Geographical information services and products provider GeoTerraImage launched its Southern African Mine dataset last month, which uses satellite imagery to produce information on mining activity in 12 countries in Southern Africa.

The dataset indicates mining activity in South Africa, Zimbabwe, Angola, Mozambique, Malawi, Namibia, Botswana, Swaziland and Lesotho, Zambia and Tanzania, as well as the Copperbelt region in the Democratic Republic of Congo.

GeoTerraImage director Mark Thompson explains that the development of the dataset, which started in January and was completed by August, was implemented as a logical follow-on to the successful completion of the South African Land Cover dataset, which includes information on local mine activity. The mapping of South African mining activity was then expanded to include other mining regions in Southern Africa.

The Southern African Mine dataset was created using imagery acquired by the US Geological Survey’s Landsat 8 satellite. Thompson says the Landsat 8 satellite can provide repeat image coverage of any given area every 16 days, providing frequent and current updates.

The satellite imagery used in the Southern African mining dataset was acquired during 2014 and 2015, making it the most recent mining reference dataset of its kind.

He explains that the satellite imagery was used to identify geographical cues, such as bare ground surfaces, that could be representative of mining activity, such as extraction pits and tailings dams. This geographical information was then evaluated against high-resolution comparable imagery in order to verify that the land use is, in fact, representative of mining activity and not other buildings or industrial activity.

The dataset provides detailed spatial information on a wide range of mining activities across Southern Africa, ranging from small quarries and road-side borrow-pits to large commercial operations. It therefore represents comprehensive baseline reference information about mining activities in the region.

Thompson says what makes the Southern African Mine dataset valuable is that the information is current and available as either spatial data in a digital map format or in spreadsheet format to support a wide range of end user information requirements and capabilities.

He highlights that, for example, the information can be used for regional environmental impact assessments to look at the number of mining operations in a hydrological catchment area, as well as catchment areas which might be affected downstream by mining activity.

Alternatively, it can be used by suppliers of regional mine resource and licence information to cross-reference and help verify their own data records.

“It is the only dataset we know of which describes the total spatial footprint of current mining activities across Southern Africa,” Thompson asserts.

He points out that a major milestone of the project was processing the significant amount of information covering all 12 countries in such a short time. “We have managed to use cutting-edge image-processing techniques to fast-track the production of a dataset that is both relevant and current, whilst ensuring the output is standardised in terms of the level of detail, accuracy and future repeatability.”

The source imagery, processing techniques and methods used to compile the Southern African Mine dataset are dynamic and can be applied to any mining area, he notes.

Thompson concludes that, depending on the success of this dataset, the company hopes to expand it to include other mining regions. “There is no technological hurdle to expanding this information,” he assures.