No abstract

Forest change in the Korean Peninsula related to different socioeconomic developments in North and South Korea and impacted on the regional environment. However, there was a lack of consistent information about forest changes, especially comparative knowledge of North and South Korea that support management and policymaking. We used the change object update method to generate the first object-based 30m land cover set for the peninsula and analyzed new observations of forest changes in North and South Korea from 1990Korea from -2000Korea from to 2000Korea from -2015 Results showed that, in North Korea, annual forest loss increased from 142 km 2•yr −1 to 257 km 2 •yr −1 , and the total loss increased from 1,407 km 2 to 3,769 km 2 . The elevation range where forest loss concentrated shifted from 100-300 m to 300-1,000 m. The conversion of forest to cropland increased from 1,256 km 2 to 3,910 km 2 , indicating North Korea's forest eroded by agriculture expansion to ensure food security. By contrast, in South Korea, despite forest total loss increased from 338 km 2 to 513 km 2 , annual loss remained at 34 km 2• yr −1 . The forest loss was concentrated at the elevation range of 0-300 m, which linked with built-up land expansion. Different public income and social developments drove distinct magnitude of forest loss in the two countries. Follow the Global Forest Observations Initiative, although forest loss might be underestimated for North Korea and overestimated for South Korea, our land change information equipped good overall accuracy ( 0.94 ± 0.031). This study could provide useful implications for forest management and regional sustainable development.

Hunchun, a typical area suffering wild boar (Sus scrofa) damage, is an important region for the Siberian Tiger (Panthera tigris) in China. By incorporating the maximum entropy model with 22 variables in the home range scale (12 variables) and in the feeding site scale (10 variables), we predicted wild boar damage risks in this area of China and analyzed how spatial factors influence damage risk. Damage risk was found to be high in areas close to the forest edge, areas with a higher forest cover and lower to medium deciduous forest proportion, low road density, and a medium river density and farmland proportion. The proportion of farmland which was identified as being in the high damage risk zone was 23.55%, of which 38.68% was within the habitat area of the Siberian Tiger. Finally, we propose wild boar damage prevention based on different management goals.

Accurate and effective mapping of forest aboveground biomass (AGB) in heterogeneous mountainous regions is a huge challenge but an urgent demand for resource managements and carbon storage monitoring. Conventional studies have related the plot-measured or LiDAR-based biomass to remote sensing data using pixel-based approaches. The object-based relationship between AGB and multi-source data from LiDAR, multi-frequency radar, and optical sensors were insufficiently studied. It deserves the further exploration that maps forest AGB using the object-based approach and combines LiDAR data with multi-sensor images, which has the smaller uncertainty of positional discrepancy and local heterogeneity, in heterogeneous mountainous regions. To address the improvement of mapping accuracy, satellite LiDAR data from GEDI and ICEsat-2, and images of ALOS-2 yearly mosaic L band SAR (Synthetic Aperture Radar), Sentinel-1 C band SAR, Sentinel-2 MSI, and ALOS-1 DSM were combined for pixel- and object-based forest AGB mapping in a vital heterogeneous mountainous forest. For the object-based approach, optimized objects during a multiresolution segmentation were acquired by the ESP (Estimation of the Scale Parameter) tool, and suitable predictors were selected using an algorithm named VSURF (Variable Selection Using Random Forests). The LiDAR variables at the footprint-level were extracted to connect field plots to the multi-sensor objects as a linear bridge. It was shown that forests’ AGB values varied by elevations with a mean value of 142.58 Mg/ha, ranging from 12.61 to 514.28 Mg/ha. The north slope with the lowest elevation (<1100 m) had the largest mean AGB, while the smallest mean AGB was located in the south slope with the altitude above 2000 m. Using independent validation samples, it was indicated by the accuracy comparison that the object-based approach performed better on the precision with relative improvement based on root-mean-square errors (RIRMSE) of 4.46%. The object-based approach also selected more optimized predictors and markedly decreased the prediction time than the pixel-based analysis. Canopy cover and height explained forest AGB with their effects on biomass varying according to the elevation. The elevation from DSM and variables involved in red-edge bands from MSI were the most contributive predictors in heterogeneous temperate forests. This study is a pioneering exploration of object-based AGB mapping by combining satellite data from LiDAR, MSI, and SAR, which offers an improved methodology for regional carbon mapping in the heterogeneous mountainous forests.

As a symbol of urban civilization and history, old and notable trees (ONTs) are facing challenges brought by rapid urbanization. Changchun is the fastest growing city in Northeast China, and throughout its development process of over 100 years it has preserved many ONTs. This study investigated all the ONTs in Changchun, and analyzed the species diversity, spatial distribution characteristics, dimension, age, and health status of trees by using ecological index and mathematical statistics, and trying to find out the underlying factors regulating their distribution. The results showed that there were 773 old trees belonging to 25 species and 2 notable trees from 1 species in Changchun. Pyrus ussuriensis was the dominant species, followed by Salix matsudana and Ulmus pumila. The urban area, population density, greening rate, and construction history did not influence the species and quantity of ONTs, while the types of land use and tree protection planning were important factors affecting the richness, diversity, and growth conditions of trees. To explore the potential reasons for their existence, the ONTs’ data in Changchun was compared with two nearby cities—Harbin and Shenyang. The comparison indicated that the geographical location and climatic conditions also controlled the distribution of ONTs. The number and dimensions of trees were driven by the history and development process of the city. Our findings suggested that preserving favorable living environments and maintaining a low intensity of human disturbance are critical factors for the survival of ONTs in cities.