The grapheme of the Chinese character “Xiao (owl)” has been studied by some ancient experts and contemporary scholars, and they have proposed two different viewpoints. Some hold an opinion that “Xiao” represents the head of a bird on a tree, while others propose that it expresses a bird on a tree. It is difficult to draw a final conclusion. Nevertheless, the present researches using the unearthed literature corpus and the handed down documents corpus to analyze the character form of “Xiao” show that it represents the head of a bird on a tree. In addition, worshipping “Xiao” and offering sacrifices of “Xiao” to Gods or ancestors in Shang Dynasty provide another evidence that “Xiao” represents the head of a bird on a tree. These materials also show that the motivation of word-making of “Xiao” was derived from the ancient event of offering sacrifices, in which the bird was dismembered and suspended on a tree on Summer Solstice Day.

2011년 3월부터 2016년 10월까지 총 6회의 번식기간 동 안 천연기념물 소쩍새(Otus sunia)를 대상으로 서식지 특 성, 둥지 특성, 번식생태 특성을 연구하였다. 그리고 최종적 으로 소쩍새의 종 및 개체군 보전을 위한 합리적이고 현실 적인 보전방안을 제시하였다. 소쩍새의 행동권은 195,361 ± 29,750m2(최소 169,198m2 - 최대 227,722m2), 핵심지역의 크기는 68,376 ± 10,413m2 (최소 59,219m2 - 최대 79,703m2)로 분석되었다. 소쩍새의 번식둥지는 자연수동(natural cavity), 딱다구리 류의 둥지(woodpeckers' nest), 까치의 둥지(magpies' nest), 인공둥지(artificial nest) 총 4가지 유형으로 분류되었다. 소쩍 새의 영소목은 느티나무(Zelkova serrata) 9그루, 소나무 (Pinus densiflora) 4그루, 오동나무(Paulownia coreana) 3그 루, 아까시나무(Robinia pseudoacacia), 호두나무(Juglans sinensis) 각각 2그루, 팽나무(Celtis sinensis), 왕버들(Salix chaenomeloides), 수양버들(Salix babylonica), 물푸레나무 (Fraxinus rhynchophylla), 양버즘나무(Platanus occidentalis), 벚나무(Prunus serrulata var. spontanea), 밤나무(Castanea crenata var. dulcis)가 각각 1그루 순으로 나타났으며, 그 중 느티나무를 가장 선호하였다. 영소목의 수고는 12.2 ± 3.0m, 둥지높이는 3.0 ± 1.6m, 흉고직경은 0.6 ± 0.3m, 둥지높 이의 직경은 0.3 ± 0.1m로 조사되었다. 한편, 인공둥지에서 번식하는 경우 수고, 둥지높이, 흉고직경이 상대적으로 낮은 나무에서도 번식이 가능했다. 소쩍새의 한배산란수는 4.3 ± 0.8개이며, 최소 3개에서 최대 6개까지 확인되었는데, 그 중 4-5개의 빈도가 가장 높 았다. 알의 특성을 분석한 결과, 장경(length) 31.4 ± 0.6mm, 단경(breadth) 26.7 ± 0.5mm, 무게(weight) 12.0 ± 0.5g, 형태지수(shape index) 85.0 ± 0.9%, 부피(volume) 11.4 ± 0.6㎤로 각각 나타났다. 소쩍새의 포란기간은 25.4 ± 0.9일, 육추기간은 23.1 ± 2.1일로 나타났다. 소쩍새는 비동시성 부화 조류로 첫 번째 알이 부화한 후 마지막 알이 부화할 때 까지는 4.0 ± 0.9일이 걸렸으며, 알의 평균 부화일수는 21.4 ± 0.6일이었다. 소쩍새의 먹이공급 횟수를 분석한 결 과, 하루 평균 53.3 ± 33.5회, 시간 평균 4.8 ± 5.2회 새끼에 게 먹이를 공급하였다. 그리고 암, 수의 먹이공급 비율을 분석한 결과, 하루 평균 53.3 ± 33.5회 중 수컷이 43.5 ± 26.8회(81.8%), 암컷이 9.7 ± 11.1회(18.2%)로 나타났다. 소쩍새의 먹이원을 확인하기 위해 배설물 18개에서 동물성 DNA를 검출한 결과, 총 9목 23과 33속이 확인되었다. 소쩍새의 서식 및 번식에 대한 위협요인은 첫째, 산림 및 자연초지 등 서식지 축소, 둘째, 노거수의 훼손 및 고사에 따른 수동(cavity)의 감소, 셋째, 경쟁종에 대한 위협, 넷째, 서식지 단절 및 로드킬(road-kill)로 도출되었다. 그러나 인 공둥지는 이러한 위협요인에 대응한 가장 합리적이고 현실 적인 대안이 될 수 있다.

본 연구는 2011년 3월부터 2012년 10월까지 한국에서 서식하는 소쩍새(Otus sunia stictonotus)를 대상으로 둥지 특성에 따른 번식생태학적 특징을 밝히기 위하여 수행되었 다. 소쩍새는 느티나무(Zelkova serrata, 4그루), 오동나무 (Paulownia coreana, 3그루), 팽나무(Celtis sinensis, 1그 루), 왕버들(Salix chaenomeloides, 1그루), 수양버들(Salix babylonica, 1그루), 물푸레나무(Fraxinus rhynchophylla, 1 그루), 아까시나무(Robinia pseudoacacia, 1그루), 양버즘 나무(Platanus occidentalis, 1그루)의 딱다구리류 둥지 (woodpecker's nest hole, 46.1%), 자연적으로 형성된 나무 구멍(natural tree hole, 38.5%), 인공둥지(artificial wood box, 15.4%)에 둥지를 틀었다. 수고(H)는 10~16.3m, 흉고 직경(DBH)은 0.2~1.2m였다. 특히, 인공둥지를 달아놓은 경우에는 수고와 흉고직경이 상대적으로 낮은 나무 (10.0m<H<10.7m, 0.2m<DBH<0.4m)에서도 번식하였다. 나무의 상태는 죽은 가지가 달린 살아있는 나무(69.2%)가 가장 많았으며, 다음으로 줄기와 가지가 모두 살아있는 나 무(23.1%), 고사목(7.7%) 순 이였다. 그리고 둥지구멍은 죽 은 가지가 달린 살아있는 나무의 줄기(54.5%)와 가지 (45.5%) 부위에 주로 위치하였다. 소쩍새의 부화율은 91.4%, 이소율은 83.0%, 번식성공률은 75.9%였다. 번식실 패요인은 미부화(unhatched, 7.1%), 둥지포기(abandon, 28.6%), 추락사(falling, 57.1%) 그리고 사망의 원인을 특정 지을 수 없는 경우(etc., 7.1%)가 있었다. 둥지유형별로는 딱다구리류 둥지는 새끼의 추락사로 인하여 이소율(69.2%) 이 낮았으며, 자연적으로 형성된 나무구멍은 둥지포기와 미 부화로 인하여 부화율(79.2%)이 낮았다. 한편, 인공둥지에 서는 모든 개체가 부화와 이소에 성공하여 부화율, 이소율, 번식성공률이 모두 높게 나타났다. 결과적으로 인공둥지는 2개를 대상으로 연구되어 통계적 유의성을 검증할 수는 없 지만, 자연둥지의 단점을 보완하고 번식성공률을 높일 수 있는 장점 들을 갖춘 것으로 판단된다. 그러나 인공둥지가 번식성공률에 미치는 영향을 명확하게 밝히기 위해서는 설 치 장소, 높이, 형태, 크기, 구멍의 크기에 따른 장기적 연구 가 필요할 것으로 판단된다.

경기도 이천에서 3개의 알을 산란하여 포란 중인 수리부엉이 둥지를 촬영하였다. 2개의 알에서 새끼가 부화하였으나 1마리는 사라졌고, 2007년 3월 8일 남은 1마리가 사망한 후 어미는 죽은 새끼를 먹었으며, 이튿날 어미는 번식을 포기하고 둥지를 떠났다.

In this study, a batch least square estimator that utilizes optical observation data is developed and utilized to determine geostationary orbits (GEO). Through numerical simulations, the effects of error sources, such as clock errors, measurement noise, and the a priori state error, are analyzed. The actual optical tracking data of a GEO satellite, the Communication, Ocean and Meteorological Satellite (COMS), provided by the optical wide-field patrol network (OWL-Net) is used with the developed batch filter for orbit determination. The accuracy of the determined orbit is evaluated by comparison with two-line elements (TLE) and confirmed as proper for the continuous monitoring of GEO objects. Also, the measurement residuals are converged to several arcseconds, corresponding to the OWL-Net performance. Based on these analyses, it is verified that the independent operation of electro-optic space surveillance systems is possible, and the ephemerides of space objects can be obtained.

The Optical Wide-field patroL-Network (OWL-Net) is a global optical network for Space Situational Awareness in Korea. The primary operational goal of the OWL-Net is to track Low Earth Orbit (LEO) satellites operated by Korea and to monitor the Geostationary Earth Orbit (GEO) region near the Korean peninsula. To obtain dense measurements on LEO tracking, the chopper system was adopted in the OWL-Net’s back-end system. Dozens of angle-only measurements can be obtained for a single shot with the observation mode for LEO tracking. In previous work, the reduction process of the LEO tracking data was presented, along with the mechanical specification of the back-end system of the OWL-Net. In this research, we describe an integrity assessment method of time-position matching and verification of results from real observations of LEO satellites. The change rate of the angle of each streak in the shot was checked to assess the results of the matching process. The time error due to the chopper rotation motion was corrected after re-matching of time and position. The corrected measurements were compared with the simulated observation data, which were taken from the Consolidated Prediction File from the International Laser Ranging Service. The comparison results are presented in the In-track and Cross-track frame.

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

As described in the previous paper (Park et al. 2013), the detector subsystem of optical wide-field patrol (OWL) provides many observational data points of a single artificial satellite or space debris in the form of small streaks, using a chopper system and a time tagger. The position and the corresponding time data are matched assuming that the length of a streak on the CCD frame is proportional to the time duration of the exposure during which the chopper blades do not obscure the CCD window. In the previous study, however, the length was measured using the diagonal of the rectangle of the image area containing the streak; the results were quite ambiguous and inaccurate, allowing possible matching error of positions and time data. Furthermore, because only one (position, time) data point is created from one streak, the efficiency of the observation decreases. To define the length of a streak correctly, it is important to locate the endpoints of a streak. In this paper, a method using a differential convolution mask pattern is tested. This method can be used to obtain the positions where the pixel values are changed sharply. These endpoints can be regarded as directly detected positional data, and the number of data points is doubled by this result.

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

By using the Optical Wide-field Patrol (OWL) network developed by the Korea Astronomy and Space Science Institute (KASI) we generated the right ascension and declination angle data from optical observation of Low Earth Orbit (LEO) satellites. We performed an analysis to verify the optimum number of observations needed per arc for successful estimation of orbit. The currently functioning OWL observatories are located in Daejeon (South Korea), Songino (Mongolia), and Oukaïmeden (Morocco). The Daejeon Observatory is functioning as a test bed. In this study, the observed targets were Gravity Probe B, COSMOS 1455, COSMOS 1726, COSMOS 2428, SEASAT 1, ATV-5, and CryoSat-2 (all in LEO). These satellites were observed from the test bed and the Songino Observatory of the OWL network during 21 nights in 2014 and 2015. After we estimated the orbit from systematically selected sets of observation points (20, 50, 100, and 150) for each pass, we compared the difference between the orbit estimates for each case, and the Two Line Element set (TLE) from the Joint Space Operation Center (JSpOC). Then, we determined the average of the difference and selected the optimal observation points by comparing the average values.

As a governmentally approved domestic entity for Space Situational Awareness, Korea Astronomy and Space Science Institute (KASI) is developing and operating an optical telescopes system, Optical Wide-field PatroL (OWL) Network. During the test phase of this system, it is necessary to determine the range of brightness of the observable satellites. We have defined standard magnitude for Low Earth Orbit (LEO) satellites to calibrate their luminosity in terms of standard parameters such as distance, phase angle, and angular rate. In this work, we report the optical brightness range of five LEO Satellites using OWL-Net.

An algorithm to automatically extract coordinate and time information from optical observation data of geostationary orbit satellites (GEO satellites) or geosynchronous orbit satellites (GOS satellites) is developed. The optical wide-field patrol system is capable of automatic observation using a pre-arranged schedule. Therefore, if this type of automatic analysis algorithm is available, daily unmanned monitoring of GEO satellites can be possible. For data acquisition for development, the COMS1 satellite was observed with 1-s exposure time and 1-m interval. The images were grouped and processed in terms of “action”, and each action was composed of six or nine successive images. First, a reference image with the best quality in one action was selected. Next, the rest of the images in the action were geometrically transformed to fit in the horizontal coordinate system (expressed in azimuthal angle and elevation) of the reference image. Then, these images were median-combined to retain only the possible non-moving GEO candidates. By reverting the coordinate transformation of the positions of these GEO satellite candidates, the final coordinates could be calculated.