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On September 23, 2024 at 9:35:50 AM +0100, Gravatar David Donnelly:

  • Updated description of Peatland Drainage and Erosion Scotland from

    ##PeatNet - Machine learning based segmentation of peatland drainage channels and erosion features in Scotland ###Machine learning based segmentation of peatland drainage channels and erosion features in Scotland These datasets provide high resolution spatial estimates of the location and extent of peatland drainage and erosion features for restoration prioritisation, climate reporting, and management. Peat makes up approximately a quarter of Scotland's soil by area. Healthy, undisturbed, peatland habitats are critical to providing resilient biodiversity and habitat support, water management, and carbon sequestration. A high and stable water table is a prerequisite to maintain carbon sink function; any drainage turns this major terrestrial carbon store into a source that feeds back further to global climate change. Drainage and erosion features are crucial indicators of peatland condition and are key for estimating national greenhouse gas emissions. Previous work on mapping peat depth and condition in Scotland has provided maps with reasonable accuracy at 100-m resolution, allowing land managers and policymakers to both plan and manage these soils and to work towards identifying priority peat sites for restoration. However, the spatial variability of the surface condition is much finer than this scale, limiting the ability to inventory greenhouse gas emissions or develop site-specific restoration and management plans. This work involves an updated set of mapping using high-resolution (25 cm) aerial imagery, which provides the ability to identify and segment individual drainage channels and erosion features. Combining this imagery with a classical deep learning-based segmentation model enables high spatial resolution, national scale mapping to be carried out allowing for a deeper understanding of Scotland's peatland resource and which will enable various future analyses using these data. ###There are multiple layers contained within the overall results: ###Drainage 1. 10 m raster of unit area density 2. 100 m raster of unit area density 3. 500 m raster of unit area density 4. Polyline of the centre line of each drain 5. Polygon ~5 m wide showing the area of the drain itself 6. Polygon buffered to the 30 m drained area as per Peatland Action/IUCN reference ###Erosion 1. 10 m raster of unit area density 2. 100 m raster of unit area density 3. 500 m raster of unit area density 4. Polygon of each individual erosion feature.
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    ##PeatNet - Machine learning based segmentation of peatland drainage channels and erosion features in Scotland ###Machine learning based segmentation of peatland drainage channels and erosion features in Scotland These datasets provide high resolution spatial estimates of the location and extent of peatland drainage and erosion features for restoration prioritisation, climate reporting, and management. Peat makes up approximately a quarter of Scotland's soil by area. Healthy, undisturbed, peatland habitats are critical to providing resilient biodiversity and habitat support, water management, and carbon sequestration. A high and stable water table is a prerequisite to maintain carbon sink function; any drainage turns this major terrestrial carbon store into a source that feeds back further to global climate change. Drainage and erosion features are crucial indicators of peatland condition and are key for estimating national greenhouse gas emissions. Previous work on mapping peat depth and condition in Scotland has provided maps with reasonable accuracy at 100-m resolution, allowing land managers and policymakers to both plan and manage these soils and to work towards identifying priority peat sites for restoration. However, the spatial variability of the surface condition is much finer than this scale, limiting the ability to inventory greenhouse gas emissions or develop site-specific restoration and management plans. This work involves an updated set of mapping using high-resolution (25 cm) aerial imagery, which provides the ability to identify and segment individual drainage channels and erosion features. Combining this imagery with a classical deep learning-based segmentation model enables high spatial resolution, national scale mapping to be carried out allowing for a deeper understanding of Scotland's peatland resource and which will enable various future analyses using these data. DOI: 10.1111/ejss.13538 ###There are multiple layers contained within the overall results: ###Drainage 1. 10 m raster of unit area density 2. 100 m raster of unit area density 3. 500 m raster of unit area density 4. Polyline of the centre line of each drain 5. Polygon ~5 m wide showing the area of the drain itself 6. Polygon buffered to the 30 m drained area as per Peatland Action/IUCN reference ###Erosion 1. 10 m raster of unit area density 2. 100 m raster of unit area density 3. 500 m raster of unit area density 4. Polygon of each individual erosion feature.