Urban low-carbon construction level index scoring system

Abstract

The invention provides an urban low-carbon construction level index scoring system. The method belongs to the technical field of urban construction, and comprises the following steps: acquiring initial landscape element information, and determining a to-be-processed water area based on the initial landscape element information; acquiring initial carbon sequestration information based on the to-be-processed water area, and determining at least one preset target point based on the initial carbon sequestration information and the initial landscape element information; based on the initial landscape element information, determining at least one piece of planned transformation information of at least one target site, the target site comprising at least one of at least one preset target point; and simulating the target site based on the initial landscape element information and the planned transformation information, and determining and outputting at least one simulation result of the target landscape of the target site. The water area advantage can be fully utilized to solve the problem of water area silting, the surrounding landscape is improved, and the water area carbon sequestration amount is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of urban construction, and in particular to a scoring system for an urban low-carbon construction level index. Background Art

[0002] The urbanization process is advancing rapidly around the world, and the urban population is increasing. As an important part of sustainable development, low-carbon construction aims to achieve green, environmentally friendly and sustainable development of cities by reducing carbon emissions, improving energy efficiency and improving environmental quality. In the process of low-carbon construction, water area transformation occupies an important position. Water area siltation is a common natural geographical phenomenon, which often occurs under the influence of natural factors such as heavy precipitation and changes in water flow speed. Water area siltation will have adverse effects on the ecological environment, hydrological conditions and human society of water areas. The accumulation of silt in water area siltation will lead to eutrophication and deterioration of water quality, which will reduce the carbon fixation in water areas.

[0003] Therefore, we hope to propose an urban low-carbon construction level index scoring system, based on which we can determine the target transformation information, make full use of the advantages of the water area to solve the problem of water siltation, improve the water area and surrounding landscape, timely monitor the upstream and downstream rivers of the wetland, predict river siltation, and further promptly determine the target transformation plan, which can increase carbon fixation by clearing inorganic silt, restoring water flow, repairing habitats and other measures to reduce the impact of siltation on the wetland landscape and ecosystem. Summary of the invention

[0004] The present invention provides a scoring system for the index of urban low-carbon construction level, which can make full use of the advantages of water areas to solve the problem of water area siltation and improve the water area and surrounding landscape. Since siltation may have various impacts on wetland landscapes, such as water quality deterioration and habitat destruction, the upstream and downstream rivers of the wetland are monitored in a timely manner, river siltation is predicted, and the target transformation plan is further determined in a timely manner. Inorganic siltation can be cleared, water flow is restored, habitats are repaired, and other measures can be taken to increase carbon fixation to reduce the impact of siltation on wetland landscapes and ecosystems.

[0005] One of the embodiments of the present specification provides a city low-carbon construction level index scoring system, including: an initial landscape determination module, used to obtain initial landscape element information, and determine a water area to be treated based on the initial landscape element information; a preset target point determination module, used to obtain initial carbon fixation information based on the water area to be treated, and determine at least one preset target point based on the initial carbon fixation information and the initial landscape element information; a planning module, used to determine at least one planned transformation information of at least one target site based on the initial landscape element information, and the target site includes at least one of the at least one preset target point; a simulation module, used to simulate the target site based on the initial landscape element information and the planned transformation information, determine at least one simulation result of the target landscape of the target site and output it; a target module, used to determine a carbon fixation score based on at least one simulation result, and determine the target transformation information based on the carbon fixation score.

[0006] One of the embodiments of the present specification provides a method for scoring an urban low-carbon construction level index, including: obtaining initial landscape element information, and determining a water area to be treated based on the initial landscape element information; obtaining initial carbon fixation information based on the water area to be treated, and determining at least one preset target point based on the initial carbon fixation information and the initial landscape element information; determining at least one planned transformation information of at least one target site based on the initial landscape element information, the target site including at least one of the at least one preset target point; simulating the target site based on the initial landscape element information and the planned transformation information, determining and outputting at least one simulation result of a target landscape of the target site; determining a carbon fixation score based on at least one simulation result, and determining target transformation information based on the carbon fixation score.

[0007] Some embodiments of the present specification also provide a city low-carbon construction level index scoring device, comprising at least one processor and at least one memory; the at least one memory is used to store computer instructions; the at least one processor is used to implement the city low-carbon construction level index scoring method described in any one of the above embodiments.

[0008] One of the embodiments of the present specification also provides a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the urban low-carbon construction level index scoring method as described in any of the above embodiments.

[0009] Beneficial effects of this application:

[0010] The application proposes a scoring system for the urban low-carbon construction level index, which can first obtain a more intuitive simulation result through three-dimensional simulation, and then implement it based on the simulation result, thereby reducing unnecessary modifications in design and communication. At the same time, by transforming the surrounding landscape of the water area to achieve the target landscape, the advantages of the water area can be fully utilized to solve the problem of water siltation, improve the surrounding landscape, and increase the carbon fixation in the water area. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0012] Figure 1 It is a schematic diagram of an application scenario of the urban low-carbon construction level index scoring system shown in some embodiments of this specification;

[0013] Figure 2 is an exemplary module diagram of a city low-carbon construction level index scoring system according to some embodiments of this specification;

[0014] Figure 3 is an exemplary flow chart of a scoring method for a city low-carbon construction level index according to some embodiments of this specification;

[0015] Figure 4 is an exemplary flow chart for determining a dredging plan for a water system of a target site according to some embodiments of this specification;

[0016] Figure 5 is a schematic diagram of a siltation simulation model according to some embodiments of the present specification;

[0017] Figure 6 is an exemplary flow chart for determining a dredging plan according to some embodiments of the present specification. DETAILED DESCRIPTION

[0018] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, without paying creative work, this specification can also be applied to other similar scenarios based on these drawings. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0019] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0020] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0021] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0022] Figure 1 It is a schematic diagram of an application scenario of the urban low-carbon construction level index scoring system shown in some embodiments of this specification.

[0023] Water areas often become silted up and need to be dredged. Through some embodiments of this specification, the water area and surrounding areas can be simulated, feasible landscape simulation results can be determined, and the landscape of the water area can be transformed based on the landscape simulation results.

[0024] In some embodiments, the application scenario 100 of the urban low-carbon construction level index scoring system may include a simulation result 110 of a target landscape of a target site, a storage device 120 , a processor 130 , and a user terminal 140 .

[0025] The simulation result 110 of the target landscape of the target site may refer to the simulation result of the target landscape that meets the user's needs after being processed by the three-dimensional simulation technology. In some embodiments, the simulation result 110 of the target landscape of the target site may include simulated buildings 111, simulated waters 112, and simulated waters 113. In some embodiments, the simulation result 110 of the target landscape of the target site may also include factors related to the landscape simulation scene such as terrain (not shown in the figure). In some embodiments, the simulation result 110 of the target landscape of the target site may be obtained by simulation modeling based on the planned transformation information by the processor 130 using three-dimensional simulation technology processing (such as 3D Unity, DirectX, OpenGL, etc.). In some embodiments, the simulation result 110 of the target landscape of the target site may be stored in the storage device 120. In some embodiments, the simulation result 110 of the target landscape of the target site in the application scenario 100 of the urban low-carbon construction level index scoring system may also include a sensor (not shown).

[0026] The storage device 120 can be used to store data and / or instructions. Data refers to a digital representation of information and can include various types, such as binary data, text data, image data, video data, etc. Instructions refer to programs that can control a device or device to perform a specific function. In some embodiments, the data may include data related to the simulation results 110 of the target landscape of the target site and the user 140. In some embodiments, the storage device 120 can store data and / or instructions used by the processor 130 to execute or use to complete the exemplary methods described in this specification. For example, the storage device 120 can store relevant information of the simulation results 110 of the target landscape of the target site. For another example, the storage device 120 can store one or more machine learning models.

[0027] In some embodiments, the storage device 120 may be part of the processor 130. The storage device 120 may include one or more storage components, each of which may be an independent device or part of another device. In some embodiments, the storage device 120 may include a random access memory (RAM), a read-only memory (ROM), a mass storage, a removable memory, a volatile read-write memory, etc. or any combination thereof. Exemplarily, the mass storage may include a magnetic disk, an optical disk, a solid-state disk, etc. In some embodiments, the storage device 120 may be implemented on a cloud platform. Exemplarily, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc. or any combination thereof.

[0028] The processor 130 may be used to process data and / or information from at least one component of the application scenario 100 of the urban low-carbon construction level index scoring system or an external data source (e.g., a cloud data center). The processor 130 may be connected to the storage device 120 via a network (not shown) or directly to access and / or receive data and information. For example, the processor 130 may be directly connected to the storage device 120 and receive relevant information of the simulation result 110 of the target landscape of the target site.

[0029] In some embodiments, the processor 130 may include one or more sub-processing devices (e.g., a single-core processing device or a multi-core multi-core processing device). Exemplarily, the processor 130 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, etc., or any combination thereof.

[0030] The user terminal 140 may refer to one or more terminal devices or software used by the user. In some embodiments, the user terminal 140 may be a mobile device, a tablet computer, a laptop computer, etc. or any combination thereof. In some embodiments, the user terminal 140 may interact with other components in the application scenario 100 of the urban low-carbon construction level index scoring system through the network 120. Among them, the user may refer to a person or group who puts forward demands and feedback on the simulation results 110 of the target landscape of the target site. In some embodiments, the demands and feedback put forward by the user on the simulation results 110 of the target landscape of the target site through the user terminal 140 may be processed by the processor 130, so as to model and / or adjust the simulation results 110 of the target landscape of the target site.

[0031] It should be noted that the application scenarios are provided only for the purpose of illustration and are not intended to limit the scope of this specification. For those of ordinary skill in the art, various modifications or variations can be made according to the description of this specification. For example, the application scenarios may also include a database. For another example, the application scenarios may implement similar or different functions on other devices. However, the changes and modifications will not deviate from the scope of this specification.

[0032] Figure 2 is an exemplary module diagram of the urban low-carbon construction level index scoring system shown in some embodiments of this specification. Figure 2As shown, the urban low-carbon construction level index scoring system 200 may include an initial landscape determination module 210 , a preset target point determination module 220 , a planning module 230 , a simulation module 240 , and a target module 250 .

[0033] An initial landscape determination module 210 is used to obtain initial landscape element information and determine a water area to be processed based on the initial landscape element information;

[0034] A preset target point determination module 220 is used to obtain initial carbon fixation information based on the water area to be processed, and determine at least one preset target point based on the initial carbon fixation information and initial landscape element information;

[0035] In some embodiments, the preset target point determination module 220 includes: a candidate module, which is used to take the difference point between the vector represented by the initial landscape element information and the vector represented by the ideal landscape element information of the water area as at least one candidate target point; a preset module, which is used to determine at least one preset target point based on at least one candidate target point and the initial carbon fixation information, including: establishing a first relationship between the ideal landscape element information and the corresponding ideal carbon fixation through a multiple linear regression model; establishing a second relationship between the landscape element information of the current water area and the corresponding current carbon fixation through a multiple linear regression model; obtaining the initial carbon fixation information of the candidate target point, determining the corresponding ideal carbon fixation and the current carbon fixation based on the first relationship and the second relationship, respectively, and determining the difference between the ideal carbon fixation and the current carbon fixation, and when the difference is greater than the preset difference threshold, taking the corresponding candidate target point as the preset target point.

[0036] A planning module 230, for determining at least one planned transformation information of at least one target site based on the initial landscape element information, the target site including at least one of the at least one preset target point;

[0037] A simulation module 240, configured to simulate the target site based on the initial landscape element information and the planned transformation information, determine and output at least one simulation result of the target landscape of the target site;

[0038] In some embodiments, the water system may include water attractions, water channels and dredging pipes in the target site, and the water system simulation results include a dredging plan. The simulation module 240 includes a water system simulation sub-module, which is used to: determine the first basic information and the first flow information of the water attraction based on the planned transformation information; determine the second basic information and the second flow information of the flow channel based on the planned transformation information; determine the water flow information of the water system in the target landscape of the target site based on the first basic information, the first flow information, the second basic information and the second flow information; determine the siltation information based on the water flow information, the real-time landscape element information and the target landscape element information; determine the dredging plan based on the water flow information and the siltation information.

[0039] In some embodiments, the water system simulation submodule includes a dredging module, which is used to: determine the terrain information and water system information of the target site based on the planned transformation information; determine the remaining water volume in each sub-area of ​​the target site based on the climate simulation information, terrain information and water system information; and determine the dredging plan based on the remaining water volume and siltation information.

[0040] The target module 250 is used to determine a carbon sequestration fraction based on at least one simulation result, and determine target transformation information based on the carbon sequestration fraction.

[0041] Figure 3 is an exemplary flow chart of a method for scoring a city low-carbon construction level index according to some embodiments of this specification. In some embodiments, process 300 may be executed by a processor. Figure 3 As shown, process 300 includes the following steps:

[0042] Step 310: Acquire initial landscape element information, and determine the water area to be processed based on the initial landscape element information.

[0043] Landscape elements may refer to the constituent elements of the water environment. For example, landscape elements may include water areas, river banks, water bodies, surrounding buildings, vegetation, organisms, etc. The initial landscape element information of a preset target point may refer to the initial landscape element information near the preset target point. The initial landscape elements may refer to the landscape elements contained in the initial landscape information before the transformation. The initial landscape element information may refer to information related to the initial landscape elements. For example, the initial landscape element information may include the area of ​​the water area, the type of organisms, the drop in water level, the increase in pollution, etc. The initial landscape element information may be determined through an existing landscape database or geographic information system data. The wetland surface information includes topographic information, sediment type and thickness, etc.

[0044] In some embodiments, aerial photography and remote sensing images can be used to obtain a wide range of landscape information, including the shape, size, surrounding vegetation coverage, etc. of the water area. By analyzing the image, the initial landscape element information of the water area can be obtained. Further, by comparing the similarity between the vector represented by the initial landscape element information and the vector represented by the ideal landscape element information of the water area, when the similarity is less than a threshold, it is determined that the corresponding water area at this time is the water area to be processed. The similarity can be determined by the distance between the vectors, and the smaller the distance, the greater the similarity.

[0045] The water area to be treated may refer to the water area that needs to be transformed. The water area may include wetlands, lakes, ponds, rivers, etc. In this specification, unless otherwise specified, wetlands are used as water areas for description.

[0046] Step 320: obtaining initial carbon fixation information based on the water area to be processed, and determining at least one preset target point based on the initial carbon fixation information and the initial landscape element information.

[0047] Each wetland to be treated may include two parts: vegetation and wetland surface. Carbon sequestration information may include the carbon sequestration of vegetation and the carbon sequestration of wetland surface. The carbon sequestration of vegetation may be determined by plant coverage, and the plant coverage may be obtained by further calculation of photo data obtained by a camera. The carbon sequestration of the wetland surface may be determined by the carbon dioxide emissions from the wetland surface. The carbon dioxide emissions may be determined by a gas detection device, such as a carbon dioxide sensor. The carbon sequestration information may be determined based on the carbon sequestration of vegetation and the carbon sequestration of the wetland surface by formula (1). The carbon sequestration information may be expressed as a fraction.

[0048]

[0049] in, is the initial carbon fixation fraction of the water area to be treated, and They represent the weights corresponding to the carbon sequestration fraction of vegetation and the carbon sequestration fraction of wetland surface, and They represent the carbon sequestration fraction of vegetation and the carbon sequestration fraction of wetland surface, respectively. The initial carbon sequestration can include the initial carbon sequestration of vegetation and the initial carbon sequestration of wetland surface. The initial carbon sequestration of vegetation can be determined by the initial coverage of plants, and the initial coverage of plants can be obtained by further calculation of the photo data obtained by the camera. The initial carbon sequestration of the wetland surface can be determined by the carbon dioxide emissions of the wetland surface.

[0050] In some embodiments, the weights corresponding to the carbon sequestration fraction of vegetation and the carbon sequestration fraction of wetland surface are proportional to the area corresponding to the water area to be treated, and the higher the area, the higher the corresponding weight. The weights can be determined according to a preset table.

[0051] The preset target point may refer to a location in the water body that needs to be modified.

[0052] In some embodiments, a difference point between a vector represented by the initial landscape element information and a vector represented by the ideal landscape element information of the water area is used as at least one candidate target point.

[0053] In some embodiments, determining at least one preset target point based on at least one candidate target point and initial carbon sequestration information includes:

[0054] S11, establishing a first relationship between ideal landscape element information and corresponding ideal carbon fixation amount through a multivariate linear regression model.

[0055] S12, establishing a second relationship between the landscape element information of the current water area and the corresponding current carbon fixation amount through a multiple linear regression model. The second relationship is determined based on historical data of the current water area (including historical carbon dioxide emissions and corresponding historical landscape element information).

[0056] S13, obtaining the initial carbon fixation information of the candidate target point, determining the corresponding ideal carbon fixation and current carbon fixation based on the first relationship and the second relationship respectively, and determining the difference between the ideal carbon fixation and the current carbon fixation, and when the difference is greater than the preset difference threshold, taking the corresponding candidate target point as the preset target point.

[0057] Since it is necessary to build parks and other buildings that can transform the landscape along the water, it is necessary not only to obtain information on landscape elements on the water surface, but also to obtain accurate wetland surface information in the underwater water area in order to further obtain accurate preset target points and transformation plans.

[0058] Based on the initial carbon fixation information, the water area to be treated is determined, and the preset target points are further determined. The scope of transformation is gradually narrowed, and the water area transformation is carried out in a targeted manner, which can improve the transformation effect and reduce the waste of resources.

[0059] Step 330: Determine at least one planned transformation information of at least one target site based on the initial landscape element information, where the target site includes at least one of the at least one preset target point.

[0060] Planned transformation information may refer to the design data and / or transformation data of the target site. For example, planned transformation information may include, but is not limited to, terrain data, building data, water data, and biological data of the target site. Among them, terrain data may include the surface height of the target site and the change of terrain; building data may include the area, volume, type, distribution, etc. of all buildings and / or structures in the target site; water data may include the area and distribution of water areas in the target site; biological data may refer to data such as the type, size, area, and water demand of all plants in the target site, and plants may include, but are not limited to, trees, shrubs, and / or herbs.

[0061] In some embodiments, the processor may use a variety of possible methods to obtain planned transformation information. For example, the processor may analyze the corresponding construction drawings of the target site, extract the planned transformation information therefrom, and input it into the processor. For another example, it is also possible to obtain terrain data, building and / or structure data, water body data, and biological data in the image based on the relevant image data of the target site, and then determine the planned transformation information by modifying at least one of the landscape element information, and input it into the processor. In some embodiments, the water body data and biological data in the initial landscape element information of the current water area can be modified to change the initial carbon fixation information of the current water area to be treated, and determine at least one planned transformation information.

[0062] In some embodiments, the processor may determine at least one planned transformation information of at least one target site through a planning model based on the initial landscape element information. The input of the planning model may include a preset target point and the initial landscape element information, and the output may be the corresponding at least one planned transformation information. The planning model may be a machine learning model, such as a deep neural network. The planning model may be obtained through training based on a first historical sample and a first label. The first historical sample may include a historical target point and corresponding historical landscape element information, and the label may be the corresponding historical planned transformation information.

[0063] The planned transformation information should include not only water body data and biological data, but also terrain data, building and / or structure data. By comprehensively considering various information such as water body data, biological data, terrain data, building and structure data, and the mutual influence of the above elements, the current status and potential influencing factors of the wetland can be more comprehensively evaluated, providing a scientific basis and effective support for the formulation and implementation of the transformation plan.

[0064] Step 340: simulate the target site based on the initial landscape element information and the planned transformation information, determine and output at least one simulation result of the target landscape of the target site.

[0065] The simulation result may refer to the simulation modeling result after the transformation of the target site. The target landscape may refer to the landscape of the target site after the transformation. The simulation result may be three-dimensional model data. For example, the simulation result may include the modeling results of three-dimensional terrain simulation, building simulation, water system simulation, etc. of the target site. In some embodiments, the simulation result may also include the simulation modeling result after adjusting or optimizing the water system simulation data of the target site. In some embodiments, the target landscape simulation result may include target landscape element information. In some embodiments, the simulation result may be characterized by the target landscape element information. The target landscape element information may refer to the landscape elements contained in the target site after the transformation. The target landscape element information may refer to the information related to the landscape elements contained in the target site after the transformation. The method for obtaining the target landscape element information may refer to the method for obtaining the initial landscape element information of this specification.

[0066] In some embodiments, the simulation result can be achieved by three-dimensional simulation technology based on the initial landscape element information and the planned transformation information. The three-dimensional simulation technology can refer to related technologies used for simulation modeling. For example, the three-dimensional simulation technology can be used to simulate and model the target site based on the initial landscape element information and the planned transformation information, and obtain data such as terrain simulation, building simulation, and water system simulation of the transformed target site. Among them, the three-dimensional simulation technology can be implemented based on at least one of 3D development engines such as 3D Unity, DirectX, and OpenGL.

[0067] Terrain simulation may refer to simulation modeling related to terrain data in the planned transformation information. For example, terrain simulation may include simulation modeling based on data such as terrain undulations, surface height changes, and terrain changes of the target site, to obtain simulation information that is the same or similar to the terrain data of the target site.

[0068] Building simulation may refer to simulation modeling related to building data in the planned transformation information. Among them, building simulation may include simulation modeling based on the building and / or structure information of the target site, and obtaining simulation information that is the same or similar to the building data of the target site. For example, a building of a corresponding type and size may be simulated at a corresponding position in a virtual scene, wherein the position and size of the building may be determined based on the ratio of the size of the virtual space to the actual planned size of the target site and the planned transformation information. For example, when the ratio of the size of the virtual space to the actual planned size of the target site is 1:1, the size and position of the building in the planned transformation information may be determined as the corresponding size and position of the building in the virtual space.

[0069] The simulation results can clearly and intuitively view the three-dimensional simulation effect of the target site and determine whether the planned transformation information meets the requirements.

[0070] Water system simulation may refer to simulation modeling related to water system data in the planned transformation information. In some embodiments, the water system may include water scenic spots, water channels, and dredging pipelines in the transformed target site.

[0071] Water system simulation can be based on the water flow in the target site and the location, direction and area of ​​the pond, and the simulation information determined by simulation modeling.

[0072] Water attractions may refer to simulated data about water flow locations determined based on simulations of target sites. For example, water attractions may include, but are not limited to, trees, shrubs, grass, ponds, pools, and / or water storage pits. In some embodiments, some water attractions may have the function of storing water and adjusting water flow. In some embodiments, water attractions may absorb a portion of the water, wherein the absorption may include, but is not limited to, plant absorption, soil infiltration, and / or evaporation. The siltation in water attractions is mainly caused by inorganic silt in the current water area, which is mainly composed of mineral particulate matter, such as sand, silt sand, etc. Because the sedimentation rate of suspended particulate matter is relatively fast when the flow rate is large, inorganic silt is usually relatively easier to accumulate in areas with large flow rates in the river.

[0073] A water channel may refer to simulation data about a water flow path determined based on a simulation of a target site. For example, a water channel may include, but is not limited to, a ditch, a trough, and a water pipe. In some embodiments, different water channels may have different maximum water flow rates.

[0074] Dredging pipelines can refer to channels that help dredge water areas in water systems and water channels. Specifically, dredging water areas can refer to the process of extracting sediments such as silt from water areas by laying dredging pipelines, and then using sediment pumps to transport the sediments to designated locations for treatment.

[0075] In some embodiments, water system simulation may also include making adjustments based on water body simulation data and simulating and modeling. For example, the adjustments may include changing the direction, quantity, and size of dredging pipes. For another example, the adjustments may include changing the direction of water flow in the water body simulation data, the size of the water flow, and the area occupied. For more information about water system simulation, see the manual. Figure 4 And its related content introduction.

[0076] Step 350: determine a carbon sequestration fraction based on at least one simulation result, and determine target transformation information based on the carbon sequestration fraction.

[0077] The target transformation information may refer to the planned transformation information that is ultimately used to be implemented. In some embodiments, the processor may determine the carbon sequestration score of the corresponding simulation result through the carbon sequestration model based on the simulation results of the same target site, and use the planned transformation information corresponding to the simulation result with the highest carbon sequestration score or the highest carbon sequestration change rate determined based on the initial carbon sequestration information as the target transformation information. The carbon sequestration change rate can be determined by formula (1).

[0078]

[0079] in, is the carbon fixation rate after transformation, is the initial carbon fixation fraction, is the carbon sequestration fraction after transformation.

[0080] The carbon sequestration model may include a vegetation determination layer, a wetland surface determination layer, and a score determination layer. The carbon sequestration model input may include simulation results. The carbon sequestration of vegetation and the carbon sequestration of wetland surfaces are obtained through the vegetation determination layer and the wetland surface determination layer. The input of the score determination layer may include the carbon sequestration of vegetation and the carbon sequestration of wetland surfaces, and the output may include the carbon sequestration score. The carbon sequestration model may be a machine learning model, for example, a graph neural network. The carbon sequestration model may be obtained by training with a second historical sample and a second label. The vegetation determination layer, the wetland surface determination layer, and the score determination layer may be obtained by joint training. The second historical sample may include historical real-time modeling results, and the second label may include the carbon sequestration of vegetation and the historical carbon sequestration of wetland surfaces, as well as the carbon sequestration score.

[0081] Since the weights of vegetation carbon sequestration and wetland surface carbon sequestration are required when determining the carbon sequestration fraction in historical data, the output carbon sequestration fraction is closer to reality and can provide a scientific basis and effective support for the formulation and implementation of the transformation plan.

[0082] In some embodiments of this specification, the target site is modeled based on three-dimensional simulation technology, and the user can more intuitively obtain the simulation effect of the target site determined based on the planned transformation information, and implement it based on the simulation results. The user can also make adjustments or modifications on this basis, and can more accurately analyze whether the landscape of the transformed target site can meet the needs of the user, and select the most appropriate simulation results as the planning scheme of the target site, which can reduce unnecessary modifications in design and communication, and reduce planning costs to a certain extent. On the other hand, by transforming the landscape around the water area into the target landscape (for example, a park), the advantages of the water area can be fully utilized to solve the problem of water siltation, improve the surrounding landscape, and improve the quality of the surrounding environment of the water area.

[0083] During the landscape transformation of the target site, silting up of the water area will cause the water level to rise, the water area to become shallower, the water area to become polluted, etc., which will affect the target landscape after the transformation. For example, pollutants accumulated in the bottom mud in the water area will be re-suspended in the water and overflow into the water area, which will affect the normal use of facilities around the water area. Therefore, the dredging plan of the water area needs to be fully considered in the landscape transformation of the target site. In some embodiments, the water system may include water scenic spots, water channels, and dredging pipelines in the target site. The simulation results of the water system may include the dredging plan for the water system of the target site, timely monitoring of the upstream and downstream rivers of the wetland, predicting the silting up of the river channel, and further timely determining the target transformation plan. Inorganic siltation may be cleaned up, water flow is restored, and habitats are repaired. Measures such as these can be taken to reduce the impact of siltation on the wetland landscape and ecosystem.

[0084] Figure 4 is an exemplary flow chart of determining a dredging solution for a water system of a target site according to some embodiments of this specification. In some embodiments, process 400 may be executed by a processor. Figure 4 As shown, process 400 includes the following steps:

[0085] Step 410: Determine first basic information and first water flow information of the water attraction based on the planned transformation information.

[0086] The first basic information may refer to the information of the water attraction itself. For example, the first basic information may include but is not limited to the size, shape, floor area, depth, location, etc. of the water attraction. In some embodiments, the real-time landscape element information of the current water attraction may include the first basic information. The real-time landscape element information may refer to the landscape elements contained in the current target site. The real-time landscape element information may refer to information related to the landscape elements contained in the current target site.

[0087] The first water flow information may refer to parameters related to the water volume of the water attraction. For example, the first water flow information may include but is not limited to the number of water inlets and / or water outlets and the water flow rate of each water inlet and / or water outlet. In some embodiments, the processor may obtain the first basic information and the first water flow information of the water attraction in a variety of ways. For example, the processor may determine the first basic information and the first water flow information of the water attraction by analyzing the simulation data based on a simulation of the target site. For another example, the first basic information and the first water flow information of the water attraction may be obtained by querying the planned transformation information input by the user.

[0088] Step 420, based on the planned transformation information, determine the second basic information and the second flow information of the flow channel.

[0089] The second basic information may refer to the information of the water channel itself. For example, the second basic information may include the location, length, width, depth, terrain height, water flow direction, and the number of connected water attractions. In some embodiments, the different terrain heights of different water channels may affect their water intake. Understandably, under the same conditions, water flow is more inclined to preferentially flow into the water channel with lower terrain. The real-time landscape element information of the current water channel may include the second basic information.

[0090] The second water flow information may refer to parameters related to the water flow channel and the water volume. For example, the second water flow information may include but is not limited to the maximum allowable water flow rate.

[0091] In some embodiments, the first basic information and the first water flow information of the water attraction can be obtained in a variety of ways. For example, the second basic information and the second water flow information of the water channel can be determined by analyzing the planned transformation information and using mathematical functions and / or statistical analysis. For example, based on the width and depth of a water channel in the planned transformation information, combined with the water flow velocity, the maximum allowable water flow of the water channel can be estimated through mathematical calculation.

[0092] Step 430 , determining water flow information of a water system in a target landscape of a target site based on the first basic information, the first water flow information, the second basic information, and the second water flow information.

[0093] A water system may refer to multiple water bodies determined based on a simulation of a target site. For example, a water system may include multiple water channels and multiple water scenic spots.

[0094] Water flow information may refer to water flow information of multiple water channels and water attractions in a water system. For example, water flow information may include water inflow and outflow of water channels and water attractions. For another example, water flow information may also include water storage capacity of multiple water attractions.

[0095] In some embodiments, the processor may analyze and process the first basic information, the first water flow information, the second basic information, and the second water flow information to determine the water flow information of the water system in the target site. For example, the water flow information may be determined using a machine learning model.

[0096] In some embodiments, the processor can determine the water flow information of the water system in the target site through the siltation simulation model based on the first basic information, the first water flow information, the second basic information and the second water flow information, wherein the siltation simulation model is a machine learning model. For more information about determining water flow information based on the water system model, see Figure 5 and its related description.

[0097] Step 440: Determine siltation information based on the water flow information, the real-time landscape element information, and the target landscape element information.

[0098] The siltation information may refer to siltation information related to water attractions and water channels. In some embodiments, the siltation information may include the location of the siltation point in the water attractions and water channels and the degree of siltation. In some embodiments, the real-time landscape element information may include the information of the current siltation. The information of the current siltation may refer to the information of the siltation in the current water attractions and water channels. The information of the current siltation may include the composition and height of the deposits, the degree of siltation, the cross-sectional area of ​​the flow, the time interval from the last cleaning of the deposits to the current time, etc. The deposits may refer to a large amount of sediment, silt, rock fragments, life production garbage and other debris accumulated in the water attractions and water channels. In some embodiments, the information of the current siltation of the water attractions and water channels can be further determined by the data obtained by the sensors arranged inside or around the water attractions and water channels. The sensors may include flow meters, cameras, component sensors, etc. The water flow rate is inversely proportional to the degree of siltation. When the water flow rate is too small, the degree of siltation of the current siltation point can be judged by the relationship between the flow rate and the degree of siltation. When the height of sediment, silt, rock fragments and other deposits in the photo can be determined based on at least one photo taken by a camera including a water feature and a water channel, the water surface and riverbed heights (i.e., target landscape element information) without sedimentation in the taken photo are compared with the initial photo without siltation to determine the current information of siltation.

[0099] In some embodiments, the processor may determine the siltation information based on the current siltation information, the water flow information, and the target landscape information.

[0100] In some embodiments, the processor may determine the correspondence through linear regression based on historical siltation information, water flow information, and target landscape information, and determine the siltation information through the correspondence based on current siltation information, water flow information, and target landscape information.

[0101] In some embodiments, the processor can determine the siltation information based on the water flow information, the real-time landscape element information, and the target landscape element information through a siltation simulation model, wherein the siltation simulation model is a machine learning model. For details about the siltation simulation model, please refer to this specification. Figure 5 Related description.

[0102] Through some embodiments of the present specification, siltation information is determined based on target landscape element information. The degree of siltation can be determined by more intuitively comparing the current landscape element information with the target landscape element information, and the effect expected to be achieved through dredging can also be determined.

[0103] Step 450, determining a dredging plan based on the water flow information and the siltation information.

[0104] Dredging programs may include programs to dredge deposits from water features and flowing channels.

[0105] In some embodiments, determining a dredging plan may include: judging whether dredging is needed based on water flow information and siltation information, as well as corresponding dredging methods and dredging information.

[0106] In some embodiments, the dredging scheme can be determined by a dredging database. The preset database includes at least one historical siltation information vector and corresponding historical water flow information, and the siltation information vector can be obtained through a siltation embedding layer. The elements in the siltation information vector include vectors corresponding to siltation points and siltation degrees. For example, the siltation information vector can be (1, 70). 1 can represent the number of the water system component that is pre-determined, and 70 can represent that the siltation degree of siltation point 1 is 70%. Water flow information can be determined by a water flow embedding layer. By inputting historical siltation information and historical water flow information into the siltation embedding layer and the water flow embedding layer respectively, the corresponding historical siltation information vector and historical water flow information vector are obtained. Each historical siltation information vector, historical water flow information vector and historical dredging method are one-to-one corresponding. In some embodiments, by comparing the current siltation information vector with each historical siltation information vector and the corresponding historical water flow information vector in the siltation database, the historical siltation information vector with the largest overall similarity is determined, and the corresponding historical dredging scheme is used as the current dredging scheme.

[0107] The similarity between the current siltation information vector and the historical siltation information vector, and the similarity between the current water flow information vector and the historical water flow information vector can be determined by the distance between the vectors. In some embodiments, the overall similarity can be determined by the siltation information similarity and the water flow information similarity. For example, the overall similarity can be determined by formula (1).

[0108]

[0109] in, is the overall similarity, is the congestion information similarity, is the weight corresponding to the similarity of congestion information, is the water flow information similarity, is the weight corresponding to the similarity of water flow information.

[0110] In some embodiments, the weight corresponding to the siltation degree is higher than the weight corresponding to the water flow information. In actual situations, the water flow may be highly affected by the external environment such as the upstream water system, and the siltation degree can better reflect the actual siltation of the current water scenic spots and water channels. Therefore, the weight corresponding to the siltation degree is higher than the weight corresponding to the water flow information, and the obtained dredging solution is the most efficient and effective in solving the current siltation problem.

[0111] In some embodiments, the dredging method may include dredging a pipeline through a dredging pipeline. The dredging information may include information related to the dredging of the pipeline. For example, the dredging information may include the dredging water flow rate of the pipeline. For details about the dredging method based on the dredging pipeline, please refer to this specification. Figure 6 Description of the content.

[0112] In some embodiments of the present specification, relevant data of the water system (e.g., water flow information) obtained by simulating the target site is used, and the siltation information is further determined based on the water flow information, the real-time landscape element information, and the target landscape element information. By determining the siltation point and the corresponding siltation degree, the location where siltation may occur corresponding to the actual situation can be obtained, and then the siltation point can be dredged in a targeted manner to reduce the management cost and ensure the normal operation of the target site.

[0113] In some embodiments, the processor may determine the congestion information through congestion model simulation.

[0114] Figure 5 It is a schematic diagram of a siltation simulation model according to some embodiments of the present specification.

[0115] like Figure 5 As shown, based on water flow information 510, real-time landscape element information 520 and target landscape element information 530, siltation information 550 is determined through a siltation simulation model 540, wherein the siltation simulation model 540 is a machine learning model. For example, the siltation simulation model can be GNN (Graph Neural Networks), etc. Each node exchanges basic information with each other through edges, thereby continuously updating its own node information until the stop condition is met. The output data of the node to be predicted is the siltation information of the node to be predicted after the graph neural network model stops updating.

[0116] In some embodiments, the processor may construct a landscape map based on water flow information, real-time landscape element information, and target landscape element information. The landscape map may include nodes and edges. Among them, the nodes may correspond to water attractions, and the attributes of the nodes may include real-time landscape element information, target landscape element information, and water flow information corresponding to the current water attraction. In some embodiments, the attributes of the nodes may also include residual water volume characteristics. The aforementioned residual water volume characteristics may be determined based on the residual water volume of each sub-area in the target site. For more information on determining the residual water volume of each sub-area in the target site, please refer to Figure 6 In some embodiments, when the water scenic spot is a natural landscape, the node information may also include siltation information before the transformation.

[0117] Edges can reflect the connection relationship between different nodes. When two nodes are connected by a water channel, the two nodes can be connected as an edge. The edge corresponds to the distance and / or direction between the two nodes, and the attributes of the edge can include the real-time landscape element information corresponding to the water channel, the target landscape element information, and the water flow information. The position of nodes and edges in the landscape map can be determined based on the planned transformation information.

[0118] In some embodiments, when a water attraction and / or a water channel is a natural landscape, the node information corresponding to the water attraction may also include the siltation information before the transformation, and the edge information corresponding to the water channel may also include the siltation information before the transformation. A natural landscape may refer to a landscape that existed before the transformation. An artificial landscape may refer to a landscape that did not exist before the transformation. In some embodiments of the present specification, considering the siltation information of a water attraction or a water channel under natural conditions can improve the accuracy of the judgment of the siltation information of the current transformed landscape.

[0119] In some embodiments, the fouling simulation model may be acquired through training.

[0120] In some embodiments, a siltation simulation model can be obtained by acquiring multiple training samples and training based on the multiple training samples and their corresponding labels. The training samples may include a historical landscape map composed of historical water flow information, historical landscape element information, and historical target landscape element information, and the corresponding sample label is historical siltation information. In some embodiments, training samples and labels can be acquired based on historical data, for example, samples and labels can be acquired based on historical water system simulation data. In some embodiments, the simulation data can also be processed based on a processor to acquire samples and labels. By using a processor to adjust and modify the simulation data, a large number of samples and labels required for training the siltation simulation model can be efficiently acquired, which can improve the efficiency of model training and reduce training costs.

[0121] Input the training samples into the initial siltation simulation model, build a loss function based on the output and label of the initial water system simulation, and update the parameters of the initial siltation simulation model through the loss function until the trained initial siltation simulation model meets the preset conditions, and obtain the trained siltation simulation model, where the preset conditions can be that the loss function is less than a threshold, converges, or the training cycle reaches a threshold, etc. For more information about the residual water model, see Figure 6 and its related description.

[0122] In some embodiments of the present specification, the landscape map can be determined based on the relevant information of the water scenic spots and the water channels, and the accuracy and efficiency of the siltation points and the corresponding siltation degrees can be improved by using the trained siltation simulation model based on the landscape map. And timely prediction and adjustment can be made by updating the data in real time.

[0123] After determining the siltation information, the siltation points in the water system need to be dredged in time, otherwise it will cause the water level of the water system to rise, the water area to become shallower, the water area to be polluted, and other problems, affecting the target landscape after the transformation. In some embodiments, the dredging plan may include dredging the pipeline through a dredging pipeline.

[0124] Figure 6 600 is an exemplary flow chart of determining a dredging solution according to some embodiments of the present specification. In some embodiments, process 600 may be executed by a processor. Figure 6 As shown, process 600 includes the following steps:

[0125] Step 610, determining the terrain information and water system information of the target site based on the planned transformation information.

[0126] The terrain information may refer to information about the ground morphology and undulation characteristics in the target site. For example, the terrain information may include but is not limited to the altitude of the terrain in each area of ​​the target site, the slope and direction of the terrain undulation, etc. In some embodiments, the landscape element information may include terrain information and water system information.

[0127] Water system information refers to information about the water network system composed of all water attractions, water channels, etc. in the target site. For example, water system information may include but is not limited to the volume of water bodies in each area of ​​the target site, the area of ​​water bodies, the flow direction and flow rate of the water system, and the evaporation of water bodies per unit time.

[0128] In some embodiments, the processor can analyze and generate corresponding terrain information and water system information based on the planned transformation information. In some embodiments, the processor can directly process the planned transformation information to filter out the terrain information and water system information of the target site.

[0129] Step 620, based on the climate simulation information, terrain information and water system information, determine the remaining water volume of each sub-area in the target site.

[0130] Climate simulation information refers to information used to simulate the climate in the target site. For example, climate simulation information may include, but is not limited to, lighting information, temperature information, precipitation information, etc. of the target site. In some embodiments, climate simulation information can be determined in a variety of ways. For example, a user independently inputs the required climate simulation information through a user terminal. For another example, the processor can collect and analyze a large amount of historical weather data in the area where the target site is located, thereby determining the most common weather and / or extreme weather (such as heavy rain, etc.) in the area where the target site is located.

[0131] Sub-areas refer to local areas in the target site. For example, sub-areas can be divided by different scenic spots, with scenic spot A being one sub-area and scenic spot B being another sub-area. For another example, sub-areas can be divided by area, with the target site divided into sub-areas of the same area, with each 100 square meters being a sub-area. For another example, sub-areas can be divided by scenic spots and areas, with scenic spot A being divided into sub-areas of 150 square meters and scenic spot B being divided into sub-areas of 100 square meters.

[0132] The residual water volume may refer to the amount of water remaining in each sub-area of ​​the target site after being absorbed by vegetation and soil within a certain period of time. The residual water volume may be expressed in mm or other units of measurement. In some embodiments, the residual water volume may also be expressed in different levels. For example, if the residual water volume of a sub-area of ​​the target site in a year is more than 200 mm, it is classified as level one, indicating that the residual water volume is too little. For another example, if the residual water volume of a sub-area of ​​the target site in a year is more than 800 mm, it is classified as level four, indicating that the residual water volume is too much.

[0133] In some embodiments, when the climate simulation information is common weather, the processor can determine whether the remaining water volume in the sub-area of ​​the target site meets daily use (e.g., irrigation, landscaping, etc.) based on the climate simulation information; when the climate simulation information is extreme weather, the processor can determine whether the remaining water volume in the sub-area of ​​the target site is dangerous (e.g., drought, flooding, etc.) based on the climate simulation information. In some embodiments, when the remaining water volume in the sub-area of ​​the target site does not meet the preset conditions, the processor can adjust the water system simulation. The preset conditions can refer to a manually preset range of remaining water volume that meets the daily water use of the sub-area of ​​the target site and is not dangerous.

[0134] In some embodiments, the processor can perform modeling or use various data analysis algorithms, such as regression analysis, discriminant analysis, etc., to analyze and process the climate simulation information, terrain information and water system information in the target site to determine the remaining water volume in each sub-area of ​​the target site.

[0135] In some embodiments, the processor may process the climate simulation information, the terrain information, and the water system information through a remaining water prediction model to determine the remaining water volume of each sub-area of ​​the target site. The remaining water prediction model may refer to a model for predicting the remaining water volume of each sub-area of ​​the target site within a certain period of time.

[0136] The remaining water volume prediction model may include a first feature extraction layer, a second feature extraction layer, and a remaining water volume determination layer. In some embodiments, the remaining water volume prediction model may process terrain information, water system information, and climate simulation information to determine the remaining water volume.

[0137] In some embodiments, the first feature extraction layer may process the terrain information and the water system information to obtain the surface features. The input of the first feature extraction layer may include the terrain information and the water system information, and the output may include the surface features. The first feature extraction layer may be a deep learning model.

[0138] In some embodiments, the second feature extraction layer can process the climate simulation information to obtain weather features. The input of the second feature extraction layer can include climate simulation information, and the output can include weather features. The second feature extraction layer can be a deep learning model.

[0139] In some embodiments, the remaining water volume determination layer may process the surface features and weather features to obtain the remaining water volume. The input of the remaining water volume determination layer may include the surface features and weather features, and the output may include the remaining water volume. The remaining water volume determination layer may be a deep learning model.

[0140] The remaining water volume prediction model can be obtained by jointly training the first feature extraction layer, the second feature extraction layer and the remaining water volume determination layer. The training samples may include sample terrain information, sample water system information and sample climate simulation information, and the labels of the training samples may include sample surface features, sample weather features and sample remaining water volume.

[0141] Weather characteristics may refer to characteristics used to characterize information such as precipitation, temperature, and sunshine of each sub-area of ​​the target site. For example, weather characteristics may be divided into different levels according to the depth of precipitation. The more precipitation, the higher the precipitation characteristic level, and vice versa. In some embodiments, weather characteristics may be determined based on climate simulation information of each sub-area of ​​the target site. In some embodiments, weather characteristics may be represented by vectors. The positions of the elements in the aforementioned vectors represent the type of weather information, such as precipitation, temperature, and sunshine. The values ​​of the elements represent the specific circumstances corresponding to each piece of weather information. For example, the weather characteristics may be (35, 24, 15), which respectively represent that the average daily precipitation of the sub-area of ​​the target site is 35 mm, the average temperature is 24°C, and the average sunshine duration is 15 h.

[0142] Surface features may refer to features used to characterize information such as terrain undulations, water system flow direction, water volume, soil type, etc. of each sub-area of ​​the target site. For example, surface features may be graded according to information such as the terrain and water system of the surface. In some embodiments, surface features may be determined based on the terrain information and water system information of each sub-area of ​​the target site. In some embodiments, surface features may be represented by vectors. The positions of the elements in the aforementioned vectors represent the type of surface information, such as the height of the terrain undulations, the water volume of the water system, and the soil infiltration volume. The values ​​of the elements represent the specific circumstances corresponding to each piece of surface information. For example, the surface features may be (10, 60, 20), which respectively represent that the average altitude of the terrain undulations of the sub-area of ​​the target site is 10m, the water volume of the water system on that day is 60mm, and the soil infiltration volume on that day is 20mm.

[0143] In some embodiments, the input of the remaining water volume prediction model may include weather characteristics and surface characteristics. The output of the remaining water volume prediction model may include the remaining water volume of each sub-area of ​​the target site. For example, the remaining water volume of sub-area A of the target site is determined based on the remaining water volume prediction model processing weather characteristics and surface characteristics.

[0144] In some embodiments, the remaining water volume prediction model can be trained based on historical data. In some embodiments, the remaining water volume prediction model can be trained based on multiple training samples and labels.

[0145] In some embodiments, the training sample includes sample weather characteristics and surface characteristics. The label is the remaining water volume of the target site sub-area. The training sample can be obtained based on historical data, and the label of the training sample can be determined by manual labeling or automatic labeling. For example, when the average weather characteristic level of the training data in one year is the highest level, the label of the training data can be automatically labeled as the remaining water volume. The above description is only an example and not a limitation, and the label of the training data can be obtained in various ways.

[0146] Step 630, determining a dredging plan based on the remaining water volume and siltation information.

[0147] Since the dredging method may include dredging the pipeline through a dredging pipeline, during the pipeline dredging process, sediment and other deposits may easily cause pipeline blockage, thereby affecting work efficiency. To prevent pipeline blockage, water flow may be added to the dredging pipeline to reduce pipeline siltation. Therefore, the dredging plan may include the dredging water flow, dredging time and dredging location of pipeline dredging. The dredging location may refer to a node where the siltation degree is greater than the siltation threshold. The dredging time may refer to the time point when the siltation degree of the siltation point is greater than the siltation threshold. The siltation threshold may be set manually.

[0148] In some embodiments, when the siltation degree of the current siltation point is higher than the siltation threshold, siltation can be performed. In some embodiments, when dredging is required, the processor can determine the dredging water flow required in the dredging pipeline based on the siltation degree of the siltation point, and determine the corresponding sub-area based on the location of the siltation point, and compare the remaining water volume and the dredging water flow within the corresponding sub-area. When the required dredging water flow is higher than the remaining water volume, supplementary water and the remaining water within the same sub-area can be introduced into the dredging pipeline at the same time for dredging.

[0149] The replenishment water volume can refer to the difference between the dredged water flow and the residual water volume at the siltation point within the same sub-area.

[0150] Through some embodiments of the present specification, the remaining water volume is determined by considering terrain information, water system information and climate information, and the remaining water in the same sub-area is introduced into the dredging pipeline for pipeline dredging. This can not only fully utilize the advantages of the water area itself (the remaining water produced by factors such as climate and terrain) to solve the problem of water area siltation and prevent excessive remaining water from causing damage to the target landscape, but also discharge the remaining water nearby, reducing the amount of supplementary water, improving the effective utilization of resources, improving the surrounding landscape, and improving the surrounding environment of the water area.

[0151] It should be noted that the above description of the relevant process is only for example and explanation, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the process under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

Claims

1. A city low-carbon construction level index scoring system, characterized in that: The system includes: An initial landscape determination module is used to obtain initial landscape element information and determine a water area to be processed based on the initial landscape element information; A preset target point determination module, used to obtain initial carbon fixation information based on the water area to be treated, and determine at least one preset target point based on the initial carbon fixation information and the initial landscape element information; A planning module, configured to determine at least one planned transformation information of at least one target site based on the initial landscape element information, wherein the target site includes at least one of the at least one preset target point; A simulation module, configured to simulate the target site based on the initial landscape element information and the planned transformation information, determine and output at least one simulation result of the target landscape of the target site; A target module is used to determine a carbon sequestration fraction based on the at least one simulation result, and to determine target transformation information based on the carbon sequestration fraction.

2. The system according to claim 1, characterized in that The preset target point determination module includes: A candidate module, used for taking a difference point between a vector represented by the initial landscape element information and a vector represented by the ideal landscape element information of the water area as at least one candidate target point; A preset module, used to determine at least one preset target point based on the at least one candidate target point and the initial carbon fixation amount information, comprising: The first relationship between the ideal landscape element information and the corresponding ideal carbon fixation was established through a multiple linear regression model; The second relationship between the landscape element information of the current water area and the corresponding current carbon fixation amount was established through a multivariate linear regression model; Obtain the initial carbon fixation information of the candidate target point, determine the corresponding ideal carbon fixation amount and the current carbon fixation amount based on the first relationship and the second relationship respectively, and determine the difference between the ideal carbon fixation amount and the current carbon fixation amount, and when the difference is greater than a preset difference threshold, use the corresponding candidate target point as the preset target point.

3. The system according to claim 2, characterized in that The water system includes water attractions, water channels and dredging pipelines in the target site. The simulation results include dredging plans. The simulation module includes a water system simulation submodule for: Based on the planned transformation information, determining first basic information and first water flow information of the water attraction; Based on the planned transformation information, determining second basic information and second flow information of the flow channel; Determining water flow information of the water system in the target landscape of the target site based on the first basic information, the first water flow information, the second basic information, and the second water flow information; Determine siltation information based on the water flow information, the real-time landscape element information, and the target landscape element information; The dredging plan is determined based on the water flow information and the siltation information.

4. The system according to claim 3, characterized in that The water system simulation submodule includes a dredging module, which is used to: Based on the planned transformation information, determining the terrain information and water system information of the target site; Determining the remaining water volume of each sub-area in the target site based on the climate simulation information, the terrain information and the water system information; A dredging plan is determined based on the remaining water volume and the siltation information.

5. A scoring method for urban low-carbon construction level index, characterized in that: include: Acquiring initial landscape element information, and determining a water area to be processed based on the initial landscape element information; Acquire initial carbon fixation information based on the water area to be treated, and determine at least one preset target point based on the initial carbon fixation information and the initial landscape element information; Based on the initial landscape element information, determining at least one planned transformation information of at least one target site, the target site including at least one of the at least one preset target point; Based on the initial landscape element information and the planned transformation information, simulating the target site, determining and outputting at least one simulation result of the target landscape of the target site; A carbon sequestration fraction is determined based on the at least one simulation result, and target transformation information is determined based on the carbon sequestration fraction.

6. The urban low-carbon construction level index scoring method according to claim 5 is characterized in that: The determining at least one preset target point based on the initial carbon fixation amount information and the initial landscape element information includes: A difference point between a vector represented by the initial landscape element information and a vector represented by the ideal landscape element information of the water area is used as at least one candidate target point; Determining at least one preset target point based on the at least one candidate target point and the initial carbon fixation amount information includes: The first relationship between the ideal landscape element information and the corresponding ideal carbon fixation was established through a multiple linear regression model; The second relationship between the landscape element information of the current water area and the corresponding current carbon fixation amount was established through a multivariate linear regression model; Obtain the initial carbon fixation information of the candidate target point, determine the corresponding ideal carbon fixation amount and the current carbon fixation amount based on the first relationship and the second relationship respectively, and determine the difference between the ideal carbon fixation amount and the current carbon fixation amount, and when the difference is greater than a preset difference threshold, use the corresponding candidate target point as the preset target point.

7. The method according to claim 6, characterized in that The water system includes water attractions, water channels and dredging pipelines in the target site. The simulation results include dredging plans. Determining the dredging plan for the water system of the target site includes: Based on the planned transformation information, determining first basic information and first water flow information of the water attraction; Based on the planned transformation information, determining second basic information and second flow information of the flow channel; Determining water flow information of the water system in the target landscape of the target site based on the first basic information, the first water flow information, the second basic information, and the second water flow information; Determine siltation information based on the water flow information, the real-time landscape element information, and the target landscape element information; The dredging plan is determined based on the water flow information and the siltation information.

8. The method according to claim 7, characterized in that Determining the dredging scheme based on the water flow information and the siltation information includes: Based on the planned transformation information, determining the terrain information and water system information of the target site; Determining the remaining water volume of each sub-area in the target site based on the climate simulation information, the terrain information and the water system information; A dredging plan is determined based on the remaining water volume and the siltation information.

9. A scoring device for urban low-carbon construction level index, characterized in that: The apparatus comprises at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to implement the urban low-carbon construction level index scoring system as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions, and when the computer instructions are executed by the processor, the urban low-carbon construction level index scoring system as described in any one of claims 1 to 4 is implemented.

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