Long-term monitoring is frequently required as part of river and stream restoration projects. An increasingly common aspect of these monitoring campaigns involves conducting repeat topographic surveys through time, to document changes in geomorphology. As topographic data becomes easier to acquire through remotely-sensed surveys (e.g. airborne LiDaR, aerial photogrammetry), ground-based surveys (e.g. ground-based LiDaR, total station surveys, rtkGPS), boat based surveys (e.g. multibeam and singlebeam SONAR) and hybrid approaches of all the above, more and more people will have time series of repeat topographic data. However, given the uncertainties in the survey data, it is not always clear how or whether these topographic data can be used to detect changes and or derive morphological sediment budgets.
The GCD software was developed primarily for morphological sediment budgeting in rivers. The volumetric change in storage is calculated from the difference in surface elevations from digital elevation models (DEMs) derived from repeat topographic surveys. As each DEM has an uncertain surface representation (which might vary in space and time), our ability to detect changes between surveys is highly dependent on surface representation uncertainties inherent in the individual DEMs. The fundamental problem is separating out the changes between the surveys that are due to geomorphic change as opposed to noise in the survey data and subsequent interpolated surfaces. GCD provides a suite of tools for quantifying those uncertainties independently in each DEM and propagating them through to the DEM of difference. The software also provides ways for segregating the best estimates of change spatially using different types of masks to help test hypotheses and better explain the results. The overall suite of tools is widely applicable to many different spatial change detection problems, not just geomorphological change.
Anyone who has (or will have) repeat topographic data sets and wants to be able to robustly quantify geomorphic changes from those data sets. This may include those responsible for conducting monitoring campaigns, and/or those interested in interpreting the data from such efforts. Participants will include resource managers, restoration practitioners, researchers, graduate students and others involved in the monitoring of rivers and/or streams. Although restoration monitoring applications will be used as examples, the skills developed are more broadly applicable to geomorphic monitoring.