• Korean Journal of Agricultural and Forest Meteorology
• /
• v.14 no.4
• /
• pp.254-259
• /
• 2012

Peeling damage of trees is usually caused by Cervidae such as deer, roe deer because of the lack of food in forests. However, it happens as part of the developing of antlers in Jeju Island when the roe deer try to remove the Velvet-the skin of the antlers. The research area is the Hannam experimental forest (400 m up to 500 m above sea level) of Korea Forest Research Institute in Jeju Island, and the survey was carried out along the 6 km long of forest road with 5 m width on both sides. Twenty five tree species (total 267 stands) are damaged by peeling; 18 (134 stands) deciduous broad-leaved species, 5 (71 stands) in evergreen broad-leaved species, 2 (62 stands) coniferous species. The most common damaged species are in order of Daphniphyllum macropodum, Cryptomeria japonica, Lindera erythrocarpa, Clerodendrum trichotomum, Zanthoxylum schinifolium. Mainly damaged trees are approximately 3~4 years old saplings, and they show the mean height $120.7{\pm}42.4cm$, diameter measured at 5 cm height $1.5{\pm}0.5cm$. The Lowest peeling beginning height is $22.1{\pm}10.1cm$, and the mean length of peeling is $27.5{\pm}10.6cm$. Once the peeling damage happens, the saplings are infected by fungi secondly, and are distorted or dead, therefore the future structure of warm-temperate forests could be in influenced in species. Warm-temperate forest landscape and species change related to the climate change is a rising issue in Jeju Island. However the changes caused by peeling damage also could be an important issue in the natural process of forest environment, afforestation, local nursery and sustainable forest management of Jeju Island.

• Korean Journal of Remote Sensing
• /
• v.28 no.2
• /
• pp.215-226
• /
• 2012

NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.1
• /
• pp.36-44
• /
• 2006

In this study, we constructed a forest fire danger map in the Yeongdong area of Gangwon-do and Northeastern area of Gyeongsangbuk-do using a forest fire rating model and geographical information system (GIS). We investigated the appropriate positions of the automatic weather station (AWS) and a comprehensive network solution (a system including measurement, communication and data processing) for the establishment of an optimum mountain meteorological observation network system (MMONS). Also, we suggested a possible plan for combining the MMONS with unmanned monitoring camera systems and wireless relay towers operated by local governments and the Korea Forest Service for prevention of forest fire.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.4
• /
• pp.34-47
• /
• 2009

Rapid urbanization is causing environmental and ecological damage, development thoughtless for the environment, and social and economical issues. It is important to grasp urban growth situations and characteristics, reflect them, and establish a policy for the solution of issues pursuant to urbanization and the sustainable and efficient development of national land. This research aims to be used as basic data in establishing an urban policy by analyzing the situations and characteristics of urban growth for the past 20 years in our entire country rather than an existing district. For this, some urban districts were sampled using a 1980s and 2000s version of land cover map produced by Ministry of Environment, and then pattern analysis for urban growth by administrative district ranks was conducted using GIS and a statistical technique. As a result, the development zone area after 1980s has increased by 2.5 times as compared to that before 1980s, and especially in the farm villages neighboring the national capital region, it has increased by 21.2 times. Special cities and metropolitan cities were developed at the districts being low in altitude, close to the principal road and the major downtown, high in road ratio, and restricted environmentally, ecologically and legally, and were diverted from mountains, forests and grassland to urban land. On the other hand, farm villages neighboring a large city, farm villages neighboring the national capital region, and local farm villages were developed at the districts being high in altitude, far from the principal road and the major downtown, low in road ratio, and not restricted environmentally, ecologically and legally, and were diverted from farmland to urban land. That is, it can be seen that urban development has been actively realized despite the unfavorable topographical conditions in the suburban districts due to lack of available land and various regulations and policies as urban growth around big cities expands.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.649-663
• /
• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.6
• /
• pp.1018-1023
• /
• 2010

Climatic change was observed and analyzed in view of impacts on agricultural ecosystem, inter alia on rice cropping. The changed climate gave rise to earlier transplanting of rice seedling and later harvest after 40 years. Also phenological change and prolonged growth duration was observed. The meteorological data was selected from the standardized climatological data of 30 year normals of 1960s and 2000s, which were published by Korea Meteorological Administration. Development stages and growing periods of rice crop were compared by analyzing critical and optimum temperatures of each growth stage during these two periods. The first appearance date of $15^{\circ}C$ was ranged from Apr. 29 to May 23 in the year-normals of 1960s and it varied from Apr. 24 to May 16 in the normals of 2000s. The difference of the first appearance date of $15^{\circ}C$ was 0~10 days earlier in the year-normals of 2000s than the 1960s. The last harvesting date was determined to be the last appearance date of mean air temperature $15^{\circ}C$. The difference in the last appearance date of $15^{\circ}C$ was 1 to 13 days later in the year-normals of 2000s than in 1960s. The plant height of a rice variety, Hwayoung-byeo was 101~109 cm in 4 local areas, Seoul, Kangneung, Kwangju and Daegu. The plant height became 1~4 cm taller under warm condition. Rice grain yields estimated with daily weather data for the year-normals of 1960s and 2000s were 453~580 kg $10a^{-1}$ and 409~484 kg $10a^{-1}$ respectively. Rice grain yield of the former period was 50~100 kg $10a^{-1}$ higher than that hat in the later period.

• Journal of the Korean earth science society
• /
• v.42 no.5
• /
• pp.524-535
• /
• 2021

Rapid climate change and oceanic warming have increased the variability of oceanic wave heights over the past several decades. In addition, the extreme wave heights, such as the upper 1% (or 5%) wave heights, have increased more than the heights of the normal waves. This is true for waves both in global oceans as well as in local seas. Satellite altimeters have consistently observed significant wave heights (SWHs) since 1991, and sufficient SWH data have been accumulated to investigate 100-year return period SWH values based on statistical approaches. Satellite altimeter data were used to estimate the extreme SWHs at the Ieodo Ocean Research Station (IORS) for the period from 2005 to 2016. Two representative extreme value analysis (EVA) methods, the Initial Distribution Method (IDM) and Peak over Threshold (PoT) analysis, were applied for SWH measurements from satellite altimeter data and compared with the in situ measurements observed at the IORS. The 100-year return period SWH values estimated by IDM and PoT analysis using IORS measurements were 8.17 and 14.11 m, respectively, and those using satellite altimeter data were 9.21 and 16.49 m, respectively. When compared with the maximum value, the IDM method tended to underestimate the extreme SWH. This result suggests that the extreme SWHs could be reasonably estimated by the PoT method better than by the IDM method. The superiority of the PoT method was supported by the results of the in situ measurements at the IORS, which is affected by typhoons with extreme SWH events. It was also confirmed that the stability of the extreme SWH estimated using the PoT method may decline with a decrease in the quantity of the altimeter data used. Furthermore, this study discusses potential limitations in estimating extreme SWHs using satellite altimeter data, and emphasizes the importance of SWH measurements from the IORS as reference data in the East China Sea to verify satellite altimeter data.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.5
• /
• pp.79-96
• /
• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1465-1483
• /
• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.67 no.1
• /
• pp.27-40
• /
• 2022

Building self-sustainable rural infrastructure and environment through smart digital agriculture technology innovation is one of the major goals of the Korean agricultural administration as a part of the nation's 4^th industry revolution. To identify areas for improving and effectively investing in the acceleration of rural development, 207 experts in the areas of crop science and smart digital agriculture technology were interviewed for their opinions and suggestions on 22 questions designed to recognize fundamental agricultural issues to be addressed and solutions to advance technology innovation and rural development. Majority of the participants expected smart digital agriculture technologies to resolve major agricultural issues and help build a better rural environment. To overcome technology gaps and resolve issues more effectively, further investment in training new technology experts and building stronger agricultural technology infrastructure is urgent, and persistent and systematic support from agricultural administration appears to be the key for accelerating the process. While the leading global groups of both public and private sectors have advanced their technologies beyond the field application stage, most of the Korean technologies remain at the early pilot stage. Aging population and lack of labor in rural areas, unknown future climate change, and challenges in sustainable rural development are expected to be resolved by smart digital agriculture technologies. Technological innovations by research institutes should be promptly deployed in the crop production field, and farm training systemically organized by local technology centers can accelerate farming revolution. Standardization of equipment and data systems is another key to the success of digitalization of food crop production and food supply chains nationwide.