# Study on the Extraction Method for Ecological Corridors under the Cumulative Effect of Road Traffic
## 2 Method
### Resistance Surface Construction
#### 2.2.1 Estimation of Ecological Resistance  
In the approach of our research design, two main factors, ecological quality and landscape pattern, are considered when constructing the ecological resistance surface. The migration resistance of species between different patches is mainly influenced by natural and anthropogenic disturbances. Areas with high habitat quality tend to have better ecological conditions, which usually represent less disturbance from outside, and such areas play an important role in conserving biodiversity and maintaining the stability and integrity of ecosystems. The remote sensing ecological index (RSEI) can be calculated from remotely sensed imagery, which focuses more on the actual ecological condition of the surface of a single pixel area. It can reflect the possible differences between the same feature classes while showing the ecological status of the study area, thus compensating for the lack of land use data. The combination of remote sensing ecological index and habitat quality index can reflect the regional ecological resistance status more comprehensively. In addition, to maximize the use of existing ecological patch linkages, the landscape pattern is calculated by the MSPA model and incorporated into the resistance surface calculation. (1) Habitat quality index calculation. The InVEST model is a series of tools used to assess natural services. Using the habitat quality calculation tools in the InVEST model, habitat quality can be quantified by measuring the sensitivity of landscape classes and the intensity of external threats. In addition, the model assumes that if the habitat quality is good, then the biodiversity of the area is high. Habitat quality scores range from 0-1, and the higher the regional habitat quality value, the higher the score. The habitat quality \(Q_{xy}\) is calculated as follows. \[i_{rxy}=1-\left(\frac{d_{xy}}{d_{r\max}}\right) \tag{1}\]  
where \(i_{rxy}\) is the impact of the threat source on each raster in the ecoregion, \(d_{xy}\) is the distance between raster \(x\) and threat source \(y\) in the ecoregion, and \(d_{r\max}\) is the impact range of threat source \(r\). \[D_{xy}=\sum_{r=1}^{R}\sum_{y=1}^{Y_{r}}\left(\frac{\omega_{r}}{\sum_{r=1}^{R} \omega_{r}}\right)r_{y}i_{rxy}\beta_{x}S_{y} \tag{2}\]  
where \(D_{xy}\) is the degree of habitat degradation of raster \(x\) at position \(j\), \(r\) is the threat source in the ecoregion, \(y\) is the influence range of threat source \(r\), \(\omega_{r}\) is the weight of threat source \(r\), \(r_{y}\) is the intensity of threat source \(y\), \(\beta_{x}\) is the level of habitat resistance to disturbance, and \(S_{y}\) is the relative sensitivity of each habitat to different threat sources. \[Q_{xy}=H_{j}\left[1-\left(\frac{D_{xj}^{z}}{D_{xy}^{z}+k^{z}}\right)\right] \tag{3}\]  
where \(H_{j}\) is the habitat suitability of land category \(j\), \(k\) is the half-saturation constant, i.e., half of the degradation maximum, and \(z\) is the default parameter of the model. (2) Remote sensing ecological index calculation. The remote sensing ecological index calculation is entirely based on remote sensing technology and natural factors, and it is used for rapid monitoring and evaluation of regional ecological conditions, which can quantitatively evaluate and compare the quality of regional ecological environment. The index uses the principal component analysis technique and integrates four evaluation indexes: vegetation index, humidity, surface temperature, and building index, which represent four ecological elements of greenness, humidity, heat, and dryness, respectively [40]. \[RSEI=f(NDVI,Wet,LST,NDBSI) \tag{4}\]  
where \(NDVI\) is the vegetation index, \(Wet\) is the humidity component, \(LST\) is the surface temperature, and \(NDBSI\) is the building and bare soil index.