## 4 Discussion  
### Forest Classification in Northeast China  
The three forest maps demonstrate some degree of spatial consistency for most of Northeast China. However, obvious differences exist among these maps. For example, the HJ-1 2010 and MCD12Q1 maps depict a small forest area for the Sanjiang Plain (the circle in Figure 5), but the GlobCover map shows a larger forest area. The Sanjiang Plain was famous for its large natural wetlands area before the middle of the 20 th century, but it is now dominated by cropland [63]. The training samples and validation samples collected from the Sanjiang Plain were used to verify the forest classification, and the results proved that a large area of cropland was present (Figure 12), supporting the results in the HJ-1 2010 and MCD12Q1 maps. In the south of the Inner Mongolia Autonomous Region (the square in Figure 5), the HJ-1-based map contains a larger forest area, but both the GlobCover 2009 and MCD12Q1 2009 maps illustrate a small area of forest. By comparing the results with Google Earth images and the field samples in multiple locations, it is suggested that forest was indeed distributed in the low hilly terrain within the square region. This indicates that HJ-1 imagery has an improved capacity to map forest areas, which can be attributed to its higher spatial resolution than moderate resolution imagery (MERIS and MODIS). The spatial disagreement of forest from the HJ-1, MCD12Q1, and GlobCover datasets inevitably led to the differences in forest area estimates. The total area of forest from HJ-1 is 18.3% and 11.8% higher than that from MCD12Q1 and GlobCover datasets, respectively. Furthermore, there is large variability in the estimated area across different forest types using HJ-1 imagery (30-m) and MODIS (500-m). MCD12Q1 land cover map indicates that approximately 65% of the forest in the study area is mixed forest (275,720 km\({}^{2}\)), while deciduous broadleaf forest (55,381 km\({}^{2}\)) is only approximately 13% of  
Figure 12: False color image of HJ-1 and a field photo collected from the Sanjiang Plain. (**a**) Sanjiang Plain; (**b**) Cropland. the total forest area. The HJ-1 results demonstrate that the dominant forest type is deciduous broadleaf forest (344,913 km\({}^{2}\)), comprising approximately 69% of the total forest area. It is worth comparing the results with those by other researchers who have classified the forest types in Northeast China using remote sensing data. [PERSON] et al. (2018) mapped the forest of Northeast China using multi-temporal SPOT-4 VEGETATION sensor data (1-km resolution), determining that the total forest area was 478,287 km\({}^{2}\), with deciduous broadleaf forest (321,734 km\({}^{2}\)) being the dominant forest type, covering approximately 67% of the total forest area. Whereas this is consistent with the HJ-1 2010 dataset, the mixed forest area (97,071 km\({}^{2}\)) estimated by [PERSON] et al. (2018) is notably larger. [PERSON] (2018) used MODIS/NDVI time-series datasets and DEM to classify different forest types and determined that the total forest area of Northeast China was 546,374.53 km\({}^{2}\), of which approximately 55% is comprised of deciduous broadleaf forest, but mixed forest was not a dominant forest type in this region. However, [PERSON] et al. (2019) classified forest subcategories in Northeast China (not including the part of Inner Mongolia) using MODIS-derived NDVI and EVI time series, and the forested regions were dominated by temperate coniferous forest and mixed forest. Furthermore, the land cover data of Northeast China issued from the Data Sharing Infrastructure of Earth System Science ([[http://www.geodata.cn](http://www.geodata.cn)]([http://www.geodata.cn](http://www.geodata.cn))) were collected, which were derived from Landsat TM/ETM+ and MODIS (250-m) in 2005. The total forest area presented by this dataset is 507,362 km\({}^{2}\), the dominant forest type is deciduous broadleaf forest, which accounts for 48% of the total forest area, and mixed forest is approximately 18% of the total forest area.