Temporal monitoring of groundcover change using digital cameras

This paper describes the development and testing of an automated method for detecting change in groundcover vegetation in response to kangaroo grazing using visible wavelength digital photography. The research is seen as a precursor to the future deployment of autonomous vegetation monitoring systems (environmental sensor networks). The study was conducted over six months with imagery captured every 90 min and post-processed using supervised image processing techniques. Synchronous manual assessments of groundcover change were also conducted to evaluate the effectiveness of the automated procedures. Results show that for particular cover classes such as Live Vegetation and Bare Ground, there is excellent temporal concordance between automated and manual methods. However, litter classes were difficult to consistently differentiate. A limitation of the method is the inability to effectively deal with change in the vertical profile of groundcover. This indicates that the three dimensional structure related to species composition and plant traits play an important role in driving future experimental designs. The paper concludes by providing lessons for conducting future groundcover monitoring experiments.