Administrative Data

In WA and the GMS the spatial resolution of movement data were managed at the shire or province level respectively. In order to analyse the movements and display them on maps, it was necessary to have a suitable set of spatial data to be able to identify all necessary locations. This allowed the calculation of centroids which could be used to draw line maps, locate the nearest roads and calculate distances, as well as automatically generate choropleth map outputs.

4.2. MATERIALS AND METHODS 73 Western Australia

Western Australia covers an area of 2 532 400 km2 _{and had 1 997 000 cattle in}

the 2008/09 year (Australian Bureau of Statistics, 2010). The state is divided into 120 local government areas (LGA) (known as shires or towns, but all referred to in this paper as shires). The human and livestock populations are concentrated in the south west of the state. Outside the Perth metropolitan area cattle production is carried out in all but one of the shires.

The spatial units identified by NLIS PIC codes are the responsibility of the relev- ant state or territory to identify and administer. In WA they are closely related to current shires in most parts of the state (some boundary changes and amalgama- tion/separation of these shires have occurred since the property codes were originally allocated, but the properties retain their original code). Because of these changes current administrative boundary data for WA were sourced from the Australian Bureau of Statistics (ABS) (Australian Bureau of Statistics, 2009), and some modi- fications of the geometry were required to ensure shire PIC codes were matched with an existing areal unit.

Shires were matched to the NLIS data codes for 120 shires, towns and cities out- side the Perth metropolitan area. The shire of Ngaanyatjarraku was created in 1993 by dividing the Wiluna Shire. There are no livestock holdings in the Ngaan- yatjarraku shire thus all NLIS records referring to Wiluna were left referring to only Wiluna. A new polygon was added to represent the location of the City of Kalgoorlie, which was originally managed as a separate administrative area. The current shire of Broomehill-Tambellup was split East-West to create Broomehill in the north, and Tambellup in the south to approximate original shire codes in the NLIS database.

To account for seasonal management differences the state was split into three regions, summer rainfall, southern rangelands and south west agricultural (Figure 4.2). The boundaries approximate the Northern Rangelands, Southern Rangelands and Agri-

cultural regions used by DAFWA4; however they were constructed using ABS shire boundary data. This allowed analysis of movements by region as well as time.

Figure 4.2: Western Australia showing management regions used in this study.

Greater Mekong Subregion

No consistent, accurate and up-to-date data sets are publicly available that cover the entire GMS5_{. Most countries have well developed GIS data sets incorporating}

boundaries of administrative units, as well as up-to-date road information, natural features (including watercourses and population areas) and land use. This data may be available under licence6 _{for use by non-government users. Cameron (1997) noted}

that Cambodia and Laos have had well developed maps at 1:50 000 resolution in 1997. Other countries have limited up-to-date data available for non-government use (if at all).

Vietnam for example, has relatively well developed spatial data, but charges full cost recovery to other government departments for access to these data, and only makes

4_{The regions are shown on the DAFWA website at http://www.agric.wa.gov.au/.}

5_{Or at least, this was the situation when this research started. In fact, efforts such as Global} Administrative Areas http://www.gadm.org/ and OpenStreetMap http://www.openstreetmap. org are improving this situation. There is also the United Nations Second Administrative Level Boundaries project http://www.unsalb.org/ which while promising early has had little progress in the target countries for this research.

6_{For example, in Australia the ABS provides data under a Creative Commons Attribution} licence which is available at http://creativecommons.org/licenses/by/2.5/au/

4.2. MATERIALS AND METHODS 75 a limited subset available to foreigners. As an example a quote of ≈ USD 20 000 was offered for a set of village point location data (Dung Do, personal communication, 2010). Compounding this problem, is a lack of consistency between geographic projection systems (and their application), confusion about datums, nomenclature, standards for naming, and in some cases the adoption (or lack thereof) of the Unicode standard for text encoding, to allow viewing of names in local languages without the need for a specific font set. Over time a number of projects have attempted to rectify this situation, and provide unified consistent data into the public domain, for example Digital Chart of the World.

A data set of provinces was created by using the freely available data set of Digital Chart of the World7_{. All data were stored in a relational database PostgreSQL}8 _with

the spatial extension PostGIS9_{. The province data were then updated by comparing}

the province boundaries with more recent data sets such as the current Cambod- ian administrative data (supplied by the Cambodian Department of Animal Health and Production), Laos administrative data (supplied by the Laos Department of Livestock and Fisheries) and various copyright restriction free data sets supplied by Non-Government Organisations such as Global Administrative Areas10 and Open- StreetMap11_{. Importantly, this process was required to take into account areal}

modifications such as the discontinuation of the Xaisomboun Special Administrat- ive Region in Laos. Map editing was done using Quantum GIS12 _{and topological}

correction managed using GRASS13_{. Most of these data had poor or limited correc-}

tion for topology, and some were very high resolution depending on the original data source. This resolution was unsuitable for regional-level analysis and mapping, in- creasing processing and rendering times, and resulting in large file sizes. To overcome this, the resolution of the underlying data was reduced using the Douglas-Peuker

7_{http://www.maproom.psu.edu/dcw/, no longer available.} 8_{http://www.postgres.org/}

9

http://postgis.refractions.net/ 10

http://www.gadm.org/, accessed repeatedly from 2009–2011. 11

http://www.openstreetmap.org/, accessed repeatedly from 2009–2011. 12

http://www.gqis.org/ 13

algorithm14 implementation in GRASS which preserved the boundary topology. A five-level hierarchical coding system was implemented (country, province, district, commune and village) and stored in the database table alongside the geographic unit name (in English as well as the local language). The hierarchical code was used as the common identifier between data and geographic location. Data matching was done using the application developed for FMD outbreak investigations using Metaphone phonetic matches (previously discussed on page 42).