Carbon sink plotting method

Abstract

The invention provides a carbon sequestration graph method. The method comprises the following steps: S1, collecting data; s2, carrying out gridding processing; s3, performing graph falling; and S4, performing graph dynamic processing. By means of the carbon sink falling graph method, dynamic monitoring can be conducted on carbon sinks, and visualization of carbon sink space distribution is achieved.

Description

Technical Field

[0001] The present invention relates to the field of ecological environment, and in particular to a carbon sink mapping method. Background Art

[0002] Carbon sinks are things in the environment that can absorb carbon dioxide from the atmosphere, such as vegetation, terrestrial soil, terrestrial rocks, etc., but there is currently a lack of methods to dynamically monitor carbon sinks and visualize their spatial distribution. Summary of the invention

[0003] In view of this, the present invention provides a carbon sink mapping method to dynamically monitor the carbon sink and realize the visualization of the spatial distribution of the carbon sink.

[0004] The above-mentioned carbon sink mapping method includes the following steps: S1, collecting data; S2, grid processing; S3, mapping; S4, making the graph dynamic.

[0005] Furthermore, a graph is generated for each of the data collected at different historical time points, and the graph generated at each time point is displayed with the time point as the horizontal axis, thereby making the graph dynamic.

[0006] Furthermore, data is collected at different time points in the future, and a graph is generated for the data collected at each time point in the future and displayed in a graphical interface, thereby realizing dynamic graphics.

[0007] Furthermore, the intervals between different time points may be 1 day, half a month, or 1 month.

[0008] Furthermore, the length of each grid unit can be set to 10m, 100m, 500m, or 1000m.

[0009] Furthermore, in the graph, the carbon dioxide absorption capacity of the carbon sinks of different grid units is displayed by using various colors, columns, or circles of different shades.

[0010] Furthermore, in step S1, data preprocessing technology is used to remove abnormal and noisy data.

[0011] Furthermore, after step S4, carbon sink data is also predicted by predicting carbon reserves.

[0012] Furthermore, the carbon storage is predicted by the following formula: Among them, C t is the carbon storage at time t, C t-1 is the carbon storage at time t-1, r is the intrinsic growth rate, K is the maximum possible value of carbon storage in the environment, and h is the carbon loss rate.

[0013] Furthermore, the carbon storage is predicted by the following methods: S1. Learning the relationship between historical carbon storage and environmental factors; S2. Predicting future environmental factors in each grid; S3. According to the formula Predicted carbon storage, where C^ is the predicted carbon storage, T, P, and L are predicted future environmental factors, representing temperature, precipitation, and soil properties, respectively.

[0014] The carbon sink mapping method of the present invention can be used to dynamically monitor the carbon sink and realize the visualization of the spatial distribution of the carbon sink. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a carbon sink mapping method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0017] like Figure 1 As shown, a carbon sink mapping method according to an embodiment of the present invention comprises the following steps:

[0018] S1. Collect data;

[0019] S2, grid processing;

[0020] S3, drop map;

[0021] S4. Graphics dynamics.

[0022] Through the above carbon sink mapping method, the carbon sink can be dynamically monitored and the spatial distribution of carbon sink can be visualized.

[0023] There are two ways to make graphics dynamic.

[0024] One method is to generate a graph for each data collected at different time points in history, and display the graph generated at each time point with the time point as the horizontal axis, so as to realize the dynamic graph. This method can obtain carbon sink graphs at different time points in history, and can have an intuitive understanding of the spatial distribution of carbon sinks at different time points in history.

[0025] The other method is to collect data at different time points in the future, generate a graph for each data point in the future and display it in a graphical interface, so as to realize the dynamic graph. This method can obtain carbon sink graphs at different time points in the future, and can dynamically display the spatial distribution of carbon sinks at different time points in the future.

[0026] The intervals between different time points are not limited, and are based on the frequency of data collection, which can be 1 day, half a month, or 1 month, etc.

[0027] Grid processing is to divide the collected data into grids according to geographical location, and one grid represents a carbon sink unit. The length of the grid unit should not be set too large, otherwise the spatial distribution of carbon sinks cannot be displayed in detail; the length of the grid unit should not be set too small, otherwise the carbon sink data will be divided too densely and inconvenient to read. The length of the grid unit also needs to be determined according to the total area of ​​the collected carbon sink data, which can be 10m, 100m, 500m, or 1000m, etc.

[0028] The grids divided according to geographical locations need to be scaled down proportionally when mapping and then displayed in the form of graphics.

[0029] Different carbon sink units contain different numbers and types of plants, so different carbon sink units have different carbon dioxide absorption capacities and need to be displayed separately. There are three ways to do this.

[0030] The first is to use the type and depth of color to distinguish and display. For example, red represents the carbon dioxide absorption capacity of the carbon sink unit in the first interval, green represents the carbon dioxide absorption capacity of the carbon sink unit in the second interval, and blue represents the carbon dioxide absorption capacity of the carbon sink unit in the third interval. The darker the color, the stronger the carbon dioxide absorption capacity of the carbon sink unit. In this way, the carbon dioxide absorption capacity of the carbon sinks in different grid units can be distinguished and displayed.

[0031] The second method is to display the carbon dioxide absorption capacity of carbon sinks in different grid units in the form of columns. That is, a column is displayed above each grid unit, and the height of the column represents the carbon dioxide absorption capacity of the carbon sink unit. The higher the height of the column, the stronger the carbon dioxide absorption capacity of the carbon sink unit; the lower the height of the column, the lower the carbon dioxide absorption capacity of the carbon sink unit.

[0032] The third method is to display the carbon dioxide absorption capacity of carbon sinks in different grid units in the form of circles. That is, a circle is displayed in each grid unit, and the diameter of the circle represents the carbon dioxide absorption capacity of the carbon sink unit. The larger the diameter of the circle, the stronger the carbon dioxide absorption capacity of the carbon sink unit; the smaller the diameter of the circle, the lower the carbon dioxide absorption capacity of the carbon sink unit.

[0033] There is no limit to the way to collect data. Currently, remote sensing technology can be used, that is, using artificial satellites, airplanes or other aircraft to sense electromagnetic waves, visible light, infrared rays, etc. reflected or radiated by the target from a long distance, so as to detect, identify the target and collect target data. The target data can be a video or a TIF format image file.

[0034] In step S1, data preprocessing technology is used to remove abnormal and noisy data, so that an accurate carbon sink graph can be obtained.

[0035] The gridded data can also be used for spatial analysis, for example, carbon sink hotspots can be analyzed for reference by relevant personnel.

[0036] After step S4, the carbon sink data can be predicted to understand the future change trend of the carbon sink. Relevant personnel can generate a carbon sink change trend chart based on the predicted carbon sink data to intuitively understand the future change trend of the carbon sink.

[0037] Since carbon storage and carbon sink data are positively correlated, carbon sink data can be predicted by predicting carbon storage.

[0038] There are two methods for predicting carbon stocks.

[0039] The first is to predict using the following formula:

[0040]

[0041] Among them, C t is the carbon storage at time t, C t-1 is the carbon storage at time t-1, r is the intrinsic growth rate, K is the maximum possible value of carbon storage in the environment, and h is the carbon loss rate.

[0042] The second one includes the following steps:

[0043] S1. Learn the relationship between historical carbon storage and environmental factors;

[0044] S2, predict future environmental factors within each grid;

[0045] S3, according to the formula Predicted carbon storage, where C^ is the predicted carbon storage, T, P, and L are predicted future environmental factors, representing temperature, precipitation, and soil properties (organic matter, minerals, pH, microbial content, etc.), respectively.

[0046] C in the first method t-1 Both the carbon storage in the first method and the historical carbon storage in the second method can be measured by ground monitoring equipment.

[0047] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0048] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A carbon sink mapping method, characterized in that: The steps include: S1. Collect data; S2, grid processing; S3, drop map; S4. Graphics dynamics.

2. The carbon sink mapping method according to claim 1, characterized in that: A graph is generated for each data collected at different time points in history, and the graph generated at each time point is displayed with the time point as the horizontal axis, thereby making the graph dynamic.

3. The carbon sink mapping method according to claim 1, characterized in that: Data is collected at different time points in the future, and a graph is generated for the data collected at each time point in the future and displayed in a graphical interface, thereby realizing dynamic graphics.

4. The carbon sink mapping method according to claim 2 or 3, characterized in that: The intervals between different time points can be 1 day, half a month, or 1 month.

5. The carbon sink mapping method according to claim 1, characterized in that: The length of each grid unit can be set to 10m, 100m, 500m, or 1000m.

6. The carbon sink mapping method according to claim 1, characterized in that: In the graph, the carbon dioxide absorption capacity of carbon sinks in different grid units is displayed using various colors, columns, or circles of different shades.

7. The carbon sink mapping method according to claim 1, characterized in that: In step S1, data preprocessing technology is used to remove abnormal and noisy data.

8. The carbon sink mapping method according to claim 1, characterized in that: After step S4, carbon sink data is also predicted by predicting carbon reserves.

9. The carbon sink mapping method according to claim 8, characterized in that: Carbon storage is predicted by the following formula: Among them, C t is the carbon storage at time t, C t-1 is the carbon storage at time t-1, r is the intrinsic growth rate, K is the maximum possible value of carbon storage in the environment, and h is the carbon loss rate.

10. The carbon sink mapping method according to claim 8, characterized in that: Carbon stocks are estimated by: S1. Learn the relationship between historical carbon storage and environmental factors; S2, predict future environmental factors within each grid; S3, according to the formula Predicted carbon storage, where C^ is the predicted carbon storage, T, P, and L are predicted future environmental factors, representing temperature, precipitation, and soil properties, respectively.

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