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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&nbsp;available from each organisation. These datasets have been processed in QGIS and should be used as input to the &#39;preprocessing.ipynb&#39; 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&nbsp;are provided:&nbsp;</p> <ol> <li><strong>labelled_field_data.zip</strong> - collection of modern and historical peat thickness samples&nbsp;(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> -&nbsp; 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&nbsp;(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