The provision of regular , high-cadence , high-detail water resource maps will support accurate and timeous monitoring of the status of local , regional and national water resources . Water surface extents are automatically generated from imagery recorded by the European Space Agency ’ s ( ESA ) Sentinel2 satellite , which has been operational since June 2015 . Sentinel2 provides multiple imaging overpasses per month , minimising information loss due to cloud cover , and supports a minimum water feature mapping size detection capability of between 0.1 and 0.4 ha ., depending on water and surrounding landscape characteristics . Each month , a set of three total surface water products are generated that describe :
( a ) the long-term maximum surface water extent ( since Sentinel2 operational commencement at the end of 2015 );
( b ) the maximum surface water extent from the preceding 6 months ; and ( c ) the current month ’ s total water surface extent . In all cases the mapped water datasets are based on 20-metre raster cells , equivalent to the base resolution of the Sentinel2 imagery used . The mapped total surface water area represents the combined extent of both natural and manmade water features , as observed within each of the assessment timeframes .
The image data modelling procedures that have been developed remove any confusing water identification issues relating to other landscape characteristics , such as dark wildfire burn scars , terrain shadows , and cloud shadows , all of which have similar spectral characteristics to water and can lead to classification confusion and mapping errors .
The GeoTerraImage water identification algorithms have been developed using in excess of 100 000 sample points , distributed across South Africa , that represent a wide range of seasonal and regional water and non-water reference characteristics .
The spectral data associated with these reference samples has been used to derive a complex set of ( image classification ) rules that can be applied repeatedly to cloud-based satellite image archives . This allows for mapping and monitoring of the total surface water extent across South Africa on a regular and repeatable basis . Since the rules are both generic and standardised , the water information outputs are directly comparable over time and have the same mapping accuracies and information content , resulting in a very reliable monitoring procedure .
Examples of modelled water extents over the Vaal Dam region are illustrated in Figures 1 to 4 , which represent the Vaal Dam ( and surrounding smaller dams ), surface water extents for the months of 12-2015 , 09-2016 and 09-2017 . These three dates represent pre-drought , mid-drought and postdrought conditions , and clearly show the timedependent fluctuations in Vaal Dam surface water area over this period . If these time-series water extents are combined into a single overlapping illustration ( Figure 4 ), then the fluctuating water levels are highlighted even further .
Note : Figures 1 to 3 have a generic image background , whilst Figure 4 has a hill shaded-terrain backdrop . u
Vaal Dam surface water extent 12-2015 .
Vaal
Dam surface water extent 09-2016 .
Vaal Dam surface water extent 09-2017 .
Combined Vaal Dam water surface extents for 12-2015 , 09-2016 and 09-2017 . netwroking contributor industry debate environment infrastruture municipalities
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