Urban Forest Accessibility In Shenyang By Network Analysis

Urban forest is one of the main natural components of an urban ecosystem, bringing great ecological, economical, and social benefits and playing an important role in ecosystem sustainability. The recreational functions of urban forest typically receive increasing concern as citizens' living standards increase. Urban forest is highly emphasized and urban forest development is widely implemented domestic and overseas. However, planners mainly concern ecological function when making and implementing plans, giving little attention to social and cultural effect, especially recreational function of urban forest. At present, the widely used method to evaluate urban forest recreation is simple statistical indicators, but this method is deficient when evaluating the spatial distribution and recreational service of urban forest. For example, can current urban forest satisfy the demand of citizens in a city and is the spatial distribution of urban forest reasonable? How can the spatial distribution of urban forest in a city be optimized to maximize its recreational function? Research theory and method of recreation-oriented urban forest spatial distribution is scarce, which obstacles urban forest development and optimization of urban forest recreational function.GIS based accessibility can acquire information of spatial distribution and service status of urban public service facilities effectively, and is gradually applied to study urban forest spatial distribution. There are various method used to calculate accessibility, such as simple buffering, cost weighted distance, minimum distance, and gravity model. However, these methods cannot measure distance between citizens and urban forest realistically, and cannot exactly reflect the process of access to urban forest from residential area. Network analysis, based on maximum service distance of urban forest, can simulate service area of urban forest and calculate urban forest accessibility more realistically by measuring the distance of actual routes followed by leisure users. To test the usefulness of network analysis when evaluating urban forest accessibility and to acquire comprehensive information about the current status of accessibility and service of Shenyang's urban forest, we studied the accessibility and service of urban forest in Shenyang (a National Forestry City in China) and its eight districts from two spects (signle level and multipule levels) on two scales based on road and population distribution data using Network Analyst model in ArcGIS 9.2. The results showed that: (1) The method of GIS-based network analysis is more precise than the traditional statistical index method and simple buffering method when calculating urban forest accessibility, and two service indicators (service area ratio and service population ratio) are better than the conventional statistical indicators used to quantify service status of urban forest. (2) Urban forest in Shenyang is insufficient and its spatial distribution is uneven. Urban forest mainly exists in the central and western part of Shenyang, and urban forest in the eastern and southern part of Shenyang is very scarce, which cannot meet citizens' recreational demand. (3) Urban forest accessibility in Shenyang is low. For the criterion that an urban forest has a service radius of 1 kilometer, the values of service area ratio and service people ratio are low, only 27.42% and 57.35% respectively. Recreational ability of urban forest is limited. (4) The current service status of different urban forest level showed great various. The higher the urban forest level, the better its service. Urban forest of level I has the most problems. (5) Urban forest spatial distribution and urban forest accessibility in the central and western part of Shenyang are better than that in the eastern and southern part. Urban forest accessibility in Shenhe District and Heping District is the highest, while that in Yuhong District and Hunnan District is the lowest among the eight districts. (6) Road richness is the key factor affecting urban forest accessibility...