CHANGE DETECTION ANALYSIS OF GULLY EROSION IN THE TSITSA RIVER CATCHMENT, SOUTH AFRICA, USING ECOGNITION SOFTWARE

The Department of Water and Sanitation is planning to construct a dam on the Mzimvubu River, South Africa. The proposed dam site falls within the catchment area of the Tsitsa River which is a tributary of the Mzimvubu River. Previous studies conducted in the catchment highlighted the erosive nature of the soils which have resulted in widespread gully erosion. Sediment produced from this erosion will reduce the capacity and life span of the dam which is a major concern for the managers of the dam project. Thus, it is important to determine the extent of gully erosion in order to mitigate its effects. Previous studies have mapped gully erosion using manual digitising techniques. This was time-consuming and contained human error and bias. This study aimed to explore the use of object based image analysis to classify gully erosion at a catchment scale. Using SPOT 5 images in eCognition, a ruleset was developed using object brightness, texture and their relationship to neighbouring objects. The gullies classified in eCognition were used to create a gully location map of the dam catchment area. The use of eCognition removed the human error component and proved to be considerably less laborious. Results of the eCognition analysis were compared with results from the manual digitisation which produced an overall accuracy of 98% with a user’s and producer’s accuracy of 23% and 28% respectively. The study could be improved by using higher resolution imagery such as aerial photographs or Quickbird as well as the use of complementary data such as LiDAR data.