Input data for predicted mud content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting mud content on the Norwegian continental margin (https://github.com/diesing-ngu/GSMgrids). The following files are included:</p><p><strong>gsm_data.csv</strong> - Data on gravel, sand and mud of surface sediments</p><p><strong>MGObsPkt_150_160_170.shp </strong>- Point shapefile of categorical samples</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>GrainSizeReg_folk8_probabilities_2023-06-28.tif</strong> - Georeferenced TIFF-file of the prediction probabilities of the predicted substrate classes. Used as additional predctors.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0