Spatial Analysis of Quantitative Data Using Echelon Analysis (Case Study: Prioritization of Bird Rich Areas in Golestan Province)

Most studies of environmental phenomena are based on quantitative spatial data and modelling. The analysis and mapping of these quantitative variables have great importance, which affects result of the environmental models. It is therefore necessary to have a systematic method for determining spatial structure of quantitative data and their classification. Echelon analysis presents a method to investigate the structure of quantitative spatial data systematically and objectively. This methed considers spatial data as topographies and divides them into structural entities. Echelon displays the variable hierarchy of the quantitative data in landscape surface as a tree structure, and provides an effective method for interpreting patterns of concentration and connectivity. In this research, we apply the Echelon analysis to detect bird richness in Golestan Province. Results of the approach in two different scales of grids show that classification in the finer scale reveals spatial pattern that are not necessarily expected in the coarser scale. Therefore, finer scales analysis is necessary for determining possible location and networks of high species richness within a region. Also, the comparison between prioritization maps and protected areas shows zones with high priority that fall outside the protected area.