SWECO25: Vegetation (vege)

The vegetation category contains the "copernicus" and "nfi" datasets. The copernicus dataset describes the dominant leaf type. After reprojecting and resampling the “High Resolution Layer: Dominant Leaf Type” (DLT) source data (EEA, 2018) to the SWECO25 grid, we generated individual layers for the two available categories (coniferous and deciduous). We provided the binary maps for (0 or 1) for each of them and computed 13 focal statistics layers by applying a cell-level function calculating the average percentage cover value for a given category in a circular moving window of 13 radii ranging from 25m to 5km. Final values were rounded and multiplied by 100. The nfi dataset describes the height of the vegetation canopy. After reprojecting and resampling the source data (Ginzler, 2021) to the SWECO25 grid with three resampling schemes (maximum, minimum, and median values), we generated and provided the three individual layers. In addition, for each of them, we provided 13 focal statistics layers obtained by applying a cell-level function calculating the average canopy height value in a circular moving window of 13 radii ranging from 25m to 5km. This dataset includes a total of 42 layers. Final values were rounded and multiplied by 100. The detailed list of layers available is provided in SWECO25_datalayers_details_vege.csv and includes information on the category, dataset, variable name (long), variable name (short), period, sub-period, start year, end year, attribute, radii, unit, and path. References: European Environment Agency [EEA]. Copernicus Land Monitoring Service - High Resolution Layer Forest. (Copenhagen, Denmark, 2018). Ginzler, C. Vegetation Height Model (National Forest Inventory). (Birmensdorf, Switzerland, 2021) Külling, N., Adde, A., Fopp, F., Schweiger, A. K., Broennimann, O., Rey, P.-L., Giuliani, G., Goicolea, T., Petitpierre, B., Zimmermann, N. E., Pellissier, L., Altermatt, F., Lehmann, A., & Guisan, A. (2024). SWECO25: A cross-thematic raster database for ecological research in Switzerland. Scientific Data, 11(1), Article 1. https://doi.org/10.1038/s41597-023-02899-1 V2: metadata update本植被类数据集包含**Copernicus**与**NFI（国家森林清查，National Forest Inventory）**两类子数据集。 Copernicus数据集用于描述优势叶型。我们将“高分辨率图层：优势叶型（Dominant Leaf Type, DLT）”源数据（欧洲环境署，2018年）重投影并重采样至SWECO25网格后，针对针叶林与落叶林两类现有类别分别生成了专属图层。我们为每一类提供了取值为0或1的二值地图，并通过像元级函数，以25米至5千米共13种半径的圆形移动窗口计算给定类别的平均覆盖百分比，进而生成了13个邻域统计图层。最终结果经取整后乘以100。 NFI数据集用于描述植被冠层高度。我们将源数据（Ginzler, 2021）重投影并以三种重采样方案（最大值、最小值与中值）重采样至SWECO25网格后，生成并提供了三类专属图层。此外，针对每一类图层，我们通过像元级函数，以25米至5千米共13种半径的圆形移动窗口计算冠层平均高度，进而生成了13个邻域统计图层。本数据集总计包含42个图层。最终结果经取整后乘以100。 可用图层的详细清单见SWECO25_datalayers_details_vege.csv，其中涵盖类别、数据集、长变量名、短变量名、时段、子时段、起始年份、结束年份、属性、半径、单位与文件路径等信息。 参考文献： 欧洲环境署（European Environment Agency, EEA）. 哥白尼陆地监测服务——高分辨率森林图层. 丹麦哥本哈根, 2018. Ginzler, C. 植被高度模型（国家森林清查，National Forest Inventory）. 瑞士比尔门斯多夫, 2021. Külling, N., Adde, A., Fopp, F., Schweiger, A. K., Broennimann, O., Rey, P.-L., Giuliani, G., Goicolea, T., Petitpierre, B., Zimmermann, N. E., Pellissier, L., Altermatt, F., Lehmann, A., & Guisan, A. (2024). SWECO25：瑞士生态研究跨主题栅格数据库. 科学数据(Scientific Data), 11(1), 第1篇文章. https://doi.org/10.1038/s41597-023-02899-1 版本2：元数据更新