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.”
For each polygon, attributes include information on planted forest, dominant tree species, and geospatial entity as follow:
ID: Polygon ID
Biome: Biome classes used in the study
Country: Country
Prc_Pln: 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).
Prc_P_U: 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.
Prc_P_L: 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.
Type: “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 < 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.”
Typ_Upp: “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 < 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.”
Typ_Lwr: “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 < 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.”
Genus: For Type = “Planted”, this attribute indicates the predicted dominant genus. NA for Type = “Natural”.
Gns_Upp: For Typ_Upp = “Planted”, this attribute indicates the predicted dominant genus. NA for Typ_Upp = “Natural”.
Gns_Lwr: For Typ_Lwr = “Planted”, this attribute indicates the predicted dominant genus. NA for Typ_Lwr = “Natural”.
Besnard_Yr: Estimated planted year based on Besnard et al. (2021) by overlay.
Du_Yr: Estimated planted year based on Du et al. (2022) by overlay.
Area_m2: Polygon area in square meters.
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.
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 = Acer
3 = Alnus
4 = Betula
5 = Carpinus
6 = Castanea
7 = Castanopsis
8 = Chamaecyparis
9 = Cryptomeria
10 = Cunninghamia
11 = Eucalyptus
12 = Fagus
13 = Ilex
14 = Larix
15 = Picea
16 = Pinus
17 = Quercus
18 = Robinia
19 = Tilia
References
-Biodiversity Center of Japan. Vegetation Survey (7) https://www.biodic.go.jp/moni1000/findings/data/index_file.html (2021).
-Kim, K.-M., Kim, C.-M. & Jun, E. J. Study on the standard for 1:25,000 scale digital forest type map production in Korea. J. Korean Assoc. Geograp. Infor. Stud 12, 143-151 (2009).
-Besnard, S. et al. Mapping global forest age from forest inventories, biomass and climate data. Earth Syst. Sci. Data, 13, 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).
