Rationale
National level environmental planning and management require information about the location of environmental features, their spatial extent and their significance. Within the GERMP/EISD framework each of the various types of information have been produced independently by institutions with the appropriate mandates. However, institutions produce information according to their own sector-specific set of standards. As a rule, differences in these standards are so extensive that data sets do not fit to each other.

Users of data have to adjust the different sets to each other before the data can be integrated. The technical burden involved in such adjustments inhibits the use of the data by non-specialists unfamiliar with the intricacies of geographic information. Furthermore, in the absence of "interoperable" data sets, every new usage of the data implies having to pay the same large integration overhead. This inflates the cost of using the data. The G-CAG database is designed to solve this problem, by building in linkages between features required to conduct environmental analysis.

The Database
The development of the G-CAG database was at the instance of the Environment Protection Agency (EPA) to meet its owns needs for data to facilitate environmental planning and decision-making at the national level, and to support sub-regional sustainable development initiatives. The World Bank mobilised the necessary financial resources for the project.

G-CAG might be seen as a generalisation and synthesis of the GERMP/EISD data, the main part of the data having been derived from the more detailed 1:250,000 databases developed under the GERMP/EISD project. Additional layers of information were compiled from other organisations. The aim was to construct a versatile and inter-operable database for use in large area planning. G-CAG is directed towards decision-makers and similar persons who need to have an overview over the country.

In one sense the data sets are intended as an introduction to the detailed data sets that are available at the custodian organisations. It could also be used as an introduction to Ghana for people that are not acquainted with the country. Data has been generalised to an approximate mapping scale of 1:1,000,000. This scale was judged appropriate for general purpose planning operations, yielding data sets of sizes that are easy to handle and still retains sufficient information detail for its purpose.

Most of the data is derived from national high-resolution data sets. The original data is thus in different scales and of different quality. A major task has been to harmonise input data to a general standard, yielding a homogeneous output. The level of generalisation varies but most of the original data sets contain information corresponding to at least a 1:250,000 scale. Apart from having a higher geographical resolution the original data sets also contains more complex databases. To fit the data in a suitable size classes were lumped together and some information had to be discarded.

G-CAG contains 51 geographically referenced and harmonised data sets covering 11 geographical themes, at the mapping scale of 1:1,000,000. These are the national and international boundaries, conservation areas, climate information, geology, hydrology, land cover, land ownership, soils, topography, infrastructure and population information (Table 1).

Table 1. Summary of major G-CAG data themes

Theme	Main Custodian institution(s)	Primary data format	Data set(s) in final G-CAG database	Data format in final G-CAG database
Boundaries	Lands Commission	ARC/INFO polygons	National Land surface Region District Map tiles (50’ and 250’ map series)	Polygon/Line
Climate data	Meteorological Services Department	Point data as ASCII	PET, year Rainfall, year, month Temperature, year, month	Polygon Polygon Polygon
Conservation areas	Forestry Department   Ghana Wildlife Department	ARC/INFO polygons 1:250000 Paper maps of varying scales	Forest reserves Forest resources Wildlife Reserves Etc	Polygon Polygon Polygon
Demography	Population Impact Project, University of Ghana, Legon	Tabular data, Excel format	Town pop District pop Region pop Population density Population time series 1984-2005 for selected features	All point data associated to the towns and administrative boundaries (polygons)
Geology	RSAU/EPA	Paper map (1:1 000,000)	Geological formations	Polygon
Hydrology	Water Research Institute	Paper map (1:1 000,000)	Principal river basins Rivers Water bodies	Polygon Line Polygon
Land cover	RSAU	ARC/INFO polygons	Land cover	Polygon
Land ownership	Lands Commission	ARC/INFO polygons	State land Stool Land	Polygon Polygon
Soil data	Soil Research	ARC/INFO polygons	Soil type	Polygon
Topography	Soil Research	ARC/INFO grid	Contour lines Elevation zones	Line Polygon
Transportation	Survey Department	ARC/INFO Lines	Roads Railroad	Line Line
Settlements	Survey Department Department of Feeder Roads	ARC/INFO polygons	District capitals Regional capitals Urban areas Town location	Polygon Point

The most important aspect of the data sets is that they have been compiled through collaboration among various national institutions. This means, in practice, that each data set has been checked and validated by the appropriate custodian agency responsible for collecting and maintaining the respective information. In other words, this constitutes an official repertoire of a uniform scale and spatially consistent data for national level planning.

The data will be distributed on CD-ROM and through the Internet.

Data Sets
The G-CAG database will include national level data on themes indicated in Table 1. Original data sets were derived from three major sources. The most important were data sets made available from custodian organisations involved in the GERMP/EISD project. These are all nationally mapped or compiled data layers at original map scales equivalent to 1:250,000.

The original data sets were quite complex and contained many attributes since they are intended for complex and detailed landscape analysis. The first task was to generalise the information to a level suitable for G-CAG. Generalisation was applied both on the spatial information (small polygons were omitted, lines were generalised, etc.), and on the attributes (classes were grouped to higher order groups, in complex databases only the most appropriate attributes were included, etc.).

The second source was data layers (normally in ARC/INFO-format) from other databases, or data that had to be digitised from paper maps. In these cases data was plotted and checked by the custodian organisation, changes were suggested and the resulting data approved before it was included in the database.

The third data source was tabular data with no geo-coding, or where data had to be interpolated. A specific example of the latter case is climate data. The interpolation was performed and checked by the Meteorological Services Department (MSD). The data set was then included in the database after harmonisation. Population data was available from the Population Impact Project (PIP) in table format. A selection of this data was made to include only major population information. The data was geo-coded by assigning the population attributes to the appropriate administrative unit.

The national boundary was extracted from the Digital Chart of the World (DCW) data set. This was used as the "standard" for adjusting the various input data sets. This would ensure that the boundary of Ghana, and the relative positions of other features, particularly in the neighbourhood of the boundary, will be consistent with other regional and international data set constructed on the basis of the DCW. The spatial databases are organised as ARC/INFO "coverages" Software

The context in which G-CAG should be used is mainly in planning and to explore the natural resources. It also provides an overview of the country. This means that many users may not be very experienced in GIS, and certainly not in handling geographical information using the ARC/INFO. The strategy has thus been to provide the data in a format that is readily accessible by easy to use.

Also, the G-CAG data set is distributed with ArcExplorer from ESRI. (It may also be down-loaded from ESRI's web site, http://www.esri.com/company/free.html. ArcExplorer is an easy-to-use "data viewer which includes very basic functionality for displaying ESRI data types. ArcExplorer reads the files directly from the database without any need for conversion.

For analytical work with the data ARC/INFO or ArcView GIS should be used. The experienced user or GIS analyst, who may want to edit, update, analyse or in any other way change the information in the database, is likely to have both experience and software access to more sophisticated GIS-tools. For the benefit of non-ARC/INFO or ArcView users ARC/INFO interchange (EXPORT) files are also provided on the distribution CD-ROM.

Further Information
General and technical information about the G-CAG project and database should be addressed to:
The Director,
Remote Sensing Applications Unit,
University of Ghana,
Legon
Tel: +233-21-500301
Fax: +233-21-500310
E-mail: gta@ug.edu.gh

Requests for individual data sets should be addressed to the respective custodian institution.