Coupling coordination research method for cultivated land utilization transformation degree and carbon emission efficiency

Abstract

The invention discloses a coupling coordination research method for cultivated land utilization transformation degree and carbon emission efficiency, which comprises the following steps of: firstly, constructing an evaluation index system of the cultivated land utilization transformation degree, determining each index weight and calculating a comprehensive score of the cultivated land utilization transformation degree of a region to be measured at each time point; then identifying a carbon emission source of a to-be-detected region, determining a carbon emission coefficient, and calculating the total carbon emission amount of the cultivated land; then collecting input data and output data of a to-be-detected region, and constructing a super-efficiency SBM model considering unexpected output to calculate a carbon emission efficiency score of the to-be-detected region; calculating to obtain the coupling coordination degree of the cultivated land utilization transformation degree and the carbon emission efficiency of the to-be-measured region; and finally evaluating the coupling coordination level of the to-be-tested region. The improved coupling coordination model is used for calculating the coupling coordination degree level of the cultivated land utilization transformation degree and the carbon emission efficiency, a researcher and a coordinator are helped to better understand and analyze the correlation, the characteristics and the development degree between the researcher and the coordinator, and therefore the decision making efficiency and the working efficiency are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of agricultural science and environmental resource management, and specifically relates to a coupling and coordination research method for the degree of cultivated land utilization transformation and carbon emission efficiency, which can be applied to the multifunctional evaluation of cultivated land resources, sustainable development of green agriculture, rural revitalization and national land space planning, etc. Background Art

[0002] With the intensification of global climate change and land resource shortages, how to achieve the transformation of cultivated land use and improve carbon emission efficiency while ensuring food security has become an important research topic in current agricultural development and environmental protection. In different stages of social development, land use patterns have corresponding spatiotemporal characteristics, which also affect changes in carbon emissions and efficiency. Scholars initially focused on the evolution of land use patterns, but now pay more attention to its ecological and social significance. Therefore, the concept of land use transformation has been proposed, and cultivated land transformation is an important part of land use transformation. At present, scholars' research no longer focuses on explicit aspects such as the quantity, quality and spatial structure of cultivated land, but is more concerned with its functional evolution, utilization efficiency, ecological security and other implicit aspects. For example, Wang et al. [1] By studying the characteristics of cultivated land in Guangdong Province, it was found that the production-ecology, ecology-life, and production-life functions of cultivated land are mainly stable synergies; He Yinjie, Wu Dafang and others [2] It is pointed out that it is necessary to achieve the trinity management of area, quality and ecology for cultivated land. With the development of agricultural modernization, the non-production functions of cultivated land, such as economic function, ecological function, leisure service function, etc., have gradually attracted attention, and cultivated land has tended to develop multifunctionally. Among them, the carbon emission efficiency of cultivated land has gradually become a hot topic among scholars. The carbon emission efficiency of cultivated land refers to the minimum carbon dioxide emission when the agricultural resource input is reduced or unchanged, emphasizing the improvement of resource utilization efficiency while achieving the production goals of cultivated land. Yang Bin et al. [3] By analyzing the comprehensive level of green and low-carbon utilization of cultivated land in the Yangtze River Economic Belt, it is found that the level of regional economic development will have a major impact on the transformation of cultivated land use. Liu et al. [4] Based on the carbon emission perspective, the super-efficiency SBM model was used to calculate China's agricultural green total factor productivity. The results showed that there were regional differences in the impact of agricultural factor endowments and regional characteristics on China's agricultural green total factor productivity. Shan et al. [5] From both dynamic and static perspectives, agricultural carbon emissions are incorporated into the agricultural carbon emission efficiency evaluation index system, and the spatiotemporal differentiation characteristics of agricultural carbon emission efficiency in Hubei Province and its influencing factors are analyzed.

[0003] Past studies have shown that the level of carbon emission efficiency is affected by aspects such as cultivated land resource endowment, technological progress, and energy input. At the same time, it is also found that there are few studies that explore the coupling and coordination relationship between cultivated land utilization transformation and carbon emissions, and the coupling degree between the two deserves further study. Therefore, the present invention proposes a systematic research method to evaluate the coupling and coordination relationship between cultivated land utilization transformation and carbon emission efficiency, and reveals the relationship, characteristics, and development level between the two through systematic analysis.

[0004] References:

[0005] [1]Wang Z, Yang H, Hu Y, et al. Multifunctional trade-off / synergyrelationship of cultivated land in Guangdong: A long time series analysis from 2010 to 2030[J]. Ecological Indicators, 2023,154:110700.

[0006] [2]He YJ,Wu DF,Liu YY,et al.Review of Research on Evaluating theEcological Security of Cultivated Land[J].Frontiers in Environmental Science,2023,11:448.doi:10.3389 / fenvs.2023.1115058.

[0007] [3] Yang Bin, Yang Jun, Wang Zhanqi, et al. Spatial-temporal pattern and causes of green and low-carbon utilization of cultivated land in the Yangtze River Economic Belt[J]. Chinese Land Science, 2022, 36(10): 63-71.

[0008] [4]Liu D, Zhu

[0009] [5]Shan T,Xia Y,Hu C,et al.Analysis of regional agricultural carbonemission efficiency and influencing factors:Case study of Hubei Province inChina[J].PLoS One,2022,17(4):e0266172. Summary of the invention

[0010] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and provide a coupling and coordination research method for the degree of transformation of cultivated land use and carbon emission efficiency. The degree of transformation of cultivated land use is evaluated by using a comprehensive index evaluation method, carbon emissions are measured based on the carbon emission coefficient method, and the carbon emission efficiency is measured using the super-efficiency SBM model of non-expected output. Finally, based on the coupling coordination degree model, the coupling and coordination relationship between the degree of transformation of cultivated land use and carbon emission efficiency is studied to systematically evaluate the interactive relationship between the degree of transformation of cultivated land use and carbon emission efficiency.

[0011] In order to achieve the above-mentioned object, the present invention provides a coupling coordination research method for the degree of cultivated land utilization transformation and carbon emission efficiency, comprising the following steps:

[0012] Construct an evaluation index system for the degree of cultivated land use transformation, determine the weight of each index, and calculate the comprehensive score of the degree of cultivated land use transformation at each time point in the tested area;

[0013] Identify the carbon emission sources in the agricultural production process in the tested area, determine the carbon emission coefficient and calculate the total carbon emission of cultivated land;

[0014] Collect input data and output data of agricultural production in the tested area, and construct a super-efficiency SBM model that takes into account unexpected output to calculate the carbon emission efficiency score of the tested area; the input data include labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films; the output data include grain output, total agricultural production value and total carbon emissions from cultivated land;

[0015] According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling coordination degree between cultivated land use transformation degree and carbon emission efficiency in the tested area is calculated;

[0016] Based on the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area, the coupling coordination level of the tested area is evaluated.

[0017] As a preferred technical solution, the steps of calculating the comprehensive score of cultivated land utilization transformation degree at each time point in the tested area are as follows:

[0018] Establish an evaluation index system for the degree of cultivated land use transformation;

[0019] Based on each indicator in the evaluation index system, collect the indicator data within the set time period of the tested area and use the standard method for normalization;

[0020] The entropy weight method is used to determine the weight of each indicator in the evaluation index system;

[0021] The weighted summation method is used to calculate the comprehensive score of the degree of cultivated land use transformation at each time point within the set time period in the tested area.

[0022] As a preferred technical solution, the evaluation index system of cultivated land utilization transformation degree consists of two target layers, five factor layers and fifteen index layers;

[0023] The two target layers are respectively explicit transformation of cultivated land use and implicit transformation of cultivated land use;

[0024] The explicit transformation of cultivated land use includes two factor layers: quantitative transformation and spatial structural transformation;

[0025] The implicit transformation of cultivated land use includes three factors: production function transformation, life function transformation and ecological function transformation;

[0026] The quantitative transformation includes three indicator layers: per capita cultivated land area, per capita crop sown area and land reclamation rate;

[0027] The spatial structural transformation includes three indicator layers: the ratio of grain crop sown area, the newly added cultivated land area and the ratio of grain to economy;

[0028] The production function transformation includes three indicator layers: the total output value of crop production per unit area, grain yield per unit area and multiple cropping index;

[0029] The transformation of life functions includes three indicator layers: per capita food security rate, agricultural employment ratio and per capita total agricultural machinery power;

[0030] The ecological function transformation includes three indicator layers: population carrying capacity of cultivated land, per capita fertilizer non-point source pollution, and the proportion of cultivated land to ecological land.

[0031] As a preferred technical solution, the total carbon emissions from cultivated land are calculated as follows:

[0032] Identify sources of carbon emissions from agriculture in the region under test over a set time period;

[0033] Determine the carbon emission coefficient of each carbon emission source according to the national greenhouse gas guidelines issued by the IPCC;

[0034] Collect carbon emissions from carbon emission sources within a set time period;

[0035] The total carbon emissions from cultivated land in the measured area within a set time period are calculated based on the product of the carbon emission coefficient and carbon emissions of each carbon emission source.

[0036] As a preferred technical solution, the super-efficiency SBM model considering non-desirable outputs takes food output and agricultural gross output value as expected outputs, takes the total carbon emissions of cultivated land as non-desirable outputs, takes labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films as inputs, and takes minimizing inputs to maximize outputs and minimize total carbon emissions as the goal, and calculates the carbon emission efficiency score of the area to be tested;

[0037] The super-efficiency SBM model considering undesirable output is expressed as:

[0038]

[0039]

[0040] Where: ρ(CEE) is the carbon emission efficiency of decision-making unit k; m is the amount of input; is the slack variable of the ith input; x ik is the i-th input of decision-making unit k; s is the quantity of expected output, and q is the quantity of undesired output; and are the slack variables for the rth expected output and the tth undesired output respectively; is the rth expected output of decision unit k; is the t-th undesirable output of decision-making unit k; x ij represents the i-th input of decision-making unit j; is the rth expected output of decision-making unit j; represents the t-th undesirable output of decision-making unit j; j is the weight of decision-making unit j; n is the number of decision-making units;

[0041] when When ρ≥1, the carbon emission efficiency calculated by the decision-making unit is effective; If one or more non-zero values ​​appear in the three, the carbon emission efficiency calculated by the decision-making unit is invalid.

[0042] As a preferred technical solution, the coupling coordination degree between the degree of cultivated land utilization transformation and carbon emission efficiency in the tested area is calculated as follows:

[0043] According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling degree between cultivated land use transformation degree and carbon emission efficiency was calculated using the improved coupling degree calculation method. The formula is:

[0044]

[0045] In the formula, C is the coupling degree between the degree of cultivated land use transformation and carbon emission efficiency, U2 is the larger value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score, and U1 is the smaller value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score.

[0046] The comprehensive development index of cultivated land utilization transformation degree and carbon emission efficiency is calculated as follows:

[0047] T=αf(TCLU)+βg(CEE),

[0048] In the formula, α and β represent the contribution of cultivated land use transformation degree and carbon emission efficiency, f(TCLU) is the comprehensive score of cultivated land use transformation degree, and g(CEE) is the carbon emission efficiency score;

[0049] Based on the coupling degree and comprehensive development index of cultivated land use transformation degree and carbon emission efficiency, the coupling coordination degree of cultivated land use transformation degree and carbon emission efficiency is calculated. The calculation formula is:

[0050]

[0051] Among them, D is the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency.

[0052] As a preferred technical solution, the coupling coordination level of the area to be tested is evaluated as follows:

[0053] If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈[0.000,0.400], the coupling coordination level of the tested area is considered to be low;

[0054] If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.400,0.600], the coupling coordination level of the tested area is considered to be low;

[0055] If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.600,0.700], the coupling coordination level of the tested area is considered to be medium;

[0056] If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.700,0.800], the coupling coordination level of the tested area is considered to be high;

[0057] If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.800,1.000], the coupling coordination level of the tested area is considered to be high.

[0058] As a preferred technical solution, it also includes: using chart tools to perform visual display based on the coupling coordination degree and coupling coordination level of the area to be tested.

[0059] On the other hand, an electronic device is provided, characterized in that the electronic device includes a processor and a memory, the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to realize the above-mentioned method for coupling and coordinating the degree of cultivated land utilization transformation and carbon emission efficiency.

[0060] On the other hand, a computer-readable storage medium is provided, storing a program, characterized in that when the program is executed by a processor, the above-mentioned method for coupling and coordinating the degree of cultivated land utilization transformation and carbon emission efficiency is implemented.

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] The present invention adopts comprehensive evaluation method, carbon emission coefficient method and super-efficiency SBM model of non-expected output to respectively calculate the cultivated land utilization transformation index, cultivated land carbon emission and carbon emission efficiency of the region; then, the improved coupling coordination degree model is used to measure the coupling degree, coordination degree and coupling coordination degree of the two systems, and summarize the spatiotemporal evolution characteristics and change trends, which has the following advantages:

[0063] (1) Effectively describe the spatiotemporal characteristics of cultivated land use transformation index

[0064] From the perspective of cultivated land use morphology, by constructing an evaluation index system for cultivated land use transformation, the spatiotemporal characteristics of cultivated land use transformation in the tested area are studied. The evaluation index system includes explicit and implicit transformation of cultivated land use, covering five subsystems: quantity, spatial structure transformation, and production, life, and ecological function transformation. It provides a more systematic and comprehensive evaluation index for the study of cultivated land use transformation, and effectively describes the spatiotemporal characteristics of cultivated land use transformation. This invention enriches the relevant empirical research on green utilization of cultivated land, and also provides a basis for theoretical research on cultivated land protection.

[0065] (2) Reveal the spatiotemporal characteristics of cultivated land carbon emissions and carbon emission efficiency.

[0066] This application identifies the carbon emission sources in the agricultural production process in the tested area, starts from the perspective of land, labor, and agricultural resource input, comprehensively considers the impact of agricultural output and total carbon emissions from cultivated land on carbon emission efficiency, and uses the carbon emission coefficient method to measure the cultivated land carbon emissions in the tested area. It can reveal the temporal and spatial characteristics of cultivated land carbon emissions and carbon emission efficiency, and can reflect the relationship between cultivated land carbon emission efficiency and input-output, which is of great significance to promoting agricultural modernization and environmental protection.

[0067] (3) Build a theoretical framework for coupled and coordinated development to systematically reveal the characteristics and degree of coupling and coordination between the two systems.

[0068] At present, there is no systematic and complete framework between cultivated land use transformation and carbon emission efficiency calculation. This application fills this gap. Based on the comprehensive index of cultivated land use transformation degree and carbon emission efficiency, the coupling degree, coordination degree and coupling coordination degree level of cultivated land use transformation degree and carbon emission efficiency in the tested area are calculated to help researchers and coordinators better understand and analyze the relationship, characteristics and development degree between the two, so as to improve decision-making and work efficiency. In terms of improving the efficiency of land resource utilization and guiding agriculture to shift towards a low-carbon development direction, this application can provide comprehensive data support and scientific guidance for the strategic planning and management of the tested area, and also provide a reference for subsequent related research. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0070] Figure 1 It is a flow chart of a coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency in an embodiment of the present invention.

[0071] Figure 2 It is a visualization diagram of the coupling coordination degree and coupling coordination level of each county in a province in an embodiment of the present invention.

[0072] Figure 3 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0074] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0075] Example 1

[0076] like Figure 1 As shown, the coupling coordination research method of the cultivated land utilization transformation degree and carbon emission efficiency in this embodiment includes the following steps:

[0077] Construct an evaluation index system for the degree of cultivated land use transformation, determine the weight of each index, and calculate the comprehensive score of the degree of cultivated land use transformation at each time point in the tested area;

[0078] Identify the carbon emission sources in the agricultural production process in the tested area, determine the carbon emission coefficient and calculate the total carbon emission of cultivated land;

[0079] Collect input and output data of agricultural production in the tested area, build a super-efficiency SBM model that takes into account non-desirable outputs, and calculate the carbon emission efficiency score of the tested area;

[0080] According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling coordination degree between cultivated land use transformation degree and carbon emission efficiency in the tested area is calculated;

[0081] Based on the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area, the coupling coordination level of the tested area is evaluated.

[0082] Example 2

[0083] In order to further verify the superiority and reproducibility of this method, this example uses counties and districts in Guangdong Province as the test areas to conduct a coupling and coordination study on the degree of cultivated land use transformation and carbon emission efficiency, and systematically evaluates the interactive relationship between the degree of cultivated land use transformation and carbon emission efficiency. The specific steps are as follows:

[0084] S1. Construct an evaluation index system for the degree of cultivated land use transformation in each county and district of Guangdong Province, determine the weight of each index and calculate the comprehensive score of the degree of cultivated land use transformation at each time point in the tested area.

[0085] Furthermore, this application first uses the comprehensive index evaluation method to evaluate the degree of cultivated land use transformation, and the process is as follows:

[0086] S101. Construct an evaluation index system for the degree of cultivated land use transformation;

[0087] Considering that the degree of cultivated land use transformation is explicitly affected by natural resources on the one hand, and implicitly affected by economic production, human life and ecological functions on the other hand, the evaluation index system of cultivated land use transformation degree constructed in this application covers two target layers, namely, explicit transformation of cultivated land use and implicit transformation of cultivated land use; among them, explicit transformation of cultivated land use mainly includes two factor layers of quantity transformation and spatial structure transformation; implicit transformation of cultivated land use mainly includes three factor layers of production function transformation, life function transformation and ecological function transformation; further, per capita cultivated land area, per capita crop sown area and The three indicator layers of land reclamation rate are selected to evaluate the quantitative transformation; the three indicator layers of grain crop sowing area ratio, newly added cultivated land area and grain-economic ratio are selected to evaluate the spatial structure transformation; the three indicator layers of per capita planting output value, grain yield per unit area and multiple cropping index are selected to evaluate the production function transformation; the three indicator layers of per capita food security rate, agricultural employment ratio and per capita total agricultural machinery power are selected to evaluate the living function transformation; and the three indicator layers of cultivated land population carrying capacity, per capita fertilizer non-point source pollution and cultivated land to ecological land ratio are selected to evaluate the ecological function transformation; the constructed evaluation indicator system is shown in Table 1:

[0088] Table 1 Evaluation index system of cultivated land use transformation degree

[0089]

[0090] S102. Based on each indicator in the evaluation indicator system, collect indicator data within a set time period of the area to be tested, and use the standard method to perform normalization processing.

[0091] In this embodiment, based on the 15 indicators in Table 1, data from 2005 to 2020 are collected from counties and districts in Guangdong Province, and normalized to process different data and eliminate data differences. The attributes with "+" in Table 1 are processed positively, and the attributes with "-" are processed negatively. The processing method is as follows:

[0092] Forward processing: x new =(xx min ) / (x max -x min ), negative processing: x new =(x max -x) / (x max -x min ),

[0093] In the formula, x new is the new value of the indicator after normalization, x is the original value of the indicator, and x min is the minimum value in the index, x max is the maximum value among the indicators.

[0094] S103: Determine the weight of each indicator in the evaluation indicator system using the entropy weight method. The entropy weight method is a conventional weighting method in the field of the present invention, and will not be described in detail in this application.

[0095] S104. Use the weighted sum method to measure the comprehensive score of cultivated land use transformation at each time point within the set time period in the measured area.

[0096] Results The natural breakpoint method was used to divide the comprehensive scores of cultivated land use transformation degree of each county in Guangdong Province into five levels from low to high, corresponding to low value area (0-0.105), lower value area (0.105-0.180), medium value area (0.180-0.234), higher value area (0.234-0.300) and high value area (0.300-0.507). In 2005, the comprehensive scores of the degree of transformation of cultivated land use in various counties and districts in Guangdong Province were generally at a low level, with an average comprehensive score of 0.207. In 2010, the comprehensive score levels of transformation of cultivated land use in various counties and districts in Guangdong Province increased overall, with an average comprehensive score of 0.220. In 2015, the comprehensive score of the degree of transformation of cultivated land use declined compared with the previous stage, with an average comprehensive score of 0.197. In 2020, the comprehensive score of the degree of transformation of cultivated land use in various counties and districts in Guangdong Province rebounded compared with the previous stage, with an average comprehensive score of 0.201.

[0097] In order to reflect the changing trend and spatial pattern of the coupling coordination degree among different regions in Guangdong Province, this application divides the counties and districts of Guangdong Province into the Pearl River Delta, East, West and North, and averages the comprehensive scores of the degree of transformation of cultivated land use in each county and district in the region to obtain the average comprehensive scores of the degree of transformation of cultivated land use in different regions. The same applies to the following carbon emission efficiency scores, coupling degree, coordination degree and coupling coordination degree.

[0098] Therefore, the overall change trend of the comprehensive score of the average cultivated land utilization transformation degree in different regions of Guangdong Province from 2005 to 2020 is shown in Table 2 below:

[0099] Table 2 Comprehensive scores of average cultivated land use transformation degree in different regions of Guangdong Province from 2005 to 2020

[0100]

[0101] It can be seen from Table 2 that the average comprehensive score of the degree of transformation of cultivated land use in Guangdong Province from 2005 to 2020 was on a downward trend as a whole, but the trend was slowing down; the overall decline was 2.76%, and the change was not large, but there were obvious differences between regions, showing a distribution pattern of "centered on the Pearl River Delta, low in the middle and high around".

[0102] S2, identify the carbon emission sources in the agricultural production process of the tested area, determine the carbon emission coefficient and calculate the total carbon emission of cultivated land. Further, this step calculates the total carbon emission of cultivated land based on the carbon emission measurement method of the carbon emission coefficient, and the steps are:

[0103] S201. In order to calculate the carbon emissions from cultivated land in Guangdong Province, it is first necessary to determine its main source and identify the carbon emission sources in the agricultural generation process within the set time period in the measured area; combined with the availability of data, this embodiment selects six aspects of agricultural production process as carbon emission sources, including fertilizers, pesticides, agricultural films, total power of agricultural machinery, land tillage and irrigation.

[0104] S202. To ensure more accurate calculation of carbon emissions, the carbon emission coefficient of each carbon emission source is determined based on the national greenhouse gas guidelines issued by the IPCC (Intergovernmental Panel on Climate Change) and relevant domestic and foreign research.

[0105] In this embodiment, the following Table 3 shows the carbon emission coefficients of the six selected carbon emission sources:

[0106] Table 3 Carbon emission coefficients of six carbon emission sources

[0107]

[0108] In Table 3, kgC is kilogram carbon dioxide equivalent, kg is kilogram, kW is kilowatt, and hm 2 For hectares.

[0109] S203: After determining the carbon emission coefficient, collect the carbon emissions of the carbon emission sources within a set time period.

[0110] Similarly, in this embodiment, the carbon emissions of the above six carbon emission sources in each county and district in Guangdong Province from 2005 to 2020 are collected.

[0111] S204. Finally, the total carbon emissions from cultivated land in the set time period of the tested area are calculated based on the product of the carbon emission coefficient and the carbon emission of each carbon emission source. The formula is:

[0112]

[0113] Where: E represents the total carbon emissions from cultivated land, T i represents the carbon emissions of the i-th carbon emission source, Indicates the carbon emission coefficient of the ith carbon emission source. Of course, the above 6 carbon emission sources in this application are only exemplary, and other carbon emission sources are also included in this application.

[0114] S3. Collect input data and output data of agricultural production in the tested area, and construct a super-efficiency SBM model that takes into account non-expected output to calculate the carbon emission efficiency score of the tested area. Among them, input data include labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films; output data include grain output, agricultural production value and total carbon emissions from cultivated land.

[0115] Furthermore, in order to better measure the carbon emission efficiency score, this application considers the super-efficiency SBM model of non-expected output. This model is a non-radial and non-angular data envelopment analysis (DEA) analysis method based on slack variable measurement, which takes into account the "slack" effect of factors and can effectively solve the carbon emission efficiency evaluation bias caused by ignoring non-expected output; at the same time, the model can make up for the deficiency of traditional DEA model that cannot sort and distinguish effective decision-making units. [6-7] The comprehensive model combining the super-efficiency model and the SBM model can simultaneously decompose multiple decision-making units with an efficiency value of 1, realize the comparison and ranking between effective decision-making units, improve the accuracy of the model, and effectively measure the comprehensive efficiency of regional carbon emissions.

[0116] Since the use of the super-efficiency SBM model that takes non-expected output into consideration when calculating the carbon emission efficiency score must take into account the three aspects of input, expected output and non-expected output, as well as the evaluation index system that connects the degree of transformation of cultivated land use, in this application, the super-efficiency SBM model that takes non-expected output into consideration takes grain output and gross agricultural output as expected output, and total carbon emissions from cultivated land as non-expected output, and takes labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films as inputs, with the goal of minimizing input to maximize output and minimize total carbon emissions, so as to achieve the coordinated unity of social and economic development and the ecological environment, and thus calculate the carbon emission efficiency score of the area to be tested.

[0117] The super-efficiency SBM model considering undesirable output is expressed as:

[0118]

[0119]

[0120] Where: ρ(CEE) is the carbon emission efficiency of decision-making unit k; m is the amount of input; is the slack variable of the ith input; x ik is the i-th input of decision-making unit k; s is the quantity of expected output, and q is the quantity of undesired output; and are the slack variables for the rth expected output and the tth undesired output respectively; is the rth expected output of decision unit k; is the t-th undesirable output of decision-making unit k; x ij represents the i-th input of decision-making unit j; is the rth expected output of decision-making unit j; represents the t-th undesirable output of decision-making unit j; j is the weight of decision-making unit j; n is the number of decision-making units;

[0121] when When ρ≥1, the carbon emission efficiency calculated by the decision-making unit is effective; If one or more non-zero values ​​appear in the three, the carbon emission efficiency calculated by the decision-making unit is invalid.

[0122] Table 4 below shows the variables in the super-efficiency SBM model considering undesirable output:

[0123] Table 4 Description of model variables

[0124]

[0125] A super-efficiency SBM model considering non-expected outputs was established to measure the carbon emission efficiency scores of counties and districts in Guangdong Province. According to the principle of the model, the cultivated land use efficiency value is greater than or equal to 1 for an effective decision-making unit, and vice versa for an invalid decision-making unit. According to the measurement results, combined with the natural breakpoint method, the carbon emission efficiency scores of counties and districts in Guangdong Province are uniformly divided into five levels from low to high, corresponding to the low value area (0.000-0.256), the lower value area (0.256-0.381), the middle value area (0.381-0.605), the higher value area (0.605-1.000), and the high value area is greater than or equal to 1.000.

[0126] In order to study the evolution trend of different regions in Guangdong Province, the average carbon emission efficiency scores of different regions were calculated. The results are shown in Table 5 below:

[0127] Table 5 Average cultivated land carbon emission efficiency scores in different regions of Guangdong Province from 2005 to 2020

[0128]

[0129]

[0130] As can be seen from Table 5, the overall carbon emission efficiency score of Guangdong Province shows a trend of first increasing and then decreasing, which is more obvious in spatial differentiation, showing a "multi-core" distribution feature; the Pearl River Delta region has the most obvious changes, while the eastern Guangdong region has always been higher than the regional average. Table 5 shows that during the period of 2005-2020, the carbon emission efficiency of Guangdong Province was in an adjustment period; the urbanization level in the Pearl River Delta region is relatively high. Although the cultivated land area and labor force in some counties and districts such as Conghua District, Baiyun District, Nanshan District, and Bao'an District have continued to decrease, they mainly grow cash crops with high output value and high carbon emission efficiency, while the development focus of other counties and districts is on the tertiary industry, the agricultural environment is poor, and the output of agricultural products is low, resulting in low carbon emission efficiency of cultivated land. The eastern region is mainly based on agricultural development, and the input-output ratio is relatively stable. The western region has a good agricultural foundation and a high proportion of cultivated land, but its economic development is poor and the traditional input is large, resulting in low efficiency in some areas. The northern region is a mountainous area. Due to the influence of the terrain, the cultivated land is relatively fragmented, the farming conditions are poor, and the utilization efficiency is low.

[0131] S4. Based on the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling coordination degree between cultivated land use transformation degree and carbon emission efficiency in the tested area is calculated.

[0132] Furthermore, the calculation process of coupling coordination is:

[0133] S401. Calculate the coupling degree between the degree of cultivated land use transformation and the carbon emission efficiency based on the comprehensive score of cultivated land use transformation and the score of carbon emission efficiency. Since there are few large-scale differences in the social sciences, the coupling degree distribution is concentrated and generally high, which reduces the coupling validity and easily leads to excessive reliance on the comprehensive development index for coupling coordination. Therefore, this application uses an improved coupling degree calculation method to calculate the coupling degree between the degree of cultivated land use transformation and the carbon emission efficiency. The formula is:

[0134]

[0135] Where C is the coupling degree between the degree of cultivated land use transformation (TCLU) and carbon emission efficiency (CEE), U2 is the larger value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score, and U1 is the smaller value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score.

[0136] S402. Next, the comprehensive development index (coordination degree) of cultivated land utilization transformation degree and carbon emission efficiency is calculated to reflect the contribution of the two to the overall development level. The formula is:

[0137] T=αf(TCLU)+βg(CEE),

[0138] In the formula, α and β represent the contribution of cultivated land use transformation degree and carbon emission efficiency, which are unknown coefficients, f(TCLU) is the comprehensive score of cultivated land use transformation, and g(CEE) is the carbon emission efficiency score;

[0139] S403. Finally, based on the coupling degree and comprehensive development index of cultivated land use transformation degree and carbon emission efficiency, the coupling coordination degree of cultivated land use transformation degree and carbon emission efficiency is calculated. The calculation formula is:

[0140]

[0141] Among them, D is the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency.

[0142] Table 6 below shows the average coupling degree of different regions in Guangdong Province:

[0143] Table 6 Average coupling degree between cultivated land use transformation degree and carbon emission efficiency in different regions of Guangdong Province from 2005 to 2020

[0144]

[0145] S5. Based on the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area, the coupling coordination level of the tested area is evaluated.

[0146] Furthermore, the closer the coupling coordination degree is to 1, the better the coordinated development level between the degree of cultivated land use transformation and carbon emission efficiency. This application divides the coupling coordination level into five levels, namely low level, lower level, medium level, higher level and high level. The following Table 7 shows the classification standards for each level:

[0147] Table 7 Coupling coordination levels and their classification standards

[0148]

[0149] In order to have a more intuitive understanding of the coupling coordination degree and coupling coordination level of the tested area, this application method also uses chart tools for visual display to help researchers and coordinators better understand and analyze the interactive relationship between the degree of cultivated land use transformation and carbon emission efficiency, thereby improving decision-making and work efficiency.

[0150] In this embodiment, the coupling coordination degree and coupling coordination level calculated for each county and district in Guangdong Province are visualized using an image tool. The results are as follows: Figure 2 As shown in Table 8, the color depth is used to show the distribution of coupling coordination degree in 2005, 2010, 2015 and 2020. The darker the color, the better the level of coordinated development and the higher the coupling coordination level. Figure 2The data shows that from 2005 to 2020, counties and districts with lower and low coupling coordination degrees occupied most of Guangdong Province. The proportion of counties and districts with lower and low coupling coordination degrees in 2005, 2010, 2015 and 2020 was 77.42%, 69.35%, 75.81% and 87.90% respectively. However, compared with 2005, the number of counties and districts with low coupling coordination degrees in Guangdong Province in the other three years decreased significantly. It can be seen that the coupling coordination degree of Guangdong Province is on an upward trend as a whole.

[0151] Table 8 Average coupling coordination degree of cultivated land use transformation degree and carbon emission efficiency in different regions of Guangdong Province from 2005 to 2020

[0152]

[0153] It should be noted that, for the sake of convenience, the aforementioned method embodiments are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited to the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously.

[0154] References:

[0155] [6]Xu Yingqi, Cheng Yu, Wang Jingjing, et al. Spatiotemporal evolution and influencing factors of carbon emission efficiency in China's low-carbon pilot cities[J]. Journal of Natural Resources, 2022, 37(05): 1261-1276.

[0156] [7]Xu Yingqi, Cheng Yu, Wang Jingjing. Spatiotemporal evolution of carbon emission efficiency and the impact of green technology innovation in China's resource-based cities[J]. Geographical Research, 2023, 42(03): 878-894.

[0157] Example 3

[0158] See also Figure 3 In one embodiment, an electronic device is provided for realizing a coupling and coordination research method of cultivated land utilization transformation degree and carbon emission efficiency. The electronic device may include a first processor, a first memory and a bus, and may also include a computer program stored in the first memory and executable on the first processor, such as a coupling and coordination research program.

[0159] Wherein, the first memory includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the first memory may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the first memory may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the first memory may also include both an internal storage unit of the electronic device and an external storage device. The first memory can be used not only to store application software and various types of data installed in the electronic device, such as the code of the coupling coordination research program, but also to temporarily store data that has been output or is to be output.

[0160] In some embodiments, the first processor may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The first processor is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing programs or modules (such as coupling coordination research programs, etc.) stored in the first memory, and calling data stored in the first memory.

[0161] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0162] The coupling coordination research program stored in the first memory in the electronic device is a combination of multiple instructions, and when running in the first processor, it can achieve:

[0163] Construct an evaluation index system for the degree of cultivated land use transformation, determine the weight of each index, and calculate the comprehensive score of the degree of cultivated land use transformation at each time point in the tested area;

[0164] Identify the carbon emission sources in the agricultural production process in the tested area, determine the carbon emission coefficient and calculate the total carbon emission of cultivated land;

[0165] Collect input data and output data of agricultural production in the tested area, and construct a super-efficiency SBM model that takes into account non-expected output to calculate the carbon emission efficiency score of the tested area; among them, input data include labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films; output data include grain output, total agricultural output value and total carbon emissions from cultivated land;

[0166] According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling coordination degree between cultivated land use transformation degree and carbon emission efficiency in the tested area is calculated;

[0167] Based on the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area, the coupling coordination level of the tested area is evaluated.

[0168] Furthermore, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0169] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0170] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above 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.

[0171] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A coupling and coordination research method for cultivated land use transformation degree and carbon emission efficiency, characterized in that: The steps include: Construct an evaluation index system for the degree of cultivated land use transformation, determine the weight of each index, and calculate the comprehensive score of the degree of cultivated land use transformation at each time point in the tested area; Identify the carbon emission sources in the agricultural production process in the tested area, determine the carbon emission coefficient and calculate the total carbon emission of cultivated land; Collect input data and output data of agricultural production in the tested area, and construct a super-efficiency SBM model that takes into account unexpected output to calculate the carbon emission efficiency score of the tested area; the input data include labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films; the output data include grain output, total agricultural production value and total carbon emissions from cultivated land; According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling coordination degree between cultivated land use transformation degree and carbon emission efficiency in the tested area is calculated; Based on the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area, the coupling coordination level of the tested area is evaluated.

2. According to claim 1, a coupling coordination research method for cultivated land utilization transformation degree and carbon emission efficiency is characterized in that: The steps of calculating the comprehensive score of cultivated land utilization transformation degree at each time point in the tested area are as follows: Establish an evaluation index system for the degree of cultivated land use transformation; Based on each indicator in the evaluation index system, collect the indicator data within the set time period of the tested area and use the standard method for normalization; The entropy weight method is used to determine the weight of each indicator in the evaluation index system; The weighted summation method is used to calculate the comprehensive score of the degree of cultivated land use transformation at each time point within the set time period in the tested area.

3. A coupling coordination research method for cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 or 2, characterized in that: The evaluation index system of cultivated land utilization transformation degree is composed of two target layers, five factor layers and fifteen index layers; The two target layers are respectively explicit transformation of cultivated land use and implicit transformation of cultivated land use; The explicit transformation of cultivated land use includes two factor layers: quantitative transformation and spatial structural transformation; The implicit transformation of cultivated land use includes three factors: production function transformation, life function transformation and ecological function transformation; The quantitative transformation includes three indicator layers: per capita cultivated land area, per capita crop sown area and land reclamation rate; The spatial structural transformation includes three indicator layers: the ratio of grain crop sown area, the newly added cultivated land area and the ratio of grain to economy; The production function transformation includes three indicator layers: the total output value of crop production per unit area, grain yield per unit area and multiple cropping index; The transformation of life functions includes three indicator layers: per capita food security rate, agricultural employment ratio and per capita total agricultural machinery power; The ecological function transformation includes three indicator layers: population carrying capacity of cultivated land, per capita fertilizer non-point source pollution, and the proportion of cultivated land to ecological land.

4. The coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 is characterized in that: The calculation of the total carbon emissions from cultivated land is specifically as follows: Identify sources of carbon emissions from agriculture in the region under test over a set time period; Determine the carbon emission coefficient of each carbon emission source according to the national greenhouse gas guidelines issued by the IPCC; Collect carbon emissions from carbon emission sources within a set time period; The total carbon emissions from cultivated land in the measured area within a set time period are calculated based on the product of the carbon emission coefficient and carbon emissions of each carbon emission source.

5. The coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 is characterized in that: The super-efficiency SBM model considering non-desirable outputs takes food output and agricultural gross output value as expected outputs, takes total carbon emissions from cultivated land as non-desirable outputs, takes labor, cultivated land, total power of agricultural machinery, effective irrigation area, fertilizers, pesticides and agricultural films as inputs, and takes minimizing inputs to maximize outputs and minimize total carbon emissions as the goal, and calculates the carbon emission efficiency score of the tested area; The super-efficiency SBM model considering undesirable output is expressed as: Where: ρ(CEE) is the carbon emission efficiency of decision-making unit k; m is the amount of input; is the slack variable of the ith input; x ik is the i-th input of decision-making unit k; s is the quantity of expected output, and q is the quantity of undesired output; and are the slack variables for the rth expected output and the tth undesired output respectively; is the rth expected output of decision unit k; is the t-th undesirable output of decision-making unit k; x ij represents the i-th input of decision-making unit j; is the rth expected output of decision-making unit j; represents the t-th undesirable output of decision-making unit j; j is the weight of decision-making unit j; n is the number of decision-making units; when When ρ≥1, the carbon emission efficiency calculated by the decision-making unit is effective; If one or more non-zero values ​​appear in the three, the carbon emission efficiency calculated by the decision-making unit is invalid.

6. The coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 is characterized in that: The calculation obtains the coupling coordination degree between the degree of cultivated land utilization transformation and carbon emission efficiency in the tested area, specifically: According to the comprehensive score of cultivated land use transformation degree and carbon emission efficiency score, the coupling degree between cultivated land use transformation degree and carbon emission efficiency was calculated using the improved coupling degree calculation method. The formula is: In the formula, C is the coupling degree between the degree of cultivated land use transformation and carbon emission efficiency, U2 is the larger value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score, and U1 is the smaller value between the comprehensive score of cultivated land use transformation and the carbon emission efficiency score. The comprehensive development index of cultivated land utilization transformation degree and carbon emission efficiency is calculated as follows: T=αf(TCLU)+βg(CEE), In the formula, α and β represent the contribution of cultivated land use transformation degree and carbon emission efficiency, f(TCLU) is the comprehensive score of cultivated land use transformation degree, and g(CEE) is the carbon emission efficiency score; Based on the coupling degree and comprehensive development index of cultivated land use transformation degree and carbon emission efficiency, the coupling coordination degree of cultivated land use transformation degree and carbon emission efficiency is calculated. The calculation formula is: Among them, D is the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency.

7. The coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 is characterized in that: The coupling coordination level of the area to be tested is evaluated as follows: If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈[0.000,0.400], the coupling coordination level of the tested area is considered to be low; If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.400,0.600], the coupling coordination level of the tested area is considered to be low; If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.600,0.700], the coupling coordination level of the tested area is considered to be medium; If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.700,0.800], the coupling coordination level of the tested area is considered to be high; If the coupling coordination degree between the degree of cultivated land use transformation and carbon emission efficiency in the tested area is D∈(0.800,1.000], the coupling coordination level of the tested area is considered to be high.

8. The coupling coordination research method of cultivated land utilization transformation degree and carbon emission efficiency according to claim 1 is characterized in that: Also includes: The coupling coordination degree and coupling coordination level of the area to be tested are visualized using chart tools.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement a coupling and coordination research method for the degree of cultivated land utilization transformation and carbon emission efficiency as described in any one of claims 1-8.

10. A computer-readable storage medium storing a program, characterized in that: When the program is executed by a processor, a coupling and coordination research method for the degree of cultivated land utilization transformation and carbon emission efficiency as described in any one of claims 1 to 8 is implemented.

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