Spatial Analysis of the Urban System in Guangdong Province of South China Using Population and Economic Indicators

The Open Geography Journal, 2008, 1, 1-14

J. Shen

“Much advance has been made in the study of the new urbanization process in post reform China. But the resulting urban system in Guangdong province has not been thoroughly analyzed creating a knowledge gap between the new urbanization process and the new urban system. This paper attempts to reveal the emerging urban system hierarchy in the 1990s in Guangdong province under socialist market economy using rank-size distribution as a yardstick. As there was substantial discrepancy among the rank-size distributions of cities in terms of population and economic indicators especially due to the existence of “temporary population” and the policy of “designating a whole county as a city”, the urban system in Guangdong province was analyzed using demographic and economic indicators. The significant role of economic development in urban growth was also identified through cross-sectional comparison and correlation analysis of time-series data on economic and urban indicators.”

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Sensitivity of GIS-derived Terrain Variables at Multiple Scales for Modelling Stoat (Mustela erminea) Activity

Applied Geography, In Press, Corrected Proof, Available online 22 September 2010

R.D. Martin, L. Brabyn, M.A. Potter

“This research combines automated Geographical Information Systems (GIS) and iterative logistic regression scripting to data-mine for terrain variables that predict stoat (Mustela erminea) visitation to tracking-stations in a New Zealand indigenous forest and explore the impact of spatial analysis scale on modelling outcomes. Variables such as curvature and density of tracks are dependent on the scale of the analysis window used to compute the values. With automated GIS analysis it is possible to derive a large number of terrain parameters that vary in computational scale. It is common for analysts to make nominal choices regarding the size and type of analysis windows when calculating these derived variables, without testing the statistical validity of that choice. Stoats are a significant pest in New Zealand and threaten extinction for a number of vulnerable native species. Field data on stoat activity, based on footprint tracking tunnels, were used to develop an Akaike Information Criterion (AIC) optimised predictive model applying stepwise model selection. Once the optimal model was determined, the sensitivity of the model to different terrain parameters was tested by systematically substituting each variable and calculating the difference this made to the model equation. The most dominant terrain predictors influencing stoat visitation were proximity to tracks, altitude, northerly and easterly aspect, mean curvature, and topographical position and slope. Proximity to tracks and mean curvature were the most sensitive variables to analysis scale. This paper demonstrates the importance of considering scale in developing predictive models and the need to test many ecologically sensible analysis scales in order to find the best predictive variables. The paper concludes that GIS-based spatial data extraction, combined with automated statistical data mining methods, has an important role in developing accurate animal activity models.

“Research highlights

  • This research demonstrates that choice of computational scale can be important for some modelling.
  • Choice of analysis scales was found to affect terrain effects in a logistic regression modelling analysis.
  • Terrain variables most influencing stoat visitation were tracks, altitude, aspect and curvature.
  • Proximity to tracks and mean curvature were the most sensitive variables to analysis scale.”

More information

Collect and Update GIS Information Directly from iOS Devices

Esri Releases ArcGIS App Update

Esri has released an updated version of its ArcGIS for iOS app. In addition to using the app to discover and explore maps, find places and addresses, and query map layers and data, users can now collect and update geographic information system (GIS) information directly from their iPhone, iPad, or iPod touch devices.

The app lets users collect, edit, and update features and attribute information while performing field data collection and inspection. The update is available at no cost from the App Store.

Users of the updated ArcGIS app can

  • Use onboard GPS to collect and update GIS data.
  • Attach photos and movies to collected data.
  • Tap on the map to get information about a location.

In addition to the ArcGIS app, an API is also available that lets developers and Esri partners create focused, spatially enabled applications for iOS devices. These custom apps can be deployed within an enterprise or to the public via the App Store.

To download the app update, visit the App Store.
To learn more about the ArcGIS for iOS app, visit

[Source: Esri press release]