Evaluation method for ecological environment vulnerability of loess area

Abstract

The invention discloses a loess area ecological environment vulnerability evaluation method, and relates to the technical field of land ecological evaluation, and the method comprises the following steps: determining a specific loess area, defining the specific boundary and key indexes of the loess area, analyzing the main difference of different loess areas, collecting the basic data of the loess area of the corresponding area, and calculating the vulnerability of the loess area. The method comprises the steps of dividing basic data into real-time data and historical data, preprocessing the real-time data and the historical data, extracting ecological environment characteristics of the preprocessed real-time data, constructing a vulnerability evaluation model in combination with the historical data, and obtaining an ecological sensitivity index, an ecological restoration index and an ecological service function index. According to the method, a long-term and dynamic monitoring system is established, comprehensive analysis of real-time data and historical data is utilized, the change trend of the vulnerability of the ecological environment is tracked in real time, the change trend of the ecological environment can be found in time, potential ecological risks can be predicted, and countermeasures can be taken in advance.

Description

Technical Field

[0001] The invention relates to the technical field of land ecological assessment, and in particular to a method for assessing the vulnerability of the ecological environment in a loess region. Background Art

[0002] The Loess region, especially the Loess Plateau, is subject to natural conditions such as loose soil, concentrated rainstorms, and broken terrain, coupled with the continuous interference of human activities such as deforestation and overgrazing, which has led to aggravated soil erosion, and the area of ​​land desertification and salinization has increased year by year. These ecological and environmental problems not only directly threaten the social and economic development of the Loess region, restrict agricultural production and the improvement of residents' quality of life, but also have a profound impact on the global ecological environment by affecting processes such as hydrological cycle and climate change. Therefore, the improvement and governance of the ecological environment in the Loess region is not only responsible for the well-being of the local people, but also an important part of maintaining global ecological security. With the continuous advancement of ecological civilization construction and the continuous progress of science and technology, we can monitor and evaluate the ecological environment in the Loess region through the application of modern scientific and technological means such as remote sensing technology, geographic information system (GIS), and big data, so as to fully and deeply understand the vulnerability characteristics, spatiotemporal evolution laws and driving mechanisms of the ecological environment in the Loess region, and provide scientific basis and decision-making reference for the protection and governance of the ecological environment in the region.

[0003] In the existing technology, the Loess region has complex and changeable ecological and environmental characteristics, and there are significant differences between different regions, which brings major challenges to the monitoring and assessment of ecological and environmental fragility. The existing evaluation methods are often difficult to fully and accurately adapt to these diverse characteristics, which in turn affects the accuracy and reliability of the evaluation data. Therefore, how to carry out targeted monitoring and assessment of the vulnerability of the loess ecological environment in different regions has become an important issue that needs to be solved urgently. Summary of the invention

[0004] The present invention aims to provide a method for evaluating the ecological environment vulnerability in the Loess Plateau region to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for evaluating the ecological environment vulnerability in a loess region comprises the following steps:

[0007] Step 1: determine the specific loess region, define the specific boundaries and key indicators of the loess region, and analyze the main differences between loess regions in different regions;

[0008] Step 2, collect basic data of the loess region in the corresponding area, divide the basic data into real-time data and historical data, and pre-process the real-time data and historical data;

[0009] Step 3: Extract the ecological and environmental characteristics of the real-time data after preprocessing, and build a vulnerability assessment model based on historical data to obtain the ecological sensitivity index, ecological resilience index, and ecological service function index to analyze the main influencing factors and regional differences of the ecological and environmental vulnerability in the Loess Plateau region;

[0010] Step 4: Obtain the ecological environmental vulnerability assessment coefficients between different loess regions based on the obtained ecological sensitivity index, ecological resilience index, and ecological service function index, and classify the ecological environmental vulnerability of the loess regions into different levels based on the basic data, and set assessment thresholds for different vulnerability levels;

[0011] Step 5: Combine the assessment threshold with the vulnerability assessment model for analysis, identify the spatial distribution characteristics and change patterns of vulnerability in the Loess Plateau region, predict future change trends in the Loess Plateau region, assess potential ecological risks under different scenarios, and obtain an evaluation report.

[0012] A further improvement of the technical solution of the present invention is that the process of analyzing the main differences between loess regions in different regions is:

[0013] Step 101, collect geographical, geological and climate data, including maps, geological reports, climate statistics, etc., to determine the geographical scope of the Loess Plateau;

[0014] Step 102, based on the geographical scope of the loess region, obtain the ecological and environmental characteristics of the loess region, such as soil type, vegetation type, hydrological characteristics, etc., and determine key indicators of its soil erosion, vegetation coverage, climate conditions and topography;

[0015] Step 103, based on the ecological and environmental characteristics of the Loess Plateau, GIS technology is used to perform terrain analysis, land use classification, and climate zone division, and comparative analysis is performed on the Loess Plateaus in different regions to identify differences and causes between regions, such as soil type, degree of soil erosion, intensity of human activities, etc.

[0016] A further improvement of the technical solution of the present invention is that the process of preprocessing the real-time data and historical data is as follows:

[0017] Step 201, real-time data is obtained through meteorological stations, satellites, hydrological monitoring stations and soil monitoring stations, wherein the real-time data includes meteorological data, remote sensing data, hydrological data and soil data.

[0018] Through the weather station network, meteorological parameters such as precipitation, temperature, humidity, wind speed, and wind direction are collected in real time. High-resolution remote sensing images are regularly acquired using satellites to monitor real-time changes in vegetation coverage, soil moisture, and surface temperature in the Loess Plateau. Hydrological monitoring stations collect real-time monitoring data on rivers, reservoirs, and groundwater levels, as well as real-time monitoring data on soil erosion. Soil monitoring stations collect real-time soil parameter data such as soil temperature, humidity, pH value, and nutrient content.

[0019] Step 202, and obtain historical data of the environment in the Loess Plateau region from the public database of the land management department, where the historical data includes climate data, vegetation data, land use data and soil erosion data

[0020] Climate data include time series data of climate parameters such as precipitation, temperature, and humidity; vegetation data include vegetation condition data such as historical vegetation cover and vegetation type; land use data include historical land use types and changes; soil erosion data include historical soil erosion conditions and erosion rates;

[0021] Step 203, preprocessing the collected real-time data and historical data, wherein the preprocessing includes data cleaning, data integration, format unification, data fusion, data standardization, unit conversion and normalization, and geo-referencing data alignment of the real-time data and historical data to ensure that all data are in the same coordinate system and projection, and on a unified time scale, and at the same time, a database and data update mechanism are established to reflect the latest environmental changes.

[0022] A further improvement of the technical solution of the present invention is that the process of analyzing the main influencing factors and regional differences of the ecological environment vulnerability in the loess region is:

[0023] Step 301, extracting ecological sensitivity features, ecological resilience features, and ecological resilience features from real-time data, analyzing the impact of remote sensing data on erosion sensitivity, such as slope and aspect, assessing the availability of hydrological data and the resilience of the ecosystem, and analyzing the pressure of meteorological data on the ecosystem, such as temperature, precipitation, extreme climate events, etc.;

[0024] Step 302, constructing a vulnerability assessment model based on the extracted ecological environment characteristics and relevant data of historical data to analyze the vulnerability of the ecological environment in the Loess Plateau region;

[0025] Step 303, using the vulnerability assessment model and combining the ecological and environmental characteristics of the pre-processed real-time data, respectively calculate the ecological sensitivity index, ecological resilience index and ecological service function index, analyze the main influencing factors of the ecological and environmental vulnerability in the Loess Region, such as climate drought, soil erosion, human activities, etc., and identify the changing trend of the ecological and environmental vulnerability in the Loess Region;

[0026] Step 304 , compare the ecological sensitivity characteristics, ecological resilience characteristics and ecological resilience characteristics of different loess regions, and analyze the differences and causes of ecological environmental fragility among regions.

[0027] A further improvement of the technical solution of the present invention is that the calculation formula of the ecological sensitivity index is:

[0028]

[0029] Among them, ESI is the ecological sensitivity index, S i is the observed value of the i-th ecological sensitivity index, max(S) is the maximum value of all ecological sensitivity indexes, n is the total number of ecological sensitivity indexes, α is the coefficient reflecting the effect of precipitation on sensitivity, and PT is the threshold of precipitation;

[0030] The calculation formula of the ecological resilience index is:

[0031]

[0032] Among them, ERI is the ecological resilience index, R j is the observed value of the jth ecological resilience indicator, R is the average value of all ecological resilience indicators, m is the total number of ecological resilience indicators, β is an index reflecting the importance of ecological resilience indicators, VG is the vegetation coverage, VG max is the maximum value of vegetation coverage;

[0033] The calculation formula of the ecosystem service function index is:

[0034]

[0035] Among them, ESFI is the ecological service function index, F k is the observed value of the kth ecological service function, F st is the standard value of ecological service function, p is the total number of ecological service function indicators, γ is an index reflecting the importance of ecological service function, PD is the pressure of human activities, PD max It is the maximum value of human activity pressure.

[0036] A further improvement of the technical solution of the present invention is that the process of setting evaluation thresholds for different levels is:

[0037] Step 401, integrating the pre-processed historical data, combining the ecological sensitivity index, the ecological resilience index, and the ecological service function index, and analyzing the correlation between the historical data and soil erosion data and the ecological sensitivity index, the ecological resilience index, and the ecological service function index;

[0038] Step 402, inputting the ecological sensitivity index, ecological resilience index and ecological service function index into the vulnerability assessment model for weighted calculation to obtain an ecological environment vulnerability assessment coefficient;

[0039] Step 403, according to the main influencing factors and regional differences of the ecological environment vulnerability in the loess region, the loess region is divided into different vulnerability levels, namely low vulnerability level, medium vulnerability level and high vulnerability level;

[0040] Step 404, and match the determined different vulnerability levels with the results of the ecological environmental vulnerability assessment coefficient, and set corresponding assessment thresholds for different vulnerability levels; apply the final determined level classification and assessment thresholds to the ecological environmental vulnerability assessment of different areas in the Loess Plateau to verify their rationality and effectiveness, and continuously improve and optimize the vulnerability assessment model and method.

[0041] A further improvement of the technical solution of the present invention is that the calculation formula of the ecological environment vulnerability assessment coefficient is:

[0042]

[0043] Among them, EVI is the ecological environment vulnerability assessment coefficient, S i is the observed value of the i-th ecological sensitivity index, R j is the observed value of the jth ecological resilience index, ESFI is the ecological service function index, R std is the standard value of ecological resilience, n is the total number of ecological sensitivity indicators, m is the total number of ecological resilience indicators, δ is the index reflecting the impact of ecological sensitivity indicators on vulnerability, ∈ is the nonlinear impact of ecological sensitivity index on vulnerability, ζ is used to adjust the root index of the summation result, ESFI th is the safety threshold of the Ecosystem Service Index, ESFI max is the maximum value of the ecosystem service function index, and θ reflects the impact of the ecosystem service function index on vulnerability.

[0044] A further improvement of the technical solution of the present invention is that the evaluation threshold range of the vulnerability level and its classification is:

[0045] Low vulnerability level: EVI ≤ T1

[0046] Medium vulnerability level: T1 <EVI≤T2

[0047] High vulnerability level: EVI>T2.

[0048] A further improvement of the technical solution of the present invention is that the process of obtaining the evaluation report is as follows:

[0049] Step 501, input the pre-processed real-time data and historical data into the vulnerability assessment model, calculate the ecological environment vulnerability coefficient of each region and compare it with the level threshold of the loess region;

[0050] Step 502, using GIS technology, visualize the calculated ecological environmental vulnerability coefficient on a map of the Loess Plateau, analyze the ecological environmental vulnerability coefficient values ​​of different regions, and identify the spatial distribution pattern and hot spots of vulnerability;

[0051] Step 503, combining historical data, analyzing the time-dependent change trend of the vulnerability level, observing the change speed and direction of the vulnerability level by drawing a time series graph, analyzing the driving factors that cause the vulnerability change, and applying a prediction model to predict the future change trend of the vulnerability level based on the change trend and driving factors;

[0052] Step 504, based on the predicted trend of change, identify potential ecological risks faced under different scenarios, such as increased soil erosion, vegetation degradation, water shortage, etc., and evaluate the identified potential ecological risks, including the possibility of risk occurrence, degree of impact and scope of impact, and propose corresponding risk response measures and suggestions based on the evaluation results, such as strengthening ecological restoration, optimizing land use structure, and improving water resource utilization efficiency.

[0053] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0054] 1. The present invention provides an ecological environmental vulnerability assessment method for the Loess Plateau. By deeply analyzing the ecological environmental characteristics, topography, climate type, vegetation coverage, soil type and intensity of human activities in different regions of the Loess Plateau, a customized assessment index system and weight distribution are designed to ensure that the assessment process can comprehensively cover and accurately reflect the uniqueness and differences of each region, and reveal the unique ecological sensitivity and resilience of each region.

[0055] 2. The present invention provides a method for evaluating the ecological environment vulnerability in the Loess Plateau region. By establishing a long-term and dynamic monitoring system and utilizing comprehensive analysis of real-time data and historical data, the changing trend of the ecological environment vulnerability can be tracked in real time. It can timely discover the changing trends of the ecological environment, predict potential ecological risks, and take countermeasures in advance.

[0056] 3. The present invention provides a method for evaluating the ecological and environmental fragility of the Loess Plateau. By combining real-time data and historical data, the method accurately evaluates the ecological and environmental fragility of various regions in the Loess Plateau and clearly displays the data on a map, so as to quickly identify hot spots with higher vulnerability and provide a scientific basis for the rational allocation of resources. At the same time, by adjusting the evaluation model and indicator weights to adapt to the specific conditions of different regions, the evaluation results are closer to reality, thereby improving the accuracy and reliability of monitoring and evaluation.

[0057] 4. The present invention provides an ecological environment vulnerability assessment method for the Loess Plateau region, which is helpful for the Loess Plateau region to achieve sustainable development. Through assessment, ecosystems degraded by human activities or natural factors can be identified, and preventive or mitigation measures can be taken, which not only helps to protect biodiversity and maintain ecological balance, but also ensures the sustainable use of natural resources and supports the economic development of local communities. In addition, the method can provide guidance for agriculture, tourism and other industries that rely on the natural environment to reduce the negative impact on the ecosystem. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0059] Figure 1 is a flow chart of the method of the present invention;

[0060] Figure 2 This is a flow chart for obtaining the ecological sensitivity index, ecological resilience index and ecological service function index of the present invention;

[0061] Figure 3 The present invention is a flowchart for obtaining the ecological environment vulnerability assessment coefficient. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] Examples, such as Figure 1-3 As shown, the present invention provides a method for evaluating the ecological environment vulnerability in the loess region, comprising the following steps:

[0064] Step 1: Determine the specific loess region, define the specific boundaries and key indicators of the loess region, and analyze the main differences between loess regions in different regions. The process of analyzing the main differences between loess regions in different regions is as follows: collect geographical, geological and climatic data, including maps, geological reports, climate statistics, etc., determine the geographical scope of the loess region, obtain the ecological and environmental characteristics of the loess region based on the geographical scope of the loess region, such as soil type, vegetation type, hydrological characteristics, etc., determine its soil erosion degree, vegetation coverage, climatic conditions and key indicators of topography and landforms, use GIS technology to analyze terrain, classify land use, and divide climate regions according to the ecological and environmental characteristics of the loess region, and conduct comparative analysis of loess regions in different regions to identify differences and causes between regions, such as soil type, degree of soil and water loss, intensity of human activities, etc.;

[0065] Step 2, collect basic data of the loess area in the corresponding area, divide the basic data into real-time data and historical data, and pre-process the real-time data and historical data. The process of pre-processing the real-time data and historical data is as follows: obtain real-time data through meteorological stations, satellites, hydrological monitoring stations and soil monitoring stations, where real-time data includes meteorological data, remote sensing data, hydrological data and soil data. Collect meteorological parameters such as precipitation, temperature, humidity, wind speed and wind direction in real time through the meteorological station network. Use satellites to regularly obtain high-resolution remote sensing images to monitor real-time changes in vegetation coverage, soil moisture, surface temperature, etc. in the loess area. Collect real-time monitoring data of rivers, reservoirs and groundwater levels, as well as real-time monitoring data of soil erosion through hydrological monitoring stations. Collect soil temperature, humidity, pH value, nutrient content and other soil parameter data through soil monitoring stations; and obtain public data from land management departments. The historical data of the environment in the Loess Plateau region are obtained from the database, where the historical data include climate data, vegetation data, land use data and soil erosion data. The climate data include time series data of climate parameters such as precipitation, temperature and humidity. The vegetation data include vegetation condition data such as historical vegetation coverage and vegetation type. The land use data include information such as historical land use type and changes. The soil erosion data include historical soil erosion conditions and erosion rates. The collected real-time data and historical data are preprocessed, where the preprocessing includes data cleaning, data integration, format unification, data fusion, data standardization, unit conversion and normalization. The real-time data and historical data are georeferenced and aligned to ensure that all data are in the same coordinate system and projection, and on a unified time scale. At the same time, a database and data update mechanism are established to reflect the latest environmental changes.

[0066] Step 3, extract the ecological and environmental characteristics of the real-time data after preprocessing, and build a vulnerability assessment model in combination with historical data to obtain the ecological sensitivity index, ecological resilience index, and ecological service function index to analyze the main influencing factors and regional differences in the ecological and environmental vulnerability of the Loess Plateau region; the process of analyzing the main influencing factors and regional differences in the ecological and environmental vulnerability of the Loess Plateau region is as follows: extract the ecological sensitivity characteristics, ecological resilience characteristics, and ecological resilience characteristics from the real-time data, analyze the impact of remote sensing data on erosion sensitivity, such as slope and slope aspect, evaluate the availability of hydrological data and the resilience of the ecosystem, and analyze the pressure of meteorological data on the ecosystem, such as temperature, precipitation, and polarity. end climate events, etc., and based on the extracted ecological and environmental characteristics and relevant data of historical data, a vulnerability assessment model is constructed to analyze the vulnerability of the ecological environment in the Loess Plateau region. The vulnerability assessment model is used in combination with the ecological and environmental characteristics of the real-time data after preprocessing to calculate the ecological sensitivity index, ecological resilience index and ecological service function index, respectively, to analyze the main influencing factors of the ecological and environmental vulnerability in the Loess Plateau region, such as climate drought, soil erosion, human activities, etc., and to identify the changing trend of the ecological and environmental vulnerability in the Loess Plateau region. The ecological sensitivity characteristics, ecological resilience characteristics and ecological resilience characteristics of different Loess Plateau regions are compared, and the differences and causes of ecological and environmental vulnerability between regions are analyzed;

[0067] The calculation formula of ecological sensitivity index is:

[0068]

[0069] Among them, ESI is the ecological sensitivity index, S i is the observed value of the i-th ecological sensitivity index, max(S) is the maximum value of all ecological sensitivity indexes, n is the total number of ecological sensitivity indexes, α is the coefficient reflecting the effect of precipitation on sensitivity, and PT is the threshold of precipitation;

[0070] The calculation formula of the ecological resilience index is:

[0071]

[0072] Among them, ERI is the ecological resilience index, R j is the observed value of the jth ecological resilience indicator, is the average value of all ecological resilience indicators, m is the total number of ecological resilience indicators, β is an index reflecting the importance of ecological resilience indicators, VG is the vegetation coverage, VG max is the maximum value of vegetation coverage;

[0073] The calculation formula of the ecological service function index is:

[0074]

[0075] Among them, ESFI is the ecological service function index, F k is the observed value of the kth ecological service function, F st is the standard value of ecological service function, p is the total number of ecological service function indicators, γ is an index reflecting the importance of ecological service function, PD is the pressure of human activities, PD max is the maximum value of human activity pressure;

[0076] Step 4: According to the obtained ecological sensitivity index, ecological resilience index and ecological service function index, the ecological environment vulnerability assessment coefficients of different loess regions are obtained, and the vulnerability of the ecological environment in the loess regions is graded in combination with the basic data. At the same time, assessment thresholds are set for different vulnerability levels. The process of setting assessment thresholds for different levels is as follows: integrating the pre-processed historical data, combining the ecological sensitivity index, ecological resilience index and ecological service function index, analyzing the correlation between historical data and soil erosion data and the ecological sensitivity index, ecological resilience index and ecological service function index, and The ecological service function index is input into the vulnerability assessment model for weighted calculation to obtain the ecological environmental vulnerability assessment coefficient. According to the main influencing factors and regional differences of the ecological environmental vulnerability in the Loess Plateau, the Loess Plateau is divided into different vulnerability levels, namely low vulnerability level, medium vulnerability level and high vulnerability level. The determined different vulnerability levels are matched with the results of the ecological environmental vulnerability assessment coefficient, and corresponding assessment thresholds are set for different vulnerability levels. The final grade division and assessment threshold are applied to the ecological environmental vulnerability assessment of different areas in the Loess Plateau to verify its rationality and effectiveness, and the vulnerability assessment model and method are continuously improved and optimized.

[0077] The calculation formula of the ecological environment vulnerability assessment coefficient is:

[0078]

[0079] Among them, EVI is the ecological environment vulnerability assessment coefficient, S i is the observed value of the i-th ecological sensitivity index, R j is the observed value of the jth ecological resilience index, ESFI is the ecological service function index, R std is the standard value of ecological resilience, n is the total number of ecological sensitivity indicators, m is the total number of ecological resilience indicators, δ is the index reflecting the impact of ecological sensitivity indicators on vulnerability, ∈ is the nonlinear impact of ecological sensitivity index on vulnerability, ζ is used to adjust the root index of the summation result, ESFI th is the safety threshold of the Ecosystem Service Index, ESFI maxis the maximum value of the ecosystem service function index, and θ reflects the impact of the ecosystem service function index on vulnerability;

[0080] The assessment threshold ranges for vulnerability levels and their classification are:

[0081] Low vulnerability level: EVI ≤ T1

[0082] Medium vulnerability level: T1 <EVI≤T2

[0083] High vulnerability level: EVI>T2;

[0084] Step 5: Combine the assessment threshold with the vulnerability assessment model for analysis, identify the spatial distribution characteristics and change patterns of vulnerability in the Loess Plateau region, predict future change trends in the Loess Plateau region, assess potential ecological risks under different scenarios, and obtain an assessment report. The process of obtaining the assessment report is as follows: input the preprocessed real-time data and historical data into the vulnerability assessment model, calculate the ecological environmental vulnerability coefficient of each region and compare it with the grade threshold of the Loess Plateau region, use GIS technology to visualize the calculated ecological environmental vulnerability coefficient on the map of the Loess Plateau region, analyze the ecological environmental vulnerability coefficient values ​​of different regions, identify the spatial distribution patterns and hot spots of vulnerability, and combine historical data to obtain the ecological environmental vulnerability coefficient. Based on the data, we analyze the changing trend of vulnerability levels over time, observe the changing speed and direction of vulnerability levels by drawing time series graphs, analyze the driving factors that lead to changes in vulnerability, and apply prediction models to predict the changing trend of vulnerability levels in the future based on the changing trends and driving factors. Based on the predicted changing trends, we identify potential ecological risks faced under different scenarios, such as increased soil erosion, vegetation degradation, water shortage, etc., and evaluate the identified potential ecological risks, including the possibility of risk occurrence, degree of impact and scope of impact. At the same time, based on the evaluation results, we put forward corresponding risk response measures and suggestions, such as strengthening ecological restoration, optimizing land use structure, and improving water resource utilization efficiency.

[0085] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for evaluating the ecological environment vulnerability in the Loess Plateau region, characterized by: The following steps are involved: Step 1: determine the specific loess region, define the specific boundaries and key indicators of the loess region, and analyze the main differences between loess regions in different regions; Step 2, collect basic data of the loess region in the corresponding area, divide the basic data into real-time data and historical data, and pre-process the real-time data and historical data; Step 3: Extract the ecological and environmental characteristics of the real-time data after preprocessing, and build a vulnerability assessment model based on historical data to obtain the ecological sensitivity index, ecological resilience index, and ecological service function index to analyze the main influencing factors and regional differences of the ecological and environmental vulnerability in the Loess Plateau region; Step 4: Obtain the ecological environmental vulnerability assessment coefficients between different loess regions based on the obtained ecological sensitivity index, ecological resilience index, and ecological service function index, and classify the ecological environmental vulnerability of the loess regions into different levels based on the basic data, and set assessment thresholds for different vulnerability levels; Step 5: Combine the assessment threshold with the vulnerability assessment model for analysis, identify the spatial distribution characteristics and change patterns of vulnerability in the Loess Plateau region, predict future change trends in the Loess Plateau region, assess potential ecological risks under different scenarios, and obtain an evaluation report.

2. The method for evaluating ecological environment vulnerability in loess regions according to claim 1 is characterized by: The process of analyzing the main differences in loess areas in different regions is: Step 101, collecting geographical, geological and climatic data to determine the geographical scope of the Loess Plateau; Step 102, based on the geographical scope of the loess region, obtain the ecological and environmental characteristics of the loess region and determine key indicators of its soil erosion, vegetation coverage, climate conditions and topography; Step 103, based on the ecological and environmental characteristics of the loess region, GIS technology is used to perform terrain analysis, land use classification, and climate zone division, and a comparative analysis is performed on the loess regions in different regions to identify the differences and causes between regions.

3. The method for evaluating the ecological environment vulnerability in the loess region according to claim 2 is characterized by: The process of preprocessing real-time data and historical data is as follows: Step 201, acquiring real-time data through meteorological stations, satellites, hydrological monitoring stations and soil monitoring stations, wherein the real-time data includes meteorological data, remote sensing data, hydrological data and soil data; Step 202, and obtaining historical data of the environment of the Loess Region from a public database of the land management department, wherein the historical data includes climate data, vegetation data, land use data and soil erosion data; Step 203 , pre-processing the collected real-time data and historical data, and performing geo-referenced data alignment on the real-time data and historical data, and establishing a database and data update mechanism.

4. The method for evaluating ecological environment vulnerability in loess regions according to claim 3 is characterized by: The process of analyzing the main influencing factors and regional differences of ecological environmental vulnerability in the Loess Plateau region is as follows: Step 301, extracting ecological sensitivity features, ecological resilience features, and ecological resilience features from real-time data, analyzing the impact of remote sensing data on erosion sensitivity, assessing the availability of hydrological data and the resilience of the ecosystem, and analyzing the pressure of meteorological data on the ecosystem; Step 302, constructing a vulnerability assessment model based on the extracted ecological environment characteristics and relevant data of historical data to analyze the vulnerability of the ecological environment in the Loess Plateau region; Step 303, using the vulnerability assessment model and combining the ecological and environmental characteristics of the pre-processed real-time data, respectively calculate the ecological sensitivity index, ecological resilience index and ecological service function index, analyze the main influencing factors of the ecological and environmental vulnerability of the Loess Region, and identify the changing trend of the ecological and environmental vulnerability of the Loess Region; Step 304 , compare the ecological sensitivity characteristics, ecological resilience characteristics and ecological resilience characteristics of different loess regions, and analyze the differences and causes of ecological environmental fragility among regions.

5. The method for evaluating ecological environment vulnerability in loess regions according to claim 4 is characterized by: The calculation formula of the ecological sensitivity index is: Among them, ESI is the ecological sensitivity index, S i is the observed value of the i-th ecological sensitivity index, max(S) is the maximum value of all ecological sensitivity indexes, n is the total number of ecological sensitivity indexes, and PT is the threshold of precipitation; The calculation formula of the ecological resilience index is: Among them, ERI is the ecological resilience index, R j is the observed value of the jth ecological resilience indicator, is the average value of all ecological resilience indicators, m is the total number of ecological resilience indicators, VG is the vegetation coverage, VG max is the maximum value of vegetation coverage; The calculation formula of the ecosystem service function index is: Among them, ESFI is the ecological service function index, F k is the observed value of the kth ecological service function, F st is the standard value of ecological service function, p is the total number of ecological service function indicators, PD is the pressure of human activities, and PD max It is the maximum value of human activity pressure.

6. The method for evaluating the ecological environment vulnerability in the loess region according to claim 5 is characterized by: The process of setting evaluation thresholds for different levels is as follows: Step 401, integrating the pre-processed historical data, combining the ecological sensitivity index, the ecological resilience index, and the ecological service function index, and analyzing the correlation between the historical data and soil erosion data and the ecological sensitivity index, the ecological resilience index, and the ecological service function index; Step 402, inputting the ecological sensitivity index, ecological resilience index and ecological service function index into the vulnerability assessment model for weighted calculation to obtain an ecological environment vulnerability assessment coefficient; Step 403, according to the main influencing factors and regional differences of the ecological environment vulnerability in the loess region, the loess region is divided into different vulnerability levels, namely low vulnerability level, medium vulnerability level and high vulnerability level; Step 404, the determined different vulnerability levels are matched with the results of the ecological environment vulnerability assessment coefficient, and corresponding assessment thresholds are set for the different vulnerability levels.

7. The method for evaluating ecological environment vulnerability in loess regions according to claim 6 is characterized by: The calculation formula of the ecological environment vulnerability assessment coefficient is: Among them, EVI is the ecological environment vulnerability assessment coefficient, S i is the observed value of the i-th ecological sensitivity index, R j is the observed value of the jth ecological resilience index, ESFI is the ecological service function index, R std is the standard value of ecological resilience, n is the total number of ecological sensitivity indicators, m is the total number of ecological resilience indicators, ESFI th is the safety threshold of the Ecosystem Service Index, ESFI max It is the maximum value of the ecosystem service function index.

8. The method for evaluating the ecological environment vulnerability in the loess region according to claim 7 is characterized by: The assessment threshold ranges of the vulnerability levels and their classifications are as follows: Low vulnerability level: EVI ≤ T1; Medium vulnerability level: T1 <EVI≤T2; High vulnerability level: EVI>T2.

9. The method for evaluating ecological environment vulnerability in loess regions according to claim 8 is characterized by: The process of obtaining the evaluation report is as follows: Step 501, input the pre-processed real-time data and historical data into the vulnerability assessment model, calculate the ecological environment vulnerability coefficient of each region and compare it with the level threshold of the loess region; Step 502, using GIS technology, visualize the calculated ecological environmental vulnerability coefficient on a map of the Loess Plateau, analyze the ecological environmental vulnerability coefficient values ​​of different regions, and identify the spatial distribution pattern and hot spots of vulnerability; Step 503, combining historical data, analyzing the time trend of vulnerability level changes, observing the change speed and direction of vulnerability level by drawing a time series graph, analyzing the driving factors leading to vulnerability changes, and applying a prediction model to predict the future trend of vulnerability level changes based on the change trend and driving factors; Step 504, based on the predicted trend of change, identify potential ecological risks faced under different scenarios, evaluate the identified potential ecological risks, and propose corresponding risk response measures and suggestions based on the evaluation results.

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