Datasets for HC's AI4ER PhD Project - I
<p>This repository contains all of the datasets required to replicate the results within the report. Note that these datasets are not necessarily the most up to date available from each organisation. These datasets have been processed in QGIS and should be used as input to the 'preprocessing.ipynb' notebook on the <a href="https://github.com/Hamish-Cam/depth-mapping">GitHub repository</a>. Note that some datasets are downloaded directly from Google Earth Engine and so are not included within this dataset repository (see notebook for download code).</p> <p>The following datasets are provided: </p> <ol> <li><strong>labelled_field_data.zip</strong> - collection of modern and historical peat thickness samples (various)</li> <li><strong>fens_outline.zip</strong> - shape file delineating the Fens boundary (Natural England)</li> <li><strong>landcover.tif</strong> - landcover classification map (UKCEH)</li> <li><strong>CROME.tif</strong> - crop map of England classification map (Rural Payments Agency)</li> <li><strong>lidar.tif</strong> - elevation map (Environment Agency)</li> <li><strong>MRVBF.tif</strong> - multiresolution valley bottom flatness (derived from lidar)</li> <li><strong>MRRTF.tif</strong> - multiresolution ridge top flatness (derived from lidar)</li> <li><strong>TWI.tif </strong>- topographic wetness index (derived from lidar)</li> <li><strong>distance_to_river.tif </strong>- euclidean distance to nearest river (derived from Ordnance Survey)</li> <li><strong>distance_to_watercourse.tif</strong> - euclidean distance to nearest watercourse (derived from Ordnance Survey)</li> <li><strong>NATMAPvector.tif </strong>- soil map classification map (LandIS)</li> <li><strong>NATMAPsoilscapes.tif</strong> - simplified soil map classification map (LandIS)</li> <li><strong>NATMAPcarbon.tif </strong>- soil carbon map (LandIS)</li> <li><strong>peaty_soils.tif</strong> - estimated map of peat occurrence (DEFRA)</li> </ol>
ShareScore
16/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 0
- Reuse readiness
- 0
- Engagement
- 8