A comprehensive framework for exploratory spatial data analysis:Moran location and variance scatterplots

A significant Geographic Information Science(GIS)issue is closely related to spatial autocorrelation,a burning question in the phase of information extraction from the statistical analysis of georeferenced data.At present,spatial autocorrelation presents two types of measures:continuous and discrete.Is it possible to use Moran’s I and the Moran scatterplot with continuous data?Is it possible to use the same methodology with discrete data?A particular and cumbersome problem is the choice of the spatial-neighborhood matrix(W)for points data.This paper addresses these issues by introducing the concept of covariogram contiguity,where each weight is based on the variogram model for that particular dataset:(1)the variogram,whose range equals the distance with the highest Moran I value,defines the weights for points separated by less than the estimated range and(2)weights equal zero for points widely separated from the variogram range considered.After the W matrix is computed,the Moran location scatterplot is created in an iterative process.In accordance with various lag distances,Moran’s I is presented as a good search factor for the optimal neighborhood area.Uncertainty/transition regions are also emphasized.At the same time,a new Exploratory Spatial Data Analysis(ESDA)tool is developed,the Moran variance scatterplot,since the conventional Moran scatterplot is not sensitive to neighbor variance.This computer-mapping framework allows the study of spatial patterns,outliers,changeover areas,and trends in an ESDA process.All these tools were implemented in a free web e-Learning program for quantitative geographers called SAKWeb#(or,in the near future,myGeooffice.org).

Spatio-temporal evolution and factor explanatory power analysis of urban resilience in the Yangtze River Economic Belt

Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.

The measure and characteristics of spatial-temporal evolution of China＇s science and technology resource allocation efficiency

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001-2010, using modified method--Data Envelopment Analysis （DEA）, science and tech- nology （S＆T） resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of S＆T resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of S＆T resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis （ESDA）. It turned out that： （1） the average of S＆T resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening. （2） The asymmetrical distribution of S＆T resource allocation effi- ciency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose S＆T resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China. （3） The coupling degree between S＆T resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of S＆T resource allocation efficiency is common in regional devel- opment, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of S＆T resources and so on. （4） In the perspective of the evolution of spatial structure, S＆T resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of S＆T resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency. （5） Viewed from LISA agglomeration map of S＆T resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the conti- nuity of S＆T resource allocation efficiency in geographical space is gradually increasing.

ndustrial eco-efficiency and its spatial-temporal differentiation in China

The aim of this paper is to study the spatialtemporal differentiation of industrial eco-efficiency in China. Using methods based on the data envelopment analysis （DEA） model and exploratory spatial data analysis （ESDA） and data from 1985, 1995, 2005, and 2008 of 30 provinces in China, the spatial-temporal pattern changes in industrial eco-efficiency are discussed. The results show that： first, the patterns of industrial eco-efficiency are dominated by clustering of relatively low efficiency provinces; second, spatial relationships between the industrial eco-efficiencies of different provinces changed slightly throughout the period and the provinces persistently exhibit spatial concentration of relatively low industrial eco-efficiency; finally, there is an obvious trend in the polarization of industrial eco-efficiency, i.e., the higher level spatial units are concentrated in eastern China, and the lower level spatial units are mainly in western and central China. （ESDA）

Analyzing space-time evolution of rural transition in a rapidly urbanizing region:A case study of Suzhou,China

Influenced by globalization,rural transition in developed Western countries has experienced processes of productivism,post-productivism,and multifunctional development.By contrast,rural transition in most developing countries has been accompanied by rapid urbanization,which has become a core topic in geography research.As the world’s largest developing country,China has undergone profound development since the reform and opening-up.Moreover,rural spaces in some eastern coastal areas have entered the stage of reconstruction after decades of industrialization and urbanization.This paper takes Suzhou as the case area and measures the process of rural transition from 1990 to 2015 by constructing an index system.It then analyzes the characteristics of space-time evolution using exploratory spatial data analysis(ESDA)methods to reveal the influence of economic and social development on rural transition.The results show that rural transition,which generally entails the weakening of rurality and enhancing of urbanity on a macro scale,tends to be heterogeneous across different regions on a micro scale.This paper argues that multifunctionality will be the main future trend of rural transition in rapidly urbanizing areas.The experience in Suzhou could provide an example for establishing policies on sustainable development in rural spaces and achieving urban-rural co-governance.