| _version_ | 1866902330413154304 |
|---|---|
| author | Gass, Leonie Hülsmann, Lisa |
| author_facet | Gass, Leonie Hülsmann, Lisa |
| contents | <p>We combined regeneration density observations from the German NFI to map the forest regeneration across Germany and evaluate potential regeneration gaps using a three-step approach. First, we combined the NFI regeneration data with environmental data to construct species-specific regeneration models. Second, we evaluated the predictive performance of the regeneration models using 10-fold blocked cross-validation and used the validated models to predict regeneration densities for the forest area of Germany. Third, we mapped indicators of regeneration quantity and quality, demonstrating their potential application for Bavaria. </p> <p>Here this repository consists of:</p> <ul> <li>data.zip (input data)</li> <li>output.zip (output data)</li> <li>GermanRegenerationMaps2012_workflow.png (code workflow to generate output.zip from data.zip)</li> <li>Predictors.png (information on predictor variables)</li> <li>Sapling_DHARMaresidual.pdf (information on model residuals)</li> </ul> <p>See additional information in related works:</p> <ul> <li>for full data references please look up our publication</li> <li>for related code see GitHub and Zenodo</li> <li>to view and explore the generated regeneration maps online please see Google Earth Engine </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18455038 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Data for German Regeneration Maps 2012 Gass, Leonie Hülsmann, Lisa forest regeneration map species distribution regeneration indicators tree species national forest inventory <p>We combined regeneration density observations from the German NFI to map the forest regeneration across Germany and evaluate potential regeneration gaps using a three-step approach. First, we combined the NFI regeneration data with environmental data to construct species-specific regeneration models. Second, we evaluated the predictive performance of the regeneration models using 10-fold blocked cross-validation and used the validated models to predict regeneration densities for the forest area of Germany. Third, we mapped indicators of regeneration quantity and quality, demonstrating their potential application for Bavaria. </p> <p>Here this repository consists of:</p> <ul> <li>data.zip (input data)</li> <li>output.zip (output data)</li> <li>GermanRegenerationMaps2012_workflow.png (code workflow to generate output.zip from data.zip)</li> <li>Predictors.png (information on predictor variables)</li> <li>Sapling_DHARMaresidual.pdf (information on model residuals)</li> </ul> <p>See additional information in related works:</p> <ul> <li>for full data references please look up our publication</li> <li>for related code see GitHub and Zenodo</li> <li>to view and explore the generated regeneration maps online please see Google Earth Engine </li> </ul> |
| title | Data for German Regeneration Maps 2012 |
| topic | forest regeneration map species distribution regeneration indicators tree species national forest inventory |
| url | https://doi.org/10.5281/zenodo.18455038 |