| hasData_Center_Short_Name |
- Deutsches GeoForschungsZentrum GFZ
|
| hasDataset_Online_Resource |
|
| hasDataset_Release_Date |
|
| hasDataset_Title |
- PebbleCounts: a Python grain-sizing algorithm for gravel-bed river imagery
|
| hasEntry_ID |
|
| hasKeyword |
- grain sizing
- grain-size distribution
- python
- science > geography > geomorphology
|
| hasSummary |
-
Grain-size distributions and their associated percentiles are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are typically achievable only at the patch (1 square meter) scale. With the advent of unmanned aerial vehicle systems and increasingly high-resolution cameras, we can now generate orthoimagery over large areas at resolutions of <1 cm. These scales, along with the complexity of many natural environments in high-mountain rivers, necessitate different approaches for photo sieving. Here, a new open-source algorithm is presented: PebbleCounts. As opposed to other image segmentation methods that use a watershed approach and automatically segment entire images, PebbleCounts relies on k-means clustering in the spatial and spectral (color) domain and rapid manual selection of well-outlined grains. This results in improved estimates for complex river-bed imagery without the need for post-processing.
|
| GCMD Sciencekeywords describing the dataset. Click on Keyword to find similar datasets | |
