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Forests provide many goods, Ecosystem services, and resources to humans such as recreation air purification and water protection functions. In rececnt years, there has been an increase in the factors that threaten the health of forests such as global warming due to climate change, environmental pollution, and the increase in interest in forests, and efforts are being made in various countries for forest management. Thus, existing forest ecosystem survey method is a monitoring method of sampling points, and it is difficult to utilize forests for forest management because Korea is surveying only a small part of the forest area occupying 63.7% of the country (Ministry of Land Infrastructure and Transport Korea, 2016). Therefore, in order to manage large forests, a method of interpolating and spatializing data is needed. In this study, The 1st Korea Forest Health Management biodiversity Shannon;s index data (National Institute of Forests Science, 2015) were used for spatial interpolation. Two widely used methods of interpolation, Kriging method and IDW(Inverse Distance Weighted) method were used to interpolate the biodiversity index. Vegetation indices SAVI, NDVI, LAI and SR were used. As a result, Kriging method was the most accurate method. [ABSTRACT FROM AUTHOR]

Deforestation in North Korea is becoming the epitome of the environmental change occurring in the Korean Peninsula. This study estimates the agro-environmental variables of North Korea's croplands and analyzes the impact of deforestation using the GEPIC (GIS-based EPIC (Environmental Policy Integrated Climate)) model and time-series land cover maps. To identify the changes in agricultural quality under deforestation, wind erosion, water erosion, organic carbon loss, and runoff were selected as the agro-environmental variables having an impact on cropland stability and productivity. Land cover maps spanning the past three decades showed that 75% of the forests were converted to croplands and that 69% of all converted croplands were originally forests, confirming the significant correlation between deforestation and cropland expansion in North Korea. Despite limitations in the verification data, we conducted qualitative and quantitative validation of the estimated variables and confirmed that our results were reasonable. Over the past 30 years, agro-environmental variables showed no clear time-series changes resulting from climate change, but changes due to spatial differences were seen. Negative changes in organic carbon loss, water erosion, and runoff were observed, regardless of the crop type. On newly-converted agricultural lands, runoff is 1.5 times higher and water-driven erosion and soil organic loss are more than twice as high compared to older croplands. The results showed that the agro-environment affected by deforestation had an impact on cropland stability and productivity. [ABSTRACT FROM AUTHOR]

Sustainable agriculture in the era of climate change needs to find solutions for the retention and proper utilization of water. This study proposes an ensemble approach for identifying the virtual water content (VWC) of main crops on the Korean Peninsula in past and future climates. Ensemble results with low uncertainty were obtained using three regional climate models, five potential evapotranspiration methods, and the Environmental Policy Integrated Climate (EPIC) crop model. The productivity results of major crops (rice and maize) under climate change are likely to increase more than in the past based on the ensemble results. The ensemble VWC is calculated using three types of crop yields and fifteen consumptive amounts of water use in the past and the future. While the ensemble VWC of rice and maize was 1.18 m³ kg-1 and 0.58 m³ kg-1, respectively, in the past, the future amounts were estimated at 0.76 m³ kg-1 and 0.48 m³ kg-1, respectively. The yields of both crops showed a decline in future projections, indicating that this change could have a positive impact on future water demand. The positive changes in crop productivity and water consumption due to climate change suggest that adaptation to climate change can be an opportunity for enhancing sustainability as well as for minimizing agricultural damage. [ABSTRACT FROM AUTHOR]

Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 27 bioclimatic zones using statistical techniques, and it was re-clustered into 14 groups to identify the environmental characteristics of these zones. In particular, we added land cover variables into the clustering to reflect not only simple climate but also social factors influencing biological habitats. In total, 53 bioclimatic variables were constructed, and principal components were generated using correlation analysis and principal component analysis (PCA). The iterative self-organizing data analysis technique algorithm (ISODATA) was used to cluster the principal components and land cover variable. The constructed bioclimatic zones were assigned codes and descriptive names based on aridity, seasonality, and naturality, and their environmental characteristics were identified. This study is significant in that it improved the understanding of biological habitats of NEA and established a basis for monitoring the distribution of species and for efficient and systematic management of biodiversity. [ABSTRACT FROM AUTHOR]