The mean wind speed and turbulence intensity profiles in the atmospheric boundary layer were extracted from a LIDAR remote sensing campaign in order to apply for CFD validation. After considering the semi-steady state field data requirements to be used for CFD validation, a neutral atmosphere campaign period, in which the main wind direction and the power-law exponent of the wind profile were constantly maintained, was chosen. The campaign site at the Pohang Accelerator Laboratory, surrounded by 40~50m high hills, with an apartment district spread beyond the hills, is to be classified as a semi-complex terrain. Nevertheless, wind speed profiles measured up to 100m above the ground fitted well into a theoretical-experimental logarithmic-law equation. The LIDAR remote-sensing data of the sub-layer of the atmospheric boundary layer has been proven to be superior to the data obtained by conventional extrapolation of the wind profile with 2 or 3 anemometer measurements.

정확하고 세밀한 적설 관측시스템은 단순히 방재 차원뿐만 아니라 수문학적 관점에 있어서 물의 순환과정을 해석하는 데에도 중요한 부분으로 인식되고 있다. 최근에는 인공위성에 탑재된 마이크로파 센서를 활용한 적설량 관측시스템이 지속적으로 발전하고 있으며, 이에 대한 검증도 활발히 진행되고 있다. 따라서 본 연구에서는 현재 한반도 적설량 관측시스템의 문제점을 파악하고, NASA의 Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E)가 제공하는 Snow Water Equivalent (SWE) Product를 활용하여 적설량 관측시스템을 제안하고자 한다. 이를 위해 적설량 관측 자료가 비교적 충분히 갖춰져 있는 관측소를 중심으로 지역적 특성을 고려하여 연구지역을 선정하고, 실 관측자료와 AMSR-E SWE 데이터에 대하여 비교 검증을 하였다. 결론적으로 오차원인 분석을 통해 앞으로의 개선점과 활용방안을 모색하였다.

High concentration of chlorophyll a occurred around the Ulleung Warm Eddy off Ulleung Island in the East Sea of Korea in spring season. The abnormal distributions of chlorophyll a were captured by satellite remote sensing and measured field data. The temporal and spatial scale of the abnormal distributions were around 20 days and 50km diameter off Ullung Island. The anomalies were quantified by estimated chlorophyll a derived from OCM and SeaWiFS ocean color data from 2000 to 2004. The origin of abnormal high concentrations was estimated by this study. It was that suspended material discharged from the Nakdong River and the coastal water located in the southeastern part of Korean Peninsula moved to northeastern coast, and then moved to off Ullung Island. The high chlorophyll a concentrations including inorganic materials were accumulated by anticyclonic eddy such as the Ullung Warm Eddy around Ullung Island in the East Sea of Korea in spring season.

A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ~lambdal~;and~;~lambda2 were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher r2 (>10~%) than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.

A virtual vessel traffic control system is introduced to contribute to prevent a marine accident such as collision and stranding from happening. Existing VTS has its limit. The virtual vessel traffic control system consists of both data acquisition by satellite remote sensing and a simulation of traffic environment stress based on the satellite data, remotely sensed data And it could be used to provide timely and detailed information about the marine safety, including the location, speed and direction of ships, and help us operate vessels safely and efficiently. If environmental stress values are simulated for the ship information derived from satellite data, proper actions can be taken to prevent accidents. Since optical sensor has a high spatial resolution, JERS satellite data are used to track ships and extract their information. We present an algorithm of automatic identification of ship size and velocity. It lastly is shown that based on ship information extracted from JERS data, a qualitative evaluation method of environmental stress is introduced.

The Yellow River delta is an important region where coastal and newly formed wetlands distribute in north China. Based on satellite remote sensing images and GIS techniques, this paper tends to delineate the dynamic changes of newly formed wetland in the Yellow River mouth from 1986.5 to 1996.10. Our results show that the newly formed wetland increased by 24.9 km2 per year. Before 1990.1 and it decreased by 2.40 km2 per year after that. The northern and southwestern parts of the Yellow River mouth are main positions of decrease and the southern and the estuary parts are main positions of increase. The advancing rate of river mouth extending into the Bo Sea is decreasing obviously. The reason for that is the decreasing of water and sediments in the Yellow River, which caused by the increasing use of water and soil conservation on upper reach.

In general, neural networks are widely used for the category classification of multispectral images. Since the input multispectral images into neural networks we, however, low contrast images, neural networks converge very slowly and are of bad performance. To overcome this problem, we propose a new image enhancement method which consists of smoothing process, finding the main valley and enhancement process. In addition the enhanced images by the proposed method are used as the input of neural networks for the category classification. When the new category classification method is applied to multispectral LANDSAT TM images, we verified that the neural networks converge very lastly and that the overall category classification performance is improved.

Nowadays, many satellites regularly produce digital multispectral images of the earth's surface. Multispectral images may be displayed as color pictures by selecting three components for assignment to the primary colors. It is desired to enhance these images to generate a display picture that are representativde of their features. in this paper, a false color image processing algorithm is proposed for the purpose of enchancement of the multispectral images based on the human perception. The mean of each primary component is transformed to equalo. Intensity and saturation are enhanced by modified piecewise linear contrast strectching and saturation enhancement method. The proposed method has been successfully applied the LANDSAT TM image and shows good enhancement.