Soil carbon sink visual management system and method

Abstract

The invention relates to the technical field of soil carbon sink management, in particular to a soil carbon sink visual management system and method. The method comprises the following steps: determining a target soil area, collecting historical carbon sink data and vegetation distribution data of the target soil area, and receiving a preset monitoring window uploaded by a user side; dividing the target soil area according to the vegetation distribution data, determining a plurality of soil sub-areas, and obtaining a plurality of carbon sink conversion rates of the plurality of soil sub-areas in combination with the historical carbon sink data and the window duration of a preset monitoring window; based on the plurality of carbon sink conversion rates, predicting expected carbon sink values of the plurality of soil sub-regions after the preset monitoring window is ended, and generating a carbon sink visual distribution diagram of the target soil region; and performing carbon sink management on the target soil area according to the carbon sink visual distribution diagram. By implementing the method, the precision, visualization and prospect of soil carbon sink management can be realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of soil carbon sink management, and particularly relates to a soil carbon sink visual management system and method. BACKGROUND

[0002] Traditional soil carbon sink management relies on manual random sampling detection and experience decision-making, and data is presented in tables and texts, lacking visual display and prediction of future carbon sink trends. There are problems such as one-sided data collection and analysis, extensive regional management, difficulty in grasping the dynamic of carbon sink in time, low data interpretation and decision-making efficiency, and poor management effect. SUMMARY

[0003] The present application provides a soil carbon sink visual management system and method to solve the problems of one-sided data collection and analysis, extensive regional management, difficulty in grasping the dynamic of carbon sink in time, and low data interpretation and decision-making efficiency in the prior art.

[0004] The technical solution of the present application to solve the above technical problems is as follows:

[0005] In a first aspect, the present application provides a soil carbon sink visual management system, comprising: a basic data collection module for determining a target soil region, collecting historical carbon sink data and vegetation distribution data of the target soil region, and receiving a preset monitoring window uploaded by a user end;

[0006] A carbon sink conversion rate calculation module is configured to divide the target soil region according to the vegetation distribution data, determine a plurality of soil sub-regions, and obtain a plurality of carbon sink conversion rates of the plurality of soil sub-regions in combination with the historical carbon sink data and the window length of the preset monitoring window.

[0007] An expected carbon sink value prediction module is configured to predict expected carbon sink values of the plurality of soil sub-regions after the end of the preset monitoring window based on the plurality of carbon sink conversion rates, and generate a carbon sink visual distribution map of the target soil region.

[0008] A carbon sink management module is configured to manage the carbon sink of the target soil region according to the carbon sink visual distribution map.

[0009] Optionally, in the carbon sink conversion rate calculation module, the target soil region is divided into a plurality of soil sub-regions according to the vegetation distribution data, including: obtaining a target collection grid of the target soil region according to the vegetation distribution data, dividing the target soil region into a plurality of soil collection grids based on the target collection grid; setting a soil property collection dimension, collecting soil properties in the plurality of soil collection grids based on the soil property collection dimension, and obtaining a plurality of grid soil properties; clustering analysis is performed on the plurality of grid soil properties, and the target soil region is divided into a plurality of soil sub-regions according to the clustering analysis result.

[0010] In the carbon sink conversion rate calculation module, the target collection grid of the target soil region is obtained according to the vegetation distribution data, including: obtaining a basic soil grid and a basic vegetation variability; dividing the vegetation distribution data into a plurality of grid vegetation distributions according to the basic soil grid; calculating the grid vegetation variability corresponding to the plurality of grid vegetation distributions to obtain a plurality of grid vegetation variability, and performing mean value calculation on the plurality of grid vegetation variability to obtain a soil vegetation variability; obtaining a grid correction factor according to the soil vegetation variability and the basic vegetation variability, correcting the basic soil grid through the grid correction factor to obtain the target collection grid.

[0011] Optionally, in the carbon sink conversion rate calculation module, the carbon sink conversion rate of the plurality of soil sub-regions is obtained by combining the historical carbon sink data and the window time length of the preset monitoring window, including: dividing the historical carbon sink data according to the plurality of soil sub-regions to obtain a plurality of sub-region carbon sink data; obtaining a plurality of carbon sink conversion rates of a plurality of soil sub-regions based on the plurality of sub-region carbon sink data and the window time length of the preset monitoring window.

[0012] The carbon sink conversion rate calculation module includes: determining a first soil sub-region from the plurality of soil sub-regions, and determining sub-region carbon sink data of the first soil sub-region from the plurality of sub-region carbon sink data to obtain first sub-region carbon sink data; obtaining a monitoring time length of the first sub-region carbon sink data, and dividing the monitoring time length into a plurality of historical monitoring windows according to a window time length of the preset monitoring window; extracting window data of the first sub-region carbon sink data based on the plurality of historical monitoring windows to obtain a plurality of window carbon sink conversion data, wherein each window carbon sink conversion data includes a carbon sink window initial value and a carbon sink window end value; for each historical monitoring window, calculating a carbon sink window conversion rate based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain a plurality of carbon sink window conversion rates; and statistically analyzing the plurality of carbon sink window conversion rates to obtain a first carbon sink conversion rate; and calculating carbon sink conversion rates of the remaining soil sub-regions in the same manner as the first soil sub-region to obtain a plurality of carbon sink conversion rates of the plurality of soil sub-regions.

[0013] The carbon sink conversion rate calculation module includes: determining a first soil sub-region from the plurality of soil sub-regions, and determining sub-region carbon sink data of the first soil sub-region from the plurality of sub-region carbon sink data to obtain first sub-region carbon sink data; obtaining a monitoring time length of the first sub-region carbon sink data, and dividing the monitoring time length into a plurality of historical monitoring windows according to a window time length of the preset monitoring window; extracting window data of the first sub-region carbon sink data based on the plurality of historical monitoring windows to obtain a plurality of window carbon sink conversion data, wherein each window carbon sink conversion data includes a carbon sink window initial value and a carbon sink window end value; for each historical monitoring window, calculating a carbon sink window conversion rate based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain a plurality of carbon sink window conversion rates; and statistically analyzing the plurality of carbon sink window conversion rates to obtain a first carbon sink conversion rate; and calculating carbon sink conversion rates of the remaining soil sub-regions in the same manner as the first soil sub-region to obtain a plurality of carbon sink conversion rates of the plurality of soil sub-regions.

[0014] The expected carbon sink value prediction module includes: obtaining a current carbon sink benchmark value of each soil sub-region; obtaining an expected carbon sink value of each soil sub-region based on the current carbon sink benchmark value of each soil sub-region and the corresponding carbon sink conversion rate; performing spatial interpolation processing on the expected carbon sink values of the plurality of soil sub-regions to generate carbon sink spatial distribution data; and performing three-dimensional visualization rendering on the carbon sink spatial distribution data to generate the carbon sink visualization distribution map of the target soil region.

[0015] In a second aspect, the present application provides a soil carbon sink visualization management method, including:

[0016] Determine a target soil area, collect historical carbon sink data and vegetation distribution data of the target soil area, and receive a preset monitoring window uploaded by a user end; divide the target soil area according to the vegetation distribution data, determine a plurality of soil sub-areas, combine the historical carbon sink data and a window length of the preset monitoring window, and obtain a plurality of carbon sink conversion rates of the plurality of soil sub-areas; based on the plurality of carbon sink conversion rates, predict expected carbon sink values of the plurality of soil sub-areas after the preset monitoring window ends, and generate a carbon sink visual distribution map of the target soil area; and perform carbon sink management on the target soil area according to the carbon sink visual distribution map.

[0017] By implementing the present application, the target soil area can be determined, the historical carbon sink data and the vegetation distribution data of the target soil area can be collected, and the preset monitoring window uploaded by the user end can be received, thereby providing multi-dimensional and all-around data support for subsequent carbon sink analysis and avoiding one-sided analysis results caused by single data;

[0018] By implementing the present application, the target soil area can be divided according to the vegetation distribution data, a plurality of soil sub-areas can be determined, the historical carbon sink data and the window length of the preset monitoring window can be combined, and a plurality of carbon sink conversion rates of the plurality of soil sub-areas can be obtained, so that the target area is divided into sub-areas with consistent characteristics, the analysis mode of “one size fits all” for the entire area is avoided, and the subsequent carbon sink management can be accurately adapted to the characteristics of each sub-area;

[0019] By implementing the present application, based on the plurality of carbon sink conversion rates, the expected carbon sink values of the plurality of soil sub-areas after the preset monitoring window ends can be predicted, and the carbon sink visual distribution map of the target soil area can be generated, so that the abstract carbon sink data is converted into intuitive images, the manager can quickly master the differences in carbon sink potential of different areas, and the difficulty of data interpretation is reduced;

[0020] By implementing the present application, the carbon sink management can be performed on the target soil area according to the carbon sink visual distribution map, the differentiated management strategies can be developed based on the area differences reflected by the visual distribution map, blind management is avoided, the management measures can accurately act on the carbon sink weak areas or potential areas, and the management effect is improved.

[0021] In summary, by implementing the present application, the precision, visualization and forward-looking of soil carbon sink management can be realized, the manager can comprehensively master the carbon sink status, develop efficient management strategies, improve the scientificity and effectiveness of carbon sink management, and promote the optimization of soil carbon sink resources and the improvement of carbon sink capacity. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1A structural schematic diagram of a soil carbon sink visual management system provided by the present application is provided.

[0023] Figure 2 A flowchart of a soil carbon sink visual management method provided by the present application is provided.

[0024] In the drawings, the components represented by each reference numeral are as follows:

[0025] The basic data acquisition module 11, the carbon sink conversion rate calculation module 12, the expected carbon sink value prediction module 13, and the carbon sink management module 14. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0027] In the description of the present application, the terms "first" and "second" are used only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" can explicitly or implicitly include one or more features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0028] In the description of the present application, the term "for example" is used to indicate "as an example, illustration or explanation". Any embodiment described as "for example" in the present application is not necessarily interpreted as more preferred or more advantageous than other embodiments. The following description is given in order to enable any person skilled in the art to implement and use the present application. In the following description, details are listed for the purpose of explanation. It should be understood that those skilled in the art can realize the present application without using these specific details. In other examples, well-known structures and processes will not be described in detail in order to avoid unnecessary details making the description of the present application obscure. Therefore, the present application is not intended to be limited to the shown embodiments, but is consistent with the broadest scope in accordance with the principles and characteristics disclosed.

[0029] Embodiment one, as shown in the present application, provides a soil carbon sink visual management system, comprising: Figure 1

[0030] The basic data acquisition module 11 is used to determine a target soil area, acquire historical carbon sink data and vegetation distribution data of the target soil area, and receive a preset monitoring window uploaded by a user end.​

[0031] a carbon sink conversion rate calculation module 12 configured to divide the target soil region according to the vegetation distribution data, determine a plurality of soil sub-regions, and obtain a plurality of carbon sink conversion rates of the plurality of soil sub-regions in combination with the historical carbon sink data and a window length of the preset monitoring window;

[0032] a predicted carbon sink value prediction module 13 configured to predict predicted carbon sink values of the plurality of soil sub-regions after the end of the preset monitoring window based on the plurality of carbon sink conversion rates, and generate a carbon sink visualization distribution map of the target soil region;

[0033] a carbon sink management module 14 configured to perform carbon sink management on the target soil region according to the carbon sink visualization distribution map.

[0034] In the soil carbon sink visualization management system provided in the embodiments of the present application, the basic data acquisition module 11 needs to be started first to determine a target soil region, collect historical carbon sink data and vegetation distribution data of the target soil region, and receive a preset monitoring window uploaded by a user end.

[0035] The core function of the basic data acquisition module 11 is to provide accurate, comprehensive and user-demand-compliant data basis for the entire soil carbon sink management process.

[0036] Firstly, the target soil region needs to be determined, which can be manually delimited by a user through map interaction, and then combined with geographic information system (GIS) technology to interface with a basic geographic database, automatically check the accuracy of the region boundary, and convert the region information into a spatial data format recognizable by the system to provide a spatial reference for subsequent region division.

[0037] Then, the historical carbon sink data and vegetation distribution data of the target soil region need to be collected, which can specifically integrate multiple data sources, such as collecting soil carbon content monitoring data of historical monitoring sites and carbon flux data inversed by remote sensing satellites as historical carbon sink data, and collecting vegetation type maps, vegetation coverage data and vegetation growth condition records obtained through field investigation as vegetation distribution data.

[0038] Finally, the preset monitoring window uploaded by the user end needs to be received, that is, a user interaction interface such as a date selector is provided to allow the user to input or select the start time and end time of the monitoring window to clearly define the monitoring window length.

[0039] In the carbon sink conversion rate calculation module 12 of the embodiments of the present application, the target soil region is divided according to the vegetation distribution data to determine a plurality of soil sub-regions, which includes:

[0040] According to the vegetation distribution data, a target collection grid of the target soil region is acquired, the target soil region is divided into a plurality of soil collection grids based on the target collection grid;

[0041] A soil property collection dimension is set, soil property collection is performed on the plurality of soil collection grids based on the soil property collection dimension, and a plurality of grid soil properties are obtained;

[0042] The plurality of grid soil properties are subjected to cluster analysis, and the target soil region is divided into a plurality of soil sub-regions according to the cluster analysis result.

[0043] In the embodiment of the application, the role of the carbon sink conversion rate calculation module 12 is to divide the complex target soil region into soil sub-regions with similar characteristics through a scientific regional division method, thereby laying a foundation for subsequent accurate calculation of the carbon sink conversion rate of each region. To achieve the above effect, first, the target collection grid of the target soil region is acquired according to the vegetation distribution data.

[0044] In the carbon sink conversion rate calculation module 12 of the embodiment of the application, the target collection grid of the target soil region is acquired according to the vegetation distribution data, comprising:

[0045] The basic soil grid and the basic vegetation variability are acquired;

[0046] The vegetation distribution data is regionally divided according to the basic soil grid, and a plurality of grid vegetation distributions are obtained;

[0047] The grid vegetation variability corresponding to the plurality of grid vegetation distributions is calculated, a plurality of grid vegetation variabilities are obtained, and the plurality of grid vegetation variabilities are subjected to mean value calculation to obtain a soil vegetation variability;

[0048] A grid correction factor is obtained according to the soil vegetation variability and the basic vegetation variability, the basic soil grid is corrected through the grid correction factor, and the target collection grid is obtained.

[0049] In the embodiment of the application, the target collection grid of the target soil region is acquired according to the vegetation distribution data, in order to determine the collection grid scale suitable for the target soil region through a scientific method, to ensure that the grid can accurately reflect the vegetation distribution characteristics and also consider the data collection efficiency, thereby providing a reasonable spatial unit basis for subsequent regional division and carbon sink analysis.

[0050] Firstly, the basic soil grid and the basic vegetation variability need to be obtained. The basic soil grid can be called from the grid library preset by the system, such as an initial grid of 100 m x 100 m, or an initial grid generated based on the area, terrain complexity and other characteristics of the target area, serving as a benchmark for grid correction. The basic vegetation variability can be set according to the overall characteristics of the vegetation type in the region, setting a benchmark value reflecting the normal spatial variability level of this type of vegetation, which can be determined based on historical data or industry standards.

[0051] Next, the vegetation distribution data of the target soil region, including vegetation type, coverage, growth condition, etc., need to be segmented into multiple grid cells according to the boundaries of the basic soil grid, obtaining grid vegetation distribution data corresponding to each grid.

[0052] Then, the grid vegetation variability is calculated for the grid vegetation distribution data in each grid, obtaining grid vegetation variability corresponding to multiple grids, which reflects the dispersion degree of vegetation characteristics in the grid.

[0053] Specifically, within a single grid, a number of sampling points are uniformly set, such as 9 sampling points in a 10 m x 10 m grid, distributed at the corners, center and midpoints of the sides of the grid. The vegetation coverage of each sampling point is collected, with a value range of 0% to 100%, such as 80% for a sampling point.

[0054] First, the average value (μ) of the vegetation coverage of all sampling points in the grid is calculated, reflecting the overall level of the grid vegetation coverage. Then, the standard deviation (σ) of the vegetation coverage is calculated, reflecting the deviation degree of each sampling point from the average value. Finally, the grid vegetation variability is represented by the coefficient of variation (CV), i.e. grid vegetation variability (CV) = (σ / μ) x 100%.

[0055] The average value of all grid vegetation variability is calculated as the soil vegetation variability reflecting the spatial variability level of the vegetation in the entire target region.

[0056] Further, the grid correction factor is obtained based on the soil vegetation variability and the basic vegetation variability, and the basic soil grid is corrected by the grid correction factor to obtain the target collection grid.

[0057] The method for calculating the grid correction factor is to compare the soil vegetation variability with the basic vegetation variability, such as grid correction factor = soil vegetation variability / basic vegetation variability. If the correction factor is greater than 1, it means that the actual vegetation variability is greater than the benchmark level, and the grid needs to be reduced. If it is less than 1, the grid can be appropriately enlarged. Then, the size of the basic soil grid is adjusted according to the grid correction factor, such as reducing the grid length to 1 / 1.5 of the original length when the correction factor is 1.5, generating a target collection grid, such as a target collection grid with a size of 10 m x 10 m.

[0058] Through the above execution steps in the carbon sink conversion rate calculation module 12, the target acquisition grid can dynamically adapt to the vegetation distribution characteristics of the target soil region, both ensuring the relative consistency of vegetation information within each grid and avoiding analysis errors caused by unreasonable grid size, providing a scientific spatial foundation for subsequent soil characteristic acquisition and regional division.

[0059] Further, it is necessary to divide the target soil region into multiple soil acquisition grids based on the target acquisition grid. That is, according to the size of the determined target acquisition grid, such as 10m x 10m, the target soil region is regularly cut according to the target acquisition grid using GIS spatial analysis tools to generate multiple continuous and non-overlapping soil acquisition grids, and the vegetation distribution data is associated with each soil acquisition grid to form a preliminary spatial unit.

[0060] Further, it is necessary to set a soil characteristic acquisition dimension, and based on the soil characteristic acquisition dimension, soil characteristics are acquired in the multiple soil acquisition grids to obtain multiple grid soil characteristics.

[0061] The soil characteristic acquisition dimension needs to include physical characteristics, chemical characteristics, biological characteristics, and other aspects of soil closely related to carbon sink processes. The physical characteristics are, for example, soil texture, bulk density, etc.; the chemical characteristics are, for example, organic carbon content, pH value, etc.; and the biological characteristics are, for example, microbial activity, etc. For all soil acquisition grids, remote sensing technology can be used to obtain large-scale soil characteristics; for key soil acquisition grids, field sampling and detection are performed to verify and correct the remote sensing data; and finally, multi-dimensional characteristic data of each soil acquisition grid, i.e., the multiple grid soil characteristics, are obtained.

[0062] Further, it is necessary to perform cluster analysis on the multiple grid soil characteristics, and according to the cluster analysis results, the target soil region is divided into multiple soil sub-regions.

[0063] First, the multi-dimensional characteristic data of each soil acquisition grid is standardized and normalized to the same dimension;

[0064] Then, K-means, hierarchical clustering, and other algorithms are used for cluster analysis, and grids with similar soil characteristics and vegetation characteristics are classified into the same category;

[0065] According to the cluster results, grids that are spatially adjacent and belong to the same category are merged to form multiple continuous soil sub-regions, and each soil sub-region is given a characteristic label, such as "high organic matter-broadleaf forest coverage area", etc., completing the fine division of the target soil region.

[0066] In the carbon sink conversion rate calculation module 12, the historical carbon sink data and the window length of the preset monitoring window are combined to obtain carbon sink conversion rates of the plurality of soil sub-regions, including:

[0067] The historical carbon sink data is divided according to the plurality of soil sub-regions to obtain sub-region carbon sink data;

[0068] The plurality of carbon sink conversion rates of the plurality of soil sub-regions are obtained based on the plurality of sub-region carbon sink data and the window length of the preset monitoring window.

[0069] In the carbon sink conversion rate calculation module 12, the plurality of carbon sink conversion rates of the plurality of soil sub-regions are obtained based on the plurality of sub-region carbon sink data and the window length of the preset monitoring window, including:

[0070] A first soil sub-region is determined from the plurality of soil sub-regions, and sub-region carbon sink data of the first soil sub-region is determined from the plurality of sub-region carbon sink data to obtain first sub-region carbon sink data;

[0071] A monitoring time length of the first sub-region carbon sink data is obtained, and the monitoring time length is window-divided according to the window length of the preset monitoring window to obtain a plurality of historical monitoring windows;

[0072] Window data of the first sub-region carbon sink data is extracted based on the plurality of historical monitoring windows to obtain a plurality of window carbon sink conversion data, and each window carbon sink conversion data includes a carbon sink window initial value and a carbon sink window end value;

[0073] For each historical monitoring window, a carbon sink window conversion rate is calculated based on the corresponding carbon sink window initial value and carbon sink window end value, and a plurality of carbon sink window conversion rates are obtained;

[0074] The plurality of carbon sink window conversion rates are statistically analyzed to obtain a first carbon sink conversion rate;

[0075] The carbon sink conversion rates of the remaining soil sub-regions are calculated in the same way as the first carbon sink conversion rate of the first soil sub-region is obtained, and a plurality of carbon sink conversion rates of a plurality of soil sub-regions are obtained.

[0076] In the embodiment, the above execution steps in the carbon sink conversion rate calculation module 12 are to calculate the carbon sink conversion rate of each soil sub-region by combining the historical carbon sink data with the preset monitoring window.

[0077] To achieve the above effects, first, the historical carbon sink data needs to be divided according to the plurality of soil sub-regions, obtaining a plurality of soil sub-region carbon sink data. That is, based on the spatial boundaries of the plurality of soil sub-regions determined, the historical carbon sink data of the target soil region, such as soil carbon storage, carbon flux data at different time points, etc., is distributed to each soil sub-region according to the spatial position, forming the soil sub-region carbon sink data corresponding to each soil sub-region. The soil sub-region carbon sink data contains time series information, such as carbon sink values for each year from 2010 to 2020.

[0078] In addition, the divided soil sub-region carbon sink data also needs to be verified to ensure that the carbon sink data of each sub-region is continuous and complete in the time dimension. If there are missing values, interpolation method or adjacent sub-region same period data reference method can be used for supplement.

[0079] Then, a first soil sub-region needs to be determined from the plurality of soil sub-regions, and the sub-region carbon sink data of the first soil sub-region is determined in the plurality of sub-region carbon sink data, obtaining the first sub-region carbon sink data. That is, any one of the plurality of soil sub-regions is selected as the first soil sub-region, and the corresponding first sub-region carbon sink data is extracted, such as the annual carbon sink value sequence from 2010 to 2020.

[0080] Then, the monitoring duration of the first sub-region carbon sink data needs to be obtained, and the monitoring duration is windowed according to the window duration of the preset monitoring window, obtaining a plurality of historical monitoring windows. That is, the monitoring duration of the first sub-region carbon sink data is divided into sliding windows according to the window duration of the preset monitoring window, such as the user-set window duration of 3 years. For example, when the monitoring duration is 10 years, 8 historical monitoring windows can be divided, such as 2010-2013, 2011-2014, …, 2017-2020, and the windows can overlap, and the overlap degree can be set according to the data volume.

[0081] Then, based on the plurality of historical monitoring windows, the first sub-region carbon sink data needs to be windowed data extraction, obtaining a plurality of window carbon sink conversion data, each window carbon sink conversion data including a carbon sink window initial value and a carbon sink window end value. That is, for each historical monitoring window, the carbon sink value at the start time of the window is extracted as the carbon sink window initial value, such as the carbon sink value in 2010 for the 2010-2013 window, and the carbon sink value at the end time of the window is extracted as the carbon sink window end value, such as the carbon sink value in 2013 in the above example, forming a plurality of window carbon sink conversion data.

[0082] Further, for each of the historical monitoring windows, the carbon sink window conversion rate needs to be calculated based on the corresponding carbon sink window initial value and carbon sink window end value, obtaining a plurality of carbon sink window conversion rates.

[0083] In the carbon sink conversion rate calculation module 12 of the embodiment of the present application, for each of the historical monitoring windows, the carbon sink window conversion rate is calculated based on the corresponding carbon sink window initial value and carbon sink window end value, and a plurality of carbon sink window conversion rates are obtained, including:

[0084] The plurality of historical monitoring windows are traversed to determine a target historical monitoring window, and the target carbon sink window initial value and the target carbon sink window end value of the target historical monitoring window are extracted;

[0085] The difference between the target carbon sink window initial value and the target carbon sink window end value is calculated to obtain a target window carbon sink increment;

[0086] The target carbon sink window conversion rate is calculated based on the target window carbon sink increment and the target carbon sink window initial value;

[0087] The calculation is repeated until the traversal is completed to obtain a plurality of carbon sink window conversion rates.

[0088] Firstly, the starting time point carbon sink value and the ending time point carbon sink value corresponding to the target window are extracted from the first sub-region carbon sink data as the target carbon sink window initial value and the target carbon sink window end value.

[0089] Then, the difference between the target carbon sink window initial value and the target carbon sink window end value is calculated to obtain a target window carbon sink increment, and the calculation method is: target window carbon sink increment = target carbon sink window end value - target carbon sink window initial value.

[0090] Next, the target carbon sink window conversion rate is calculated based on the target window carbon sink increment and the target carbon sink window initial value.

[0091] The calculation method of the carbon sink window conversion rate is: target carbon sink window conversion rate = (target carbon sink window end value - target carbon sink window initial value) / (target window duration x target carbon sink window initial value). For example, the carbon sink window initial value of a 3-year window is 50 tons of carbon per hectare, and the carbon sink window end value is 65 tons of carbon per hectare, and the window conversion rate is: (65-50) / (3 x 50) x 100% = 10% per year.

[0092] Next, a plurality of carbon sink window conversion rates of a plurality of carbon sink windows are calculated according to the above method.

[0093] The plurality of carbon sink window conversion rates are statistically analyzed to obtain a first carbon sink conversion rate. That is, the plurality of carbon sink window conversion rates calculated, such as the conversion rates of the aforementioned 8 windows, are statistically analyzed, and the average value, the median value or the weighted average value can be taken. If the weighted average value is taken, different weights can be given according to the distance of the carbon sink window from the current time, and the weight of the recent window is higher. Finally, the weighted value is taken as the first carbon sink conversion rate of the first soil sub-region.

[0094] Finally, the carbon sink conversion rates of the remaining soil sub-regions are calculated in the manner of obtaining the first carbon sink conversion rate of the first soil sub-region, to obtain multiple carbon sink conversion rates of multiple soil sub-regions.

[0095] In the expected carbon sink value prediction module 13 of the embodiments of the present application, based on the multiple carbon sink conversion rates, the expected carbon sink values of the multiple soil sub-regions after the end of the preset monitoring window are predicted, and a carbon sink visualization distribution map of the target soil region is generated, including:

[0096] obtaining the current carbon sink benchmark value of each soil sub-region;

[0097] obtaining the expected carbon sink value of each soil sub-region based on the current carbon sink benchmark value and the corresponding carbon sink conversion rate of each soil sub-region;

[0098] performing spatial interpolation processing based on the expected carbon sink values of the multiple soil sub-regions to generate carbon sink spatial distribution data;

[0099] performing three-dimensional visualization rendering on the carbon sink spatial distribution data to generate the carbon sink visualization distribution map of the target soil region.

[0100] In the embodiments of the present application, the purpose of the above execution steps in the expected carbon sink value prediction module 13 is to realize the prediction of future carbon sink values by combining carbon sink conversion rates with current carbon sink data and convert them into intuitive spatial distribution maps.

[0101] First, the current carbon sink benchmark value of each soil sub-region needs to be obtained. That is, the carbon sink data of each soil sub-region at the current time point is collected as the benchmark value for prediction. The data sources can include the latest field monitoring data and high-resolution remote sensing inversion data.

[0102] Then, the expected carbon sink value of each soil sub-region is obtained based on the current carbon sink benchmark value and the corresponding carbon sink conversion rate of each soil sub-region. That is, for each soil sub-region, the expected carbon sink value is calculated using a prediction formula, which is: expected carbon sink value = current carbon sink benchmark value x (1 + carbon sink conversion rate x window duration).

[0103] For example, the current carbon sink benchmark value of a certain soil sub-region is 50 tons of carbon per hectare, the carbon sink conversion rate is 10% per year, and the preset monitoring window duration is 3 years. Then the expected carbon sink value = 50 x (1 + 10% x 3) = 65 tons of carbon per hectare, which can intuitively reflect the carbon sink size at the end of the window.

[0104] Then, based on the expected carbon sink values of the plurality of soil sub-regions, spatial interpolation processing is performed to generate carbon sink spatial distribution data. That is, based on the spatial coordinates of each soil sub-region and the corresponding expected carbon sink values as basic data, spatial interpolation algorithms such as Kriging interpolation and inverse distance weighted interpolation are used for spatial interpolation processing. During the interpolation process, auxiliary information such as the terrain and vegetation distribution of the target soil region needs to be combined to optimize the interpolation model, so that the generated continuous carbon sink spatial distribution data can smoothly transition and also retain the characteristics of key regions, and finally form rasterized carbon sink spatial distribution data covering the entire target soil region. The carbon sink spatial distribution data can be presented as 1m x 1m resolution raster data.

[0105] Finally, the carbon sink spatial distribution data needs to be rendered for three-dimensional visualization to generate a carbon sink visualization distribution map of the target soil region.

[0106] Specifically, based on the carbon sink spatial distribution data, a three-dimensional visualization engine is used for rendering processing. A color mapping scheme can be used to convert the raster data into a two-dimensional heat map, such as blue, green, and red representing low to high carbon sink values in sequence; three-dimensional surface rendering is achieved by superimposing the elevation data of the target soil region, so that the high and low carbon sink values are intuitively presented through the terrain, and sunlight effects, shadow effects, etc. can be added to enhance the visual performance.

[0107] Finally, an interactive carbon sink visualization distribution map of the target soil region is generated, and users can view the expected carbon sink values at different locations by zooming, panning, clicking, and querying.

[0108] In the embodiments of the present application, the carbon sink management module 14 is used to manage the carbon sink of the target soil region according to the carbon sink visualization distribution map. For example, the high / low value area of the carbon sink can be identified in combination with the carbon sink visualization distribution map. Protective measures are taken for the high value area, and targeted improvement programs are developed for the low value area, etc. The system records the implementation of the measures, regularly collects carbon sink data to generate new distribution maps, compares and evaluates the effects, dynamically adjusts the strategies, and forms a management closed loop.

[0109] In summary, by implementing the soil carbon sink visualization management system provided in the embodiments of the present application, at least the following can be achieved:

[0110] 1. Precise, visual, and forward-looking management of soil carbon sink;

[0111] 2. From data collection to management, based on soil sub-regions as the basic unit, the accuracy of soil carbon sink analysis, prediction, and management can be improved;

[0112] 3. Through three-dimensional visualization, carbon sink data is converted into an easy-to-read distribution map, reducing the understanding threshold and facilitating reading and developing targeted management strategies.

[0113] Embodiment two, as Figure 2 shown, based on the same inventive concept of the soil carbon sink visualization management system provided in embodiment one, the present embodiment also provides a soil carbon sink visualization management method, comprising:

[0114] S100: determining a target soil area, collecting historical carbon sink data and vegetation distribution data of the target soil area, and receiving a preset monitoring window uploaded by a user terminal;

[0115] S200: dividing the target soil area according to the vegetation distribution data to determine a plurality of soil sub-areas, combining the historical carbon sink data and the window length of the preset monitoring window to obtain a plurality of carbon sink conversion rates of the plurality of soil sub-areas;

[0116] S300: based on the plurality of carbon sink conversion rates, predicting expected carbon sink values of the plurality of soil sub-areas after the end of the preset monitoring window, and generating a carbon sink visualization distribution map of the target soil area;

[0117] S400: carbon sink management of the target soil area according to the carbon sink visualization distribution map.

[0118] In step S200 of the embodiment, the target soil area is divided according to the vegetation distribution data to determine a plurality of soil sub-areas, comprising: obtaining a target collection grid of the target soil area according to the vegetation distribution data, dividing the target soil area into a plurality of soil collection grids based on the target collection grid, and determining a plurality of soil collection grids; setting a soil property collection dimension, collecting soil properties in the plurality of soil collection grids based on the soil property collection dimension, and obtaining a plurality of grid soil properties; clustering analysis is performed on the plurality of grid soil properties, and the target soil area is divided into a plurality of soil sub-areas according to the clustering analysis result.

[0119] In step S200 of the embodiment, the target collection grid of the target soil area is obtained according to the vegetation distribution data, comprising: obtaining a basic soil grid and a basic vegetation variation degree; dividing the vegetation distribution data into a plurality of grid vegetation distributions according to the basic soil grid; calculating the grid vegetation variation degrees corresponding to the plurality of grid vegetation distributions to obtain a plurality of grid vegetation variation degrees, and performing mean value calculation on the plurality of grid vegetation variation degrees to obtain a soil vegetation variation degree; obtaining a grid correction factor according to the soil vegetation variation degree and the basic vegetation variation degree, correcting the basic soil grid through the grid correction factor to obtain the target collection grid.

[0120] In step S200 of the embodiment of the present application, in the carbon sink conversion rate calculation module, the historical carbon sink data and the window length of the preset monitoring window are combined to obtain multiple carbon sink conversion rates of multiple soil sub-regions, including: dividing the historical carbon sink data according to the multiple soil sub-regions to obtain multiple sub-regional carbon sink data; and obtaining multiple carbon sink conversion rates of multiple soil sub-regions based on the multiple sub-regional carbon sink data and the window length of the preset monitoring window.

[0121] In step S200 of the embodiment of the present application, the multiple carbon sink conversion rates of multiple soil sub-regions are obtained based on the multiple sub-regional carbon sink data and the window length of the preset monitoring window, including: determining a first soil sub-region from the multiple soil sub-regions, and determining sub-regional carbon sink data of the first soil sub-region in the multiple sub-regional carbon sink data to obtain first sub-regional carbon sink data; obtaining a monitoring time length of the first sub-regional carbon sink data, window dividing the monitoring time length according to the window length of the preset monitoring window to obtain multiple historical monitoring windows; window data extracting the first sub-regional carbon sink data based on the multiple historical monitoring windows to obtain multiple window carbon sink conversion data, each window carbon sink conversion data including a carbon sink window initial value and a carbon sink window end value; for each historical monitoring window, calculating a carbon sink window conversion rate based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain multiple carbon sink window conversion rates; and statistically analyzing the multiple carbon sink window conversion rates to obtain a first carbon sink conversion rate; and calculating carbon sink conversion rates of the remaining soil sub-regions in the manner of obtaining the first carbon sink conversion rate of the first soil sub-region to obtain multiple carbon sink conversion rates of multiple soil sub-regions.

[0122] In step S200 of the embodiment of the present application, in the carbon sink conversion rate calculation module, for each historical monitoring window, a carbon sink window conversion rate is calculated based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain multiple carbon sink window conversion rates, including: traversing multiple historical monitoring windows to determine a target historical monitoring window, and extracting a target carbon sink window initial value and a target carbon sink window end value of the target historical monitoring window; calculating a difference value of the target carbon sink window initial value and the target carbon sink window end value to obtain a target window carbon sink increment; calculating a target carbon sink window conversion rate based on the target window carbon sink increment and the target carbon sink window initial value; and repeating until the traversal is completed to obtain multiple carbon sink window conversion rates.

[0123] In step S300 of the embodiment, based on the carbon sink conversion rates, expected carbon sink values of the plurality of soil sub-regions after the end of the preset monitoring window are predicted, and a carbon sink visualization distribution map of the target soil region is generated, including: obtaining a current carbon sink benchmark value of each soil sub-region; based on the current carbon sink benchmark value of each soil sub-region and the corresponding carbon sink conversion rate, an expected carbon sink value of each soil sub-region is obtained; based on the expected carbon sink values of the plurality of soil sub-regions, spatial interpolation processing is performed to generate carbon sink spatial distribution data; the carbon sink spatial distribution data is rendered in three dimensions to generate the carbon sink visualization distribution map of the target soil region.

[0124] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0125] Those skilled in the art should understand that embodiments of the present application can provide methods, systems or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowcharts and / or block diagrams. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in one or more flows and / or blocks.

[0127] These computer program instructions can also be stored in a computer-readable memory that can guide the computer or other programmable data processing devices to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in one or more flows and / or blocks.

[0128] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate computer-implemented processes, thus the instructions executed on the computer or other programmable devices provide the function for implementing the processes specified in the flowchart Figure 1 one flow or multiple flows and / or the functions specified in the flowchart Figure 1 one flow or multiple flows and / or the functions specified in the flowchart

[0129] Although the preferred embodiments of the application have been described, those skilled in the art will be able to make additional modifications and variations to these embodiments without departing from the spirit and scope of the application.

[0130] Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the spirit and scope of the present application. Accordingly, it is intended that the present application embrace all such modifications and changes as fall within the scope of the present application and its equivalents.

Claims

1. A soil carbon sink visual management system, characterized by, The system comprises: a basic data collection module for determining a target soil area, collecting historical carbon sink data and vegetation distribution data of the target soil area, and receiving a preset monitoring window uploaded by a user terminal; a carbon sink conversion rate calculation module for dividing the target soil area according to the vegetation distribution data, determining a plurality of soil sub-areas, combining the historical carbon sink data and the window length of the preset monitoring window, and obtaining a plurality of carbon sink conversion rates of the plurality of soil sub-areas; an expected carbon sink value prediction module for predicting expected carbon sink values of the plurality of soil sub-areas after the end of the preset monitoring window based on the plurality of carbon sink conversion rates, and generating a carbon sink visualization distribution map of the target soil area; a carbon sink management module for carbon sink management of the target soil area according to the carbon sink visualization distribution map.

2. The system of claim 1, wherein, In the carbon sink conversion rate calculation module, the target soil area is divided according to the vegetation distribution data to determine a plurality of soil sub-areas, comprising: obtaining a target collection grid of the target soil area according to the vegetation distribution data, and dividing the target soil area into a plurality of soil collection grids based on the target collection grid; setting a soil property collection dimension, collecting soil properties in the plurality of soil collection grids based on the soil property collection dimension, and obtaining a plurality of grid soil properties; performing cluster analysis on the plurality of grid soil properties, and dividing the target soil area into a plurality of soil sub-areas according to the cluster analysis results.

3. The system of claim 2, wherein, In the carbon sink conversion rate calculation module, the target soil area is divided according to the vegetation distribution data to obtain a target collection grid, comprising: obtaining a basic soil grid and a basic vegetation variation degree; dividing the vegetation distribution data into a plurality of grid vegetation distributions according to the basic soil grid; calculating the grid vegetation variation degrees corresponding to the plurality of grid vegetation distributions, obtaining a plurality of grid vegetation variation degrees, and performing mean value calculation on the plurality of grid vegetation variation degrees to obtain a soil vegetation variation degree; obtaining a grid correction factor according to the soil vegetation variation degree and the basic vegetation variation degree, correcting the basic soil grid through the grid correction factor, and obtaining the target collection grid.

4. The system of claim 1, wherein, In the carbon sink conversion rate calculation module, the plurality of carbon sink conversion rates of the plurality of soil sub-areas are obtained by combining the historical carbon sink data and the window length of the preset monitoring window, comprising: dividing the historical carbon sink data according to the plurality of soil sub-areas to obtain a plurality of sub-area carbon sink data; obtaining a plurality of carbon sink conversion rates of the plurality of soil sub-areas based on the plurality of sub-area carbon sink data and the window length of the preset monitoring window.

5. The system of claim 4, wherein, In the carbon sink conversion rate calculation module, the plurality of carbon sink conversion rates of the plurality of soil sub-areas are obtained based on the plurality of sub-area carbon sink data and the window length of the preset monitoring window, comprising: determining a first soil sub-area from the plurality of soil sub-areas, and determining sub-area carbon sink data of the first soil sub-area in the plurality of sub-area carbon sink data to obtain first sub-area carbon sink data; determining a first soil sub-area from the plurality of soil sub-areas, and determining sub-area carbon sink data of the first soil sub-area in the plurality of sub-area carbon sink data to obtain first sub-area carbon sink data; obtaining a monitoring time length of the first sub-region carbon sink data, performing window division on the monitoring time length according to a window time length of the preset monitoring window to obtain a plurality of historical monitoring windows; performing window data extraction on the first sub-region carbon sink data based on the plurality of historical monitoring windows to obtain a plurality of window carbon sink conversion data, each window carbon sink conversion data comprising a carbon sink window initial value and a carbon sink window end value; for each historical monitoring window, calculating a carbon sink window conversion rate based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain a plurality of carbon sink window conversion rates; statistically analyzing the plurality of carbon sink window conversion rates to obtain a first carbon sink conversion rate; calculating the carbon sink conversion rates of the remaining soil sub-regions in the same manner as obtaining the first carbon sink conversion rate of the first soil sub-region to obtain a plurality of carbon sink conversion rates of a plurality of soil sub-regions.

6. The system of claim 5, wherein, In the carbon sink conversion rate calculation module, for each historical monitoring window, a carbon sink window conversion rate is calculated based on the corresponding carbon sink window initial value and the carbon sink window end value to obtain a plurality of carbon sink window conversion rates, comprising: traversing the plurality of historical monitoring windows to determine a target historical monitoring window, and extracting a target carbon sink window initial value and a target carbon sink window end value of the target historical monitoring window; calculating the difference between the target carbon sink window initial value and the target carbon sink window end value to obtain a target window carbon sink increment; calculating a target carbon sink window conversion rate based on the target window carbon sink increment and the target carbon sink window initial value; repeating until the traversal is completed to obtain a plurality of carbon sink window conversion rates.

7. The system of claim 1, wherein, In the expected carbon sink value prediction module, based on the plurality of carbon sink conversion rates, the expected carbon sink values of the plurality of soil sub-regions after the end of the preset monitoring window are predicted, and a carbon sink visualization distribution map of the target soil region is generated, comprising: obtaining a current carbon sink reference value of each soil sub-region; obtaining an expected carbon sink value of each soil sub-region based on the current carbon sink reference value of each soil sub-region and the corresponding carbon sink conversion rate; performing spatial interpolation processing based on the expected carbon sink values of the plurality of soil sub-regions to generate carbon sink spatial distribution data; performing three-dimensional visualization rendering on the carbon sink spatial distribution data to generate a carbon sink visualization distribution map of the target soil region.

8. A soil carbon sink visualization management method, characterized by, The method is performed by the system of any one of claims 1-7, comprising: determining a target soil region, collecting historical carbon sink data and vegetation distribution data of the target soil region, and receiving a preset monitoring window uploaded by a user terminal; dividing the target soil region into a plurality of soil sub-regions according to the vegetation distribution data, and obtaining a plurality of carbon sink conversion rates of the plurality of soil sub-regions in combination with the historical carbon sink data and a window time length of the preset monitoring window; based on the plurality of carbon sink conversion rates, predicting the expected carbon sink values of the plurality of soil sub-regions after the end of the preset monitoring window, and generating a carbon sink visualization distribution map of the target soil region; managing the carbon sink of the target soil region according to the carbon sink visualization distribution map.

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