Road domain scale traffic infrastructure ecological benefit improvement quantitative evaluation method

Abstract

The invention discloses a road domain scale traffic infrastructure ecological benefit improvement quantitative evaluation method, and belongs to the crossing field of traffic engineering and ecological informatics. According to the method, acquisition of ecological environment changes before and after road construction is taken as a research object, and multi-source ecological environment data such as vegetation, soil, weather, habitat quality and landscape pattern of a road influence area and a contrast area are acquired; an integrated evaluation index system is constructed from three dimensions of a land resource occupation reduction rate, an ecological function improvement rate and a landscape pattern optimization rate; by comparing a traditional construction scene with an ecological optimization road scene, the net ecological effect improvement amount generated by ecological engineering measures is quantitatively calculated. The method overcomes the defects that an existing evaluation method neglects positive benefits, is extensive in scale and is single in index, achieves the precise, quantitative and integrated benefit evaluation of the whole process of linear traffic engineering such as roads and railways from source avoidance to function improvement, and provides core technical support for ecological design and decision making.

Description

Technical Field

[0001] This application relates to the field of ecological assessment and environmental information processing technology for road engineering, specifically to a quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale. Background Technology

[0002] Promoting the coordinated development of transportation infrastructure construction and high-level ecological environment protection is a core requirement of the national strategies of "ecological civilization construction" and "building a strong transportation nation." The impact of linear transportation infrastructure such as highways and railways on the ecological environment encompasses the entire process of "planning-design-construction-operation-maintenance," involving influences on all ecological elements such as water systems, soil, climate, and organisms. With the continuous expansion of transportation infrastructure construction, the impact of road engineering on regional ecological environment structure and processes is becoming increasingly significant. Problems such as land occupation, habitat fragmentation, vegetation destruction, and soil erosion generated during road construction have become important factors restricting the green development of transportation infrastructure.

[0003] In recent years, with the deepening of the concepts of green transportation and ecological road construction, various ecological engineering measures have been gradually introduced into engineering practice to mitigate the adverse impacts of road construction on ecosystems and promote the restoration of ecological functions. These mainly include the following two approaches: First, in the planning and design phase, through scientifically sound alternative site selection, rerouting, and other source protection measures, or by adopting green overall design, the negative impacts of linear transportation infrastructure on regional ecosystems can be avoided, reduced, remedied, or offset, and even net benefits can be achieved for key objectives. Second, in the road construction phase, by introducing low-impact construction and ecological restoration measures such as slope ecological protection, ecological corridors, and animal passages, the intensity of soil erosion and the mitigation of ecological problems such as desertification or rocky desertification in local areas can be improved to a certain extent. This can more effectively reduce negative ecological impacts than conventional construction, and can be considered as enhancing ecological benefits.

[0004] Currently, environmental impact assessments for transportation projects mainly follow standards such as the "Technical Guidelines for Environmental Impact Assessment," but these focus on qualitative or semi-quantitative predictions and assessments of negative environmental impacts. They lack a systematic and quantitative assessment framework for the positive ecological benefits resulting from optimized site selection and ecological restoration. Existing research and practice often concentrate on single indicators such as post-construction slope vegetation restoration, or on large-scale land use change analysis based on remote sensing indices, resulting in a single assessment dimension. Secondly, the assessment area often uses the project area or buffer zone as the assessment unit, ignoring the characteristics of road alignment engineering, and the accuracy is insufficient to reflect subtle ecological changes at the road scale. Thirdly, data and methods are fragmented; remote sensing inversion, landscape index calculation, and ecological value assessment are often conducted independently, lacking model tools for automated coupling analysis of engineering boundary data, multispectral remote sensing data, and ecological background parameters. Consequently, methods typically focus on describing the degree of road ecological impact or classifying evaluation levels, making it difficult to distinguish whether ecological changes are caused by natural restoration, climate fluctuations, or ecological engineering measures, and also failing to quantitatively reflect the "improvement effect" of ecological engineering measures compared to traditional road construction methods.

[0005] Therefore, especially in the context of the country's promotion of "ecological protection red line" management and exploration of "gross ecosystem product (GEP)" accounting, there is an urgent need to propose a technical method that can scientifically quantify the net positive ecological benefits of green infrastructure construction throughout the entire road construction process, so as to realize the transformation of road ecological effects from qualitative judgment to quantitative assessment and improved measurement. This has important theoretical value and practical urgency. Summary of the Invention

[0006] In view of this, this application provides a method, apparatus, electronic device, computer-readable storage medium, and computer program product for quantitatively assessing the improvement of ecological benefits of transportation infrastructure at the road scale.

[0007] One aspect of this application provides a method for quantitatively assessing the ecological benefits of transportation infrastructure at the road scale, comprising: in response to a benefit assessment instruction, acquiring target road boundary data for road construction, wherein the target road boundary data characterizes the boundary range of the constructed road, and the transportation infrastructure includes the constructed road; based on a preset area occupancy loss calculation rule, calculating a land resource occupancy reduction rate according to multiple different land occupation types in the target road boundary data and type coefficients corresponding to the land occupation types, wherein the land resource occupancy reduction rate includes a permanent land occupation reduction rate, a temporary land occupation reduction rate, and an ecological space occupation reduction rate; calculating the ecological function improvement rate and landscape pattern optimization rate of the constructed road respectively based on the target road boundary data and regional remote sensing data corresponding to the target road boundary data, wherein the ecological function improvement rate characterizes the degree of improvement in ecosystem function, and the landscape pattern optimization rate characterizes the richness and complexity of landscape elements or ecosystems; and, based on a control scenario, performing a weighted summation of the land resource occupancy reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate to obtain data for evaluating the ecological benefit improvement of the constructed road.

[0008] Another aspect of this application provides a quantitative assessment device for the ecological benefit improvement of transportation infrastructure at the road-scale, comprising: an acquisition module, configured to acquire target road boundary data for road construction in response to a benefit assessment instruction, wherein the target road boundary data characterizes the minimum boundary range of direct ecological background occupation by the constructed road, and the transportation infrastructure includes the constructed road; and a first calculation module, configured to calculate a land resource occupation reduction rate based on preset area occupation loss calculation rules, according to multiple different land occupation types in the target road boundary data and type coefficients corresponding to the land occupation types, wherein the land resource occupation reduction rate includes permanent land occupation. The system uses three metrics: reduction rate, temporary land use reduction rate, and ecological space use reduction rate. A second calculation module calculates the ecological function improvement rate and landscape pattern optimization rate of the constructed roads based on the target road boundary data and the corresponding regional remote sensing data. The ecological function improvement rate represents the degree of difference in the ecosystem function of the ecological background occupied by different construction schemes, and the landscape pattern optimization rate represents the degree of difference in the richness and complexity of the ecosystem of the ecological background occupied by different construction schemes. A benefit evaluation module performs a weighted summation of the land resource use reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate to obtain data for evaluating the ecological benefit improvement of the constructed roads.

[0009] Another aspect of this application provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the method as described above.

[0010] Another aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed, are used to implement the method described above.

[0011] Another aspect of this application provides a computer program product comprising computer-executable instructions which, when executed, are used to implement the method described above.

[0012] According to the embodiments of this application, based on preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. At the same time, based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data, the ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated respectively. Finally, the land resource occupancy reduction rate, ecological function improvement rate and landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of the constructed road. Since the reduction rate of permanent land occupation, the reduction rate of temporary land occupation and the reduction rate of ecological space occupation are considered in the process of green road construction, the degree of difference in the ecological impact between different green road construction schemes can be accurately and scientifically quantified, thereby quantitatively calculating the ecological benefits generated by different schemes. At the same time, the ecological benefit improvement quantitative evaluation method provided by the embodiments of this application requires less computational resources, which is convenient for rapid evaluation of different construction projects. Attached Figure Description

[0013] The above and other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0014] Figure 1 An exemplary system architecture for applying a quantitative assessment method for improving ecological benefits, according to an embodiment of this application, is shown;

[0015] Figure 2 A flowchart is shown for a method for quantitatively assessing the improvement of ecological benefits of transportation infrastructure at the road scale according to an embodiment of this application.

[0016] Figure 3 The diagram illustrates the routes of the conventional and green solutions according to embodiments of this application.

[0017] Figure 4A schematic diagram of target road boundary data according to an embodiment of this application is shown;

[0018] Figure 5 A schematic diagram of the initial land occupation boundary data according to an embodiment of this application is shown;

[0019] Figure 6 A schematic diagram illustrating land use type identification during zoning according to an embodiment of this application is shown;

[0020] Figure 7 A schematic diagram comparing the comprehensive vegetation coverage index of different schemes according to embodiments of this application is shown.

[0021] Figure 8 A schematic diagram comparing water conservation capacity indicators of different schemes according to embodiments of this application is shown;

[0022] Figure 9 A schematic diagram comparing the road surface dryness index of different schemes according to embodiments of this application is shown;

[0023] Figure 10 A schematic diagram comparing the landscape diversity indices of different schemes according to embodiments of this application is shown;

[0024] Figure 11 A schematic diagram comparing the plaque cohesion index of different schemes according to embodiments of this application is shown;

[0025] Figure 12 A block diagram of a road-scale transportation infrastructure ecological benefit enhancement quantitative assessment device according to an embodiment of this application is shown;

[0026] Figure 13 A block diagram of an electronic device suitable for implementing the methods described above, according to an embodiment of this application, is shown. Detailed Implementation

[0027] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0029] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0030] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0031] Existing studies and technical specifications on the impacts of highway construction projects focus on assessing the effects of slope ecological restoration, while research on improving ecological benefits is far from sufficient. Furthermore, most studies are qualitative descriptions of large-scale national land use changes and environmental pollution, lacking unified, quantitative, and reliable assessment standards and technical methods. Secondly, existing ecological studies on green road construction mostly discuss the negative impacts of single projects, but these projects have both positive and negative benefits, demonstrating a severe lack of understanding of ecological benefits.

[0032] Furthermore, ecological impact assessments for road projects are often limited to the scale of the area where the road is located, resulting in an overly broad assessment scope. Studies at the road-area scale often use the road width as a buffer zone on both sides of the road axis as the road vector boundary, which cannot be refined to the local slope width and has relatively low accuracy.

[0033] In view of this, embodiments of this application provide a method for quantitatively evaluating the improvement of ecological benefits of transportation infrastructure at the road-area scale. This method includes acquiring target road boundary data for road construction, wherein the target road boundary data characterizes the boundary range of the constructed road; calculating the land resource occupation reduction rate based on preset area occupancy loss calculation rules, according to multiple different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types, wherein the land resource occupation reduction rate includes the permanent land occupation reduction rate, the temporary land occupation reduction rate, and the ecological space occupation reduction rate; calculating the ecological function improvement rate and landscape pattern optimization rate of the constructed road based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data; and performing a weighted summation of the land resource occupation reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate to obtain data for evaluating the improvement of ecological benefits of the constructed road. This method overcomes the shortcomings of traditional methods in scientifically answering the ecological and environmental benefits of land transportation, innovatively proposing the concept of a road-area ecological index, and scientifically and accurately quantifying the ecological benefit improvement rate of the overall greening decision-making scheme.

[0034] In the embodiments of this application, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security and network security.

[0035] Figure 1 An exemplary system architecture 100 according to embodiments of this application, on which a quantitative assessment method for improving ecological benefits can be applied, is shown. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this application, in order to help those skilled in the art understand the technical content of this application, but do not mean that the embodiments of this application cannot be used in other devices, systems, environments or scenarios.

[0036] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0037] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103.

[0038] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0039] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0040] It should be noted that the quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can generally be executed by server 105. Correspondingly, the quantitative assessment device for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can generally be located in server 105. The quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can also be executed by a server or server cluster that is different from server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the quantitative assessment device for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can also be located in a server or server cluster that is different from server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Alternatively, the quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Accordingly, the quantitative assessment device for improving the ecological benefits of transportation infrastructure at the road scale provided in this application embodiment can also be installed in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0041] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0042] Figure 2 A flowchart is shown for a method for quantitatively assessing the improvement of ecological benefits of transportation infrastructure at the road scale according to an embodiment of this application.

[0043] like Figure 2 As shown, the quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale includes operations S201~S204.

[0044] In operation S201, in response to the benefit assessment instruction, target road boundary data for road construction is obtained, wherein the target road boundary data characterizes the minimum boundary range of the ecological background directly occupied by the constructed road, and the transportation infrastructure includes the constructed road;

[0045] In operation S202, based on the preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to the different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. The land resource occupancy reduction rate includes the permanent land occupancy reduction rate, the temporary land occupancy reduction rate, and the ecological space occupancy reduction rate.

[0046] In operation S203, based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data, the ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated respectively. The ecological function improvement rate represents the degree of difference in the ecosystem function of the ecological background occupied by different construction schemes, and the landscape pattern optimization rate represents the degree of difference in the richness and complexity of the ecosystem of the ecological background occupied by different construction schemes.

[0047] In operation S204, the land resource occupation reduction rate, ecological function improvement rate, and landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of road construction.

[0048] According to embodiments of this application, the benefit assessment instruction can be generated automatically by staff performing corresponding operations on electronic devices such as mobile phones and computers, with the electronic device responding to the operation. Green road construction can refer to highway engineering construction, such as expressways including highways, bridges, and tunnels. Target road boundary data can refer to road boundary range data determined from engineering construction drawings.

[0049] According to embodiments of this application, the engineering construction drawings include roadbed and pavement engineering, bridge engineering, tunnel engineering, slope engineering, temporary works, and other engineering works. In addition to roads, transportation infrastructure can also include servers, gas stations, etc.

[0050] According to an embodiment of this application, after obtaining target road boundary data, based on the land occupation type of each plot in the target road boundary data and the type coefficient corresponding to that land occupation type, the reduction rate of permanent land occupation, the reduction rate of temporary land occupation, and the reduction rate of ecological space occupation corresponding to the target road boundary data are calculated based on a preset area occupation loss calculation rule. Permanent land occupation can refer to land permanently occupied by projects such as roadbed and pavement engineering, bridge engineering, tunnel engineering, and slope engineering. Temporary land occupation can refer to land temporarily occupied by projects such as temporary works, such as borrow pits and construction access roads. Ecological space can refer to the ecological system space occupied by engineering construction that has special ecological functions or requires special protection, such as nature reserves and wetland parks.

[0051] According to an embodiment of this application, multi-source high-resolution remote sensing data of the constructed road is acquired from satellites. Regional remote sensing data corresponding to the target road boundary data is then determined from this multi-source high-resolution remote sensing data. The ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated by combining the target road boundary data. Then, the land resource occupation reduction rate, ecological function improvement rate, and landscape pattern optimization rate are weighted and summed to obtain ecological benefit improvement data for evaluating the constructed road. The magnitude of this ecological benefit improvement data characterizes the disturbance of the green road construction to the surrounding environment and ecosystem, thereby revealing the extent of the green road construction's impact on ecological benefits.

[0052] According to the embodiments of this application, based on preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. At the same time, based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data, the ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated respectively. Finally, the land resource occupancy reduction rate, ecological function improvement rate and landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of the constructed road. Since the reduction rate of permanent land occupation, the reduction rate of temporary land occupation and the reduction rate of ecological space occupation are considered in the process of green road construction, the impact of green road construction on the ecological impact and ecological benefits can be accurately and scientifically quantified. At the same time, the ecological benefit improvement quantitative evaluation method provided by the embodiments of this application requires less computational resources, which is convenient for rapid evaluation of different construction projects.

[0053] According to an embodiment of this application, obtaining target road boundary data for green road construction includes: mapping initial road design data onto a preset coordinate system using graphic design software to obtain first road coordinate data; deleting data unrelated to the road alignment from the first road coordinate data to obtain second road coordinate data; performing data segmentation on the second road coordinate data, connecting the line vectors belonging to the road portion into surfaces, and deleting elements outside the road portion again to obtain target road boundary data; collecting actual green road construction data using aerial photography equipment; and performing boundary correction processing on the target road boundary data using the actual green road construction data to obtain new target road boundary data.

[0054] According to embodiments of this application, the initial road design data can be data in any editable format, such as DWG format data, and the graphic design software can be a software program that graphically processes the editable format data.

[0055] According to embodiments of this application, the preset coordinate system can be a geographic coordinate system or a custom coordinate system. First road coordinate data can be obtained by mapping the initial road design data onto the preset coordinate system. Data unrelated to the road alignment, such as dimension annotations, fills, coordinate grids, and mileage markings, are deleted from the first road coordinate data to obtain second road coordinate data.

[0056] According to the embodiments of this application, due to the differences in standards during the mapping stage of various projects, the second road coordinate data is divided into types such as bridges, tunnels, and temporary land occupation. Then, the line vectors belonging to the road part are connected into surfaces, and the elements other than the road are deleted to obtain the target road boundary data.

[0057] According to an embodiment of this application, when the target road boundary data has been implemented, orthophotos of the constructed road (i.e., actual green road construction data) can be collected using aerial photography equipment such as drones to perform boundary correction processing on the target road boundary data, resulting in new target road boundary data. This new target road boundary data includes the precise vector boundary of the actual land area, such as the road width and the slopes on both sides of the road surface. The correction operation can eliminate the error between the spatial distribution during construction and the design scheme. Using this new target road boundary data can improve the accuracy of ecological benefit assessment.

[0058] According to embodiments of this application, the land resource occupation reduction rate includes the land use occupation reduction rate and the ecological space occupation reduction rate.

[0059] According to an embodiment of this application, based on a preset area occupancy loss calculation rule, a land resource occupancy reduction rate is calculated according to multiple different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. This includes: based on a preset segmentation and connection rule, segmenting permanent land occupation boundary data and temporary land occupation boundary data from the target road boundary data; for any first boundary data in the permanent land occupation boundary data and temporary land occupation boundary data, generating a land occupancy reduction rate according to the type coefficients corresponding to the land occupation types in the preset occupancy loss mapping table and the land occupation parameters of each land occupation type in the first boundary data, wherein the land occupation type represents different types of ecosystems; and when the target road boundary data includes wetland protection areas, determining the ecological space occupancy reduction rate by overlaying the target road boundary data and the spatially corresponding wetland protection area data according to a preset protection area sensitivity coefficient table.

[0060] According to an embodiment of this application, the target road boundary data at this time includes permanent land occupation boundary data and temporary land occupation boundary data. In order to accurately evaluate the ecological space occupation reduction rate, it is necessary to divide the permanent land occupation boundary data and the temporary land occupation boundary data to calculate the permanent land occupation reduction rate and the temporary land occupation reduction rate separately.

[0061] According to an embodiment of this application, permanent land occupation boundary data and temporary land occupation boundary data are segmented from the target road boundary data based on preset segmentation and connection rules. Thus, for each type of land occupation parameter in the segmented permanent land occupation boundary data and temporary land occupation boundary data in the target road boundary data, the permanent land occupation reduction rate and temporary land occupation reduction rate can be calculated by combining the type coefficient corresponding to the land occupation type in the preset occupation loss mapping table.

[0062] According to the embodiments of this application, due to the complexity of green road construction, it may pass through some important protected areas, such as wetland parks. In this case, it is necessary to consider the impact of passing through these protected areas on the ecological environment. Therefore, based on the preset protected area sensitivity coefficient table, the ecological space occupation reduction rate is determined according to the wetland protected area data and the target road boundary data corresponding to the target road boundary data.

[0063] According to an embodiment of this application, based on a preset segmentation and connection rule, permanent land occupation boundary data and temporary land occupation boundary data are segmented from target road boundary data, including: segmenting vector lines in the target road boundary data to obtain multiple target vector lines; connecting multiple target vector lines belonging to the road to obtain initial land occupation boundary data; and performing data removal processing on the initial land occupation boundary data to obtain permanent land occupation boundary data and temporary land occupation boundary data.

[0064] According to an embodiment of this application, the vector lines in the target road boundary data are segmented using graphic design software to obtain multiple target vector lines. The target vector lines belonging to the road are connected to obtain the initial land occupation boundary data. Since the initial land occupation boundary data at this time contains data that is unrelated to the permanent land occupation boundary data or the temporary land occupation boundary data, the permanent land occupation boundary data and the temporary land occupation boundary data can be obtained by performing a data removal operation.

[0065] According to embodiments of this application, the initial land occupation boundary data includes data belonging to permanent land occupation and temporary land occupation.

[0066] The process involves removing data from the initial land occupation boundary data to obtain permanent land occupation boundary data and temporary land occupation boundary data. This includes removing data belonging to temporary land occupation and bridge land occupation from the initial land occupation boundary data to obtain permanent land occupation boundary data; and removing data belonging to permanent land occupation and bridge land occupation from the initial land occupation boundary data to obtain temporary land occupation boundary data.

[0067] According to the embodiments of this application, since the land occupation reduction rate is a statistical measure of the actual land occupation impact on the ecology, and bridge and tunnel crossings are harmless crossings compared to roadbed crossings, their impact can be ignored.

[0068] According to an embodiment of this application, for permanent land occupation boundary data, it is necessary to remove the data belonging to temporary land occupation and bridge land occupation from the initial land occupation boundary data to obtain the permanent land occupation boundary data. Similarly, removing the data belonging to permanent land occupation and bridge land occupation from the initial land occupation boundary data can obtain the temporary land occupation boundary data.

[0069] According to an embodiment of this application, a land occupancy reduction rate is generated based on the type coefficient corresponding to the land occupancy type in a preset occupancy loss refraction table and the land occupancy parameters of each land occupancy type in the first boundary data. This includes: for each land occupancy type in the first boundary data, determining the land occupancy parameters of the land occupancy type based on the first boundary data, wherein the land occupancy parameters include land area data; determining the area conversion coefficient corresponding to the land occupancy type from a preset occupancy loss mapping table, wherein the preset occupancy loss mapping table includes area conversion coefficients corresponding to different ecosystems, and the area conversion coefficient represents a type coefficient; calculating the ecological value loss of the land occupancy type based on the land area data and the area conversion coefficient; and calculating the land occupancy reduction rate corresponding to the first boundary data based on multiple ecological value loss amounts.

[0070] According to an embodiment of this application, taking the permanent land occupation reduction rate as an example, the permanent land occupation boundary data is used as a mask to extract the land use type raster data related to the permanent land occupation boundary data from the land use type raster data corresponding to the green road construction. From this raster data, land occupation parameters such as the land area data of each land occupation type can be determined. The land occupation type can refer to different types of ecosystems such as grassland and wetland.

[0071] According to the embodiments of this application, for each land occupation type, the area conversion coefficient of the land occupation type is determined based on the typical ecosystem unit area occupation loss conversion table (i.e., the preset occupation loss mapping table) shown in Table 1, and then the ecological value loss corresponding to the land occupation type is calculated based on the land occupation area data and the area conversion coefficient.

[0072] Table 1

[0073]

[0074] In one specific embodiment, for example, the land type is a farmland ecosystem, and the land area is 10 hm². 2 At this point, the ecological value loss is 10 × 4.01 × D, where D is the standard equivalent factor, which characterizes the value of ecosystem services, for example, D = 3406.5.

[0075] According to embodiments of this application, the permanent land occupation reduction rate can be obtained by weighted averaging of multiple ecological value losses corresponding to different land occupation types. The calculation of the temporary land occupation reduction rate is roughly the same as that of the permanent land occupation reduction rate, the only difference being the weighting of the two in the weighted average.

[0076] According to an embodiment of this application, based on a preset protection area sensitivity coefficient table, the ecological space occupancy reduction rate is determined according to wetland protection area data and target road boundary data corresponding to target road boundary data. This includes: performing regional overlay processing on wetland protection area data and target road boundary data to obtain first protection area data containing only overlapping areas; removing the area data occupied by permanent and temporary land occupation boundary data from the first protection area data to obtain second protection area data; merging the second protection area data, permanent land occupation boundary data, and temporary land occupation boundary data to obtain third protection area data; classifying the third protection area data by land use type to obtain multiple divided areas with different land use areas, wherein the ecological sensitivities of different divided areas are different; determining the sensitivity conversion coefficient for each divided area from the preset protection area sensitivity coefficient table, wherein the preset protection area sensitivity coefficient table includes sensitivity conversion coefficients corresponding to different ecological sensitivities, and the sensitivity conversion coefficient represents a type coefficient; and calculating the ecological space occupancy reduction rate based on the multiple divided areas and the sensitivity conversion coefficient corresponding to each divided area.

[0077] According to an embodiment of this application, wetland protection area data and target road boundary data are overlaid to obtain first protection area data containing only overlapping areas. The area data occupied by permanent land occupation boundary data and temporary land occupation boundary data are erased from the first protection area data to obtain second protection area data that does not occupy ecological space.

[0078] According to the embodiments of this application, the data of the second protected area, the data of the permanent land occupation boundary, and the data of the temporary land occupation boundary are merged to obtain the data of the third protected area. The data of the third protected area is divided into different areas such as unoccupied area, reasonable utilization area, restoration and reconstruction area, prohibited development area, and conservation area. Based on the preset protected area sensitivity coefficient table shown in Table 2, the sensitivity conversion coefficient of each area is determined. Based on each area and its corresponding sensitivity conversion coefficient, the area reduction rate of the area is calculated. The ecological space occupation reduction rate is calculated by weighted averaging the reduction rates of multiple areas.

[0079] Table 2

[0080]

[0081] In Table 2, "green" and "traditional" represent two different construction schemes corresponding to the same construction goal. "Traditional" represents a scheme that is mainly based on economic, engineering, and safety factors, but lacks ecological constraints; "green" represents a scheme that adopts a seamless, low-impact design and construction technology for the main project, which is fully integrated with nature and has a low environmental impact, in response to different ecological protection goals. This corresponds to the actual green road construction data in the embodiments of this application.

[0082] According to embodiments of this application, the land resource occupation reduction rate includes the permanent land occupation reduction rate, the temporary land occupation reduction rate, and the ecological space occupation reduction rate;

[0083] The process involves weighted summation of the land resource occupation reduction rate, ecological function improvement rate, and landscape pattern optimization rate to obtain data for evaluating the ecological benefit improvement of road construction. This includes determining the weight coefficient of each evaluation indicator from a weight coefficient table, where the evaluation indicators include the permanent land occupation reduction rate, temporary land occupation reduction rate, ecological space occupation reduction rate, ecological function improvement rate, and landscape pattern optimization rate; and calculating the ecological benefit improvement data based on multiple evaluation indicators and their corresponding weight coefficients.

[0084] According to an embodiment of this application, any evaluation index is generated based on multiple evaluation sub-indicators corresponding to different plots of land in the target road boundary data.

[0085] Before calculating the ecological benefit improvement data, the process includes: for any evaluation indicator, determining the target standardization formula corresponding to the evaluation indicator based on the correlation between the evaluation indicator and the ecological benefit improvement indicator; using the target standardization formula to standardize multiple evaluation sub-indicators to obtain multiple new evaluation sub-indicators; generating new evaluation indicators based on the multiple new evaluation sub-indicators, and using the multiple new evaluation indicators to calculate the ecological benefit improvement data.

[0086] According to embodiments of this application, the ecological function improvement rate can be divided into vegetation coverage index, water conservation capacity index, road surface dryness index, and surface heat index. The landscape pattern optimization rate can be divided into landscape diversity index and patch cohesion index.

[0087] According to the embodiments of this application, for each evaluation index among the permanent land use reduction rate, temporary land use reduction rate, ecological space use reduction rate, vegetation coverage index, water conservation capacity index, road surface dryness index, surface heat index, landscape diversity index, and patch cohesion index, the weight coefficient of the evaluation index can be determined from the weight coefficient table shown in Table 3.

[0088] Table 3

[0089]

[0090] According to an embodiment of this application, based on formula (1), and based on multiple evaluation indicators and the weighting coefficients corresponding to each evaluation indicator Calculate data on ecological benefit improvement :

[0091] (1)

[0092] in, As evaluation indicators, The weighting coefficient for the indicator; This is an ecological benefit evaluation index, which represents the data on the improvement of ecological benefits. The higher the value, the higher the ecological benefits.

[0093] According to the embodiments of this application, since the target road boundary data can be divided into multiple plots of data when calculating each evaluation index based on the target road boundary data, and the evaluation index is calculated by weighted average of multiple evaluation sub-indicators based on multiple plots of data, each evaluation index can be standardized.

[0094] According to the embodiments of this application, when performing standardization processing, the correlation between the evaluation index and the ecological benefit improvement index must first be determined according to Table 3, that is, the direction of influence in Table 3. If the direction of influence is positive, the target standardization formula of formula (2) can be used to standardize the multiple evaluation sub-indicators of the evaluation index. If the direction of influence is positive, the target standardization formula of formula (3) can be used to standardize the multiple evaluation sub-indicators of the evaluation index, thereby generating a new evaluation index based on multiple new evaluation sub-indicators.

[0095] (2)

[0096] (3)

[0097] in, This indicates a new evaluation sub-indicator. This represents the i-th evaluation sub-index. , Let represent the maximum and minimum values ​​among the i-th evaluation sub-indicators, which can be the 95% and 5% threshold points of the i-th evaluation sub-indicator, respectively. After dimensionless standardization... The higher the value, the greater the positive effect on improving ecological benefits.

[0098] According to embodiments of this application, the ecological function improvement rate includes the comprehensive vegetation coverage index, water conservation capacity index, road surface dryness index, and surface heat index.

[0099] The ecological function improvement rate is generated as follows: Regional remote sensing data of the area corresponding to the constructed road is acquired. This data includes a set of normalized vegetation indices, humidity indices, bare soil and building indices, and surface heat indices. The target road boundary data is used as a target mask to extract target remote sensing data from the regional data. This target data includes the target normalized vegetation index, target humidity index, target bare soil and building index, and target surface heat index. Based on these indices, the comprehensive vegetation coverage index, water conservation capacity index, road surface dryness index, and surface heat index are calculated, respectively.

[0100] According to an embodiment of this application, a buffer zone is first set for the target road boundary data, and then remote sensing data of the area corresponding to the target road boundary data with the buffer zone is acquired from the satellite. The buffer zone is divided by a preset distance on both sides of the road axis, such as 100 meters or 500 meters.

[0101] According to an embodiment of this application, the target road boundary data with a buffer is used as a target mask, and the target remote sensing data at the road domain scale is cropped out from the buffer.

[0102] According to the embodiments of this application, the target normalized vegetation index is processed based on formula (4) to calculate the comprehensive vegetation cover index. :

[0103] (4)

[0104] Wherein, FVC represents the overall vegetation cover, with a value ranging from 0 to 100%; NDVI represents the target normalized vegetation index; NDVIv represents the normalized vegetation index of pure plant pixels. In this embodiment, NDVIv is defined as having an annual cumulative change frequency of 95%, and FVC with a cumulative frequency of 95% or higher is defined as 1; NDVIs represents the NDVI value of bare soil or pixels without vegetation cover. In this embodiment, NDVIs is defined as having a cumulative frequency of 5%, and vegetation cover with a cumulative frequency of less than 5% is defined as 0.

[0105] According to an embodiment of this application, the target humidity index is processed based on formula (5) to calculate the water conservation capacity index. :

[0106] (5)

[0107] Wherein, b2 represents the green light band; b3 represents the red light band; b4 represents the near-infrared band; b8 represents the near-infrared band; b11 represents the short-wave infrared band 1 (SWIR1); and b12 represents the short-wave infrared band 2 (SWIR2). All of the above light bands can be obtained from the target remote sensing data.

[0108] According to an embodiment of this application, the Normalized Difference Bare Soil Index (NDBSI) is represented by the average of the Soil Index (SI) and the Index-based Built-up Index (IBI), as shown in formula (6):

[0109] (6)

[0110] Among them, the bare soil index and the engineering construction index are the target bare soil and building indices.

[0111] According to embodiments of this application, the surface heat index It can be calculated using formula (7):

[0112] (7)

[0113] in, This indicates that Landsat 8 uses the thermal infrared band 10. It can be the target surface heat index obtained from remote sensing data.

[0114] According to embodiments of this application, the landscape pattern optimization rate includes a landscape diversity index and a patch cohesion index.

[0115] The landscape pattern optimization rate is generated as follows: the target road boundary data is expanded to obtain boundary expansion data; based on the land use type data corresponding to the construction road and the boundary expansion data, multiple expanded patch parameters corresponding to the boundary expansion data are determined, wherein each expanded patch parameter includes an edge depth, edge contrast and edge similarity coefficient of an expanded patch; the landscape diversity index and patch cohesion index are calculated based on the multiple expanded patch parameters.

[0116] According to an embodiment of this application, the road expansion is set up in the same way as the buffer zone described above. The calculation of the landscape diversity index (SHDI) and the patch cohesion index (COHESION) within the area covered by the target road boundary data and the acquisition of cell values ​​are achieved by using the moving window method.

[0117] According to an embodiment of this application, the boundary expansion data is used as a mask to crop the land use type data corresponding to the construction road, thereby obtaining the raster data of the land use type of the expanded area, namely the expanded patch parameters, which include edge depth, edge contrast and edge similarity coefficient.

[0118] According to the embodiments of this application, the landscape diversity index H and the patch cohesion index COHESION are calculated based on formula (8) and formula (9), respectively.

[0119] (8)

[0120] Where H represents the landscape diversity index; Pi represents the proportion of area occupied by landscape type i; and N represents the number of landscape types, where landscape can refer to different types of ecosystems.

[0121] (9)

[0122] Where i represents the landscape type; j represents the number of expanded patches; n represents the sum of expanded patches in landscape type i; and m represents the sum of landscape types. Indicates the area of ​​the expanded patch; A represents the perimeter of the expanded patch; A represents the total landscape area.

[0123] Figure 3 The diagram illustrates the routes of the conventional and green solutions according to embodiments of this application. Figure 4 A schematic diagram of target road boundary data according to an embodiment of this application is shown. Figure 5 A schematic diagram of the initial land boundary data according to an embodiment of this application is shown. Figure 6 A schematic diagram illustrating land use type identification when dividing areas according to an embodiment of this application is shown. Figure 7A schematic diagram comparing the comprehensive vegetation coverage index of different schemes according to embodiments of this application is shown. Figure 8 A schematic diagram comparing water conservation capacity indicators of different schemes according to embodiments of this application is shown. Figure 9 A schematic diagram comparing the road surface dryness index of different schemes according to embodiments of this application is shown. Figure 10 A schematic diagram comparing the landscape diversity index of different schemes according to embodiments of this application is shown. Figure 11 A schematic diagram comparing the plaque cohesion index of different schemes according to embodiments of this application is shown.

[0124] In one specific embodiment, a previously constructed section of highway is used as an example. This highway was designed with the following features during the design phase: Figure 3 The traditional scheme (blue lines) and the green scheme (red lines) are shown. Figure 3 (a) and (b) in the diagram belong to different sections of the expressway. The green scheme has been implemented, and the target road boundary data corresponding to the green scheme is as follows: Figure 4 (a) and the new target road boundary data after correction based on aerial photography equipment, such as Figure 4 As shown in (b).

[0125] According to an embodiment of this application, the initial land occupation boundary data is obtained by processing the data using the ecological benefit enhancement quantitative assessment method of this application. Figure 5 As shown, after classifying land use types when calculating the rate of reduction in ecological space occupation, the following results can be obtained: Figure 6 The multiple division areas shown in the accompanying drawings of this embodiment only show a portion of the highway.

[0126] According to embodiments of this application, the ecological benefit enhancement quantitative assessment method of this application is used to calculate the comprehensive vegetation coverage index for both the traditional and green schemes, such as... Figure 7 As shown, the average comprehensive vegetation cover of the green scheme project area, at 67.426%, is lower than the 71.465% of the traditional scheme. This indicates that before construction, the green scheme selected areas with relatively poor comprehensive vegetation cover, thus avoiding damage to areas with higher vegetation cover. The maximum value of the green scheme (96.47%) is close to the maximum value of the traditional scheme (97.45%), showing that in some areas, despite selecting poorer ecological regions, the green scheme still maintained a high comprehensive vegetation cover. The minimum value is significantly lower than the traditional scheme by 0.16%, further proving that the green scheme selected areas with poorer ecological conditions before construction. This strategy, to some extent, reduces disturbance to ecologically better areas and minimizes the damage to vegetation caused by transportation infrastructure.

[0127] According to the embodiments of this application, the water conservation capacity index of two schemes is calculated simultaneously, such as... Figure 8 As shown, the average water conservation capacity of the green scheme is 0.522, slightly lower than the 0.568 of the traditional scheme, and the improvement rate of the single ecological benefit of water conservation reaches 8.10%. The green scheme's minimum value of -0.1993 is lower than the traditional scheme's -0.1692, indicating that the green scheme selected areas with lower humidity for construction, protecting areas with higher humidity and healthier ecosystems. This strategy further protects these ecologically sensitive areas by reducing disturbance to areas with higher humidity.

[0128] According to the embodiments of this application, a comparative analysis of the road surface dryness index of the two schemes shows that, as Figure 9 As shown, the average NDBSI of the green scheme is -0.1658, slightly higher than that of the traditional scheme (-0.1737). This indicates that before construction, the green scheme selected areas with higher aridity, protecting areas with lower aridity and better ecological conditions. Although the minimum (-0.4745) and maximum (0.2450) are the same for both schemes, indicating that the impact of the two schemes is similar in extreme cases, the green scheme's strategy effectively reduces further damage to areas with better ecological conditions by selecting areas with poorer ecology for construction.

[0129] According to the embodiments of this application, a comparative analysis of the landscape diversity indices of the two schemes shows that, as Figure 10 As shown, the average SHDI of the green scheme is 96.39, slightly lower than the 96.76 of the traditional scheme. This indicates that the green scheme selected areas with lower landscape diversity for construction before construction began, thus avoiding damage to areas with higher landscape diversity. Although both schemes have the same maximum value of 100, this shows that under optimal conditions, the green scheme can maintain the same overall landscape diversity as the traditional design scheme.

[0130] According to the embodiments of this application, a comparative analysis of the patch cohesion index of the two schemes shows that, as Figure 11 As shown, the average cohesion of the green scheme is 0.18, higher than that of the traditional scheme (0.16). This indicates that before construction, the green scheme selected areas with lower cohesion for construction, thus protecting areas with higher cohesion and healthier ecosystems. Although both schemes have the same maximum value of 1.37, indicating that there is no difference in landscape connectivity under optimal conditions, the green scheme's strategy effectively reduces further damage to areas with better ecological conditions by selecting areas with poorer ecology for construction.

[0131] According to the embodiments of this application, after normalizing and standardizing the nine indicators, including the reduction rate of land resource occupancy, the improvement rate of ecological function, and the optimization rate of landscape pattern, from the perspective of the overall road area scale of a certain section of the highway under study, the ecological benefit improvement of the green scheme compared with the traditional scheme is 6.283%, achieving the initial target of an ecological benefit improvement of no less than 5%. Among them, the improvement rate of ecological function and the optimization rate of landscape pattern are both positive, and only the temporary land use and ecological space use are negative. The reduction rate of permanent land resource occupancy is the highest, reaching 21.955%; the ecological benefit improvement rates of indicators such as vegetation coverage, water conservation capacity, and landscape diversity index all exceed 5%; while the ecological benefit improvement rates of surface heat index and patch cohesion index are not significant. For a detailed comparison, please refer to Table 4, the table of ecological benefit improvement of low environmental impact linear transportation infrastructure design technology at the road area scale.

[0132] Table 4

[0133]

[0134] The ecological benefit improvement in Table 4 is calculated using formula (10):

[0135] (10)

[0136] in, The increase in ecological benefits is calculated as a percentage. This indicates the ecological benefit improvement data for a specific section of the green project; This represents the ecological benefit improvement data for a specific section of the traditional scheme.

[0137] Figure 12 A block diagram of a device for quantitatively assessing the improvement of ecological benefits of transportation infrastructure at the road scale according to an embodiment of this application is shown.

[0138] like Figure 12 As shown, the quantitative assessment device 1200 for improving the ecological benefits of transportation infrastructure at the road scale for green road construction includes an acquisition module 1210, a first calculation module 1220, a second calculation module 1230, and a benefit evaluation module 1240.

[0139] The acquisition module 1210 is used to acquire target road boundary data for road construction in response to a benefit assessment instruction. The target road boundary data represents the minimum boundary range of the ecological background directly occupied by the constructed road. The transportation infrastructure includes the constructed road.

[0140] The first calculation module 1220 is used to calculate the land resource occupation reduction rate based on the preset area occupation loss calculation rules, according to the different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. The land resource occupation reduction rate includes the permanent land occupation reduction rate, the temporary land occupation reduction rate and the ecological space occupation reduction rate.

[0141] The second calculation module 1230 is used to calculate the ecological function improvement rate and landscape pattern optimization rate of the constructed road based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data. The ecological function improvement rate represents the degree of difference in the ecosystem function of the ecological background occupied by different construction schemes, and the landscape pattern optimization rate represents the degree of difference in the richness and complexity of the ecosystem of the ecological background occupied by different construction schemes.

[0142] The benefit evaluation module 1240 is used to perform weighted summation on the land resource occupation reduction rate, ecological function improvement rate and landscape pattern optimization rate to obtain data for evaluating the ecological benefit improvement of the constructed road.

[0143] According to the embodiments of this application, based on preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. At the same time, based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data, the ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated respectively. Finally, the land resource occupancy reduction rate, ecological function improvement rate and landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of the constructed road. Since the reduction rate of permanent land occupation, the reduction rate of temporary land occupation and the reduction rate of ecological space occupation are considered in the process of green road construction, the impact of green road construction on the ecological impact and ecological benefits can be accurately and scientifically quantified. At the same time, the ecological benefit improvement quantitative evaluation method provided by the embodiments of this application requires less computational resources, which is convenient for rapid evaluation of different construction projects.

[0144] Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or implemented by hardware or firmware in any other reasonable manner by integrating or packaging circuits, or implemented in any one of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0145] For example, any multiple of the acquisition module 1210, the first calculation module 1220, the second calculation module 1230, and the benefit evaluation module 1240 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this application, at least one of the acquisition module 1210, the first calculation module 1220, the second calculation module 1230, and the benefit evaluation module 1240 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the acquisition module 1210, the first calculation module 1220, the second calculation module 1230, and the benefit evaluation module 1240 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0146] It should be noted that the quantitative assessment device for improving the ecological benefits of transportation infrastructure at the road scale in the embodiments of this application corresponds to the quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale in the embodiments of this application. The description of the quantitative assessment device for improving the ecological benefits of transportation infrastructure at the road scale is specifically referred to the quantitative assessment method for improving the ecological benefits of transportation infrastructure at the road scale, and will not be repeated here.

[0147] Figure 13 A block diagram of an electronic device suitable for implementing the methods described above, according to an embodiment of this application, is shown. Figure 13 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0148] like Figure 13 As shown, an electronic device 1300 according to an embodiment of this application includes a processor 1301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1302 or a program loaded from a storage portion 1308 into a random access memory (RAM) 1303. The processor 1301 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1301 may also include onboard memory for caching purposes. The processor 1301 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0149] RAM 1303 stores various programs and data required for the operation of electronic device 1300. Processor 1301, ROM 1302, and RAM 1303 are interconnected via bus 1304. Processor 1301 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 1302 and / or RAM 1303. It should be noted that the programs may also be stored in one or more memories other than ROM 1302 and RAM 1303. Processor 1301 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0150] According to embodiments of this application, the electronic device 1300 may further include an input / output (I / O) interface 1305, which is also connected to a bus 1304. The electronic device 1300 may also include one or more of the following components connected to the input / output (I / O) interface 1305: an input section 1306 including a keyboard, mouse, etc.; an output section 1307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1308 including a hard disk, etc.; and a communication section 1309 including a network interface card such as a LAN card, modem, etc. The communication section 1309 performs communication processing via a network such as the Internet. A drive 1310 is also connected to the input / output (I / O) interface 1305 as needed. A removable medium 1311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1310 as needed so that computer programs read from it can be installed into the storage section 1308 as needed.

[0151] According to embodiments of this application, the method flow according to embodiments of this application can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1309, and / or installed from removable medium 1311. When the computer program is executed by processor 1301, it performs the functions defined in the system of embodiments of this application. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0152] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0153] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this application. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the methods provided in the embodiments of this application.

[0154] When the computer program is executed by the processor 1301, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc. described above can be implemented by computer program modules.

[0155] The embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. This application does not depart from its scope, and those skilled in the art can make various substitutions and modifications, all of which should fall within the scope of this application.

Claims

1. A quantitative assessment method for the improvement of ecological benefits of transportation infrastructure at the road-area scale, characterized in that, include: In response to a benefit assessment directive, target road boundary data for road construction is acquired, wherein the target road boundary data characterizes the minimum boundary range within which the constructed road directly encroaches on the ecological baseline, and the transportation infrastructure includes the constructed road; Based on the preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to the different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types. The land resource occupancy reduction rate includes the permanent land occupancy reduction rate, the temporary land occupancy reduction rate, and the ecological space occupancy reduction rate. Based on the target road boundary data and the regional remote sensing data corresponding to the target road boundary data, the ecological function improvement rate and landscape pattern optimization rate of the constructed road are calculated respectively. The ecological function improvement rate represents the degree of difference in the ecosystem function of the ecological background occupied by different construction schemes, and the landscape pattern optimization rate represents the degree of difference in the richness and complexity of the ecosystem of the ecological background occupied by different construction schemes. The land resource occupation reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of the constructed road.

2. The method according to claim 1, characterized in that, Obtain target road boundary data for road construction, including: The initial road design data is mapped onto a preset coordinate system using graphic design software to obtain the first road coordinate data; Delete data unrelated to road alignment from the first road coordinate data to obtain the second road coordinate data; The second road coordinate data is segmented, and the line vectors belonging to the road portion are connected into a surface. Then, the elements outside the road are deleted to obtain the target road boundary data. Aerial photography equipment was used to collect actual road construction data for the road under construction. The target road boundary data is corrected using the actual road construction data to obtain new target road boundary data.

3. The method according to claim 1, characterized in that, The land resource occupation reduction rate includes the land use occupation reduction rate and the ecological space occupation reduction rate; Among them, based on the preset area occupancy loss calculation rules, the land resource occupancy reduction rate is calculated according to the different land occupation types in the target road boundary data and the type coefficients corresponding to the land occupation types, including: Based on preset segmentation and connection rules, permanent land occupation boundary data and temporary land occupation boundary data are segmented from the target road boundary data; For any first boundary data in the permanent land occupation boundary data and the temporary land occupation boundary data, the land occupation reduction rate is generated according to the type coefficient corresponding to the land occupation type in the preset occupation loss mapping table and the land occupation parameter of each land occupation type in the first boundary data, wherein the land occupation type represents different types of ecosystems. If the target road boundary data includes a wetland protection area, the ecological space occupancy reduction rate is determined based on a preset protection area sensitivity coefficient table, according to the wetland protection area data corresponding to the target road boundary data and the target road boundary data.

4. The method according to claim 3, characterized in that, Based on preset segmentation and connection rules, permanent land occupation boundary data and temporary land occupation boundary data are segmented from the target road boundary data, including: The vector lines in the target road boundary data are segmented to obtain multiple target vector lines; The multiple target vector lines belonging to the road are connected to obtain the initial land occupation boundary data; The initial land occupation boundary data is processed by data removal to obtain the permanent land occupation boundary data and the temporary land occupation boundary data.

5. The method according to claim 4, characterized in that, The initial land occupation boundary data includes data on both permanent and temporary land occupation. Specifically, the initial land occupation boundary data undergoes data removal processing to obtain the permanent land occupation boundary data and the temporary land occupation boundary data, including: The data belonging to temporary land occupation and bridge land occupation are removed from the initial land occupation boundary data to obtain the permanent land occupation boundary data. The temporary land occupation boundary data is obtained by removing data belonging to permanent land occupation and bridge land occupation from the initial land occupation boundary data.

6. The method according to claim 3, characterized in that, Based on the type coefficients corresponding to the land occupation types in the preset occupancy loss refraction table and the land occupation parameters for each land occupation type in the first boundary data, the land occupation reduction rate is generated, including: For each type of land occupation in the first boundary data, land occupation parameters for that type of land occupation are determined based on the first boundary data, wherein the land occupation parameters include land area data; The area conversion factor corresponding to the land occupation type is determined from the preset occupation loss mapping table, wherein the preset occupation loss mapping table includes area conversion factors corresponding to different ecosystems, and the area conversion factor represents a type coefficient; Based on the land area data and the area conversion factor, calculate the ecological value loss of the land area type; Based on the multiple ecological value loss amounts, calculate the land occupation reduction rate corresponding to the first boundary data.

7. The method according to any one of claims 3 to 6, characterized in that, Based on a preset sensitivity coefficient table for protected areas, the ecological space occupancy reduction rate is determined according to the wetland protected area data corresponding to the target road boundary data and the target road boundary data, including: The wetland protection area data and the target road boundary data are overlaid to obtain first protection area data that only contains the overlapping areas. The area data occupied by the permanent land occupation boundary data and the temporary land occupation boundary data is removed from the first protected area data to obtain the second protected area data; The data of the second protected area, the permanent land occupation boundary data, and the temporary land occupation boundary data are merged to obtain the data of the third protected area. The data of the third protected area is processed by land use type classification to obtain multiple classified areas with different land use areas, wherein the ecological sensitivity of different classified areas is different; The sensitivity conversion coefficient for each of the divided areas is determined from the preset protection area sensitivity coefficient table, wherein the preset protection area sensitivity coefficient table includes sensitivity conversion coefficients corresponding to different ecological sensitivities, and the sensitivity conversion coefficient represents a type coefficient; The ecological space occupancy reduction rate is calculated based on the multiple defined regions and the sensitive conversion factor corresponding to each defined region.

8. The method according to claim 1, characterized in that, The land resource occupation reduction rate includes the permanent land occupation reduction rate, the temporary land occupation reduction rate, and the ecological space occupation reduction rate. The land resource occupation reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate are weighted and summed to obtain data for evaluating the ecological benefit improvement of the constructed road, including: The weight coefficients for each evaluation indicator are determined from the weight coefficient table, wherein the evaluation indicators include the permanent land use reduction rate, the temporary land use reduction rate, the ecological space use reduction rate, the ecological function improvement rate, and the landscape pattern optimization rate. The ecological benefit improvement data are calculated based on multiple evaluation indicators and the weighting coefficients corresponding to each evaluation indicator; Wherein, any of the evaluation indicators is generated based on multiple evaluation sub-indicators corresponding to different plots of land in the target road boundary data; Before calculating the aforementioned ecological benefit improvement data, the following is also included: For any of the evaluation indicators, a target standardization formula corresponding to the evaluation indicator is determined based on the correlation between the evaluation indicator and the ecological benefit improvement indicator. The target standardization formula is used to standardize multiple evaluation sub-indicators to obtain multiple new evaluation sub-indicators; New evaluation indicators are generated based on multiple new evaluation sub-indicators, and the ecological benefit improvement data are calculated using multiple new evaluation indicators.

9. The method according to claim 1, characterized in that, The ecological function improvement rate includes the comprehensive vegetation coverage index, water conservation capacity index, road surface dryness index, and surface heat index. The ecological function improvement rate is generated in the following way: Acquire regional remote sensing data corresponding to the area of ​​the constructed road, wherein the regional remote sensing data includes the normalized vegetation index set, humidity index set, bare soil and building index set, and surface heat index set of the area; The target road boundary data is used as a target mask to cut out the target remote sensing data from the regional remote sensing data. The target remote sensing data includes the target normalized vegetation index, the target humidity index, the target bare soil and building index, and the target surface heat index. The comprehensive vegetation coverage index, the water conservation capacity index, the road surface dryness index, and the surface heat index are calculated based on the target normalized vegetation index, the target humidity index, the target bare soil and building index, and the target surface heat index, respectively.

10. The method according to claim 1 or 9, characterized in that, The landscape pattern optimization rate includes the landscape diversity index and the patch cohesion index. The landscape pattern optimization rate is generated in the following way: The target road boundary data is subjected to road expansion processing to obtain boundary expansion data; Based on the land use type data corresponding to the constructed road and the boundary expansion data, multiple expansion patch parameters corresponding to the boundary expansion data are determined, wherein each expansion patch parameter includes an edge depth, edge contrast and edge similarity coefficient of the expansion patch; The landscape diversity index and patch cohesion index are calculated based on the various expanded patch parameters.

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