Tree Species Map England
收藏Open Data Forestry2026-02-23 更新2026-05-16 收录
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https://data-forestry.opendata.arcgis.com/documents/4ed4d3a72db8497cb6b0b58208996705
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<p style='text-align:justify;'><span style='font-size:12.0pt; line-height:107%;'>The species map represents a predicted distribution of common
tree species in England, produced using a time series of multispectral
satellite remote sensing data (Sentinel-2) and machine learning. A classifier
based on the XGBoost algorithm was trained to distinguish tree species,
utilising a time-series of surface reflectance data and labelled training
samples from the sub-compartment database (SCDB). To enhance classification
performance, minority species with fewer than 1,000 training samples were
grouped into broader categories, resulting in a total of 35 classes. Given the
significant class imbalances, a sample weighting strategy was employed to guard
against significant underfitting of the minority classes.</span></p>
<p style='text-align:justify;'><span style='font-size:12.0pt; line-height:107%;'>Model evaluation demonstrated strong classification
performance, with an overall accuracy of 89% and balanced class accuracy of
90%. Predictions were made at the pixel level and used to generate a <a>species classification and confidence raster</a> output.
Field validation for Norway spruce within the Ips typographus demarcated area,
confirmed a precision of 69%, aligning with test data results for this class.
Additional validation using National Forest Inventory (NFI) data further
reinforced model reliability, though accuracy was observed to be worse for
underrepresented species. </span></p>
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