Spatial analysis and geovisualization on the relationship between the green land and the population in the urban area - A case study in Taipei city

Plants are essential to human lives. Green land, such as parks, is the lung of a city. It does not only provide oxygen for people to breathe, but also provide a space for people to relax or to have some social activities. In this study, we would like to figure out the relationship between the green land and the nearby population. The average area of green land for each person is calculated as an index and is mapped as the base layer for the spatial analysis. The first discussion is focused on the distribution of the green land index. The higher index usually suggests a better living quality in an urban environment. The second focus is to examine the relationship between the green land index and the price of the real estate. A special attention is paid to those area where the green land index is high but the price is comparatively low. Finally, a survey is conducted to understand the habitant's feeling about their living quality in different index area. To distinguish the green land in Taipei City, the multispectral images taken by the SPOT satellites are used to calculate the vegetation indices, such as the NDVI (Normalized Difference Vegetation Index) and the greenness index. The green land is classified based on the vegetation indices. Since the government has published the population layer as the open data, the polygons in the population layer are used as the statistical unit. An adequate buffer is grown around the population polygon for calculating the area of green land inside the buffer. So, the average area of green land for each person can be calculated as the proposed index, we call it the “Normalized Green Area Index (NGAI)”. This NGAI is served as an evaluation on the living quality associated to the green land in the urban area. Then, the NGAI is mapped as the base layer for further spatial analysis. The price of real estates in Taipei City is the other open data we used in this study. Usually the residential real estates around a park have higher price. The NGAI is used to investigate and to verify this presumption. For those area where has higher NGAI but lower price, we will try to find out the reason behind the phenomenon. To understand the living quality around the city, we conducted a survey to habitants in different NGAI area. The statistical summary of the survey is served as a bridge to connect the NGAI and the living quality about the green land near the habitants. We hope the proposed approach can be applied to different cities and be associated to more domain knowledge in the future.