The purpose of this study is to elucidate the spatio-temporal characteristics of ultrafine dust generation in East Asia and the synoptic climate patterns related to its dispersal which has its adverse effects on public health across East Asia. To achieve this purpose, Level 3 monthly Aerosol Optical Depth (AOD) data extracted from MODIS satellite imagery (MOD08_M3) representing particle matters less than 2.5 micrometer (PM2.5) and the NCEP-NCAR reanalysis I upper-level climatic data associated with the exacerbation of ultrafine dust problem are analyzed for the recent 20-year (2001-2020) period. Analyses of long-term average MOD08 data show that high AOD value exceeding 0.5 or more frequently occurred in populous cities in East Asia but mainly in the vicinity of densely populated large rivers and the eastern lowlands in China between mid-winter and mid-spring, which is attributable to the accumulation effects of continuous fossil fuel consumption for heating and manufacturing. Despite the overall decreasing trend of ultrafine dust across China in the 2010s, the weakened westerlies in the warmer climate as well as its continuous generation from the densely populated industrial regions of China provide a favorable synoptic climate condition for frequent severe ultrafine dust problems across East Asia including South Korea. These results indicate that ultrafine dust from China is a long-lasting transboundary environmental problem across East Asia, which needs long-term international cooperation in developing the sustainable policies.

아시아 지역의 인구증가와 하천주변 및 삼각주 평야 저지대의 인구밀도 집중으로 인해 우기 시 아시아의 많은 지역에서 홍수로 인한 대규모 인명 및 재산 피해가 발생하고 있다. 본 연구에서는 NOAA에서 제공하는 1992년부터 2003년까지의 나이트라이트 위성영상자료를 수집하여 인명 및 재산피해 정보와의 상호 공간분석을 통해 메콩강 유역의 홍수피해에 대한 분석을 실시하였다. 인명 및 재산피해 자료는 EM-DAT에서 제공하는 지 역 공간분포자료를 활용하였으며, 메콩강 주하천 격자로 부터 모든 임의 격자의 떨어진 거리를 계산하여 해당 격자에서의 나이트라이트 강도와 인명 및 재산피해와의 상관분석을 수행하였다. 그 결과, 나이트라이트 강도가 클수록 홍수피해가 큰 것으로 분석되었으며, 특히, 하천으로부터 가까 운 거리에서 나이트라이트 강도가 높게 나타났다. 이는 높은 나이트라이트 강도를 갖는 격자, 즉 인구밀집도가 상대적으로 높은 격자가 메콩강 하 천주변으로 분포되어 있으며, 홍수피해와 양의 상관관계를 갖고 있음을 의미한다. 이와 같이 나이트라이트 위성영상정보는 에너지소비, 재해 등 다양한 공간분석을 통해 사회경제적 영향성 평가를 위한 대리변수로 사용이 가능할 것으로 판단된다.

This paper described the estimation of corn and soybeans yields of four states in the US Midwest using time-series satellite imagery and climate dataset between 2001 and 2012. We first constructed a database for (1) satellite imagery acquired from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) including NDVI (Normalized Di°erence Vegetation Index), EVI (Enhanced Vegetation Index), LAI (Leaf Area Index), FPAR (Fraction of Photosynthetically Active Radiation), and GPP (Gross Primary Productivity), (2) climate dataset created by PRISM (Parameter-Elevation Regressions on Independent Slopes Model) such as precipitation and mean temperature, and (3) US yield statistics of corn and soybeans. ˜en we built OLS (Ordinary Least Squares) regression models for corn and soybeans yields between 2001 and 2010 after correlation analyses and multicollinearity tests. These regression models were used in estimating the yields of 2011 and 2012. Comparisons with the US yield statistics showed the RMSEs (Root Mean Squared Errors) of 0.892 ton/ha and 1.095 ton/ha for corn yields in 2011 and 2012 respectively, and those of 0.320 ton/ha and 0.391 ton/ha for soybeans yields. ˜is result can be thought of as a good agreement with the in-situ statistics because the RMSEs were approximately 10% of the usual yields: 9 ton/ha for corn and 3 ton/ha for soybeans. Our approach presented a possibility for extending to more advanced statistical modeling of crop yields using satellite imagery and climate dataset.

Space-borne remote sensing is an effective and inexpensive way to identify crop fields and detect the crop condition. We examined the multi-temporal spectral characteristics of rice fields in South Korea to detect their phenological development and condition. These rice fields are compact, small-scale parcels of land. For the analysis, moderate resolution imaging spectroradiometer (MODIS) and RapidEye images acquired in 2011 were used. The annual spectral tendencies of different crop types could be detected using MODIS data because of its high temporal resolution, despite its relatively low spatial resolution. A comparison between MODIS and RapidEye showed that the spectral characteristics changed with the spatial resolution. The vegetation index (VI) derived from MODIS revealed more moderate values among different land-cover types than the index derived from RapidEye. Additionally, an analysis of various VIs using RapidEye satellite data showed that the VI adopting the red edge band reflected crop conditions better than the traditionally used normalized difference VI.

Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer to the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentrations of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDI. We studied to find out the relationship between the measured chlorophyll a from the ship and the estimated chlorophyll a from the SeaWiFS satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) in the northern part of the East China Sea. Chlorophyll_a=0.121Ln(X) + 0.504, R2 = 0.73 (1) We also determined total suspended sediment mass (SS) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-situ data and the ratio (LWN(490 nm)/LWN(555 nm)) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS=-0.703 Ln(X) + 2.237, R2 = 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMI, Terra/MODIS and Orbview/SeaWiFS.

침수지에 대한 신속하고 정확한 지도의 제작은 홍수재해 복구와 관리 및 예방을 위한 중요한 자료로 사용된다. 타 위성영상에 비하여 기상조건에 관계없이 영상자료의 획득이 용이한 레이더 영상을 이용하여 침수지 조사와 홍수후의 농경지 복구 상태를 파악하고자 하였다. 1999년 여름 경기도 북부 지역에 발생한 홍수 사상을 사례지로 하여 C-band RADARSAT 위성영상을 이용하였고, 침수 시점인 8월 4일 영상과 그 전후 영상을 포함하여 세 시기의 영상을 이