Case03A-Mapping Place Names in Guangxi China

Chapter 3 Spatial Smoothing and Spatial Interpolation

This chapter covers two generic tasks in GIS-based spatial analysis: spatial smoothing and spatial interpolation. Both are useful to visualize spatial patterns and highlight spatial trends. Spatial smoothing computes the average values of a variable in a larger spatial window to smooth its variability across space. Spatial interpolation uses known (observed) values at some locations to estimate (interpolate) unknown values at any given locations.

There are three case studies. The first case study of place names in southern China illustrates some basic spatial smoothing and interpolation methods. The second illustrates how to use area-based spatial interpolation methods to transform population data between different census areal units. The third demonstrates how to use the spatio-temporal kernel density estimation (STKDE) method for detecting spatiotemporal crime hotspots.

Case Study 3A:Mapping Place Names in Guangxi, China

This case study examines the distribution pattern of contemporary Zhuang place names (toponyms) in Guangxi, China, based on a study reported in Wang et al. (2012). Zhuang, part of the Tai language family, are the largest ethnic minority in China and mostly live in the Guangxi Zhuang Autonomous Region (a provincial unit simply referred to as “Guangxi” here). The Sini? cation of ethnic minorities, such as the Zhuang, has been a long and ongoing historical process in China. The impact has been uneven in the preservation of Zhuang place names. The case study is chosen to demonstrate the bene? t of using GIS in historical-linguistic-cultural studies. Spatial analysis techniques such as spatial smoothing and spatial interpolation methods can help enhance the visualization of the spatial pattern of Zhuang place names.

The data folder Guangxi includes:

1. point feature Twnshp.zip for all townships in the region with the field Zhuang identifying whether a place name is Zhuang (=1) or non-Zhuang (=0) (mostly Han), and

2. two polygon features County.zip and Prov.zip for the boundaries of counties and the provincial unit, respectively.

Computational Methods and GIS Applications in Social Science - KNIME Lab Manual

Lingbo Liu, Fahui Wang

External resources

• Github for Workbook Issue Report
• Github for Geospatial Analytics