With the enhancement of the spatial resolution of satellite imagery (1 m or less), the satellite image analysis has been considered as the indispensable means for remote sensing of nuclear proliferation activities in the restricted access areas such as North Korea. Notably, in the case of an open-pit uranium mine, e.g. the Pyongsan uranium mine, the mining activity can be presumed if detecting the location and extent uranium tailing piles near shafts within temporal images. Several studies have researched on the target detection for minerals of interest such as limestone and coal to evaluate the economic activities by utilizing similarity measures, e.g., a spectral angle mapper and a spectral information divergence (SID). Thus, this paper presented a systematic change detection methodology for monitoring the uranium mining activity in the Pyongsan uranium mine with a similarity measure of SID. The proposed methodology using the target detection results consists of the following five steps. The first step is to acquire stereo images of areas of interest for change detection. The second step is to preprocess the stereo images as following measures: (i) the QUick Atmospheric Correction and the image-to-image registration with ENVI and (ii) the Gram-Schmidt pansharpening. The third step is to extract spectral information for minerals of interest, i.e., uranium tailing piles, by sampling pixels within the reference image. It is based on the satellite analysis report for the Pyongsan uranium mine by CSIS, which specified the location of the uranium tailing piles. As the fourth step, the target detection for uranium tailing piles was performed through the similarity measure of SID between the extracted spectral information and the spectral reflectance of the image. In the fifth step, the change detection was processed using the multivariate alteration detection algorithm, which compares the target detection results by canonical correlation analysis. Furthermore, this paper evaluated the performance of the proposed methodology with the change detection accuracy assessment index, i.e., the area under a receiver operating characteristic curve. In conclusion, this paper suggests the systematic change detection methodology utilizing time series analysis of target detection for uranium tailing piles, which can save time and cost for humans to interpret large amounts of satellite information at the restricted access areas. As future works, the feasibility of the proposed methodology would be investigated by analyzing distribution of minerals of interest regarding nuclear proliferation at Yongbyon, which has the historical events of suspicious nuclear activities.

풍력자원평가를 수행할 때 풍력자원의 특성이 동질한 바람권역을 파악하여 측정지점을 선택하여야 한다. 본 연구에서는 풍력자원의 공간적인 동질성을 파악하기 위하여 시계열 바람벡터의 유사성, 시계열 풍속의 피어슨 상관계수, 시계열 풍향의 코사인, 시 계열 풍속의 일치도 지수, 24시간 자기상관함수, 풍력자원 요인의 주성분을 유사도 척도로 이용하여 바람권역을 군집분석하였다. 주성 분분석을 수행하여 와이블 풍속분포의 척도계수 및 형상계수가 제 1 주성분으로, 지형고도와 24시간 자기상관함수가 제 2 주성분인 것으로 파악되었다. 단순지형인 제주도와 복잡한 산지지형인 포항지역에 여러 가지 유사도 척도를 적용하여 바람권역을 분류하였으며, 다연상관계수와 상자그림으로 군집내 풍력자원 요인이 유의미한 통계적 차이가 존재하는가를 평가하였다. 결론적으로 시계열 바람벡 터의 유사도와 풍력자원 요인의 주성분 거리가 가장 효과적인 군집분석의 척도임을 확인하였다.

With the rapid development of the global economy, transport safety and security have become the key issues in maritime transportation all over the world. In practical applications, the Automatic Identification System (AIS)-based measurement of similarities between different vessel trajectories plays an important role in improving maritime transportation, e.g., maritime navigation, maritime supervision and management. However, the received AIS datasets are usually composed of a large amount of redundant information which could significantly increase the computational complexity. To deal with this problem, a Douglas-Peucker (DP)-based calculation method is introduced in this paper to accurately compress the spatio-temporal AIS trajectories while preserving the main geometrical structures. Based on the compressed trajectories, it is able to accelerate the Dynamic Time Warping (DTW) algorithm for the measurement of similarities between different vessel trajectories. In particular, the combination of DP and DTW has the capacity of significantly reducing the computational cost and guaranteeing the accuracy of similarity measures. The experimental results have demonstrated the superior performance of the proposed method in terms of computational cost and accuracy of similarity measures.