# Developing a GIS Model for Identifying Bear Corridors with Open-Source Data: The Romanian Context
## 2 Materials and Methods  
The spatial databases embedded within the spatial analysis models form the foundation for integrated territorial assessments. These assessments consider both regionalization, such as identifying favorable areas for specific wildlife species, in this case, _Urtsus arctos_, and the prediction of potential movements between these areas, including the identification of ecological transit corridors. In the current study, several open-source spatial databases were collected, and these databases were later incorporated into spatial predictions regarding bear behavior. Modelling identified the ecological conditions required by bears for survival, reproduction, and improved connectivity of isolated populations. Regarding the development of the spatial databases, the research methodology was structured in two stages: first, the preparation of the support spatial database (Digital Elevation Model (DEM), land use classes (CLC), urban areas, and the network of communication paths and hydrological resources) was conducted. Second, the preparation of spatial analysis sub-models to obtain derived databases (slope, distance to transport infrastructure, water sources and urban areas) was performed, thus obtaining the modelled databases (favorability for _Urtsus arctos_) (Table 1). To identify the ecological corridors using the cost connectivity tool of the ArcGIS geoinformational software (ArcMap 10.8.2), the construction of a spatial analysis model that incorporates the support databases was based on the integrated management of the species and expert knowledge data (Figure 2). The modelling was based on expert knowledge of the ecological requirements of the species and consisted of the generation of spatial datasets that represent the main environmental factors on which the presence of the brown bear in the studied area depends. Through spatial analysis methods, these datasets were processed to obtain a quantifiable model of the degree of favorability for hunting grounds. Once the areas that have the highest degree of favorability are identified, they will represent the core areas necessary for establishing travel routes and for identifying areas where the construction of ecological corridors is necessary. The integration within the spatial analysis model of the factors that contribute to the identification of areas with different degrees of favorability/restrictiveness was conducted using the weighted average method using the following values as the basis of calculation: abiotic factors (30%), biotic factors (40%), and the negative anthropic factors (30%). The visualization of the degrees of restrictiveness/favorability was made on the basis of the reclassification of the digital database obtained as a result of the weighted average type analysis of four categories according to the score obtained by each individual hunting ground as follows: Category I (130-151 Points); Category II (100-130 Points); Category III (85-103 Points); Category IV (46-85 Points). \begin{table}
\begin{tabular}{c c c c} \hline \hline
\begin{tabular}{c} Extracted from Copernicus Land \\ Monitoring Service [21] \\ \end{tabular} & Vector, raster & 100 m/25 m \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Databases used in modelling. The Category I hunting grounds represent the core areas [28] used in the modelling of ecological corridors. These represent the areas where the quality of the habitat allows reproduction and survival in optimal conditions while respecting the ecological requirements of the species. The elevation of relief is one of the favorable factors considered for defining the cost grid, thus taking into account the needs of the species and the physical-geographical peculiarities of the study area, as well as the altitudinal distribution of the forest floors. The Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) is a globally recognized dataset generated from radar data collected during NASA's 2000 space shuttle mission.