GIS Techniques for Cross-Time Analysis of China County Data
Mark Henderson
Department of Environmental Science, Policy, and Management
University of California, Berkeley
mhenders@nature.berkeley.edu
Abstract: In this presentation I'll report on recent work on the regional systems analysis of contemporary China by
Dr. G. William Skinner's team at UC Davis, with particular emphasis on the techniques we have developed for
managing and analyzing data for county-level administrative units whose boundaries change over time. The regional
systems analysis project aims to model the spatial structures of China's economy and society at multiple hierarchical
levels. GIS coverages of China's transportation network and county boundaries as of 1982 and 1990 provide the
framework for carrying out this analysis. But county boundaries are subject to the modifiable areal unit problem
(MAUP), which is only compounded when comparing units that change over time. To address this problem we have
developed methods to split and merge counties to achieve units that are comparable across the time frame of our
analysis. We manage and automate these analytical transformations using the region subclass features of Arc/Info
GIS. These techniques may be applied fruitfully to the analysis of data for any administrative units whose
boundaries change over two or more points in time.
Outline:
A. Regional Systems Analysis of Contemporary China
1. Theoretical framework for the model
Views “cities as systems in systems of cities”
Identifies a hierarchy of cities from metropolises to villages
Regions as cities’ social/economic “catchment” areas
Social spatial structures are expected to relate to the distance from nodes at each hierarchical level
2. Two maps: Macroregional zones and City System zones
3. Example: Birth Planning Policy in Lower Yangzi (tables)
4. Example: Birth Planning Policy in Lower Yangzi (graphs)
5. Data used to construct the model
Statistical data: 1982 census, 1985 agricultural census, 1990 census, 1988 Shandong market data
GIS data: 1:1,000,000-scale map of China, 1:250,000-scale map of Shandong
6. Satellite imagery: DMSP-OLS nighttime light images
7. Satellite imagery: AVHRR 1 km images
8. Satellite imagery: Landsat images
9. Recent Developments
Linked household data from 1990 census to county, township, and settlements
Linked 1982 and 1990 county records and maps
Completed central place analysis for Shandong
Revising all-China model for an 8-level hierarchy
B. Cross-Time Analysis of County Data
10. Challenges for GIS
Geocoding (ID) differences between tabular data and GIS maps for approximately the same dates
Geocoding differences over time: ID’s that change
Areal differences over time: boundaries that change
Modifiable Areal Unit Problem (MAUP)
Performing regional systems analysis with county boundaries
11. Problems due to scale: MQ units
City districts (qu) are usually too small to map
For GIS purposes, these are merged into a larger, mappable unit
New geocode required to represent the merged unit
12. Addressing administrative inconsistency: MC units
Government has created “county-level cities”
For analytical purposes, these units are merged into Municipal-Compatible (MC) units
13. Facilitating analysis over time: XT units
County boundaries have changed over time
Cross-time comparisons require equivalent units
Merge units from each time period into the smallest common unit
14. Facilitating regional analysis: RS units
Regional systems may divide some peripheral units
Apply a rule for apportioning county populations among different systems
15. Automating XT units with Arc/Info Regions (1)
Regions consist of one or more polygons sharing a single database record
Our approach uses region subclasses for each temporal and analytical file
“Atomic” polygons are the largest indivisible units across all files
16. Automating XT units with Arc/Info Regions (2)
REGIONXAREA command
RELATE regions to component arcs and polygons for cartographic use