CN112561722A - Ecological system attribute component composition structure time evolution quantitative analysis method - Google Patents
Ecological system attribute component composition structure time evolution quantitative analysis method Download PDFInfo
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Abstract
A quantitative analysis method for the time evolution of the composition structure of the attribute components of an ecosystem relates to an analysis method for the composition of the attribute components of the ecosystem. The method comprises the following steps: firstly, calculating an attribute component frequency parameter quantization index; and secondly, respectively obtaining a unitary linear regression time trend model of each frequency parameter by taking the quantization index of each frequency parameter as a dependent variable and time as an independent variable to form a trend model parameter set and obtain the time evolution condition of the structure formed by the attribute components of the ecological system. The invention provides a method for constructing a change trend mathematical model by utilizing time sequence data of ecological system attribute component frequency parameter quantitative indexes so as to quantitatively reflect the time evolution rule of an ecological system attribute component composition structure and realize the quantitative analysis of the time evolution of the ecological system attribute component composition structure.
Description
Technical Field
The invention relates to an ecosystem attribute component composition analysis method.
Background
At present, a graphic method is adopted to express the long-term evolution process of the composition structure of the attribute components of the ecosystem, and the long-term evolution trend characteristics of the composition structure of the attribute components of the ecosystem are visually displayed in an attribute component frequency two-dimensional isoline distribution graphic mode. However, the method lacks corresponding quantitative description, and is difficult to carry out quantitative analysis on the time evolution law of the structure of the attribute components of the same ecosystem and to carry out comparative analysis on the time evolution law of the structure of the attribute components of different ecosystems.
Disclosure of Invention
The invention provides a method for quantitatively describing the long-term evolution trend of the composition structure of the attribute components of an ecosystem and quantitatively analyzing the time evolution rule of the structure of the attribute components of the same ecosystem.
The invention relates to a method for quantitatively analyzing the time evolution of an attribute component composition structure of an ecosystem, which comprises the following steps of:
firstly, calculating an attribute component frequency parameter quantization index: acquiring multi-period frequency distribution data of the attribute components of the ecological system, and respectively calculating quantization indexes of frequency parameters;
and secondly, respectively obtaining a unitary linear regression time trend model of each frequency parameter by taking the quantization index of each frequency parameter as a dependent variable and time as an independent variable to form a trend model parameter set, and further obtaining the time evolution condition of the structure formed by the attribute components of the ecological system.
Further, in the step one, the attribute component of the ecosystem is vegetation index or ecological parameter or … ….
Further, in the first step, the frequency parameter includes a concentration value, an average value, a variation degree, a symmetry degree and a deviation degree of frequency distribution in each period.
The invention provides a method for constructing a change trend mathematical model by utilizing time sequence data of ecological system attribute component frequency parameter quantitative indexes so as to quantitatively reflect the time evolution rule of an ecological system attribute component composition structure and realize the quantitative analysis of the time evolution of the ecological system attribute component composition structure.
Drawings
FIG. 1 is a line graph showing the trend of the forest ecosystem of the Black Dragon Jiangxu province in 2010-2019, which is constructed in the embodiment 1 by taking the year as the horizontal axis and taking the quantitative indicators (concentration value, average value, variation degree, symmetry degree and deviation degree) as the vertical axis;
FIG. 2 is a graph of a one-dimensional linear regression time trend model for each frequency parameter in example 1.
Detailed Description
The technical solution of the present invention is not limited to the following specific embodiments, but includes any combination of the specific embodiments.
The first embodiment is as follows: the method for quantitatively analyzing the time evolution of the composition structure of the attribute components of the ecosystem in the embodiment comprises the following steps:
firstly, calculating an attribute component frequency parameter quantization index: acquiring multi-period frequency distribution data of the attribute components of the ecological system, and respectively calculating quantization indexes of frequency parameters;
and secondly, respectively obtaining a unitary linear regression time trend model of each frequency parameter by taking the quantization index of each frequency parameter as a dependent variable and time as an independent variable to form a trend model parameter set, and further obtaining the time evolution condition of the structure formed by the attribute components of the ecological system.
The second embodiment is as follows: the present embodiment differs from the first embodiment in that: in the first step, the attribute component of the ecological system is a vegetation index or an ecological parameter. Other steps and parameters are the same as those in the first embodiment.
The third concrete implementation mode: the present embodiment is different from the first or second embodiment in that: in the first step, the frequency parameters comprise concentration values, average values, variation degrees, symmetry degrees and deviation degrees of frequency distribution in each period. Other steps and parameters are the same as in one or both embodiments.
Example 1
The vegetation index NDVI of the forest ecosystem of Heilongjiang province in 2010-2019 is used for analysis:
firstly, respectively calculating the concentration value, average value, variation degree, symmetry degree and deviation degree indexes of frequency distribution in each year by using frequency distribution data of a vegetation index NDVI of a forest ecosystem in the Heilongjiang province in 2010-2019, wherein the result is shown in a table 1;
TABLE 1
| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | |
| Attribute concentration value | 0.81 | 0.83 | 0.83 | 0.83 | 0.83 | 0.87 | 0.85 | 0.89 | 0.85 | 0.83 |
| Average value of attribute | 0.81 | 0.82 | 0.82 | 0.79 | 0.82 | 0.83 | 0.85 | 0.84 | 0.82 | 0.80 |
| Degree of change of attribute | 0.04 | 0.04 | 0.05 | 0.07 | 0.05 | 0.06 | 0.04 | 0.07 | 0.06 | 0.06 |
| Attribute midpoint values | 0.49 | 0.47 | 0.50 | 0.47 | 0.45 | 0.45 | 0.46 | 0.47 | 0.46 | 0.46 |
| Degree of distribution symmetry | 0.32 | 0.36 | 0.33 | 0.36 | 0.38 | 0.42 | 0.39 | 0.42 | 0.39 | 0.37 |
| Attribute skewness | 0.32 | 0.35 | 0.32 | 0.32 | 0.37 | 0.38 | 0.39 | 0.37 | 0.36 | 0.34 |
Secondly, constructing a trend line graph (as shown in figure 1) by taking indexes of concentration value, average value, variation degree, symmetry degree and deviation degree of frequency distribution of each year as dependent variables and time as independent variables, wherein the horizontal axis of the figure 1 is the year, and the vertical axis is a quantitative index; then, a mathematical model construction tool is used for carrying out model fitting on the quantization index time series data in the graph 1, a unary linear regression time trend model (shown in the graph 2) of each frequency parameter is obtained, and a trend model parameter set is formed. As can be seen from fig. 2, the trends of the concentration values and the average values of the attributes are increased year by year, which indicates that the NDVI values of the components of the forest ecosystem occupying the largest area are gradually increased; the average value increasing trend is smaller than the change amplitude of the concentrated value, so that the integral attribute structure is more stable; the attribute change degree is increased year by year, and the increase of the overall difference degree of the component attributes in the ecological system is reflected; the distribution symmetry and the attribute deviation degree increase year by year, which shows that the dispersion degree of the vegetation index NDVI concentration value and the average value is increased year by year compared with the midpoint value.
Claims (3)
1. A quantitative analysis method for the time evolution of the composition structure of the attribute components of an ecosystem is characterized in that the quantitative analysis of the time evolution of the composition structure of the attribute components of the ecosystem is carried out according to the following steps:
firstly, calculating an attribute component frequency parameter quantization index: acquiring multi-period frequency distribution data of the attribute components of the ecological system, and respectively calculating quantization indexes of frequency parameters;
and secondly, respectively obtaining a unitary linear regression time trend model of each frequency parameter by taking the quantization index of each frequency parameter as a dependent variable and time as an independent variable to form a trend model parameter set, and further obtaining the time evolution condition of the structure formed by the attribute components of the ecological system.
2. The method according to claim 1, wherein the ecosystem attribute component is a vegetation index or an ecological parameter in step one.
3. The method of claim 1, wherein the frequency parameters in step one include concentration, average, variation, symmetry and deviation of frequency distribution of each period.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114202451A (en) * | 2021-12-16 | 2022-03-18 | 华侨大学 | Evolution analysis method, device, equipment and storage medium of service ecosystem |
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Patent Citations (5)
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| CN103136333A (en) * | 2013-01-29 | 2013-06-05 | 冯力新 | Datamation, representation method and application for abstract properties |
| CN108346108A (en) * | 2018-01-08 | 2018-07-31 | 中国矿业大学(北京) | The ecosystems services evolution analysis method and device of ecotone |
| CN108875002A (en) * | 2018-06-14 | 2018-11-23 | 环境保护部南京环境科学研究所 | A kind of desert ecosystem Red List appraisal procedure based on remote sensing and GIS |
| WO2020101192A1 (en) * | 2018-11-16 | 2020-05-22 | 고려대학교 산학협력단 | System and method for monitoring soil gas and performing responsive processing on basis of result of monitoring |
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| CN114202451A (en) * | 2021-12-16 | 2022-03-18 | 华侨大学 | Evolution analysis method, device, equipment and storage medium of service ecosystem |
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