CN112508758A - Ecological system internal type component and attribute component composition structure cooperative description method - Google Patents
Ecological system internal type component and attribute component composition structure cooperative description method Download PDFInfo
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Abstract
A cooperative description method for the internal type component and attribute component structure of an ecosystem relates to a cooperative description method for the internal type and attribute component structure of the ecosystem. The invention aims to solve the technical problem that the existing method is difficult to comprehensively display the internal composition structure condition of the ecosystem. The method comprises the following steps: generating attribute raster data of the type component in the ecosystem; and constructing the frequency distribution of the attribute components of the types inside the ecosystem. The invention organically combines the type components and the attribute component composition structures in the ecosystem to integrate the advantages of the two composition structure description methods and overcome the respective defects of the single composition structure description method, thereby forming the description method which can comprehensively reflect the internal composition structures of the ecosystem. The invention belongs to the field of description of an attribute structure of an ecosystem.
Description
Technical Field
The invention relates to a cooperative description method for an internal type and attribute composition structure of an ecosystem.
Background
The strength and quality of the ecosystem function depend on the quality of the internal structure of the ecosystem, so that the overall and systematic description of the internal structure, especially the composition structure of the ecosystem is necessary. In the past, when evaluating the internal composition structure condition of the ecosystem, a description method of the type component composition structure is generally adopted, namely, on the basis of classifying the internal components of the ecosystem, the type component composition structure in the ecosystem is expressed through a histogram of the distribution area or the occupied area ratio of the type components; however, the above method cannot reflect the variation of the attributes in each subtype component of the ecosystem. The patent 'ecosystem attribute component composition structure description method based on remote sensing vegetation indexes' provides a description method for representing ecosystem attribute component composition structures by using the remote sensing vegetation indexes, but aims at the overall attributes of an ecosystem, and does not contain information in the aspect of ecosystem internal type component composition structures, so that the internal composition structure condition of the ecosystem is difficult to display comprehensively.
Disclosure of Invention
The invention aims to solve the technical problem that the existing method is difficult to comprehensively display the internal composition structure condition of an ecosystem, and provides a cooperative description method for composition structures of internal type components and attribute components of the ecosystem.
The ecological system internal type component and attribute component composition structure collaborative description method is carried out according to the following steps:
firstly, generating attribute raster data of an internal type component of an ecosystem:
carrying out statistical analysis on the subtype component distribution grid data in the ecological system, carrying out spatial superposition and classification on the subtype component distribution grid data and the vegetation index of a research area or ecological parameter grid data, and extracting attribute distribution grid data in each subtype component of the ecological system;
constructing a histogram for representing the internal type component composition structure of the ecosystem by taking the subtype as a horizontal axis and the number of the subtype grids as a vertical axis;
secondly, constructing the frequency distribution of attribute components of the internal types of the ecological system:
according to the grid value statistics of the ecological system attribute distribution grid data, a grouping scheme of the ecological system attribute components is formulated; carrying out statistical calculation on internal attribute raster data of each subclass component of the ecological system to obtain grid frequency of each subclass internal attribute component;
constructing a type internal attribute component frequency distribution diagram representing the type internal attribute component composition structure description in the ecosystem;
and forming a structure distribution diagram formed by the internal type components and the attribute components of the ecosystem by taking the characteristic value of the attribute grouping as a horizontal axis and taking the area occupied by the internal attribute grouping of the subtype as a vertical axis for each subtype of the ecosystem.
The invention organically combines the type components and the attribute component composition structures in the ecosystem to integrate the advantages of the two composition structure description methods and overcome the respective defects of the single composition structure description method, thereby forming the description method which can comprehensively reflect the internal composition structures of the ecosystem.
Drawings
FIG. 1 is a diagram of a forest ecosystem vegetation index NDVI grid data in experiment I;
FIG. 2 is a graph of the first experiment showing the NDVI data of the vegetation index of deciduous and broad-leaved forests;
FIG. 3 is a graph of evergreen conifer vegetation index NDVI raster data for experiment one;
FIG. 4 is a graph of the leaf fall conifer vegetation index NDVI grid data in experiment one;
FIG. 5 is a graph of the NDVI grid data for the vegetation index of Miao forest in experiment one;
FIG. 6 is a plot of the first experiment showing the broadleaf shrub vegetation index NDVI;
fig. 7 is a frequency distribution diagram of NDVI components of vegetation index of types inside forest ecosystems of jilin province in experiment one.
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 cooperatively describing the internal type component and attribute component composition structure of the ecosystem of the embodiment is carried out according to the following steps:
firstly, generating attribute raster data of an internal type component of an ecosystem:
carrying out statistical analysis on the subtype component distribution grid data in the ecological system, carrying out spatial superposition and classification on the subtype component distribution grid data and the vegetation index of a research area or ecological parameter grid data, and extracting attribute distribution grid data in each subtype component of the ecological system;
constructing a histogram for representing the internal type component composition structure of the ecosystem by taking the subtype as a horizontal axis and the number of the subtype grids as a vertical axis;
secondly, constructing the frequency distribution of attribute components of the internal types of the ecological system:
according to the grid value statistics of the ecological system attribute distribution grid data, a grouping scheme of the ecological system attribute components is formulated; carrying out statistical calculation on internal attribute raster data of each subclass component of the ecological system to obtain grid frequency of each subclass internal attribute component;
constructing a type internal attribute component frequency distribution diagram representing the type internal attribute component composition structure description in the ecosystem;
and forming a structure distribution diagram formed by the internal type components and the attribute components of the ecosystem by taking the characteristic value of the attribute grouping as a horizontal axis and taking the area occupied by the internal attribute grouping of the subtype as a vertical axis for each subtype of the ecosystem.
The following experiments are adopted to verify the effect of the invention:
experiment one:
the ecological system internal type component and attribute component composition structure collaborative description method is carried out according to the following steps:
firstly, generating attribute raster data of an internal type component of an ecosystem:
spatial superposition processing is carried out on the NDVI data of the vegetation indexes of Jilin province in 2000 and the type distribution data of the forest land in 2000 to obtain the NDVI grid data (shown in figures 1-6) of the forest ecosystem and the interior type vegetation indexes of the forest ecosystem, and the attribute grading is shown in Table 1.
TABLE 1 Attribute ranking System
Carrying out statistical analysis on the subtype component distribution grid data in the ecological system, carrying out spatial superposition and classification on the subtype component distribution grid data and the vegetation index of a research area or ecological parameter grid data, and extracting attribute distribution grid data in each subtype component of the ecological system;
constructing a histogram for representing the internal type component composition structure of the ecosystem by taking the subtype as a horizontal axis and the number of the subtype grids as a vertical axis;
secondly, constructing the frequency distribution of attribute components of the internal types of the ecological system:
and generating an ecosystem and an attribute frequency distribution map of each subclass of the ecosystem by the vegetation index NDVI raster data, wherein the ecosystem and the attribute frequency distribution map of each subclass of the ecosystem are obtained by carrying out equidistant grouping statistics on the vegetation index NDVI data of the forest land types and each subclass of the forest land types. The division interval of the vegetation index NDVI is 0.02, which is formed with the horizontal axis representing the median value (feature value) of the division and the vertical axis representing the spatial area occupied by each subclass.
The internal structure analysis of the forest ecosystem of Jilin province is shown in figure 7: in 2000, the vegetation index NDVI distribution of the forest ecosystem of the Jilin province appears as a skewed unimodal distribution, with peaks located in the extremely high-value region, the number of forests falling into the high-value and medium-value regions of NDVI drops sharply, and little forest land remains to the low-value region. The secondary classification of the forest ecosystem in Jilin province mainly comprises five subclasses, wherein the deciduous coniferous forest accounts for the main body, the distribution area is as high as 79.14%, the area proportion of other subclasses is not large, and the area proportion of the coniferous forest, the evergreen coniferous forest, the deciduous coniferous forest and the deciduous broadleaf bush is 11.43%, 4.74%, 2.83% and 1.84% in sequence; the statistical distribution form of the area of the deciduous coniferous forest is similar to the whole forest ecological system, except for a main peak positioned in an extremely high value area, a secondary peak with lower area occupation ratio is also generated in a middle and high value area; the statistical distribution of the areas of the other four subclasses is shown as a single peak with the majority in the region of very high values, and the distribution of the areas is very small for the other NDVI value regions.
Claims (2)
1. The cooperative description method for the internal type component and attribute component composition structure of the ecosystem is characterized by comprising the following steps of:
firstly, generating attribute raster data of an internal type component of an ecosystem:
carrying out statistical analysis on the subtype component distribution grid data in the ecological system, carrying out spatial superposition and classification on the subtype component distribution grid data and the vegetation index of a research area or ecological parameter grid data, and extracting attribute distribution grid data in each subtype component of the ecological system;
constructing a histogram for representing the internal type component composition structure of the ecosystem by taking the subtype as a horizontal axis and the number of the subtype grids as a vertical axis;
secondly, constructing the frequency distribution of attribute components of the internal types of the ecological system:
according to the grid value statistics of the ecological system attribute distribution grid data, a grouping scheme of the ecological system attribute components is formulated; carrying out statistical calculation on internal attribute raster data of each subclass component of the ecological system to obtain grid frequency of each subclass internal attribute component;
constructing a type internal attribute component frequency distribution diagram representing the type internal attribute component composition structure description in the ecosystem;
and forming a structure distribution diagram formed by the internal type components and the attribute components of the ecosystem by taking the characteristic value of the attribute grouping as a horizontal axis and taking the area occupied by the internal attribute grouping of the subtype as a vertical axis for each subtype of the ecosystem.
2. The method for describing composition structure of type components and attribute components in ecosystem in cooperation with according to claim 1, wherein the grouping interval of the grouping scheme in the second step is 0.02.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104156876A (en) * | 2014-08-21 | 2014-11-19 | 安徽省环境科学研究院 | Technical framework of ecological system supply service and value assessment |
| CN104166782A (en) * | 2014-06-05 | 2014-11-26 | 刘健 | Method for remote sensing and estimating woodland soil organic carbon |
| CN105205330A (en) * | 2015-09-30 | 2015-12-30 | 西安科技大学 | Ecological safety evaluating method based on fishing net model |
| CN106446444A (en) * | 2016-10-14 | 2017-02-22 | 中国科学院遥感与数字地球研究所 | Soil moisture spatial predication research based on Bayes maximum entropy and priori knowledge |
| CN106548017A (en) * | 2016-10-25 | 2017-03-29 | 中国科学院地理科学与资源研究所 | A kind of ecological construction data processing method based on LU data and NDVI data |
| CN107194610A (en) * | 2017-06-16 | 2017-09-22 | 北京师范大学 | Urban ecological safety evaluation method based on configuration process functional mode |
| CN107273820A (en) * | 2017-05-26 | 2017-10-20 | 中国科学院遥感与数字地球研究所 | A kind of Land Cover Classification method and system |
| CN109636171A (en) * | 2018-12-06 | 2019-04-16 | 西安理工大学 | A kind of comprehensive diagnos and risk evaluating method that regional vegetation restores |
-
2020
- 2020-12-02 CN CN202011401088.XA patent/CN112508758B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104166782A (en) * | 2014-06-05 | 2014-11-26 | 刘健 | Method for remote sensing and estimating woodland soil organic carbon |
| CN104156876A (en) * | 2014-08-21 | 2014-11-19 | 安徽省环境科学研究院 | Technical framework of ecological system supply service and value assessment |
| CN105205330A (en) * | 2015-09-30 | 2015-12-30 | 西安科技大学 | Ecological safety evaluating method based on fishing net model |
| CN106446444A (en) * | 2016-10-14 | 2017-02-22 | 中国科学院遥感与数字地球研究所 | Soil moisture spatial predication research based on Bayes maximum entropy and priori knowledge |
| CN106548017A (en) * | 2016-10-25 | 2017-03-29 | 中国科学院地理科学与资源研究所 | A kind of ecological construction data processing method based on LU data and NDVI data |
| CN107273820A (en) * | 2017-05-26 | 2017-10-20 | 中国科学院遥感与数字地球研究所 | A kind of Land Cover Classification method and system |
| CN107194610A (en) * | 2017-06-16 | 2017-09-22 | 北京师范大学 | Urban ecological safety evaluation method based on configuration process functional mode |
| CN109636171A (en) * | 2018-12-06 | 2019-04-16 | 西安理工大学 | A kind of comprehensive diagnos and risk evaluating method that regional vegetation restores |
Non-Patent Citations (7)
| Title |
|---|
| 何云玲等: "基于NDVI云南地区植被生态系统对气候变化的适应性分析", 《生态科学》 * |
| 刘远 等: "MODIS,CYCLOPES和CLASS 3种LAI产品在韩江流域的对比", 《国土资源遥感》 * |
| 吕缀: "基于MODIS数据的陕西省2015年NDVI变化分析", 《甘肃科技》 * |
| 巴音德乐黑等: "基于MODIS NDVI的大兴安岭北坡植被覆盖时空变化特征", 《林业资源管理》 * |
| 张君等: "1982-2013年陕西不同植被类型NDVI变化特征分析", 《干旱区资源与环境》 * |
| 王凉 等: "RS技术在城市化进程中的动态监测及驱动力分析--以浙江省杭州市萧山区为例", 《理工科研》 * |
| 鲁韦坤等: "云南省陆地生态系统和土地利用类型的NDVI时空变化特征", 《气象与环境科学》 * |
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