Step 105: Based on the ratio of the inferred spatial distributions of the two location points, divide the overlapping spatial distributions according to the ratio to obtain the final spatial distribution prediction.

[0077] In this embodiment, step 105 specifically includes: Step 1051, selecting the location point that first completes the extrapolated spatial distribution from the two location points, and defining the range where its extrapolated spatial distribution intersects with the second red line as a first value. Step 1052, selecting the location point that last completes the extrapolated spatial distribution from the two location points, and defining the range where its extrapolated spatial distribution intersects with the first red line as a second value. Step 1053, calculating the ratio of the first value to the second value, and dividing the overlapping spatial distribution into a first distribution region and a second distribution region proportionally according to the ratio. Step 1054, merging the first distribution region with the extrapolated spatial distribution corresponding to the location point that first completes the extrapolated spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that first completes the extrapolated spatial distribution. Step 1055, merging the second distribution region with the extrapolated spatial distribution corresponding to the location point that last completes the extrapolated spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that last completes the extrapolated spatial distribution.

[0078] Specifically, research shows that segmenting based on the ratio between the projected ranges of the respective location points is the most accurate strategy. In practice, we determine the value of the intersection between the projected spatial distribution of the location point that completes the project first and the subsequently formed second red line. This range theoretically represents the largest contamination range for the location point that completed the project first. Similarly, we determine the value using the intersection between the projected spatial distribution of the location point that completed the project last and the first formed red line. This range theoretically represents the largest contamination range for the location point that completed the project last. The overlapping spatial distribution is divided based on the ratio between these two values; that is, the ratio of the first value to the second value is equal to the ratio of the first distribution area to the second distribution area. Therefore, we can merge the first distribution area with the location point that completed the project first, and merge the second distribution area with the location point that completed the project last, to obtain the corresponding final spatial distribution predictions.

[0079] This invention addresses the technical problem of existing technologies that rely on human experience to accurately predict the spatial distribution of pollution generated from production and consumption within a target area. This allows for precise prediction of the spatial distribution, enabling subsequent pollution control and responsibility allocation based on accurate data.

[0080] Example 2

[0081] Please refer to Figure 2 The diagram below illustrates the structure of a spatial distribution prediction system based on ecological and environmental impacts, as provided in another embodiment of the present invention. The system includes: a location determination module, an initial spatial module, a deduced spatial module, an overlapping spatial module, and a distribution prediction module.

[0082] The location determination module is used to acquire urban planning layout data of the target area, determine the location points for production and consumption in the target area based on the urban planning layout data, and determine the business type and business scale of each location point.

[0083] In this embodiment, the location determination module is specifically used for: extracting areas with production and operation attributes and consumption and operation attributes as initial points for production and consumption based on urban planning layout data of the target area; statistically analyzing the production and consumption quantities of each initial point within a preset period, selecting the top n types of goods with the highest production and consumption quantities as the main products of the initial point; determining the initial point as a location point when any one of the main products is determined to have ecological pollution characteristics; using the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period as the operating scale of the location point; and proportionally setting the operating type of the location point according to the proportion of the production and consumption quantities of the main products with ecological pollution characteristics at the location point within the preset period to the total production and consumption quantities of the location point.

[0084] The initial spatial module is used to determine the type and scope of ecological pollution of each location point based on its business type and scale, determine the weight value of the location point based on the type of ecological pollution, and determine the initial spatial distribution of the location points based on the weight value and the scope of ecological pollution.

[0085] In a first aspect of this embodiment, the initial space module is used to determine the type and scope of ecological pollution of each location based on its business type and scale. Specifically, this includes: determining the main product and its production process of each location based on its business type; when the main product is determined to have ecological pollution characteristics, classifying it as the type of ecological pollution of the location; determining the amount of pollution generated when producing and consuming one unit of the main product based on its production process; determining the total amount of pollution generated by the location based on its business scale; and determining the scope of ecological pollution of the location based on the total amount of pollution.

[0086] In a second aspect of this embodiment, the initial spatial module is used to determine the weight value of the location point according to the type of ecological pollution, and to determine the initial spatial distribution of the location point according to the weight value and the range of ecological pollution. Specifically, this includes: setting a first initial value for the location point according to the type of ecological pollution; calculating the spatial distance between the location point and surrounding location points; when the ecological pollution ranges of the location point and surrounding location points overlap, selecting the surrounding location point with the smallest spatial distance value; calculating the product of the spatial distance value of the surrounding location point and the first initial value as the weight value of the location point; determining the inscribed circle of the ecological pollution range of the location point; and expanding the inscribed circle outward by a multiple of the weight value to obtain the initial spatial distribution of the location point.

[0087] The extrapolation space module is used to determine the influencing factors that affect the ecological pollution changes at the location point, and to perform spatiotemporal extrapolation on the location point with a preset time period as the prediction duration, so as to obtain the extrapolated spatial distribution of the location point after the preset time period.

[0088] In this embodiment, the extrapolation space module is specifically used to: determine the benign and malignant influencing factors affecting the ecological pollution changes at the location point based on the main products of the location point and its surrounding locations; establish a cellular automaton model, using the benign and malignant influencing factors as the influencing conditions of the cellular automaton model, using a preset time period as the extrapolation time of the cellular automaton model, controlling the cellular automaton model to execute the extrapolation development mode until the extrapolation development time reaches the extrapolation time, and using the output spatial scale as the extrapolation spatial distribution of the location point.

[0089] The overlapping space module is used to identify two locations in the target region where the extrapolated spatial distribution overlaps, and to determine the overlapping spatial distribution of the two locations.

[0090] In this embodiment, the overlapping space module is specifically used to: determine two locations in the target area where the extrapolated spatial distribution overlaps, based on the extrapolated spatial distribution of each location point; select the location point that completes the extrapolated spatial distribution first among the two locations, and use the edge of its extrapolated spatial distribution as a first red line; select the location point that completes the extrapolated spatial distribution last among the two locations, and use the edge of its extrapolated spatial distribution as a second red line; and use the intersection range defined by the first red line and the second red line as the overlapping spatial distribution of the two locations.

[0091] The distribution prediction module is used to divide the overlapping spatial distribution according to the ratio of the inferred spatial distribution of the two location points, so as to obtain the final spatial distribution prediction.

[0092] In this embodiment, the distribution prediction module is specifically used for: selecting the location point that first completes the extrapolated spatial distribution from two location points, and defining the range where its extrapolated spatial distribution intersects with the second red line as a first value; selecting the location point that last completes the extrapolated spatial distribution from two location points, and defining the range where its extrapolated spatial distribution intersects with the first red line as a second value; calculating the ratio of the first value to the second value, and dividing the overlapping spatial distribution into a first distribution region and a second distribution region according to the ratio; merging the first distribution region with the extrapolated spatial distribution corresponding to the location point that first completes the extrapolated spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that first completes the extrapolated spatial distribution; merging the second distribution region with the extrapolated spatial distribution corresponding to the location point that last completes the extrapolated spatial distribution to obtain the final spatial distribution prediction corresponding to the location point that last completes the extrapolated spatial distribution.

[0093] Example 3

[0094] This invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the spatial distribution prediction method based on ecological and environmental impact described in any of the above embodiments.

[0095] Example 4

[0096] Please refer to Figure 3 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present invention. The terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the spatial distribution prediction method based on ecological and environmental impact described in any of the above embodiments.

[0097] Preferably, the computer program can be divided into one or more modules / units (such as a computer program, a computer program), and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0098] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can be any conventional processor. The processor is the control center of the terminal device, connecting various parts of the terminal device through various interfaces and lines.

[0099] The memory mainly includes a program storage area and a data storage area. The program storage area can store the operating system, applications required for at least one function, etc., while the data storage area can store related data, etc. Furthermore, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard drive, a SmartMedia Card (SMC), a Secure Digital (SD) card, and a Flash Card, or other volatile solid-state storage devices.

[0100] It should be noted that the aforementioned terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that the aforementioned terminal devices are merely examples and do not constitute a limitation on the terminal devices. They may include more or fewer components, or combine certain components, or different components.

[0101] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for predicting spatial distribution based on eco-environmental impact, characterized in that, The method comprises the following steps: obtaining urban planning layout data of a target region, determining location points for production and consumption in the target region according to the urban planning layout data, and determining the business type and business scale of each location point; determining the ecological pollution type and ecological pollution range of each location point according to the business type and business scale of each location point, determining the weight value of each location point according to the ecological pollution type, and determining the initial spatial distribution of each location point according to the weight value and the ecological pollution range; determining the influence factor of the location point affecting the change of ecological pollution, performing space-time deduction on the location point with a preset time period as the prediction length to obtain the deduction spatial distribution of the location point after the preset time period; determining two location points in the target region with the deduction spatial distribution overlapping, and determining the overlapping spatial distribution of the two location points; dividing the overlapping spatial distribution according to the ratio of the deduction spatial distribution of the two location points to obtain the final spatial distribution prediction; wherein the step of obtaining urban planning layout data of a target region, determining location points for production and consumption in the target region according to the urban planning layout data, and determining the business type and business scale of each location point comprises: extracting regions with production and consumption attributes as initial points for production and consumption according to the urban planning layout data of the target region; statistically analyzing the production and consumption quantities of each initial point in a preset period, selecting the top n product categories with the largest production and consumption quantities as the main products of the initial point, and determining the initial point as a location point when any of the main products is determined to have ecological pollution properties; taking the production and consumption quantities of the main products with ecological pollution properties in the location point in a preset period as the business scale of the location point; respectively setting the business type of the location point according to the proportion of the production and consumption quantities of the main products with ecological pollution properties in the location point in a preset period to the total production and consumption quantities of the location point.

2. The method of claim 1, wherein the method is based on an eco-environmental impact. The step of determining the ecological pollution type and ecological pollution range of each location point according to the business type and business scale of each location point comprises: determining the main products and their process flows of the location point according to the business type of the location point; determining the main products as the ecological pollution type of the location point when it is determined that the main products have ecological pollution properties; determining the total pollution amount generated by the location point according to the business scale, determining the ecological pollution range of the location point according to the total pollution amount, and determining the weight value of the location point according to the ecological pollution type.

3. The method of claim 1, wherein the method is based on an eco-environmental impact. The step of determining the weight value of each location point according to the ecological pollution type, and determining the initial spatial distribution of each location point according to the weight value and the ecological pollution range comprises: setting a first initial value for each location point according to the ecological pollution type of the location point; calculating a spatial distance value of the position point and a surrounding position point, selecting a surrounding position point with a minimum spatial distance value when the ecological pollution range of the position point and the surrounding position point overlap, and calculating a product of the spatial distance value of the surrounding position point and the first initial value as a weight value of the position point; determining an inscribed circle of the ecological pollution range of the position point, and expanding the inscribed circle outward by a multiple of the weight value to obtain an initial spatial distribution of the position point.

4. The method of claim 1, wherein the method is based on an eco-environmental impact. The step of determining an influence factor affecting the position point to change the ecological pollution, and performing spatio-temporal deduction on the position point with a preset time period as a prediction length to obtain a deduction spatial distribution of the position point after the preset time period, specifically includes: determining a benign influence factor and a malignant influence factor affecting the position point to change the ecological pollution according to the main products of the position point and surrounding position points; establishing a cellular automaton model, taking the benign influence factor and the malignant influence factor as influence conditions of the cellular automaton model, taking the preset time period as a deduction time of the cellular automaton model, controlling the cellular automaton model to execute a deduction development mode until the deduction development time reaches the deduction time, and taking an output spatial scale as a deduction spatial distribution of the position point.

5. The method of claim 1, wherein the method is based on an eco-environmental impact. The step of determining two position points with overlapping deduction spatial distributions in the target area and determining an overlapping spatial distribution of the two position points, specifically includes: determining two position points with overlapping deduction spatial distributions in the target area according to the deduction spatial distribution of each position point; selecting a position point that first completes the deduction spatial distribution from the two position points, and taking an edge of the deduction spatial distribution of the position point as a first red line; selecting a position point that last completes the deduction spatial distribution from the two position points, and taking an edge of the deduction spatial distribution of the position point as a second red line; taking an intersection range enclosed by the first red line and the second red line as an overlapping spatial distribution of the two position points.

6. An eco-environmental impact-based spatial distribution prediction system, characterized by, comprises: a position determination module, an initial spatial module, a deduction spatial module, an overlapping spatial module, and a distribution prediction module; The position determination module is configured to obtain urban planning layout data of a target area, determine position points for production and consumption in the target area according to the urban planning layout data, and determine the business type and business scale of each position point; The initial spatial module is configured to determine the ecological pollution type and ecological pollution range of each position point according to the business type and business scale of the position point, determine the weight value of the position point according to the ecological pollution type, and determine the initial spatial distribution of the position point according to the weight value and the ecological pollution range; The deduction spatial module is configured to determine an influence factor affecting the position point to change the ecological pollution, and perform spatio-temporal deduction on the position point with a preset time period as a prediction length to obtain a deduction spatial distribution of the position point after the preset time period; The overlapping space module is configured to determine two position points in the target region where the deduced space distribution exists overlap, and determine the overlapping space distribution of the two position points. The distribution prediction module is configured to divide the overlapping space distribution according to a ratio of the deduced space distribution of each of the two position points, to obtain a final space distribution prediction corresponding to the ratio. The position determination module is configured to obtain city planning layout data of a target region, determine position points in the target region where production and consumption are performed according to the city planning layout data, and determine the business type and business scale of each position point, specifically including: According to the city planning layout data of the target region, extract regions with production and consumption attributes as initial points of production and consumption; Statistically analyze the production and consumption quantities of each initial point in a preset period, select the top n product categories with the largest production and consumption quantities as main products of the initial point, and determine the initial point as a position point when it is determined that any one of the main products has an ecological pollution property; The production and consumption quantities of the main products with the ecological pollution property in the position point in a preset period are used as the business scale of the position point. The proportion of the production and consumption quantities of the main products with the ecological pollution property in the position point in a preset period to the total production and consumption quantities of the position point is used to set the business type of the position point according to the proportion.

7. The spatial distribution prediction system based on eco-environmental impact according to claim 6, wherein, The initial space module is configured to determine the ecological pollution type and ecological pollution range of the position point according to the business type and business scale of each position point, specifically including: determining the main products and their process flows of the position point according to the business type of the position point; determining the main products as the ecological pollution type of the position point when it is determined that the main products have an ecological pollution property; determining the total pollution amount generated by the position point according to the business scale, and determining the ecological pollution range of the position point according to the total pollution amount, according to the process flow of the main products and the pollution amount generated when producing and consuming one unit of the main products; The initial space module is configured to determine the weight value of the position point according to the ecological pollution type, and determine the initial space distribution of the position point according to the weight value and the ecological pollution range, specifically including: setting a first initial value for the position point according to the ecological pollution type of the position point; calculating the spatial distance value between the position point and the surrounding position points, selecting the surrounding position point with the smallest spatial distance value when the ecological pollution ranges of the position point and the surrounding position points overlap, and calculating the product of the spatial distance value of the surrounding position point and the first initial value as the weight value of the position point; determining the inscribed circle of the ecological pollution range of the position point, and expanding the inscribed circle outward by a multiple of the weight value to obtain the initial space distribution of the position point.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program; wherein the computer program, when executed, controls a device in which the computer readable storage medium is located to perform the method for predicting spatial distribution based on ecological environmental impact according to any one of claims 1-5.

9. A terminal device, comprising: A computer program product comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the method for predicting spatial distribution based on ecological environmental impact according to any one of claims 1-5.

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