Existing research on evaluating the level of integrated rural-urban development by quantitative assessment methods often fails to separate the overall development index and coordinated development index and demonstrate cross-sectional and time series data simultaneously, and results in the "black box" effect by data aggregation. This article proposes a three dimensional coordinate system, including overall development index, coordinated development index, and temporal dimension and then converts the three dimensional coordinate system into a two dimensional coordinate system with the "nine squares" method, thereby making it possible to quantitatively evaluate the characteristics of change of each city within a city group. The level of balance and integration of development between urban and rural areas is divided into economic, industrial, infrastructural, and public services. An assessment on the characteristics of change of 19 cities in the Sichuan and Chongqing region during 2006-2011 was carried out. The research result shows that cities in the region achieved remarkable results in reducing the gap in economy and public services fields between urban and rural areas, but large gaps in the fields of industry and infrastructure still exist. The progress in Chongqing Municipality and the city of Chengdu is much greater than in other cities in the region. This research can provide theoretical guidance and methodological tools for improving rural-urban development in the Sichuan and Chongqing region, and can be useful for the evaluation of integrated rural-urban development in other cities of China.

Urban spatial analysis should be based on reliable measurements, and the most basic measurement of a city is its size. Defining urban boundaries objectively is fundamental for determining effective city size. In recent years, a number of Chinese and international scholars have developed improved methods of urban boundary identification. Among these, the majority apply vector data that can reflect the spatial organization relationships of entities internal of cities. However, access to these vector data is often limited. In this study, based on existing research a new method of urban boundary identification with remote sensing data as input and using neighborhood dilation and quantification is put forward. Our method takes a spatial neighboring merging approach. By changing the neighboring range of pixels, different numbers of spatial clusters are obtained. An optimal radius can be determined according to the scaling relationships between the neighboring range of pixels and the numbers of spatial clusters. GIS technology is then adopted to define urban boundaries. By applying this method to analyze remote sensing images of the Beijing area, we found the effective range of pixels. Remote sensing data used by this method are characterized by real-time acquisition and easy access. Also, the calculation procedure is straightforward. Thus, in future efforts of urban boundary identification, our new method may provide a complement to existing methods.

Using spatial analysis methods, the geographic pattern of pickpocket incidents along the Chang'an Street in Beijing was examined in this study. First, the crime distribution along the street was identified. The results demonstrate that major crime clustering areas existed in the Xidan business area (A), Jianguomen area (B), and Dawanglu-Sihui Area (C). By comparing the spatial pattern of crimes with population density and point of interest (POI) density along the street, it was found that crimes tended to be clustered around locations having higher POI density. In the next step, spatiotemporal patterns of offences in the three areas were analyzed using kernel density estimation and space-time hotspot matrix. The results indicate that zone A maintained higher crime level between 10 a.m. and 6 p.m. and the peak time appeared at 12 a.m., and the offences concentrated in the major shopping malls. However, in zones B and C, the higher level of crimes occurred in the hours around 6 a.m. and 6 p.m., which are the periods of peak traffic flow in the morning and evening. Lastly, some detailed crime prevention and suppression suggestions and strategies are proposed on the basis of the spatial attributes and blind areas theory.