| PSR (pressure- state-response) model | Pressure indicators based on the effects of human economic and social activities on the environment, the status quo of ecosystem and natural environment represented by the status indicators, and the response indicators are established to prevent the negative impacts of human activities on the environment | Three basic questions “what happened, why did it happen and how to do it” are answered, which fully explain the situation of the evaluation object compared with the reference standard | Applicable to regional environment, soil and water resources and agricultural protection |
| VSD (exposure-sensitive- adaptation) model | Vulnerability is studied from three dimensions: exposure degree, sensitivity and adaptive potential. Each indicator is refined with circle-level data, and evaluated effectively and clearly by “aspect layer—index layer—parameter layer” | It fails to clarify which reflects the natural factors, and which reflects the human factors | Suitable for the basic data of comprehensive regional EV measurement |
| Pressure sensitivity resilience model | The intensity of ecological pressure includes area-weighted average fractal dimension reciprocal and disturbance indexes. The ecological sensitivity includes soil erosion sensitivity index, terrain index and landscape fragmentation index. The ecological resilience refers to the self-resilience of an ecosystem and when it is disturbed, it is related to the stability of its internal organizational structure | The emphasis is put on the natural factors, and the proportion of human factors in the index is not high | The vulnerability of ecologically fragile areas are measured and compared |
| Fuzzy evaluation method | Establish the index system and weight, calculate factors for the membership of each evaluation index vector, evaluate regional vulnerability degree | Fuzzy trigonometric functions can reduce the shortcomings of subjective effects, which has certain objectivity, but the index of significance is not obvious, and is a heavy workload | Suitable for a specific areas or multiple regions |
| Analytic hierarchy process (AHP) | Establish the evaluation index, score and weight the index, multiplied by the score value and weight, which are added up to obtain the total score to determine the degree of ecological vulnerability | It provides a clearer idea and logic for selection of related indices. The index selection is subjective | Suitable for the analysis of regional and internal evaluation units |
| Principal component method | Data standardization, set up the correlation coefficient matrix, calculate eigenvalues and eigenvectors and cumulative contribution rates, and obtain the main ingredients of vulnerability analysis | Variable selection of dimensions is not restricted, but it particularly focuses on the main ingredients, which causes some information to be missed, and fails to fully reflect the index of all information | Suitable for regional analysis of the internal evaluation unit |
| BP neural network method | Set the objective function of the calculated index, and the weight between the input and output layers of the index can be adjusted and modified with the gradient descent method | Intervention processing, compatibility | Deals with the measurement of regional ecological vulnerability with some complex states |
| Cause-result evaluation method | Establish the corresponding index system according to the characteristics and causes of EV, and the entropy weight method is usually used to assign the weight to each index | Relatively simple, and difficult to deal with complex state | Used for the comparison of vulnerability degrees between regions for a rough analysis |
| Set pair analysis | Establish coefficient of difference degree and correlation degree, weights set, scheme set and evaluation set, the standard deviation classification method is used to measure and classify the EV | The calculation is complicated, and the analysis result has some intuitiveness | Can be used to measure and analyze the EV of regional units |
| Landscape ecology model | Computer simulation data is used to characterize the dynamic characteristics of EV, which is combined with GIS, remote sensing data and other system analysis data | This model focuses on local spatial analysis and ignores the influence of human factors | Analysis of EV from the perspectives of regional space and spatial heterogeneity |
| Grey relational degree | The reference sequence of ecological vulnerability characterization and the comparative sequence of influencing system behavior are determined, the data are processed dimensionless, the grey correlation coefficients of the reference sequence and the comparative sequence are calculated, and the correlation degree is sorted | The degree of correlation between vulnerability factors is emphasized | Used for comparative analysis between regions |
| Matter-element extension model | The classical domain, node domain and object element to be evaluated are determined, the index weight is set, the correlation degree is calculated, and finally the vulnerability degree of the member to be evaluated is obtained | This method is suitable for multi-factor analysis, which uses formal language to deal with the characteristics of ecological vulnerability | Used for delicate analysis of fragility between regions |
