A Comprehensive Evaluation Study on the Ecological Conservation Model of Saihanba, China and Its Application in the Asia-Pacific Regions

: The key of this paper is to extract several representative characteristic indicators and establish the ecosystem characteristic index system of Saihanba by collecting and preprocessing the data in Saihanba area for a comprehensive evaluation. A gray correlation model was used to calculate the correlation degree and rank the cities based on the characteristic indicators, with Beijing as the central point and extended to Xinjiang, Japan and other regions. Through the integration of the data from the official website and books, the data of the representative ecological aspects of the Saihanba was obtained and divided into 12 characteristic indicators to build the characteristic indicator system of the Saihanba ecological environment, and the maximum characteristic value and CR value were solved by using the hierarchical analysis method to assign values to the indicators and obtain the weight vector of each indicator. Based on the principal component analysis, the correlation matrix between the indicators was established to determine the importance of the factors, and finally, a comprehensive comparison and analysis of the changes in environmental conditions before and after the restoration of the Saihanba was performed. Based on the multivariate nonlinear regression fitting bias and optimization and TOPSIS comprehensive evaluation method to assess the importance of the indicators, it can be concluded that Saihanba played an important role in the fight against sandstorms in Beijing; through the evaluation model, the in-depth analysis of environmental indicators in Xinjiang region and Japan, the impact of the ecological model on environmental conditions in different regions was derived, which has positive implications for the promotion of similar ecological reserves.


Introduction
Since the 18th Party Congress, General Secretary Xi Jinping has put forward a series of new ideas, new perspectives and new assertions on the construction of ecological civilization based on the strategic height of the five-in-one general layout of the socialist cause with Chinese characteristics [1] . This reflects that it should carry forward and adhere to the ecological concept of green water and green mountains are golden mountains, not only respect nature, protect nature, fear nature, and live in harmony with nature, but also build an ecological civilization system and promote the transformation of economic and social development to comprehensive green growth.
In order to witness the concept of green water and green mountains are the silver mountain of gold, the Saihanba was born a miracle of turning a wasteland into a sea of forests [2] , from an untouched wilderness to the largest artificial forest in the world. Saihanba is located in Weichang Manchu and Mongolian Autonomous County in the northernmost part of Hebei Province, However, more than half a century ago, it was a bleak scene of yellow sand covering the sky and birds without trees. Due to years of wars, the ecology of China was seriously damaged, especially the land of Saihanba was seriously degraded, and by the time of the founding of New China, the original forest was gone, and it became a vast wasteland covered with sand. In order to respond to the national green call, people started to build forestry and restore vegetation to Saihanba [3] . This afforestation machinery not only effectively blocked the southward movement of Hunshandake sand, but also blocked the wind and sand from invading Beijing and Tianjin.

Methods
The main purpose of this paper is to construct an evaluation model to quantitatively evaluate the impact of Saihanba on the ecological environment, to learn from Saihanba ecological protection model and to promote it. The first step is to carry out the selection of each indicator and the choice of each evaluation method, and to collect relevant data to justify it. Several details are thus considered as follows.
(1) Whether the selection of the indicators is appropriate and appropriate to the reality; (2) Whether the selection of evaluation methods meets the needs of the problem; (3) Whether there are sufficient data samples for processing. The specific questions are shown below.
1. The key to the problem is to clarify the important role of Saihanba under the ecological benefits,to analyze the changes in the environment before and after Saihanba, and to quantitatively evaluate the impact on the environment after its restoration.
2. The focus is on the impact of the restoration of Saihanba forest on Beijing's ability to resist sandstorms.
3. To achieve the goal of carbon neutrality, the data were used to determine the existing ecological forests in China, the specific area of specific trees, and the balance of land area for different industries in order to determine the geographical location and scale of building ecological zones. 4. To determine the existing ecological forests in the Asia-Pacific region through the data,the specific area of specific trees, and balance the land area of different industries, in order to determine the geographical location and scale of the constructed ecological zones, and to assess their impact on the absorption of greenhouse gases and reduction of carbon emissions. 5. To propose feasible solutions and recommendations for ecological reserves based on the model established in this paper.
For convenience, next , some assumptions and notations will be introduced .  The impact of major natural disasters is not considered in the forecast model.  The statistical data information obtained from the official indicators is true and reliable.  The interrelationship between the indicators of the evaluation of ecological civilization construction is neglected.  The countries and regions involved in the projection or the construction and development of ecological civilization in accordance with the original process and laws. The symbols used and their descriptions are shown in the following Tab. 1. According to the requirements, the relevant data collected through various channels will then be analyzed for the characteristics of Saihanba and its characteristic indicators will be selected. Next, species and genetic diversity will be analyzed.
An ecosystem is an organically unified whole of organisms and environment in the natural environment, where the environment and organisms constrain and influence each other, and the two are in a long-term dynamic balance. Species diversity (Gao et al. 2014) is the most important structural and functional unit of biodiversity, and refers to the richness of biological species such as animals, plants, and microorganisms on Earth [4] . Maintaining species and genetic security can promote ecosystem stability, improve the service capacity of ecosystems, and maintain balanced development of ecosystems. For the evaluation of the value of maintaining forest biodiversity, the Shannon-Winener index method (Fu et al. 2019), which reflects the diversity of species, is commonly used. After processing the data, the value of maintaining species diversity per unit area of ecosystem can be determined for ecosystems with different richness classes and then the index can be finally calculated. The calculation formula is shown below.

⋅ .
(1) In the above equation, U is the value of maintaining biodiversity; S i is the value of biodiversity per unit area of grade i with S-W index; A i is the forest area of level i.
(1) Plant species diversity The classification and distribution of plant communities has been a hot research topic in vegetation ecology. The relationship between plant communities and ecosystems can be objectively and accurately explained by the species and number of vegetation, and the richer the plant species as well as the more the number, the more stable and balanced the ecosystem will be.
(2) Animal species diversity Animals are the most important part of nature and play an important role in the ecological chain.
The diversity of animal species can also describe the stability and balance of the ecosystem.
(3) Diversity of microorganisms Microorganisms are essential existences in nature, playing an important role in decomposing and producing substances, and maintaining the normal functioning of ecosystems. Now, the ecological regulation function will be analyzed concretely.
(1) Vegetation cover Vegetation cover is an important indicator of the condition of surface vegetation, which can, to a certain extent, reflect the condition of the ecosystem and provide a living environment, and is important for hydrology, ecology, and regional changes.The formula is as follows.
. (2) In the above equation, a is the vegetation cover, S 1 is the forest area, and S t is the total land area. According to the data collected in recent years, it is possible to visualize the trend of vegetation cover in Saihanba and make a line graph as shown in the following Fig. 1. (2) Carbon sequestration In the climate change and the balance and stability of the natural world, it is indispensable to have the indicator of carbon sequestration, which reflects the productivity of vegetation communities under natural environmental conditions and the quality status of terrestrial ecosystems. The equation of carbon sequestration is as follows.
In the above equation, C is the amount of carbon sequestration, C 1 is the yield of carbon sequestration products, C 2 is the carbon content per unit of product, and C 3 is the rate of carbon sequestration. The value of the amount of carbon sequestered is associated with the target of achieving carbon neutrality in the national region, and its indicator has a certain basis. The rate of change of the amount of solid carbon is shown in the following Fig. 2. (3) Water deficit and surplus The water deficit reflects the dry and wet condition of the climate, which can provide a strong basis for the rational allocation of water supply and demand, and thus improve the management of the ecological environment.
(4) water content (Fu et al. 2019) Cultured water is to maintain the normal circulation of water in the area, so as to avoid loss and damage to the ecology of water. The main components of water conservation include water regulation and water purification. The formula for regulating water is shown below. Q = A ꞏ (P − E − I) .(4) Q is the regulated water volume; P is the average annual precipitation; E is the average annual stand evapotranspiration; I is the surface runoff; and A is the stand area. The variation of the cultured water volume from 1962 to 2021 is shown in the following Fig. 3. (5) Soil consolidation capacity The fertility as well as the solidity of the soil in an ecological environment can reflect the stability of the ecological state of mind. The formula for calculating the soil consolidation capacity of an ecological reserve is as follows.
In the above equation: V is the forest soil consolidation capacity; A is the area of forested land; M 0 and M f are the soil erosion modulus of non-forested land and the soil erosion modulus of forested land, respectively; ρ is the soil capacity; m is the cost required to dig and transport a unit volume of soil.
The Ecosystem status has a significant impact on environment. It is mainly reflected in the following aspects： (1) Air temperature Air temperature is a characteristic indicator representing the hot and cold of a place, and is inextricably linked to the ecological environment of the area.
(2) Precipitation Precipitation is the product of the influence of the atmosphere, the most basic link of the water cycle process, a reference indicator of the water balance, and an important indicator reflecting the characteristics of dryness and wetness in a certain area.
(3) Frost Reflecting the climatic characteristics of the weather gradually becoming colder, it is the frost caused by the atmospheric temperature of the region and other climatic, the enhanced time of frost can reflect the ecological environment of the region has been improved. Therefore, frost-fall can also reflect a characteristic indicator of the ecological environment of the region.
(4) Land utilization rate Land utilization rate is an indicator that reflects the degree of land use.In the construction of ecological protection, the abandoned land will be developed to open up the required type of land use, which in turn increases the use of land and improves the land utilization rate. The increase in land use can also reveal the high development indicators of the region or country, and its characteristics can be judged by the type of land it has developed. The formula for calculating the land utilization rate is as follows.
. (6)  In the above equation, Z denotes land utilization; S b denotes utilized land; S t denotes total land utilization. (5) Air quality Air quality reflects the degree of air pollution, which can reflect the ecological environment good or bad. In the ecological protection construction, air quality has also become an important characteristic indicator to reflect the change trend of ecological environment. The change trend in recent years is shown in the following Fig. 4. (6) Surface water quality compliance rate The surface water quality compliance rate reflects the quality of water bodies in the area and can reflect the water purification capacity of vegetation and the water circulation capacity in the ecology. The change of surface water quality compliance rate in recent years is shown in the following Fig. 5. Combining each of these indicators can be integrated into a general characteristic indicator diagram, as shown in Fig. 6 below. After collecting information from books, literature and other ways to extract the characteristic indicators, the characteristic indicator system and evaluation model of the impact of Saihanba on ecological environment will be constructed. The general idea of this paper is shown in the following Fig. 7.
For comparative analysis of environmental conditions before and after restoration of Saihanba, it is possible to analyze the need to apply evaluation class methods. By collecting and processing data, suitable indicators can be selected as a way to build an evaluation model of the impact of Saihanba on ecological environment, and then its characteristics can be described and judged numerically. The evaluation model can be used to compare and analyze the environmental changes and impacts before and after restoration. By collecting information on all aspects of Saihanba, it extracted species and genetic safety, ecological regulating functions and the state of Saihanba ecosystem as three major aspects, and then subdivided them into 12 ecosystem characteristic indicators such as species diversity, vegetation cover, carbon sequestration, water deficit, water content, soil consolidation capacity, temperature, precipitation, frostfall, land utilization rate, air quality and surface water quality compliance rate, to build The evaluation model of the ecological impact of Saihanba. Based on the collected data, the weighting of the indicators of Saihanba was analyzed by multilevel analysis and principal component analysis, using subjective and objective methods, respectively. The maximum eigenvalues and CR values were solved by Python programming software, and the weight vectors of each indicator were solved by arithmetic mean, geometric mean and eigenvalue methods using hierarchical analysis. Principal component analysis was used to establish the correlation matrix between indicators and indicators and to determine the importance of the factors by using SPSS software, and finally to compare and analyze the environmental conditions of each indicator before and after the restoration of Saihanba.The hierarchical analysis method is supported by referring to Table 2, which provides the Judgment matrix scalar definition, and Table 3, which presents the Average Random Consistency Index.

Hierarchical analysis method
(1) Calculate the consistency index CI (consistency index) CI = . (7) where λ max is the maximum eigenvalue of the judgment matrix.
(2) Find the consistency index RI  (3) Calculate the consistency ratio CR (consistency radio) CR= (8) When CR < 0.01, the consistency of the judgment matrix can be considered acceptable; otherwise, the value of the judgment matrix will need to be modified (Deng 2012, Wang 2002, Liu 2014.

Weight vector calculation method
The methods of finding the weight vector by hierarchical analysis are: geometric average, arithmetic average method, eigenvector method and least squares method.
(1) Geometric averaging It can be expressed from the calculation equation as follows.
(2) Arithmetic averaging Since each column in the judgment matrix A approximates the distribution of the assigned weights, the weight vector can be estimated by the arithmetic averaging method. The calculation formula is shown as follows.
(3) Eigenvector method The right multiplication of the weight vector W by the weight ratio matrix A.
In the above equation: λ max is the maximum eigenvalue of the judgment matrix, and finally, the obtained weight vector can be found by normalizing it.
(4) Least squares The fitting method is used to determine the weights such that the residual sum of squares is minimized, i.e., the following model is solved. indicators from the characteristics of the Saihanba ecosystem. The target layer is ecological and environmental protection construction, the guideline layer is biodiversity, vegetation cover, water content, soil consolidation capacity, temperature, precipitation, land utilization rate, air quality, surface water quality compliance rate and other 9 indicators, and the scheme layer is wind resistance and sand fixation, and protect the environment and maintain the ecological balance and stability. The Saihanba ecosystem level evaluation model is shown in the following figure Fig. 8. The judgment matrix A i of the evaluation factors of the ecological environment of Saihanba can be expressed as follows.
The judgment factors are biodiversity, vegetation cover, water content, soil consolidation capacity, temperature, precipitation, land use rate, air quality, and surface water quality attainment rate corresponding to By using the Python programming software, the assigned data are substituted into the formula to solve for the maximum eigenvalue, CR, and the weight of each feature indicator, and the results are shown in the table 4. From the above table , it can be seen that CR < 0.10. Therefore, the above judgment matrix passed the consistency test. The results of the weights of each characteristic index are shown in the following table. Based on the Table 5,arithmetic mean, geometric mean and eigenvalue methods, calculated using Python programming software, the code is located in the appendix, thus running the following table of weight vectors.
In order to ensure the robustness of the results, three methods were used in this paper to find out the weights separately, and then the scores of each scheme were calculated based on the obtained weight matrix and ranked and analyzed comprehensively, which avoided the bias caused by using a single method and yielded a more comprehensive and effective conclusion.

Principal component analysis method
The refined indicators were used to make a comprehensive evaluation of the ecological condition of the Saihanba, and the SPSS software was used to analyze the components of the indicators in detail. The state of the ecosystem can be measured by six indicators: forest cover, carbon sequestration, water quality, urban air quality, and surface water quality standards. There are numerical correlations among these characteristic indicators, and the importance of the indicators varies. Therefore, the weight of the indicators can be compared and analyzed by factor analysis (Liu 2021) [5] .
(1) Related matrix According to the following Tab. 7, the indicators are analyzed for correlation, and a matrix of coefficients between indicators can be created as a way to see the correlation between indicators. (2)Common factor variance The following Tab. 8 is a plot of the variance of the common factor, which indicates the extent to which the original information contained in the six characteristic indicators is represented by the extracted common factor, and the explanatory power of the extracted degree surface common factor for each variable is strong. Therefore, it can be seen that the forest cover as well as the land area has a strong explanatory power for each variable. (

3) Total variance explained
The total variance explained can reflect the variance contribution and cumulative contribution of each component, and only the first component has a characteristic root greater than 1, while SPSS can only extract the first component, as shown in the following Tab. 9.
(4) Gravel map The gravel plot is to judge the importance of each factor, and the horizontal axis is the factor serial number, and the vertical axis is the size of the eigenvalue. Fig. 9 is shaped as an obvious steep slope, the first factor has a larger eigenvalue, while the last five have an eigenvalue less than 1, which has a weaker role, therefore, the focus should be on the first component.
In order to quantitatively evaluate the impact of the restoration of Saihanba on the environment, i.e. through the collection of data from Saihanba and pre-processing of the data, each characteristic index was integrated as an evaluation model for constructing the impact of Saihanba on the ecological environment, and through line and bar charts, the data were used to visually show the changes in Saihanba between 1962 and 2021 [6] . The annual forest cover increased year by year, from a wasteland to a dense green plantation. The amount of carbon sequestered, the amount of water contained, the air quality, and the rate of surface water quality compliance all increase year by year. In this paper, it used hierarchical analysis and principal stratum analysis to assign values to the characteristic indicators of the extracted ecosystem, as well as principal component analysis of the characteristic indicator factors, and then the characteristic values were compared to extract the indicators with the largest percentages. Before the restoration of Saihanba, the values of forest cover, water content, species richness and other indicators were low, but after the artificial restoration, the ecosystem of Saihanba has been stabilized and strengthened, and all characteristic indicators have been significantly enhanced. The ecological protection and construction of civilized development and green ecology also play a key role in fighting against wind and fixing sand and maintaining the ecological balance and stability.

Results
With the economic development and human activities, the earth has been bearing a heavy burden. Protecting the environment has become a topic of equal importance for all countries in the world, and carbon neutrality has become a direction that many countries want to work hard to develop. As a country with a large population, China has to take up the responsibility to achieve the goal of carbon neutrality as soon as possible. China is responding positively to the goal of carbon neutrality, which is not only an effectively way to deal with climate problems, but also the right path based on scientific development. The project plans to extend the ecological protection model of Saihanba to 5 counties and cities in Xinjiang region, including Shache County, Kashgar County, Aksu City, Minfeng County, and Hami City, as a way to establish ecological zones. Carbon neutrality requires consideration of both natural and human factors, and is subdivided into: carbon dioxide released from vegetation and carbon dioxide emitted from industrial production. China has invested in increasing carbon sinks, developing carbon capture and storage technologies, etc. to achieve a balance between emissions and absorption. By establishing an ecological reserve in Xinjiang, the forest exchange rate can be increased and greenhouse gases can be effectively controlled, thus advancing Chinese progress towards carbon neutrality. The scope of the study was extended from China to the Asia-Pacific region to address the impact of eco-regions on greenhouse gas absorption and carbon emission reduction. By collecting information on the characteristic indicators of each country in the Asia-Pacific region and extracting the characteristic and representative indicators, further analysis and comparison were conducted, and three Asia-Pacific countries, Australia, Mexico and Japan, were finally selected. In this thesis, a gray correlation analysis model was used to correlate forest cover, temperature, precipitation, carbon dioxide emissions, and land use rate as the characteristic indicators with the Asia-Pacific countries. The raw data were processed to obtain the following data table, as follows (See Tab. 10). After the calculation of the correlation coefficient, the following data table can be obtained in Tab. 11. Finally, the correlation is calculated as shown in the following Tab. 12.

Discussion
In order to quantitatively evaluate the role of Saihanba in the protection of Beijing against sandstorms, the wind and sand fixation capacity of Saihanba can be modeled by extracting the corresponding indicators from the available data, and further analyzing the impact and effect of Saihanba on the sandstorm in Beijing. In this project, it used multiple non-linear regression fitting and TOPSIS method to refine the data and to calculate the algorithm to obtain the importance of each indicator to the wind and sand stabilization in Beijing.
To address the core need to discuss the relationship between the restoration of Saihanba forest and the impact of Beijing's resistance to dust storms, a multivariate nonlinear regression fit will be applied to select relevant data and establish a Beijing environmental improvement index system, with the environmental index of Saihanba as the independent variable and the quantified Beijing environment as the dependent variable. Thus, the annual average precipitation index of Beijing is chosen as the dependent variable, and the area covered, forest stock, and water content of the Saihanba are the dependent variables, and the multivariate nonlinear regression fit is shown in the following equation (AN 2015).
And then the partial derivative can be obtained as follows.
Eventually, the optimal equation is formed as follows.
After the correlation analysis of the factors affecting the ability of Beijing to resist dust storms, the factors were extracted according to Pearson correlation coefficients, and three characteristic factors were screened for comparative analysis with the average precipitation of Beijing. According to the experimental results of regression analysis, the method of multivariate nonlinear regression model shows that the annual average precipitation index of Beijing is positively correlated with the cover area, forest storage and water content of Saihanba, which are important factors affecting the resistance to dust storms in Beijing.
The TOPSIS comprehensive evaluation method is a method of ranking the proximity of evaluation objects to ideal objects. It is able to evaluate the extracted indexes as well as the data to the reference object with data and produce good comparable evaluation ranking results.
Among the corresponding indicator data, find the minimum value of each indicator in each column, noted as z i + (i = 1,2,ꞏꞏꞏ ,m). The final vector is formed as: , .
his vector represents the ideal indicator, and similarly, find the minimum value of each indicator in each column, denoted as z i − (i = 1,2,ꞏꞏꞏ ,m), the final vector is formed as: , .
This vector represents the least desirable indicator. Define the distance of the sample from the ideal target as D i + .

(19)
Similarly, define the distance of the sample from the undesirable target as D i − .

∑ .
(20) Define the score of the indicator Si.
From the data analysis, it is known that S i will be located between [0,1]. When S i approaches to 1, it implies that the characteristics of indicator i are closer to the ideal value, and the more important it is for the ecological environment. Conversely, when S i approaches to 0, it implies that the characteristics of indicator i are far from the ideal value, and the importance of indicator i to the ecosystem is smaller.
A multiple non-linear regression fit was applied for the influence factors of Saihanba on the resistance to dust storms in Beijing. Based on the collected indicators, the average precipitation indicator was extracted as the dependent variable, and the ecosystem indicators of Saihanba, such as the area covered, forest stock and water content, were extracted as independent variables. After correlation, bias and optimization, it found that the characteristic indicators of Saihanba are positively correlated with the average precipitation indicator of Beijing. Finally, from the above results, it can be concluded that the restoration of Saihanba has significantly improved the ecological environment of Saihanba, with a significant increase and change in the degree of change of each characteristic indicator, which has an important role in resisting wind and fixing sand, protecting the environment and maintaining the stability of ecological balance during years of continuous restoration. In turn, it can resist certain wind and sand to Beijing, allowing Beijing to reduce the degree of harm caused by dust storms, and play a certain role in protection and anti-sand.
For the ecological conservation model of Saihanba, the scope of Saihanba was expanded to the whole country through evaluation plus prediction, as well as the scope of data to be collected. From this, one can refer to the solution of the first two questions, and use the evaluation model to construct the ecosystem model by first refining the characteristic indicators. Using the gray correlation model, the cities were ranked by correlation based on the characteristic indicators using Python coding software.
Based on the collected data, the national data of precipitation and carbon dioxide were filtered, and the degree of precipitation and the degree of carbon dioxide emissions were visually represented in different shades of color in the left graph using ArcMap software.
Through the collected data, forest coverage, temperature, precipitation, carbon dioxide emission and land utilization rate were extracted as the characteristic indicators, and after data comparison and screening, the regions with lower indicators were extracted, namely Xinjiang, Gansu and Tibet. These three regions were then selected for the next round of screening based on the correlation of the characteristic indicators, and the most suitable regions were finally selected for analysis and proposed construction. Next, a gray correlation analysis model will be discussed in the following for more detailed.
Gray correlation analysis is a systematic theoretical analysis method that uses gray correlation order to describe the strength, size and order of factors. The basic idea of this method is to measure the degree of association between indicators based on the degree of similarity or dissimilarity between them, the higher the degree of similarity, the higher the degree of association between the region and the selected indicators, and the lower the degree of similarity, the lower the degree of association between the region and the selected indicators. The gray correlation analysis model can be established to calculate the correlation value between each region and the indicators, and thus the influence degree of the characteristic indicators on each region can be analyzed (Meng, 2021) [7] .
The basic principles of gray correlation analysis are as follows: (1) Determine the data series to be analyzed. The formula for the reference series is For comparing series, the formula is Where k is the resolution factor. (4) Calculate correlation In the above equation, r i is the correlation between the parent series and the child series, the higher the value, the higher the degree of correlation and the better the fit.
(5) Ranking of correlations, and analysis of the ranking results. Applied to the degree of correlation of the indicators found in the paper to the national region. The evaluation index system was determined according to the evaluation purpose, and the evaluation indexes were collected. The forest coverage, temperature, precipitation, carbon dioxide emission and land utilization rate were refined as characteristic indicators with new construction, Gansu and Tibet. The raw data were processed to obtain the following data in Tab. 13. After the calculation of the correlation coefficient, the following data can be obtained in Tab. 14. Finally, the correlation is calculated, as shown in Tab. 15.
It can be seen that Xinjiang has the least correlation with the extracted index, and the place needs to build an ecological zone for the improvement of environmental indicators and environmental quality.  Based on the selected Xinjiang region, an in-depth understanding of the topography, frequency of occurrence of dust storms, precipitation, land utilization and other indicators of Xinjiang was developed to form a comprehensive evaluation. Using BigMap software, a more intuitive and comprehensive observation of Xinjiangs topography, land size, and the provinces connected to it was made, so as to understand the characteristic indicators of each county-level region in Xinjiang through the selected five counties and cities, such as Shache County, Kashgar County, Aksu City, Minfeng County, and Hami City, as the establishment of ecological zones. Regional Location Fig. 10 as shown below. Based on the wasteland area, topography, wind direction and the causes of sandstorm formation in Xinjiang, several geographical locations were selected, marked by red dots and represented by tree symbols to establish ecological zones around. According to the climate, latitude, precipitation, topography and other factors, it is possible to plant Hong Sen Sophora species in Xinjiang, which is a fast-growing and productive tree species with drought tolerance, high added value, strong nitrogen fixation capacity, wind and sand control, and can effectively improve the soil and ecological environment. As Xinjiang is prone to receive sandstorms, the planting of Acacia Hong Sen can form a slope protection network and Table 12. Relevance Table   Table 15. Relevance Table   r1 r2 r3 0.39 2.35 1.06 effectively prevent landslides. When establishing the ecological environment in the selected area, it was noted that the land in Xinjiang region is vast and there are parts of the region that are able to have a lot of wasteland for the development of ecological reserves. While establishing the ecological reserve, a reasonable distribution and balance of ecological forest land, economic development land and industrial land bureau is needed.

Conclusions
Protect the ecological environment like an eye, and treat it like life. Ecology plays a very important role in China and the world. Ecological environment is a necessary condition for human survival, production and life. For a long time [8] , China has attached great importance to ecological construction and environmental protection, although ecological problems in some areas have been significantly improved. However, due to natural, historical and man-made reasons, the ecological problems in China are still very serious, for example, the most serious land desertification, due to ecological destruction and excessive human logging, the land degradation gradually turns into desert, causing sandstorm hazards to other cities, but after the correct method of ecological restoration and protection, and with it comes unexpected surprises [9] , for example, the creation of sand on the For example, the construction workers of Saihanba Forest in Hebei province, who have followed the call of the Party, have struggled hard and dedicated themselves to the desert and sandy land where yellow sand covers the sky and no birds have trees, and have interpreted the concept of green water and green mountains is the silver mountain of gold with their practical actions, and have forged the spirit of Saihanba which remembers the mission, hard work and green development. Therefore, it is important to make a correct evaluation of the ecology.
Therefore, in this question, it analyzed the ecology of Saihanba, selected suitable indicators and built an evaluation model, then predicted which cities need to establish ecological reserves, how to build them and the scale of construction.
In the model building process, it especially considered the condition of existing ecological forests in China and other Asia-Pacific regions according to the requirements of the topic; the specific area of specific trees. It also made a series of recommendations on balancing the layout of ecological forest land, land for economic development and industrial land, and whether there is sufficient available land in the geographic area of the approach to develop the ecological reserve.
It mainly used principal component analysis and hierarchical analysis. After searching and integrating the data, it quantified the qualitative decision problems and down-scaled the data to maximize the analysis of the data, then analyzed the largest individual differences in the principal components, and used the judgment matrix passed by the consistency test to find the weights, and found the indicators that are easier to understand, such as species and genetic safety, the The three main aspects of the data were: species and genetic safety, ecological regulation function, and the state of the Saihanba ecosystem. Then, based on this, it refined the branching to form several ecosystem characteristics indicators, and constructed an evaluation model to compare and analyze the environmental conditions before and after restoration of the Saihanba [10] .
Multiple non-linear regression analysis is a statistical method of analyzing data in order to understand whether two or more variables are correlated, the direction and strength of correlation, and to build mathematical models in order to observe specific variables to predict them [11]. One assumes the temperature and air quality index of Saihanba as independent variables, and the scores of Beijing environmental indicators after quantitative analysis as dependent variables, and perform multivariate nonlinear fitting followed by ANOVA to derive the independent variables with significant effects.
Gray correlation analysis is a method to quantitatively describe and compare the development and change trend of a system. The basic idea is to determine the degree of similarity of several shapes of the reference data columns and several comparison data columns to determine whether they are closely related, and it reflects the degree of correlation between curves. It applied this method to analyze the degree of influence of each factor on the results, and then used the changes of each assessment object over time as a sub-series, and found out the correlation degree between each sub-series and the parent series, and drew conclusions according to the correlation magnitude of environmental indicators. Through the above model, it correctly evaluate and make predictions to build some ecological protection zones in urban areas respectively to avoid or reduce the possibility of dust storms raging in urban areas and to stop the impact and harm caused by dust storms to the ecological environment and economy. The following are feasible solutions and suggestions based on the analysis of the processed data and models: for example, in order to resist or reduce the harm caused by sand and dust storms, it firstly identify three provinces and cities in need of ecological environment improvement based on five indicators: forest coverage, temperature, precipitation, carbon dioxide emission and land utilization rate from cities in China, namely Xinjiang, Gansu and Tibet; Asia-Pacific countries of Australia, Mexico and Japan, and then based on gray correlation analysis, identify the provinces and cities with the weakest ecological environment as Xinjiang; Japan, after analyzing the data, geographic location and climate based on Xinjiang and Japan, establish ecological reserves, in turn, in five places, Aksu Prefecture, Minfeng County, Kashgar Land, Hami County and Hotan City, and Kyushu, Shikoku and Fukushima City from the west to the north of Japan, to achieve carbon neutral, considering the economic level and the size of the land area to finally establish the appropriate scale. The construction of ecological civilization and economic and social development are interdependent and mutual promotion, human beings should protect the environment while using the development and utilization of resources, in order to further build the ecological civilization system and achieve sustainable development, therefore, for the establishment of ecological reserves it will has the following suggestions: 1. Attach great importance to the construction of nature reserves In order to better call for the five-in-one ecological civilization construction of General Secretary Xi Jinping, and further raise awareness of the construction of ecological protection, not only to establish ecological protection areas in the province, but also to the urban areas, so that the structure of ecological protection objectives is more complete.

Increase the standardization of ecological reserves and financial investment
Strengthen the facilities of infrastructure construction, the use of high-tech technology, optimize the construction equipment, and in order to ensure the full establishment of ecological reserves, should be taken to detect and patrol, increase ecological propaganda, call for more business investment, which also has the core area still has farmers living traditional farming activities are frequent, that the activities are too disturbing, the government still needs to take measures to solve its problems.
3. Strengthen the supervision of the nature reserve Although there is a response to the call of the state to establish ecological reserves, but some of the personnel have not arrived, the whole task of the pilot program lags behind, can not guarantee the timely completion of the establishment of ecological reserves, there are also users of illegal occupation of natural reserves, crack down on criminal acts of destruction of natural resources, the government should take measures to increase the management system, to enhance the standardization of protected areas and the legal system. 4. Strengthen the welfare policy of nature reserves The government should honor and pay tribute to the staff who work or keep their posts, and can add some subsidy measures to their families. Issuing certificates to encourage their behavior will attract more young people to join the construction of natural ecological areas.
To sum up, it should insist on the harmonious coexistence of man and nature, adhere to and implement the policy of giving priority to protection, conservation and natural restoration, protect the ecological environment like an eye, treat the ecological environment like a life, let the natural ecological beauty live on earth forever, return nature to tranquility, harmony and beauty, vigorously promote and develop the construction of ecological civilization, and strive to build a beautiful China, so as to realize the sustainable development of the Chinese nation.