Establishment method and application of EVI, ESV and EVI-ESV ecological environment quality evaluation models

Abstract

The invention relates to the technical field of resource, workflow, personnel or project management, and discloses a construction method and application of EVI, ESV and EVI-ESV ecological environment quality evaluation models. Ecological vulnerability indexes (EVI) of a research area are calculated through ecological vulnerability evaluation index factor data obtained from a cloud platform in real time, the main crop planting area, the unit area yield and the agricultural product price data of the research area are obtained through local statistics yearbook to calculate the ecological system service standard value equivalent, and the ecological system service standard value equivalent is calculated. And calculating an ecological system service value (ESV) of the research area in combination with a land utilization type. The cloud platform data has real-time and dynamic characteristics, ensures that the ecological vulnerability and ecological system service value evaluation can follow the local environment change, and has enough accuracy. Meanwhile, a sudden change year can be calculated by using data over the years, then whether the sudden change year is matched with a real event or not is compared, and whether the selected evaluation index is reliable or not is judged accordingly, so that it is ensured that the calculation method is reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of resource, workflow, personnel or project management, and in particular to an "EVI-ESV" ecological environment quality evaluation model and its application. Background Art

[0002] The existing evaluation of the ecological environment is mainly based on the natural attributes of the ecosystem, such as sensitivity and resilience, and ignores its socio-economic attributes, that is, the potential ecological supply value. Existing studies believe that the value of ecosystem services has become a core indicator for determining the safety and stability of the ecosystem and achieving sustainable development, providing an important basis for ecological compensation and ecological protection decision-making. This study believes that ecological vulnerability (EVI) and (ecosystem service value) ESV are two interacting ecosystem attributes, which are mutually based and complementary. Generally speaking, areas with high EVI are often vulnerable to damage to ESV; and a decrease in ESV may further increase the degree of ecological vulnerability. Therefore, the establishment of an "EVI-ESV" system comprehensive evaluation system can provide a more comprehensive understanding of the quality and stability of the ecosystem, and provide a more scientific basis for ecological protection and sustainable development. Summary of the invention

[0003] A method for constructing an "EVI" ecological environment quality evaluation model includes the following steps:

[0004] Step 1: Based on the principles of scientificity, feasibility, integrity, and regionality, select a set of indicator factors that can be obtained online in real time and have historical data that affect the ecological fragility of the study area, obtain the real-time and historical data of the indicator factors, reproject each indicator factor into the WGS84 ellipsoid and UTM plane coordinate system, unify the resolution, and perform normalization processing;

[0005] Step 2: Use the principal component analysis (PCA) to perform KMO test and Bartlett's test on all indicator factors. Usually, KMO statistic > 0.6 indicates that PCA analysis is suitable, otherwise, it is not suitable for analysis. At the same time, Bartlett's test corresponding P value < 0.05 also indicates that PCA analysis is suitable.

[0006] Step 3: Determine the principal components. According to the principle of eigenvalue λ>1, the number of principal components that affect the ecological fragility of the study area was extracted, and the cumulative variance contribution rate was calculated. Then the variance contribution rate corresponding to each principal component was divided by the cumulative variance contribution rate to determine the principal component weight;

[0007] Step 4: Based on the rotated principal component loading matrix, analyze the contribution rate of each indicator factor to ecological vulnerability;

[0008] Step 5: Calculate the ecological vulnerability index of previous years through the comprehensive index method;

[0009] Step 6: Normalize the EVI and divide it into five levels with an interval of 0.2: I-slightly vulnerable, II-mildly vulnerable, III-moderately vulnerable, IV-severely vulnerable, and V-extremely vulnerable, and perform zoning and graded statistics.

[0010] A method for constructing an "ESV" ecological environment quality evaluation model includes the following steps:

[0011] Step 1: Obtain historical data on the planting area, unit area yield, and average price of the main crops in the study area. Step 2: Refer to the revised method of the equivalent value of unit area service of China's terrestrial ecosystem proposed by Xie Gaodi et al.: The economic value of an ecological service value equivalent factor is 1 / 7 of the unit area grain yield. Calculate the economic value of grain per unit area of ​​farmland ecosystem;

[0012] Step 3: Calculate the ecosystem service value of different land use types;

[0013] Step 4: Use the natural break point classification method to divide the ecosystem service value into five levels, and perform zoning and classification statistics.

[0014] A method for constructing an "EVI-ESV" ecological environment quality evaluation model, including an existing "EVI" evaluation model and an existing "ESV" evaluation model, includes the following steps:

[0015] Step 1: Based on data accuracy and model precision, combined with the study area environment, regional characteristics, ecological zoning, and data calculation factors, grid division of appropriate size is performed.

[0016] Step 2: Based on the two dimensions of EVI and ESV, the Z-score method was used to standardize the study area grid, where the X-axis represents the standardized ESV and the Y-axis represents the standardized EVI. Based on this, four ecological quadrants were divided in the study area.

[0017] An application of the "EVI-ESV" ecological environment quality evaluation model uses the EVI model to monitor the ecological vulnerability of the study area in real time, and uses the ESV model to monitor the supply of ecological service value.

[0018] The ecological zoning results provide targeted scientific advice.

[0019] An "EVI-ESV" ecological environment quality evaluation model was applied. After clarifying the spatial differentiation characteristics of ecological vulnerability and ecosystem service value in the study area, the factor detection module and interaction detection module of the geographic detector were used to quantitatively analyze the impact of each indicator factor and the interaction between factors on the spatial pattern of EVI and EVS. When carrying out ecological protection and restoration, the factors with the highest ranking of single factor driving force and the factors with the highest ranking of interactive synergy were given priority for intervention. DETAILED DESCRIPTION

[0020] 1. Through field investigation of the upper reaches of the Dadu River, highlighting the special geographical environment and main production methods of the region, nine indicators including humidity, vegetation coverage, surface temperature, slope, terrain undulation, gross national product, population, land use type, and grazing intensity were selected to construct an ecological vulnerability assessment model for the upper reaches of the Dadu River. The data sources are as follows: The data on vegetation coverage, surface temperature, land use type, population, and gross national product used in this study are from the Resource and Environmental Science Data Platform ( https: / / www.resdc.cn / ), with a resolution of 1km. Humidity data comes from NASA ( https: / / worldview.earthdata.nasa.gov / ), obtained through MODIS inversion with a resolution of 1 km. DEM data comes from the Geospatial Data Cloud (https: / / www.gscloud.cn / ) with a resolution of 30 m, and slope and terrain relief data are generated using ArcGIS software. The main crop planting area and unit area yield in the study area are from the Aba Statistical Yearbook and the Ganzi Statistical Yearbook. Agricultural product prices are from the National Compilation of Agricultural Product Cost and Benefit Data. A total of data from 2000 to 2020 were obtained.

[0021] 2. After normalizing the 9 indicators, the spatial principal component analysis method was used to determine the 5 principal components and weights, and then the ecological vulnerability index of the upper reaches of the Dadu River from 2000 to 2020 was calculated according to the comprehensive index method. The EVI was normalized and divided into 5 levels with an interval of 0.2: Ⅰ-slightly vulnerable, Ⅱ-mildly vulnerable; Ⅲ-moderately vulnerable; Ⅳ-severely vulnerable; Ⅴ-extremely vulnerable. The results show that the overall ecological vulnerability of the upper reaches of the Dadu River has been greatly improved. The area of ​​slightly vulnerable and slightly vulnerable areas has increased year by year, the area of ​​moderately vulnerable and severely vulnerable areas has shown a downward trend, and the scope of extremely vulnerable areas has almost shrunk to 0. This shows that since 2011, with the implementation of a series of national ecological protection and environmental construction projects, forests and grasslands in the basin have been protected and restored on a large scale, and the overall ecological environment has improved. However, after 2015, the ecological environment in some areas has deteriorated.

[0022] 3. Based on the planting area, unit area yield and average price of the main crops (wheat, corn, potato and highland barley) in the upper reaches of the Dadu River, the ecosystem service supply value of the upper reaches of the Dadu River was calculated from 2000 to 2020. The results show that the ecosystem service value of the upper reaches of the Dadu River has generally increased, with the largest increase from 2005 to 2010, and then the growth rate has slowed down. In the past 20 years, grassland has the highest proportion of all land use types and the highest ecological supply value, which provides convenient conditions for grazing. Overall, the ecological construction measures implemented in the upper reaches of the Dadu River in recent years have had a certain positive impact on the restoration of the ecological environment in the area. However, with the rapid development of social economy, land use patterns are developing in a dangerous direction, increasing the reclamation of cultivated land and the continuous expansion of urban construction land, which has had varying degrees of negative impact on the ecological environment of the area and neighboring areas.

[0023] 4. The ecological vulnerability and ecosystem supply values ​​of the upper reaches of the Dadu River were substituted into the above-mentioned Z-score method standardization calculation formula, and the upper reaches of the Dadu River were divided into four different ecological quadrants according to the calculation results. The results show that the study area is mainly composed of high vulnerability-low supply areas (Ⅱ) and low vulnerability-low supply areas (Ⅲ), among which the low vulnerability-low supply area (Ⅲ) accounts for the largest proportion, indicating that the mismatch between EVI and ESV is prominent, which brings certain risks to the stability of the ecological environment. From a socio-economic perspective, the function of providing ecological products and services for human society and the earth's life system is still relatively weak, and the quality and stability of the ecological environment are not high. Therefore, taking corresponding measures to give play to the low vulnerability advantages of Ⅲ and enhance the supply value of ecosystem services is an important way to promote the sustainable development of the study area.

[0024] 5. After clarifying the spatial differentiation characteristics of ecological fragility and ecosystem service value in the study area, the factor detection module and interactive detection module of the geographic detector were used to quantitatively analyze the impact of each indicator factor and the interaction between factors on the spatial pattern of EVI and EVS. The results showed that during the entire study period, the main driving factors affecting the spatial differentiation of EVI were grazing intensity, wetlands, vegetation coverage, surface temperature and other factors, and the main driving factors affecting the spatial differentiation of ESV were land use type and population. The interaction between the factors was stronger than the single factor effect, which confirmed that ecological quality and stability is a complex multi-factor comprehensive process. Therefore, adhering to the implementation of ecological protection and construction measures, strictly controlling grazing intensity, and improving the value transformation of ecosystem cultural service products are effective means to promote the sustainable development of the study area.

Claims

1. A method for constructing an "EVI" ecological environment quality evaluation model, characterized in that: The following steps are involved: Step 1: Based on the principles of scientificity, feasibility, integrity, and regionality, select a set of indicator factors that can be obtained online in real time and have historical data that affect the ecological fragility of the study area, obtain the real-time and historical data of the indicator factors, reproject each indicator factor into the WGS84 ellipsoid and UTM plane coordinate system, unify the resolution, and perform normalization processing; Step 2: Use the principal component analysis (PCA) to perform KMO test and Bartlett's test on all indicator factors. Usually, KMO statistic > 0.6 indicates that PCA analysis is suitable, otherwise, it is not suitable for analysis. At the same time, Bartlett's test corresponding P value < 0.05 also indicates that PCA analysis is suitable. Step 3: Determine the principal components. According to the principle of eigenvalue λ>1, the number of principal components that affect the ecological fragility of the study area was extracted, and the cumulative variance contribution rate was calculated. Then the variance contribution rate corresponding to each principal component was divided by the cumulative variance contribution rate to determine the principal component weight; Step 4: Based on the rotated principal component loading matrix, analyze the contribution rate of each indicator factor to ecological vulnerability; Step 5: Calculate the ecological vulnerability index of previous years through the comprehensive index method; Step 6: Normalize the EVI and divide it into five levels with an interval of 0.2: I-slightly vulnerable, II-mildly vulnerable, III-moderately vulnerable, IV-severely vulnerable, and V-extremely vulnerable, and perform zoning and graded statistics.

2. A method for constructing an "ESV" ecological environment quality evaluation model, characterized in that: The following steps are involved: Step 1: Obtain historical data on the planting area, unit area yield, and average price of the main crops in the study area. Step 2: Refer to the revised method of the equivalent value of unit area service of China's terrestrial ecosystem proposed by Xie Gaodi et al.: The economic value of an ecological service value equivalent factor is 1 / 7 of the unit area grain yield. Calculate the economic value of grain per unit area of ​​farmland ecosystem; Step 3: Calculate the ecosystem service value of different land use types; Step 4: Use the natural break point classification method to divide the ecosystem service value into five levels, and perform zoning and classification statistics.

3. A method for constructing an "EVI-ESV" ecological environment quality evaluation model, comprising the "EVI" evaluation model described in claim 1 and the "ESV" evaluation model described in claim 2, characterized in that: The following steps are involved: Step 1: Based on data accuracy and model precision, combined with the study area environment, regional characteristics, ecological zoning, and data calculation factors, grid division of appropriate size is performed. Step 2: Based on the two dimensions of EVI and ESV, the Z-score method was used to standardize the study area grid, where the X-axis represents the standardized ESV and the Y-axis represents the standardized EVI. Based on this, four ecological quadrants were divided in the study area.

4. An application of the "EVI-ESV" ecological environment quality evaluation model, characterized in that: The EVI model is used to monitor the ecological vulnerability of the study area in real time, and the ESV model is used to monitor the supply of ecological service value. Based on the results of the "EVI-ESV" ecological zoning, scientific suggestions are provided in a targeted manner.

5. The application of the "EVI-ESV" ecological environment quality evaluation model as claimed in claim 4 is characterized by: After clarifying the spatial differentiation characteristics of ecological vulnerability and ecosystem service value in the study area, the factor detection module and interaction detection module of the geographic detector were used to quantitatively analyze the impact of each indicator factor and the interaction between factors on the spatial pattern of EVI and EVS. When carrying out ecological protection and restoration, the factors with the highest ranking of single factor driving force and the factors with the highest ranking of interactive synergy should be intervened first.