Tree crown coverage benefit evaluation method and system

Abstract

The invention relates to the technical field of green land benefit evaluation, and discloses a crown coverage benefit evaluation method and system, and the method comprises the following steps: 1, constructing a crown coverage benefit comprehensive evaluation system; green ecological benefit indexes and social and economic benefit indexes are set in the crown covering benefit comprehensive evaluation system; step 2, collecting topographic features, ecological features and land utilization features of crown covering plates in the target area; and step 3, based on the data collected in the step 2, calculating green ecological benefit indexes and social economic benefit indexes of the crown covering plate. According to the method, the crown covering benefit can be accurately evaluated, reliable information reference can be provided for investigation and optimization of the current situation of the crown covering benefit, the improvement of the urban environment quality is facilitated, and the welfare of people is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of green space benefit evaluation, and specifically relates to a method and system for evaluating the benefit of tree canopy coverage. Background Art

[0002] With the transformation of the urban development model, urban construction has gradually shifted from "emphasizing quantity" to "emphasizing quality". Under the current new development and new goals, it is necessary to continuously improve the quality of urban greening, create a good ecological environment, and achieve high-quality development through the construction of urban green space systems, park systems, urban renewal actions, etc. Among them, large trees are an important part of various urban green spaces, and trees are also one of the few urban ecological infrastructure investments that can increase in value over time.

[0003] Around the world, the value that trees provide to humans and the environment is being recognized. Many cities are launching tree-planting programs to involve the community and expand the scale of urban forests. Increasing the benefit of tree canopy coverage can not only improve the key indicator of urban greening coverage rate, but also provide key "road shading" for citizens and more abundant "under-forest activity spaces".

[0004] However, the existing research on the benefit of tree canopy coverage started relatively late, there is less relevant research, and most of it focuses on the correlation analysis between tree canopy coverage and other factors. Few people evaluate the benefit of tree canopy coverage, so it is difficult to accurately grasp the actual status of the benefit of tree canopy coverage, which hinders the further improvement of the benefit of tree canopy coverage. Summary of the Invention

[0005] The present invention aims to provide a method and system for evaluating the benefit of tree canopy coverage, which can accurately evaluate the benefit of tree canopy coverage and provide reliable information reference for the investigation and optimization of the current situation of the benefit of tree canopy coverage.

[0006] To achieve the above object, the basic solution provided by the present invention is as follows:

[0007] Solution 1

[0008] A method for evaluating the benefit of tree canopy coverage, comprising the following steps:

[0009] Step 1, constructing a comprehensive evaluation system for the benefit of tree canopy coverage; in the comprehensive evaluation system for the benefit of tree canopy coverage, there are green ecological benefit indicators and social and economic benefit indicators; the green ecological benefit indicators include thermal environment indicators, biodiversity indicators and carbon sink amounts; the social and economic benefit indicators include the richness of activities under the canopy, the type index of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of under-forest space and the richness of business forms under the canopy;

[0010] Step 2, collecting the topographic features, ecological features and land use features of the tree canopy coverage blocks in the target area;

[0011] Step 3: Based on the data collected in Step 2, calculate the green ecological benefit indicators and social and economic benefit indicators of the tree canopy coverage area.

[0012] Solution 2

[0013] A tree canopy coverage benefit evaluation system is applied to a tree canopy coverage benefit evaluation method as described in Solution 1; it includes a data processing module and an evaluation module;

[0014] The data processing module is used to collect the topographic features, ecological features, and land use features of the tree canopy coverage area in the target area and convert them into the spatial distribution features of the tree canopy benefits; a comprehensive evaluation system for tree canopy coverage benefits is preset in the evaluation module; the comprehensive evaluation system for tree canopy coverage benefits is constructed with green ecological benefit indicators and social and economic benefit indicators; the green ecological benefit indicators include thermal environment indicators, biodiversity indicators, and carbon sink amounts; the social and economic benefit indicators include the richness of activities under the canopy, the type index of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of the space under the forest, and the richness of business forms under the canopy;

[0015] The evaluation module is also used to calculate the green ecological benefit indicators and social and economic benefit indicators of the tree canopy coverage area based on the spatial distribution features.

[0016] The working principle and advantages of the present invention are as follows: The tree canopy coverage benefit evaluation method and system provided by the present invention construct a comprehensive evaluation system including two dimensions of green ecological benefits and social and economic benefits for the tree canopy coverage benefit. Combining the topographic features, ecological features, and land use features of the tree canopy coverage area collected, it can intuitively and quantitatively represent the tree canopy coverage benefit by calculating the green ecological benefit indicators and social and economic benefit indicators, accurately evaluate the tree canopy coverage benefit, help accurately grasp the actual status of the tree canopy coverage benefit, and can provide reliable information reference for the investigation and optimization of the tree canopy coverage benefit status, guiding the greening and ecological construction of the central urban area from the perspective of planning and design technology. Brief Description of the Drawings

[0017] Figure 1 It is a schematic structural diagram of Embodiment 1 of a tree canopy coverage benefit evaluation method and system of the present invention. Detailed Embodiments

[0018] The following is a more detailed description through specific embodiments:

[0019] Embodiment 1

[0020] The embodiment is basically as shown in the appendix Figure 1 shown: A tree canopy coverage benefit evaluation method includes the following steps:

[0021] Step 1: Construct a comprehensive evaluation system for the benefits of tree canopy coverage; the comprehensive evaluation system for the benefits of tree canopy coverage is provided with green ecological benefit indicators and social and economic benefit indicators.

[0022] The green ecological benefit indicators include thermal environment indicators, biodiversity indicators, and carbon sequestration; the social and economic benefit indicators include the richness of activities under the canopy, the types of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of the space under the forest, and the richness of business forms under the canopy.

[0023] In this step, it also includes obtaining data in the field of the benefits of tree canopy coverage and extracting key indicators from it to supplement the comprehensive evaluation system for the benefits of tree canopy coverage.

[0024] The data in the field of the benefits of tree canopy coverage includes structured data and unstructured data; the structured data includes GEE data, forest resource datasets, and satellite remote sensing datasets; the unstructured data includes literature data and report data themed on tree canopy coverage and the benefits of tree canopy coverage. In this embodiment, the literature data and report data can be crawled from websites.

[0025] Specifically, when extracting key indicators, an LSTM model is used for key indicator extraction; and after the key indicators are extracted, the key indicators that are repeated in the comprehensive evaluation system for the benefits of tree canopy coverage are screened out. This setting can combine big data analysis to expand the evaluation dimensions of the benefits of tree canopy coverage in real time and ensure comprehensive evaluation.

[0026] Step 2: Collect the topographic features, ecological features, and land use features of the tree canopy coverage blocks in the target area.

[0027] In this step, by analyzing the remote sensing data corresponding to the target area, the tree canopy coverage blocks in the target area are confirmed. When analyzing the remote sensing data, the remote sensing data is pre-registered and image-enhanced, and the processed image data is obtained. Specifically, the image registration includes registering the geographic coordinates of the remote sensing data with the geographic coordinates of the GIS data to facilitate subsequent spatial display of the tree canopy coverage blocks. The image enhancement includes filtering the remote sensing data to remove noise.

[0028] A BP neural network is used to classify the image data, and the image data is divided into tree canopy coverage image data and other image data; the tree canopy coverage image data is associated with the GIS map, and a visual area location map of the tree canopy coverage blocks is obtained. By using the above method, the tree canopy coverage blocks can be effectively divided and visually displayed, which is convenient for intuitively confirming the current situation of tree canopy coverage.

[0029] The ecological features include canopy coverage rate, canopy shape, canopy height, leaf density, leaf area index, canopy porosity, diffuse radiation coefficient, forest canopy density, and the types of organisms under the canopy. Among them, the canopy coverage rate refers to the ratio of the canopy coverage area to the relevant area (such as the total area of the target region). The canopy shape refers to the shape of the tree canopy, including spherical, conical, disc-shaped, oblate spherical, oblate conical, columnar, etc. The canopy height refers to the vertical distance from the ground or reference plane to the highest part of the canopy. The leaf density refers to the number of leaves or leaf area per unit area. The leaf area index refers to the ratio of the leaf area to the ground area within the canopy over a certain period of time. The canopy porosity refers to the ratio of the pore area of the plant canopy to the relevant area. The diffuse radiation coefficient refers to the value of solar radiation whose direction has been changed by scattering. The forest canopy density refers to the degree to which the tree canopies of arbors are connected to each other and cover the ground.

[0030] The topographic features include topographic undulation, topographic slope, topographic height, and the folded area of the region under the canopy; the folded area of the region under the canopy is the area of the secondary shadow coverage region under the canopy shadow, and there is a height difference between the secondary shadow coverage region and the planting ground of the tree corresponding to the canopy.

[0031] When collecting the folded area of the region under the canopy, the following steps are included:

[0032] S1. Based on the visualization area position map of the canopy coverage plate, the canopy coverage plate is divided again; in the secondary division, the topographic map corresponding to the position of the canopy coverage plate is called and cut into several cells, and according to the relative height values in the topographic map, the cells containing the terrain with a relative height value greater than 2.5 m are extracted as reference cells; in this embodiment, the cell area is 5 m 2 . And, for the edges of the canopy coverage plate, they are all cut into complete cells to completely cover the canopy coverage plate and its surrounding areas.

[0033] S2. Collect the point cloud data at the reference cells, and use the MSAC algorithm for point cloud analysis to obtain a three-dimensional parameter model; based on the plane height, the three-dimensional parameter model is segmented into planes, and the plane segmentation line is used as the reference edge line of the secondary shadow coverage region. Specifically, after confirming the reference edge line, combined with the elevation of the planting ground of the tree corresponding to the canopy, the secondary shadow coverage region in each reference cell region can be distinguished.

[0034] Step 3. Based on the data collected in Step 2, calculate the green ecological benefit index and the social and economic benefit index of the canopy coverage plate.

[0035] Specifically, in this embodiment, when calculating the green ecological benefit index and the social and economic benefit index of the tree canopy coverage section, for the thermal environment index among them, indicators such as temperature, humidity, and wind speed need to be considered. The dry-bulb temperature method or the globe thermometer temperature method can be used to measure the environmental thermal state at the tree canopy coverage section as the thermal environment index. Among them, the dry-bulb temperature method reflects the environmental thermal state by measuring the air temperature. The dry-bulb temperature refers to the air temperature, which is affected by solar radiation, atmospheric stability, and water vapor content. The globe thermometer temperature method reflects the environmental thermal state by measuring the temperature of the globe (i.e., the black surface at the tree canopy coverage section). The globe thermometer temperature is affected by solar radiation, atmospheric stability, and wind speed. For the biodiversity index, it is comprehensively represented by measuring the species richness index, evenness index, ecological dominance index, diversity index, and habitat fragmentation index at the tree canopy coverage section.

[0036] For the carbon sink volume index, in this embodiment, it can be calculated based on the following formula: Carbon sink volume = (Carbon emission - Carbon sink volume) ÷ (Appropriate time interval). Among them, the carbon emission refers to the carbon dust input into the environment at the tree canopy coverage section within a certain time period, and the carbon sink volume refers to the amount obtained from the emission pool at the tree canopy coverage section during this time period. The appropriate time interval refers to the time span for collecting these emissions and calculating the carbon sink, which is set according to the actual calculation requirements in practical applications.

[0037] For the index of the richness of activities under the canopy, the types of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of the space under the forest, and the richness of business forms under the canopy, they are obtained by on-site collection and statistics at the tree canopy coverage section. Preferably, remote sensing technology can be used to assist in data collection and statistics. Among them, the coverage rate of tree-lined roads refers to the proportion of the area of tree-lined roads at the tree canopy coverage section to the total land area at the tree canopy coverage section, and the calculation formula is: Coverage rate of tree-lined roads = Area of tree-lined roads / Total area of roads × 100%. The utilization rate of the space under the forest refers to the proportion of the utilized area of the space under the forest to the total forest area at the tree canopy coverage section, and the calculation formula is: Utilization rate of the space under the forest = Utilized area of the space under the forest / Total forest area × 100%.

[0038] Step 4: Based on the data in Step 2 and Step 3, use statistical methods to statistically analyze and obtain the spatial distribution characteristics of the tree canopy benefits; according to the spatial distribution characteristics of the tree canopy benefits, generate a benefit optimization strategy. In this embodiment, the statistical analysis using statistical methods includes first using the correlation analysis method to establish an association between each index in the green ecological benefit index and the social and economic benefit index and each spatial distribution characteristic, and taking the green ecological benefit index and the social and economic benefit index with a correlation ranking in the top 50% as the statistical basis for this spatial distribution characteristic. Based on the statistical basis, determine the spatial distribution characteristics.

[0039] Specifically, the spatial distribution characteristics include spatial heterogeneity, spatial autocorrelation, spatial distribution pattern, and spatial variation degree. Among them, spatial heterogeneity refers to the differences in the canopy coverage benefits at different spatial positions. Spatial autocorrelation means that there is spatial autocorrelation in the canopy coverage benefits, that is, the canopy coverage benefits at adjacent spatial positions may be similar, which indicates that the growth and distribution of trees are affected by adjacent trees. The spatial distribution pattern refers to the regularity presented by the spatial distribution pattern of the canopy coverage benefits, including continuous strip distribution, patchy distribution, etc. The spatial variation degree indicates that the spatial variation degree of the canopy coverage benefits may vary due to factors such as region, tree species, and growth environment. For example, the canopy coverage benefits in some regions may be relatively stable, while in other regions, there may be large variations.

[0040] When generating the benefit optimization strategy, based on the spatial heterogeneity, spatial autocorrelation, spatial distribution pattern, and spatial variation degree of the canopy benefits, optimization suggestions are generated for the arrangement intervals, species categories, and species combination methods of tree species to achieve the optimization of the canopy coverage benefits.

[0041] This embodiment also provides a canopy coverage benefit evaluation system, which is applied to a canopy coverage benefit evaluation method as described above; it includes a data processing module and an evaluation module;

[0042] The data processing module is used to collect the topographic features, ecological features, and land use features of the canopy coverage blocks in the target area and convert them into the spatial distribution characteristics of the canopy benefits; a comprehensive evaluation system for canopy coverage benefits is preset in the evaluation module; the comprehensive evaluation system for canopy coverage benefits is constructed with green ecological benefit indicators and social and economic benefit indicators; the green ecological benefit indicators include thermal environment indicators, biodiversity indicators, and carbon sequestration amounts; the social and economic benefit indicators include the richness of activities under the canopy, the types of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of the space under the forest, and the richness of business forms under the canopy;

[0043] The evaluation module is also used to calculate the green ecological benefit indicators and social and economic benefit indicators of the canopy coverage blocks based on the spatial distribution characteristics.

[0044] A canopy coverage benefit evaluation method and system provided by this embodiment can accurately evaluate the canopy coverage benefits and provide reliable information references for the investigation and optimization of the current situation of the canopy coverage benefits.

[0045] In particular, first, this solution constructs a comprehensive evaluation system for the canopy coverage benefit, which includes two dimensions: green ecological benefit and social and economic benefit. Combining the topographic features, ecological features, and land use features of the canopy coverage area collected, it can intuitively and quantitatively represent the canopy coverage benefit by calculating the green ecological benefit index and social and economic benefit index, accurately evaluate the canopy coverage benefit, and help accurately grasp the actual status of the canopy coverage benefit. Furthermore, through the analysis of the above indicators and features, the comprehensive spatial distribution characteristics of the canopy benefit can be statistically analyzed; according to the spatial distribution characteristics of the canopy benefit, an efficiency optimization strategy can be generated, which can provide a reference for improving the urban environmental quality; it helps to improve the canopy coverage benefit and make more efficient use of the space under the canopy.

[0046] Second, among the characteristic information of the canopy coverage area collected in this solution, it includes diverse characteristic information such as topographic features, ecological features, and land use features, which can comprehensively consider the development status of the canopy coverage area. Among them, in the topographic features, the folded area feature of the area under the canopy is specially designed. Through this feature, a detailed analysis can be carried out on some canopy coverage areas in specific regions. In the actual construction of urban green spaces, due to the layout characteristics of the city, there will be many highly staggered spaces. For example, in Chongqing, there are many multi-level and staggered road or area layouts. In this case, for the trees located in the highly staggered spaces, the canopy coverage areas may also be highly staggered, and the corresponding canopy coverage areas include secondary shadow coverage areas and the planted ground areas of the trees corresponding to the canopies. The ecological benefits and economic benefits generated by these two areas are also different. This solution pays special attention to this characteristic and conducts a separate analysis of the folded area feature of the area under the canopy, which helps to more accurately evaluate the canopy coverage benefit.

[0047] Embodiment 2

[0048] A method for evaluating the canopy coverage benefit. On the basis of Embodiment 1, in step 4, the generated efficiency optimization strategy further includes the following strategies:

[0049] Step a: Associate other image data of the target area with the GIS map and obtain a visual area location map of the area outside the canopy coverage area of the target area;

[0050] Step b: Based on the visual area location map obtained in step a, perform a secondary division on this area; in the secondary division, call the topographic map of the corresponding location of the target area and cut it into several cells, and extract the cells containing the terrain with a relative height value greater than 2.5 m as auxiliary cells according to the relative height values in the topographic map; in this embodiment, the cell area is 20 m 2 .

[0051] Step c: Collect the point cloud data at the auxiliary cells, and use the MSAC algorithm to perform point cloud analysis and obtain a three-dimensional parameter model. Perform plane segmentation on the three-dimensional parameter model based on the plane height, and use the plane segmentation line as the auxiliary edge line. If the auxiliary edge lines of adjacent auxiliary cells can be connected, merge the two adjacent auxiliary cells.

[0052] Step d: Retrieve the point cloud data around the auxiliary edge line and perform fuzzy recognition. The fuzzy recognition is used to identify whether there are entities within 10 m on both the left and right sides of the auxiliary edge line. If not, set a recommended tree-planting label for the area of the auxiliary cell corresponding to the auxiliary edge line. If there are entities and the entity occupancy rate is less than 35%, set a reference tree-planting label for the area of the auxiliary cell corresponding to the auxiliary edge line. In other cases, no marking is done.

[0053] In practical applications, based on the above labels, the tree-planting areas can be selected to expand the scale of the urban forest. In the area of the auxiliary cell with the recommended label, since there are actually at least two height planes that enjoy the canopy coverage area, both planes can independently provide shaded spaces, which can maximize the canopy coverage benefit. Moreover, different green spaces can be constructed. For example, in the height plane where the trees are located, there is a complete understory space, while in the other height planes, there are shaded spaces. And it helps to disperse the pedestrian flow in the shaded areas.

[0054] This embodiment also provides a canopy coverage benefit evaluation system, which is the same as the system described in Embodiment 1 and will not be elaborated here.

[0055] A canopy coverage benefit evaluation method and system provided by this embodiment can perform a detailed analysis of the terrain of the target area, and can intelligently extract the recommended tree-planting spaces (areas of the auxiliary cells with labels) that can have secondary shadow coverage areas, which can provide an effective guiding direction for urban forest construction and canopy coverage benefit improvement.

[0056] The above are only embodiments of the present invention. Specific structures and characteristics and other common knowledge in the art are not described in detail herein. Those of ordinary skill in the art know all the common general technical knowledge in the technical field to which the invention pertains before the filing date or the priority date, are able to obtain all the prior art in this field, and have the ability to apply the conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given by this application, complete and implement this solution in combination with their own abilities. Some typical well-known structures or well-known methods should not become an obstacle for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can also be made, and these should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent.

Claims

1. A method for evaluating the canopy coverage benefit, characterized in that, It includes the following steps: Step 1, construct a comprehensive evaluation system for canopy coverage benefits; the comprehensive evaluation system for canopy coverage benefits is provided with green ecological benefit indicators and social and economic benefit indicators; the green ecological benefit indicators include thermal environment indicators, biodiversity indicators, and carbon sequestration; the social and economic benefit indicators include the richness of activities under the canopy, the type index of facilities under the canopy, the coverage rate of shaded roads, the utilization rate of the space under the forest, and the richness of business forms under the canopy; Step 2, collect the topographic features, ecological features, and land use features of the canopy coverage blocks in the target area; Step 3, based on the data collected in Step 2, calculate the green ecological benefit indicators and social and economic benefit indicators of the canopy coverage blocks.

2. The canopy coverage benefit assessment method according to claim 1, wherein In Step 1, it also includes obtaining data in the field of canopy coverage benefits and extracting key indicators from them to supplement the comprehensive evaluation system for canopy coverage benefits.

3. The canopy coverage benefit evaluation method according to claim 2, wherein, The data in the field of canopy coverage benefits includes structured data and unstructured data; the structured data includes GEE data, forest resource datasets, and satellite remote sensing datasets; the unstructured data includes literature data and report data with the theme of canopy coverage and canopy coverage benefits.

4. The canopy coverage benefit evaluation method according to claim 2, characterized in that, When extracting key indicators, an LSTM model is used to extract key indicators; and after the key indicators are extracted, the key indicators that are repeated with those in the comprehensive evaluation system for canopy coverage benefits are screened out.

5. The canopy coverage benefit evaluation method according to claim 1, characterized in that It also includes Step 4, based on the data in Step 2 and Step 3, statistically analyze to obtain the spatial distribution characteristics of canopy benefits; according to the spatial distribution characteristics of canopy benefits, generate benefit optimization strategies.

6. The canopy coverage benefit evaluation method according to claim 1, wherein The ecological features include canopy coverage rate, canopy shape, canopy height, leaf density, leaf area index, canopy porosity, diffuse radiation coefficient, forest canopy closure, and biological categories under the canopy.

7. A method for evaluating the canopy coverage benefit according to claim 1, characterized in that In Step 2, by analyzing the remote sensing data corresponding to the target area to confirm the canopy coverage blocks in the target area; when analyzing the remote sensing data, the remote sensing data is also pre-registered and image-enhanced in advance, and the processed image data is obtained; a BP neural network is used to classify the image data, and the image data is divided into canopy coverage image data and other image data; the canopy coverage image data is associated with the GIS map, and the visual area position map of the canopy coverage blocks is obtained.

8. The canopy coverage benefit assessment method according to claim 7, characterized in that, The topographic features include terrain undulation, terrain slope, terrain height, and the folded area of the area under the canopy; the folded area of the area under the canopy is the area of the secondary shadow coverage area under the canopy shadow, and there is a height difference between the secondary shadow coverage area and the planting ground of the trees corresponding to the canopy.

9. The canopy coverage benefit assessment method according to claim 8, characterized in that When collecting the folded area of the area under the canopy, it includes the following steps: S1, based on the visual area position map of the canopy coverage block, conduct a secondary division of the canopy coverage block; in the secondary division, call the topographic map corresponding to the position of the canopy coverage block and cut it into several cells, and extract the cells containing the terrain with a relative height value greater than 2.5m as reference cells according to the relative height values in the topographic map; S2, Collect the point cloud data at the reference cell, and perform point cloud analysis using the MSAC algorithm to obtain a three-dimensional parameter model; perform plane segmentation on the three-dimensional parameter model based on the plane height, and use the plane segmentation line as the reference edge line of the secondary shadow coverage area.

10. A crown coverage benefit evaluation system, characterized in that, Applied to a method for evaluating the canopy coverage benefit as described in any one of claims 1-9; including a data processing module and an evaluation module; The data processing module is used to collect the topographic features, ecological features, and land use features of the canopy coverage plates in the target area, and convert them into the spatial distribution features of the canopy benefits; a comprehensive evaluation system for canopy coverage benefits is preset in the evaluation module; a green ecological benefit index and a social and economic benefit index are set up in the construction of the comprehensive evaluation system for canopy coverage benefits; the green ecological benefit index includes a thermal environment index, a biodiversity index, and a carbon sink amount; the social and economic benefit index includes the richness of activities under the canopy, the type index of facilities under the canopy, the coverage rate of tree-lined roads, the utilization rate of the space under the trees, and the richness of business forms under the canopy; The evaluation module is also used to calculate the green ecological benefit index and the social and economic benefit index of the canopy coverage plate based on the spatial distribution features.

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