CN112507839A - Method for rapidly measuring and calculating carbon fixation amount of urban landscape - Google Patents
Method for rapidly measuring and calculating carbon fixation amount of urban landscape Download PDFInfo
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Abstract
The invention discloses a method for quickly measuring and calculating the carbon fixation amount of an urban landscape, and relates to the technical field of carbon fixation amount calculation. The method comprises the step A of establishing an urban landscape plant database. The plant carbon fixation amount test data in the existing literature is used as the basis of a plant database. And B, establishing a plant image identification system. And carrying out class identification on the plant image by adopting a convolution neural network model in deep learning. And step C, using the unmanned aerial vehicle to acquire the landscape image. And D, establishing an urban landscape GIS model. And E, calculating the total green quantity and distribution of the urban landscape. And F, calculating the total daily average solid carbon amount and distribution of the urban landscape. Compared with the prior art, the method can save more manpower, time and instrument cost, is simple and convenient to operate, and has higher popularity and popularization value. In addition, the method of the invention records the measuring and calculating results in the map, facilitates the visual analysis of data, is beneficial to the management and improvement of landscape with pertinence after the management personnel, and improves the carbon sequestration effect of urban landscape greening.
Description
Technical Field
The invention relates to the technical field of carbon sequestration calculation, in particular to a method for quickly measuring and calculating the carbon sequestration of urban landscapes.
Background
With the rapid development of cities, the emission of CO is increased due to the increase of industrial emission2The main greenhouse gases cause great damage to the ecological environment of the city and influence the good operation of the city. Two main strategies are provided for improving urban environment and improving the health level of citizens, one is energy conservation and emission reduction, the other is carbon sink, and the combination of emission source control and carbon sink becomes a powerful means for controlling greenhouse effect in many countries. Urban carbon sink means that green plants in urban area can absorb CO in the atmosphere through photosynthesis2Ability to absorb and fix in vegetation and soil. The research on the carbon sink of the urban landscape is developed, the carbon sink potential of the urban landscape is improved, and the method has important theoretical and practical significance for relieving the pressure of urban carbon emission reduction and slowing down global climate change.
Although there are many carbon sink researches on forest ecosystems in forestry, forestry scientists do not and have difficulty developing carbon sink function researches on urban vegetation from the perspective of micro-scale and urban vegetation types. Landscape scientists attach importance to the research on urban landscapes, urban landscaping coverage, plant individuals, variety characteristics and the like, but lack basic data and research on vegetation biomass, growth amount and the like related to the ecological function of plants, so that the research on related carbon sink is rare in urban landscaping.
Certainly, from the number of cities and the green space conditions of the cities in China, the carbon sink function of the cities is really very small compared with ecological systems such as forests and the like. However, with the development of urbanization, the level of urban landscape greening is improved, and the carbon sink potential of the part is very large. The carbon sink function of the urban landscape greening is directly evaluated, the ecological value of the urban landscape is reflected, and the carbon sink function is directly related to the carbon balance of the city.
The information acquisition of the urban landscape greening carbon sink information is not a simple technology, the greening carbon sink information, namely the carbon fixation condition, is accurately obtained, a large amount of manpower is required to be consumed to count the carbon fixation amount of each plant and the green leaf amount condition one by one, and the carbon fixation amount calculation method of the conventional plants adopted on forests and farmlands at present is not suitable for urban landscape greening calculation, for example: a biomass method, an assimilation box method, a vorticity correlation method, and the like. The biomass method is to calculate the biomass of the greening, and multiply the biomass by a biomass-carbon reserve conversion factor to obtain the carbon reserve, wherein the biomass-carbon reserve conversion factor is generally between 0.45 and 0.55, but the biomass-carbon reserve conversion factor has great difference on the types and the forms of plants in the urban landscape greening, and great errors are inevitably generated when the empirical method is adopted for measurement. The assimilation box method is to seal the plant to be tested and the growing environment required by the plant in a box body, measure the carbon sink amount of the plant by measuring the change of the gas concentration in the box body in unit time, and is generally suitable for farmlands and grasslands in flat areas. Vorticity-related flux observations were made by measuring vertical wind velocity and CO2The fluctuation of the density realizes the direct observation of the carbon flux from the meteorological point of view, and can obtain a large amount of CO with high time resolution in a short time2Flux and environmental variation data, but the application of the method is subject to the limit of topographic and meteorological conditions, and the test requires that the underlying surface is flat and uniform, so the test method is not suitable for urban environments.
In view of the influence factors of the carbon sink in urban landscape greening, the carbon sink capacity and unit area of a single plant are mainly included, and in order to know the carbon sequestration benefit condition of urban landscape greening, urban landscape greening investigation, GIS technology establishment management platform and plant database can be carried out by means of an unmanned aerial vehicle for rapid measurement and calculation.
The Unmanned Aerial Vehicle is an Unmanned Aerial Vehicle which is controlled by remote control equipment and software and hardware adaptive to the Unmanned Aerial Vehicle. The unmanned aerial vehicle has the advantages of simple flight operation, flexible take-off and landing, less influence of environmental conditions and suitability for tasks under different regional scales. At present, as the flight control system of the unmanned aerial vehicle is open and the hardware technology is mature, the unmanned aerial vehicle makes a major breakthrough in the technology, and the application scene is gradually expanded.
GIS (Geographic Information Systems) is a product of crossing various disciplines, provides various spatial and dynamic Geographic Information in real time by adopting a Geographic model analysis method on the basis of Geographic space, and is a computer technology system for providing Geographic research and Geographic decision service. Its basic function is to convert tabular form data (whether it comes from a database, spreadsheet file, or directly entered in a program) into a geographic graphic display, and then to browse, manipulate, and analyze the display results. It can range from intercontinental maps to very detailed block maps.
Meanwhile, the related technical method for measuring the carbon fixation amount of the greening comprises the following steps: a method for detecting forest carbon sink amount (application number: 201410348570.X) is characterized in that each tree species is sampled, the cell wall rate of each tree species is measured in a laboratory, and the storage amount of each tree species at a survey point, namely the average breast height, the tree height and the like of each tree species at the survey point are obtained. Multifunctional small carbon sink measurement assimilation box device (application number: 201410640610.8) the patent measurement method requires that plants are placed in a closed assimilation box facility and is only suitable for measuring small plants, potted plants and the like. A method for measuring carbon sink of single tree in city (application number: 201510178889.7) comprises measuring crown light energy utilization rate G, crown width D, root respiration ratio B, leaf shading rate f and instantaneous photosynthetic rate Pi。
The measurement and calculation methods of the greening solid carbon content need to sample and research plants, and need to consume a large amount of manpower and time.
In summary, the existing calculation methods for the greening carbon sequestration amount all need professionals with certain forestry professional knowledge to investigate and test plants on site, and a large amount of labor and time are consumed for investigating the condition once. Therefore, on the aspect of urban landscape, the carbon sequestration situation of the urban landscape is blank data because of large requirement of professionals, time and labor consumption in field investigation and lack of carbon sequestration measurement and data statistics of the urban landscape.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings in the prior art and provides a method for rapidly measuring and calculating the carbon fixation amount of urban landscapes.
The invention relates to a method for rapidly measuring and calculating the carbon fixation amount of urban landscapes, which records the carbon fixation amount database information of different plants based on the existing documents, adopts an artificial intelligent image recognition technology to establish a plant image recognition system, utilizes an unmanned aerial vehicle image acquisition technology to carry out on-site scanning on landscape greening through an unmanned aerial vehicle, and rapidly measures and visually displays the carbon fixation amount conditions of the urban landscape greening based on a geographic information technology (GIS) model, wherein the carbon fixation amount conditions comprise the carbon fixation amount size and the carbon fixation amount distribution condition of different regions. The ecological benefit of the current urban landscape can be scientifically evaluated through the visual display of the measuring and calculating results, and the method is also beneficial to reasonably planning urban landscape greening later and constructing ecological and low-carbon urban landscape.
The method comprises the following steps
Step 1: and establishing an urban landscape plant database. The urban landscape plant data comprises plant leaf area index information and plant daily average unit area carbon fixation amount information. The leaf area index parameter of the plant is an important parameter reflecting the plant morphology, and can reflect the flourishing degree of the leaves of the plant, and the flourishing degree of the leaves of the plant has a close relation with the types of the plant. The carbon fixation amount per unit area of the average day is an important parameter capable of reflecting the carbon fixation capacity of the plant leaves, and means the fixed CO2 amount in the average day under the condition that the total area of the plant leaves is 1 square meter, and the fixed CO2 amount is usually the average value of spring days, autumn days and summer days. The existing literature is used for taking the test data of the carbon fixation amount of plants as the basis of a plant database. Considering the conditions of extreme samples and test conditions in test data, acquiring centralized trend data by using a method of statistically cutting an average value, discarding 10% of maximum data and 10% of minimum data in the data, taking the average value and standard deviation of the remaining data, and establishing a plant database containing leaf area indexes of different plant species and daily average unit leaf area carbon content information.
Step 2: and establishing a plant image recognition system. And classifying and identifying the plant images by using a convolution neural network model in deep learning. The urban landscape plant photos are collected, the more the number of collected samples is, the higher the accuracy is, the accuracy of the identification system is related to the number of collected samples, and the requirement of the number of collected photos that the identification rate of the system reaches more than 90% is met. In the process of extracting the plant image identification features, the shape of leaves, the shape of petals and the shape of crown of the plant are taken as identification feature elements. And training and testing the sample by adopting a convolution neural network model in deep learning.
And step 3: and using the unmanned aerial vehicle to obtain landscape images. The unmanned aerial vehicle can acquire the landscape image according to the preset flight track, and an unmanned aerial vehicle device, a flight navigation and control system, a ground monitoring system, a high-definition digital camera and a data transmission system are needed for completing the step.
And 4, step 4: and establishing an urban landscape GIS model. Landscape plants of the same plant type are made into closed multi-section lines by using CAD, and the identified plant types are arranged on different layers by using a plant image identification system. And respectively introducing the layers into ArcGIS according to surface elements (Polygon), and establishing a GIS model of urban landscape plant species distribution.
And 5: and calculating the total green quantity and distribution of the urban landscape. Calculating the green quantity of plants in each surface element layer through the formulas (1-4), assigning the green quantity to table attributes of different surface element layers, and combining the surface element layers through a combination tool (Merge) to obtain the total green quantity of landscape greening.
The arbor green quantity calculation method is that the arbor green quantity is calculated according to the recognized arbor species by using an arbor category crown diameter-crown height equation and a crown shape-green quantity equation. The shrub and herb green quantity obtaining method is obtained by calculation according to the leaf area index and the coverage area of plant species.
The crown diameter and crown height formula of the arbor can be calculated by the formula (1):
(1)
y＝1/(a+be-cx)
in the formula: x is the diameter of the arbor, m; y is the crown height of the arbor, m; a, b, and c are coefficients determined by the type of arbor, for example: weeping willow a is 0.832, b is 0.042 and c is 0.758.
The green amount of the arbor can be calculated according to the shape, the diameter and the height of the crown of the tree of the variety:
(2)
LAtree＝f(x，y)
| serial number | Crown shape | Arbor green quantity calculation formula |
| 1 | Ovoid and spherical | LAtree＝πx2y/6 |
| 2 | Conical shape | LAtree＝πx2y/12 |
| 3 | Ball fan | LAtree＝π(2y3-y2)/3 |
| 4 | Segment shape | LAtree＝π(3xy2-2y3)/6 |
| 5 | Cylindrical shape | LAtree＝πx2y/4 |
In the formula: LAtreeGreen amount of this kind of arbor, m2(ii) a x is the diameter of the arbor, m; y is the crown height of the arbor, m.
The green quantity of shrubs and herbaceous plants can be calculated by the following formulas (3) and (4):
(3)
LAshurb＝LAIshurbSshurb
LAgrass＝LAIgrassSgrass (4)
in the formula: LAshurbGreen amount of this species of shrub, m2；LAgrassThe green amount of the grass of this kind, m2；LAIshurbThe leaf area index of the species of shrub; LAIgrassThe leaf area index of the species of shrub; sshurbM is the area covered by the species of shrub2；SgrassM is the area covered by the grass2。
The green amount value of a unit area is added to the table attribute in each surface element layer, the green amount of the unit area in each layer surface element is converted into grid data information by using a surface element grid conversion tool (Polygon to ramp) in ArcGIS, and then the data of each plant grid layer is added by a grid Calculator (ramp Calculator), so that the green amount distribution condition of landscape greening can be displayed in a map.
Step 6: and calculating the total daily average solid carbon amount and distribution of the urban landscape. According to the formula (5), the daily average fixed carbon amount of each plant in the urban landscape plant database and the daily average leaf area of each plant in the urban landscape plant database and the plant green amount of each surface element calculated in the step (5) are utilized to calculate the daily average fixed carbon amount value of each surface element to be assigned to the table attributes of different plant surface element layers, and the surface element layers are combined through a combination tool (Merge), so that the total daily average fixed carbon amount data of urban landscape greening can be obtained.
WCO2＝wCO2，i×LAi (5)
In the formula: wCO2The daily average carbon fixation amount of the urban landscape is g/d; w is aCO2，iThe carbon fixation amount per daily average leaf area of the plant type i, g/m2·d；LAiGreen amount of plant species i, m2。
Adding a column of daily average fixed carbon value of unit area to the attribute of the layer table of each layer element, converting the daily average fixed carbon value of unit area in each layer surface element into grid data information by using a surface element grid transfer tool (Polygon to scanner) in ArcGIS, and adding the data of each plant grid layer by a grid Calculator (scanner Calculator) so as to display the daily average fixed carbon distribution condition of greening landscape in a map.
As described above, the present invention has, compared with the prior art:
the method utilizes an unmanned aerial vehicle image acquisition technology, an artificial intelligent image recognition technology and a geographic information technology to quickly measure and calculate the carbon fixation amount of the urban landscape. Compared with the existing field actual measurement method, the method can save more manpower, time and instrument cost, is simpler and more convenient to operate, can be completed without professional operation in the fields of landscapes and forestry, and has higher popularity and popularization value. In addition, compared with the prior art that the measurement result is only one data value, the measurement result is recorded in the map, so that the visual analysis of the data is convenient, the management and the improvement of landscapes in a more targeted manner after managers are facilitated, and the carbon sequestration effect of urban landscape greening is improved.
Drawings
FIG. 1 is a flow chart of a rapid measurement and calculation method for carbon fixation of urban landscapes, which is disclosed by the invention;
FIG. 2 is a landscape greening plant distribution model established in a GIS according to an embodiment of the present invention;
FIG. 3 is a view of a landscape greening amount distribution map established in a GIS according to an embodiment of the present invention;
fig. 4 is a view showing a distribution diagram of the daily average fixed carbon amount of landscape greening established in the GIS according to the embodiment of the present invention.
Detailed Description
The invention is further described in the following with reference to the figures and examples
The invention relates to a method for rapidly measuring and calculating the carbon fixation amount of an urban landscape, which comprises the steps (as shown in an attached figure 1).
Step A: and establishing an urban landscape plant database. The plant carbon fixation amount test data in the existing literature is used as the basis of a plant database. Considering the extreme samples and the test conditions in the test data, the central tendency data is obtained by statistically cutting the mean value, 10% of the maximum data and 10% of the minimum data in the data are discarded, and the mean value and the standard deviation of the rest data are obtained, for example: the average daily solid carbon amount data of camphor trees in unit area comprises 28 groups, the first three groups of maximum data and the first three groups of minimum data need to be removed, and the average value and the standard deviation of the rest 22 groups of data are calculated. According to this method, a database of leaf area indices for different plant species and carbon fixation per leaf area per day is established, as shown in the following table
TABLE 1 urban landscape plant database
And B: and establishing a plant image recognition system. And carrying out class identification on the plant image by adopting a convolution neural network model in deep learning. In the process of extracting the plant image identification features, the shape of leaves, the shape of petals and the shape of crown of the plant are taken as identification feature elements. According to the types of the landscape plants, the urban landscape plants are photographed by using the unmanned aerial vehicle, the overlook photo picture of the common landscape plants is obtained, and at least more than 500 photos are collected for each plant type. And processing the plant images shot by the unmanned aerial vehicle, converting the plant images into images with uniform size and format, and establishing a common urban landscape plant image library. And randomly selecting the first 80% of each plant category as a training number set sample, and the last 20% as a test data set sample, and constructing convolutional neural image recognition classification.
And C: and using the unmanned aerial vehicle to obtain landscape images. And selecting the time with good weather condition and no cloud, and enabling the unmanned aerial vehicle carrying the high-resolution digital camera to take aerial photos of the measurement area according to the preset flight route. In order to ensure that the proportion scales of all parts of the images are consistent and the definition of the images is ensured, the lens is arranged to be vertically downward, the flying altitude of the unmanned aerial vehicle can be fixed at 50m according to the test environment, the ground resolution of the images is 2cm, and the course overlapping degree is 80%.
Step D: and establishing an urban landscape GIS model. And identifying the plant type in the landscape image shot by the unmanned aerial vehicle by using a plant image identification system. And drawing the plants in the landscape image into a closed multi-section line graph by using CAD software, and placing the plant in different plant type layers according to the identified plant types. And according to the plant types, exporting CAD files of the plant types. CAD files of different plant species are introduced into ArcGIS according to surface elements (Polygon), and a GIS model of urban landscape plant species distribution is established, as shown in the attached figure 2.
Step E: and calculating the total green quantity and distribution of the urban landscape. And calculating the green quantity of the plants in each surface element, assigning the green quantity to the table attributes of different surface element layers, and combining the surface element layers through a combination tool (Merge) to obtain the total green quantity of the landscape greening.
The method for calculating the plant green quantity of each surface element can be divided into arbor green quantity acquisition and shrub green and herb green quantity acquisition.
The arbor green quantity obtaining method is to calculate the arbor green quantity according to the recognized arbor species and the crown diameter.
Arbor category crown diameter-crown height equation:
(I)
y＝1/(a+be-cx)
in the formula: x is the diameter of the arbor, m; y is the crown height of the arbor, m; a, b and c are coefficients, and are determined by the types of trees.
Crown shape-green volume equation:
(II)
LAtree＝f(x，y)
| serial number | Crown shape | Arbor green quantity calculation formula |
| 1 | Ovoid and spherical | LAtree＝πx2y/6 |
| 2 | Conical shape | LAtree＝πx2y/12 |
| 3 | Ball fan | LAtree＝π(2y3-y2)/3 |
| 4 | Segment shape | LAtree＝π(3xy2-2y3)/6 |
| 5 | Cylindrical shape | LAtree＝πx2y/4 |
In the formula: LAtreeGreen amount of this kind of arbor, m2(ii) a x is the diameter of the arbor, m; y is the crown height of the arbor, m.
The green quantity of shrubs and herbaceous plants can be calculated by leaf area indexes and plant coverage areas in a plant database, as shown in formula (III) and formula (IV):
(III)
LAshurb＝LAIshurbSshurb
LAgrass＝LAIgrassSgrass (IV)
in the formula: LAshurbGreen amount of this species of shrub, m2；LAgrassThe green amount of the grass of this kind, m2；LAIshurbThe leaf area index of the species of shrub; LAIgrassThe leaf area index of the species of shrub; sshurbM is the area covered by the species of shrub2；SgrassM is the area covered by the grass2。
For example, there are 5 pagodatree trees in the pagodatree layer, the diameter of the pagodatree is 3.5m, and the height y of the pagodatree is 1/(0.654+0.311 e) according to the equation of diameter-height-0.634x) 1.45m, the total green content of Sophora japonica is 70m2. For example, the Rhododendron has a leaf area index of 2.19 and a coverage area of 10m2The green amount of the rhododendron is 21.9m2。
A column of unit area green quantity value is added to each layer table attribute, and the unit area green quantity in each layer surface element is converted into Raster data information by using a surface element to Raster tool (Polygon to Raster) in ArcGIS. The layers are scaled by a grid Calculator (rank calcutor) according to the formula' Con (isnut ("brown bamboo _ polygon toster _ green dose"), 0, "brown bamboo _ polygon toster _ green dose") + Con (isnut ("azalea _ polygon toster _ green dose"), 0, "azalea _ polygon toster _ green dose") + Con (isnut ("purple leaf moster _ polygon toster _ green dose"), 0, "purple leaf moster _ polygon toster _ green dose") + Con (isnut ("star anise disc _ polygon toster _ green dose"), 0, "blue leaf moster _ polygon toster _ green dose" + Con (isnut ("polygon toster _ green dose"), 0, "gold disc _ polygon _ 12 (" star disc _ polygon toster _ green dose ") +0," blue leaf tster _ green dose "+ palm osler _ green dose" +0, "polygon red leaf tster _ green dose" + brown leaf tsetse _ green dose "+ 0," polygon red _ palm green dose "+ palm osler _ green dose" + brown leaf tstree _ green dose "+ brown dose" +0, "polygon tster _ green dose" + brown "brown tablet _ green dose" + brown "for" brown "green dose" + brown "for" green ", 0," brown "green dose" + brown "for" green for "brown" for "brown" green for "for a" for a "brown plant for a" for a "brown plant for a, 0, "lagerstroemia _ polygon Toraster _ Green amount") + Con (IsNull ("Gardenia _ Polygon Toraster _ Green amount"), 0, "Gardenia _ polygon Toraster _ Green amount") + Con (IsNull ("Po _ Polog _ Polygon _ Green amount"), 0, "Po _ Polog _ Polygon _ Raster _ Green amount") and Con (IsNull ("Ire _ Polygon Toraster _ Green amount") and 0, "Ire _ Polygon _ polygon _ Green amount") and Con (IsNull ("IsNull _ Polygon _ polygon _ Red amount") and 0, "Sage _ Polygon _ polygon _ Green amount" and 0, "Valencia _ polygon _ Polygon _ Red _ Green amount" and Con (IsNu _ Sage _ Red _ Green amount "+ Taber _ Green amount" +0, "Polygon _ Red _ Green amount" and Polygorge _ Green amount "+ Polygorster _ Green amount" 0, "Kongkura _ Green amount" and Polygorge _ Green amount "," Kangkura _ Green amount "+ 0" Polygon _ Green amount "(" Karstroe _ Red Toraster _ Green amount "") (Israh _ Green amount "+ 0, Karstroe _ Green amount", "Kangkura _ Green amount" + Polygorge _ Green amount "," Karstroe _ Green amount "(" Karstroe _ Green amount "", "Kangkura _ Green amount" "," Kang, 0, "glossy privet _ polygon Toraster _ Green amount") + Con (IsNull ("Osmanthus _ polygon Toraster _ Green amount"), 0, "Osmanthus _ polygon Toraster _ Green amount") + Con (IsNull ("Forsythia Kitao _ polygon Toraster _ Green amount"), 0, "Forsythia _ polygon Toraster _ Green amount") + Con (IsNull ("Red maple _ polygon Toraster _ Green amount"), 0, "Red maple _ polygon Toraster _ Green amount") + Con (IsNull ("Red Sage _ polygon Toraster _ Green amount"), 0, "Red maple _ polygon Toraster _ Green amount", "0," yellow Yang Toraster _ Green amount "," Red Toraster _ Green amount "," 0, "Red Guitar Toraster _ Green amount", "Red Guitar Green amount", "0" and Red Toraser Green amount "as calculated in the context of the" Red Toraster _ Green range ". After the calculation is finished, the distribution situation of the green amount of landscape greening can be obtained in the map, as shown in the attached figure 3.
Step F: and calculating the total daily average solid carbon amount and distribution of the urban landscape. And (5) calculating the daily average fixed carbon value of each surface element and assigning the daily average fixed carbon value to table attributes of different plant surface element layers by utilizing the daily average fixed carbon amount per leaf area of each plant in the urban landscape plant database and the plant green amount of each surface element calculated in the step (5) according to a formula (V), and merging the surface element layers by using a merging tool (Merge) to obtain the total daily average fixed carbon data of urban landscape greening.
WCO2＝wCO2，i×LAi (V)
In the formula: wCO2The daily average carbon fixation amount of the urban landscape is g/d; w is aCO2，iThe carbon fixation amount per daily average leaf area of the plant type i, g/m2·d；LAiGreen amount of plant species i, m2。
For example: the daily average carbon content of semen Ginkgo is 6.9g/m2The total area of green displayed in the attribute list is 45m2The daily average carbon fixation amount of the ginkgo tree is 310.5 g.
A column of daily average solid carbon value of a unit area is added to each layer table attribute, and in ArcGIS, the green amount of the unit area in each layer surface element is converted into Raster data information by using a surface element to Raster tool (Polygon to Raster). The layers are scaled by a grid Calculator (rank Calculator) according to the formula' Con (isnut ("brown bamboo _ polygon Toraster _ fixed carbon"), 0, "brown bamboo _ polygon Toraster _ fixed carbon") + Con (isnut ("azalea _ polygon Toraster _ fixed carbon"), 0, "azalea _ polygon Toraster _ fixed carbon") 0, "+ Con (isnut (" purple leaf bill _ polygon Toraster _ fixed carbon ")," purple leaf bill _ polygon Toraster _ fixed carbon "+ 0," purple leaf bill _ polygon Toraster _ fixed carbon "+ Con (isnut (" polygon disc _ polygon _ fixed carbon "), 0," polygon bill _ polygon Toraster _ fixed carbon ") +0," polygon bill _ polygon _ fixed carbon "+ 0," polygon bill _ polygon count "+ 0," polygon bill _ polygon count "+ fixed carbon" +0, "polygon bill _ polygon count (" polygon count "+ 0," polygon bill _ polygon count "+ fixed carbon" +0, "polygon count" + polygon count ("polygon count" + brown sugar "+ brown carbon" + brown sugar "+ 0," polygon count "+ brown sugar (" polygon count "+ brown carbon" + brown sugar "+ brown rice _ polygon count", black "black sugar (" brown sugar "+ brown rice" black rice, 0, "jatropha-polygon-total-solid-carbon-amount" + Con (IsNull ("crape myrtle-polygon-total-solid-carbon-amount"), 0, "jatropha-polygon-total-solid-carbon-amount") + Con (IsNull ("gardenia-polygon-total-solid-carbon-amount"), 0, "gardenia-polygon-total-solid-carbon-amount") + Con (IsNull ("riprap-polygon-total-solid-carbon-amount"), 0, "haya-polygon-total-solid-carbon-amount") + Con (IsNull ("riprap-polygon-total-solid-carbon-amount") +0, "iris-polygon-total-solid-carbon-amount") + Con (isnuster-total ("iris-polygon-total-solid-carbon-amount"), 0, "iris-polygon-total-solid-carbon-amount" + seal-carbon-amount "+ 0," polygon-total-solid-carbon-amount "+ 0," tago-total-solid-carbon-amount "+ 0," tago-tree-total-amount "+ 0," jatropha "polygon-total-solid-carbon-amount" +0, "jatropha" total-solid-amount "+ n-tree-total-solid-carbon-amount" +0, "jatropha" is "for" total-solid-amount "+ 1" for "total" per-tree, 0, a "total-solid-total-amount" + each tree ("jatropha" total-amount "+ 0, 0, 0, "wintergreen _ PolygonToRaster _ fixed carbon level") + Con (IsNull ("golden leaf privet _ PolygonToRaster _ fixed carbon level"), 0, "golden leaf privet _ PolygonToRaster _ fixed carbon level") + Con (IsNull ("osmanthus _ PolygonToRaster _ fixed carbon level"), 0, "osmanthus _ PolygonToRaster _ fixed carbon level") + Con (IsNull ("golden leaf forsythia _ PolygonToRaster _ fixed carbon level"), 0, "forsythia _ polygonjaponicater _ PolygonToRaster _ fixed carbon level") + Con (IsNull ("red maple _ PolygonToRaster _ fixed carbon level"), 0, "red maple _ polygonjaster _ fixed carbon level" +0, "red maple _ polykuster _ fixed carbon level" +0, "polykuntze _ carbon level", and "polykuntze _ carbon level" +0 "in a red maple _ polykuntze _ c _ fixed carbon level" +0, "yellow maple _ range (" osram _ fixed carbon level "+ 0," polykuntze _ c _ range. After the calculation is finished, the distribution condition of the daily average fixed carbon amount of landscape greening can be obtained in a map, as shown in the attached figure 4.
In summary, the invention has the following advantages:
1) it is known that plants absorb carbon dioxide from the atmosphere by photosynthesis, alleviating the greenhouse effect. The method can obtain the ecological benefit of the urban landscape, is convenient for improving and improving, and is beneficial to the benefit of urban environment.
2) By adopting the unmanned aerial vehicle technology and the existing experience model and data, the carbon sequestration amount value of the urban landscape is quickly measured and calculated, the investment of a large amount of labor, equipment and time cost in field research is saved, and the working efficiency is improved.
3) The artificial intelligence big data recognition is adopted in the plant species recognition process, so that operators in non-landscape or forestry professional fields can be helped to finish work, the operation is simple, no professional threshold limitation exists, and the popularization and the rapid popularization of the method are facilitated.
4) The carbon fixation result can be displayed on a map, and a city manager can visually see the total amount and the distribution condition of the carbon fixation of the urban landscape, so that the visualized ecological benefit information can be more beneficial to planning and management of the urban landscape.
Claims (9)
1. A method for rapidly measuring and calculating the carbon fixation amount of urban landscapes is characterized by comprising the following steps:
a, establishing an urban landscape plant database;
b, establishing a plant image identification system;
c, acquiring a landscape image by using an unmanned aerial vehicle;
d, establishing an urban landscape GIS model;
e, calculating the total green quantity and distribution of the urban landscape;
and F, calculating the total daily average solid carbon amount and distribution of the urban landscape.
2. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step A. further comprises the following steps:
a.1, performing data processing on actually measured data in a plant carbon fixation amount test document by adopting a method of statistically cutting an average value, discarding 10% of maximum data and 10% of minimum data in the data, taking an average value and a standard deviation of residual data, and establishing a plant database containing leaf area indexes of different plant species and daily average unit leaf area carbon fixation amount information.
3. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step B further comprises the following steps:
b.1, collecting urban landscape plant photos, wherein the collection quantity meets the requirement that the system recognition rate reaches more than 90%;
b.2, in the process of extracting the plant image identification features, taking the shape of leaves, the shape of petals and the shape of crown of the plant as identification feature elements;
and B.3, training and testing the sample by adopting a convolution neural network model in deep learning.
4. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step C further comprises the following steps:
c.1, carrying out aerial photography on the measurement area according to a preset flight route;
and C.2, ensuring that the proportion scales of all parts of the later image are consistent and the definition of the image is ensured, setting the lens to be vertically downward, fixing the flight altitude of the unmanned aerial vehicle at 50m according to the test environment, and ensuring the ground resolution of the image to be 2cm and the course overlapping degree to be 80%.
5. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step D further comprises the following steps:
d.1, preparing the landscape plant into a closed multi-section line by using CAD;
d.2, setting the identified plant types on different layers by using a plant image identification system;
and D.3, introducing different plant types into the ArcGIS according to the surface element (Polygon) respectively, and establishing a GIS model of the urban landscape plant species distribution.
6. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step E. further comprises the following steps:
e.1, calculating the green quantity of each surface element including arbors, shrubs and herbaceous plants;
e.2, assigning the green quantity to table attributes of different surface element layers, and combining the surface element layers through a combination tool (Merge) to obtain a landscape total green quantity value;
and E.3, converting each surface element layer into grids according to the green quantity of the unit area by using a surface element grid-to-grid tool (Polygon to grid), and adding each grid layer by using a grid Calculator (grid Calculator) to obtain the landscape green quantity distribution GIS model.
7. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 1, wherein the step F further comprises the following steps:
f.1, calculating the daily average carbon fixation amount of inner plants of each surface element including arbors, shrubs and herbaceous plants by utilizing the urban landscape plant database and the calculated plant green amount;
f.2, assigning the daily average solid carbon quantity value to the surface element table attributes on different layers, and combining all the surface element layers through a combination tool (Merge) to obtain a landscape total daily average solid carbon quantity value;
and F.3, converting the daily average solid carbon amount of each surface element layer into grids according to unit area by using a surface element grid-transferring tool (Polygon to grid), and adding the grids of the layers by using a grid Calculator (a grid Calculator) to obtain the GIS model of the landscape daily average solid carbon amount distribution condition.
8. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to claim 6, wherein in the step E1, the green amount of the arbor can be calculated according to an arbor category crown diameter-crown height equation and a crown shape-green amount equation;
the crown diameter and crown height formula of the arbor can be calculated by the formula (I):
y＝1/(a+be-cx) (I)
in the formula: x is the diameter of the arbor, m; y is the crown height of the arbor, m; a, b, and c are coefficients determined by the type of arbor, for example: weeping willow a is 0.832, b is 0.042, and c is 0.758;
the green amount of the arbor can be calculated according to the shape, the diameter and the height of the crown of the tree of the variety:
LAtree＝f(x，y) (II)
In the formula: LAtreeGreen amount of this kind of arbor, m2(ii) a x is the diameter of the arbor, m; y is the crown height of the arbor, m;
the green amount of shrubs and herbs can be calculated by formula (III) and formula (IV):
LAshurb＝LAIshurbSshurb (III)
LAgrass＝LAIgrassSgrass (IV)
in the formula: LAshurbGreen amount of this species of shrub, m2；LAgrassThe green amount of the grass of this kind, m2；LAIshurbThe leaf area index of the species of shrub; LAIgrassThe leaf area index of the species of shrub; sshurbM is the area covered by the species of shrub2；SgrassM is the area covered by the grass2。
9. The method for rapidly measuring and calculating the carbon fixation amount of the urban landscape according to the claim 7, wherein in the step F1, the carbon fixation amount value and the green fixation amount value in the map layer are multiplied according to the formula V, so that the carbon fixation amount of the urban landscape can be obtained, and the distribution and the size condition of the carbon fixation amount of the urban landscape are displayed in a map;
WCO2＝wCO２，i×LAi (V)
in the formula: wCO2The daily average carbon fixation amount of the urban landscape is g/d; w is aCO2，iThe carbon fixation amount per daily average leaf area of the plant type i, g/m2·d；LAiGreen amount of plant species i, m2。
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