Spatial database of planted forests in East Asia using machine learning (final products)

The shapefile depicts the distribution of planted forests in East Asia (China, Japan, ROK, and DPRK) and associated dominant tree species to the genus level. The dataset is in a shapefile where each polygon is 0.009° by 0.009° (approximately 1km²) in size within the forested area of 2020 (5m or greater in tree height) based on the FAO’s definition of “forest.” <br> For each polygon, attributes include information on planted forest, dominant tree species, and geospatial entity as follow: <strong>ID:</strong> Polygon ID <strong>Biome:</strong> Biome classes used in the study <strong>Country:</strong> Country <strong>Prc_Pln:</strong> Percent planted forest predicted by the three models (upper bound, midpoint, and lower bound). The values are means of the three models, which is the main result of our study. NA for ROK and majority of areas in Japan, where national planted forest maps were used as a final planted/natural label (see References). <strong>Prc_P_U:</strong> Percent planted forest predicted by the upper bound model. NA for ROK and majority of areas in Japan, where national planted forest maps were used as a final planted/natural label. Note that values are not always higher than Prc_Pln. <strong>Prc_P_L:</strong> Percent planted forest predicted by the lower bound model. NA for ROK and majority of areas in Japan, where national planted forest maps were used as a final planted/natural label. Note that values are not always lower than Prc_Pln. <strong>Type:</strong> “Planted” or “Natural” forests based on the main result. For our predicted percent planted forest, “Planted” if Prc_Pln is 0.5 or greater and “Natural” if Prc_Pln &lt; 0.5. For Prc_Pln = NA, national planted forest maps were used to determine if the given polygon is a planted forest, and if not, “Natural.” <strong>Typ_Upp:</strong> “Planted” or “Natural” forests based on the upper bound model. For our predicted percent planted forest, “Planted” if Prc_P_U is 0.5 or greater and “Natural” if Prc_P_Upp &lt; 0.5. For Prc_P_Upp = NA, national planted forest maps were used to determine if the given polygon is a planted forest, and if not, “Natural.” <strong>Typ_Lwr:</strong> “Planted” or “Natural” forests based on the lower bound model. For our predicted percent planted forest, “Planted” if Prc_P_L is 0.5 or greater and “Natural” if Prc_P_L &lt; 0.5. For Prc_P_L = NA, national planted forest maps were used to determine if the given polygon is a planted forest, and if not, “Natural.” <strong>Genus:</strong> For Type = “Planted”, this attribute indicates the predicted dominant genus. NA for Type = “Natural”. <strong>Gns_Upp:</strong> For Typ_Upp = “Planted”, this attribute indicates the predicted dominant genus. NA for Typ_Upp = “Natural”. <strong>Gns_Lwr:</strong> For Typ_Lwr = “Planted”, this attribute indicates the predicted dominant genus. NA for Typ_Lwr = “Natural”. <strong>Besnard_Yr:</strong> Estimated planted year based on Besnard et al. (2021) by overlay. <strong>Du_Yr:</strong> Estimated planted year based on Du et al. (2022) by overlay. <strong>Area_m2:</strong> Polygon area in square meters. <br> Planted forest in this map includes forests planted for restoration purposes, commercial plantation, and other artificial planting for other purposes, such as for landscape and disaster prevention, of all ages. <br> Raster files are available for percent planted forest, type, and dominant genus, where 1 = "Planted" and 0 = "Natural" for the type. Values are 99 for natural forests for percent planted forest and dominant genus. Numbers for dominant genera are as follows: 1 = Abies 2 = Acacia 3 = Betula 4 = Camellia 5 = Castanea 6 = Cedrus 7 = Cryptomeria 8 = Cunninghamia 9 = Eucalyptus 10 = Larix 11 = Liriodendron 12 = Morus 13 = Picea 14 = Pinus 15 = Populus 16 = Quercus 17 = Robinia <br> References -Biodiversity Center of Japan. <em>Vegetation Survey (7)</em> https://www.biodic.go.jp/moni1000/findings/data/index_file.html (2021). -Kim, K.-M., Kim, C.-M. &amp; Jun, E. J. Study on the standard for 1:25,000 scale digital forest type map production in Korea. <em>J. Korean Assoc. Geograp. Infor. Stud</em> <strong>12</strong>, 143-151 (2009). -Besnard, S. <em>et al.</em> Mapping global forest age from forest inventories, biomass and climate data. <em>Earth Syst.</em> <em>Sci. Data</em>, <strong>13</strong>, 4881-4896 (2021). -Du, Z. et al. A global map of planting years of plantations v2. figshare https://doi.org/10.6084/m9.figshare.19070084.v2 (2022).本数据集为东亚（中国、日本、大韩民国、朝鲜民主主义人民共和国）人工林分布及其优势树种属级分类的矢量形状文件（Shapefile）格式数据。数据集中每个多边形对应2020年林区（依据联合国粮食及农业组织（Food and Agriculture Organization，FAO）对“森林”的定义，即树木高度≥5米）内的区域，尺寸为0.009°×0.009°（约1平方千米）。 每个多边形附带的属性信息涵盖人工林相关参数、优势树种及地理空间实体，具体字段说明如下： **ID**：多边形唯一标识符 **Biome**：本研究采用的生物群系类别 **Country**：所属国家 **Prc_Pln**：由三个模型（上界、中点、下界）预测的人工林占比，其数值为三个模型结果的均值，为本研究的核心结果。大韩民国及日本大部分区域该字段为NA，此类区域采用国家官方人工林地图作为最终人工/天然林标签（详见参考文献）。 **Prc_P_U**：由上界模型预测的人工林占比。大韩民国及日本大部分区域该字段为NA，此类区域采用国家官方人工林地图作为最终人工/天然林标签。需注意，该字段数值未必始终高于Prc_Pln。 **Prc_P_L**：由下界模型预测的人工林占比。大韩民国及日本大部分区域该字段为NA，此类区域采用国家官方人工林地图作为最终人工/天然林标签。需注意，该字段数值未必始终低于Prc_Pln。 **Type**：基于核心研究结果判定的森林类型，分为"人工林"与"天然林"。当Prc_Pln≥0.5时判定为"人工林"，Prc_Pln<0.5时判定为"天然林"；若Prc_Pln为NA，则采用国家官方人工林地图判定该多边形是否为人工林，否则归类为"天然林"。 **Typ_Upp**：基于上界模型预测结果判定的森林类型。当Prc_P_U≥0.5时判定为"人工林"，Prc_P_U<0.5时判定为"天然林"；若Prc_P_U为NA，则采用国家官方人工林地图判定该多边形是否为人工林，否则归类为"天然林"。 **Typ_Lwr**：基于下界模型预测结果判定的森林类型。当Prc_P_L≥0.5时判定为"人工林"，Prc_P_L<0.5时判定为"天然林"；若Prc_P_L为NA，则采用国家官方人工林地图判定该多边形是否为人工林，否则归类为"天然林"。 **Genus**：当Type为"人工林"时，该字段为预测得到的优势树种属；当Type为"天然林"时，该字段为NA。 **Gns_Upp**：当Typ_Upp为"人工林"时，该字段为基于上界模型预测得到的优势树种属；当Typ_Upp为"天然林"时，该字段为NA。 **Gns_Lwr**：当Typ_Lwr为"人工林"时，该字段为基于下界模型预测得到的优势树种属；当Typ_Lwr为"天然林"时，该字段为NA。 **Besnard_Yr**：通过叠加分析基于Besnard等人2021年的研究得到的人工林种植年份估算值。 **Du_Yr**：通过叠加分析基于Du等人2022年的研究得到的人工林种植年份估算值。 **Area_m2**：多边形面积，单位为平方米。 本数据集所涵盖的人工林包括所有林龄的、用于生态修复、商业造林及其他人工种植用途（如景观营造、防灾减灾）的森林。 本数据集同时提供人工林占比、森林类型及优势树种属的栅格文件，其中森林类型栅格中1代表"人工林"，0代表"天然林"。人工林占比及优势树种属栅格中，天然林对应数值为99。优势树种属的编码对应关系如下：1=冷杉属（Abies）、2=金合欢属（Acacia）、3=桦木属（Betula）、4=山茶属（Camellia）、5=栗属（Castanea）、6=雪松属（Cedrus）、7=柳杉属（Cryptomeria）、8=杉木属（Cunninghamia）、9=桉属（Eucalyptus）、10=落叶松属（Larix）、11=鹅掌楸属（Liriodendron）、12=桑属（Morus）、13=云杉属（Picea）、14=松属（Pinus）、15=杨属（Populus）、16=栎属（Quercus）、17=刺槐属（Robinia）。 ### 参考文献 1. 日本生物多样性中心. 《植被调查（第7辑）》[EB/OL]. https://www.biodic.go.jp/moni1000/findings/data/index_file.html, 2021. 2. Kim K-M, Kim C-M, Jun E J. 韩国1:25000比例尺数字森林类型图制作标准研究[J]. 韩国地理信息学会志, 2009, 12:143-151. 3. Besnard S, et al. Mapping global forest age from forest inventories, biomass and climate data[J]. Earth System Science Data, 2021, 13:4881-4896. 4. Du Z, et al. A global map of planting years of plantations v2[DB/OL]. figshare, https://doi.org/10.6084/m9.figshare.19070084.v2, 2022.