• Spatial Information Research
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• v.16 no.2
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• pp.173-192
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• 2008

Recent climate fluctuation and environmental change at global scale are causing more incidences of disasters and calamities over the world. In a response to this environmental crisis, international collaboration for Earth Observation(EO) is obtaining more significance in order to understand, watch, and forecast changes in the earth system. As such, aerial monitoring based on remotely sensed data, indispensable for EO, is also drawing more attentions. In this context, we discuss diverse aspects of future developments in the Korean domestic system for aerial monitoring. This paper first thoroughly examines current status of national and international collaboration system arid research of aerial monitoring. It then suggests specific development plans for four critical dimensions such as research, organization, institutional systems, and strategies. Our study would facilitate systematically establishing policies for aerial monitoring in Korea and creating a domestic GEOSS(Global Earth Observation System of Systems) in the near future.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.590-598
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• 2019

Aerial photographs taken by an image sensor fixed on a flight body, e.g. without a gimbal, are generally distorted according to its attitude, altitude and angle of view in flight. This can result in a significant difficulty of analyzing geometric information which should be integrated for numerous still frames. In this study, a simulation method of observation performance that uses geometric relationships between navigation data and image data is suggested, and this method is shown to be very useful for easily examining the integrated information such as the total range of photography, the time of target acquisition, etc.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.47-56
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• 1999

In this study, tie point observation in aerial triangulation was automated by the image processing methods. The technique includes boundary extraction and We matching processes. The procedures were applied to extract points of Interest and to find their conjugate points in the other images. The image coordinates of the identified points were then used to compute their absolute coordinates. An algorithm was developed in this study for the automation of observation in aerial triangulation, which is a manual process of selecting a tie point and recording the image coordinate of the selected point. The developed algorithm automates this process through the application of a mathematical operator to extract points of interest from an arbitrary image. The root m square error of image coordinates of the developed algorithm is $6.8{\mu}m$, which is close to that of the present analytical method. In a manual environment, the accuracy of the result of a photogrammetric process is heavily dependant on the level of skill and experience of the human operator. No such problem exists in an automated system. Also, as a result of the automated system, the time spent in the observation process could be reduced by a factor of 61.2%, thereby reducing the overall cost.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.580-585
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• 2005

A QRT(Quad-Rotor Type) hovering robot system is developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV(Unmanned Aerial Vehicle) is equipped with four propellers driven by each electric motor, an embedded controller using a DSP, INS(Inertial Navigation System) using 3-axis rate gyros, a CCD camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. The developed hovering robot shows stable flying performances under the adoption of RIC(Robust Internal-loop Compensator) based disturbance compensation and the vision based localization method. The UAV can also avoid obstacles using eight IR and four ultrasonic range sensors. The VTOL(Vertical Take-Off and Landing) flying object flies into indoor fire spots and sends the images captured by the CCD camera to the operator. This kind of small-sized UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment.

• Atmosphere
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• v.20 no.4
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• pp.519-530
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• 2010

In this paper we review current research on Atmospheric Brown Clouds (ABCs) with lightweight Unmanned Aerial Vehicles (UAVs) and miniaturized instruments. The UAV technology for in-situ measurements, including aerosol concentration, aerosol size distribution, aerosol absorption, cloud drop size distribution, solar radiation fluxes (visible and broadband), and spectral radiative fluxes, is a leading-edge technology for cost-effective atmospheric sounding, which can fill the gap between the ground measurement and satellite observation. The first experimental observation with UAVs in Korea, Cheju ABC Plume Monsoon Experiment (CAPMEX), conducted during summer 2008 revealed that the Beijing plumes exerted a strong positive influence on the net warming and fossil-fuel-dominated black-carbon plumes were approximately 100% more efficient warming agents than biomass-burning-dominated plumes. Long-term sustainable routine UAV measurements will eventually provide truly three-dimensional data of ABCs, which is necessary for the better understanding of their climate impacts and for the improvement of numerical models for air pollution, weather forecast and climate change.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.400-406
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• 2002

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is performed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with frame imagery and vise versa. The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.55-67
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• 2012

Real-time image georeferencing is required to generate spatial information rapidly from the image sequences acquired by multi-sensor systems. To complement the performance of position/attitude sensors and process in real-time, we should employ on-line aerial triangulation based on a sequential estimation algorithm. In this study, we thus attempt to derive an efficient on-line aerial triangulation algorithm for real-time georeferencing of image sequences. We implemented on-line aerial triangulation using the existing Given transformation update algorithm, and a new inverse normal matrix update algorithm based on observation classification, respectively. To compare the performance of two algorithms in terms of the accuracy and processing time, we applied these algorithms to simulated airborne multi-sensory data. The experimental results indicate that the inverse normal matrix update algorithm shows 40 % higher accuracy in the estimated ground point coordinates and eight times faster processing speed comparing to the Given transformation update algorithm. Therefore, the inverse normal matrix update algorithm is more appropriate for the real-time image georeferencing.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.684-690
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• 2010

Digitalized Image Information is variously used like to substitute or help human's visual ability. Unmanned observation Camera is useful for the preventing disaster, risk factor and object observation but it is mostly to depend on awareness for human's vision. The purpose of this paper is to show that Unmanned Aerial Camera carries out object recognition and autonomous position tracking. when the informations about a specific object are given. For this purpose, we have to solve complicated problems like change according to object movement and variation of color and brightness information with refraction, interference and scattering of light and noise from environmental factors like weather. But, as the first step we limit the scope of this study with simplified environment in this paper. Our goal is the study and experience about object recognition and tracking via simplified environment with unmanned aerial camera. We obtained successful results of this study and experiment.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.803-813
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• 2022

In this study, we improved the water-based condensation particle counter in Atmospheric Research Aircraft NARA and investigated the condensation particle number concentration over the Korean peninsula. Pump and set point information were changed to improve the instrument used by aircraft for observation. Ground-based observational result showed that the error between two instruments, which are water-based condensation particle counter and butanol-based condensation particle counter, was 4.7%. Aerial observational result revealed that the number concentration before improvement indicate large variation with unstable condition, whereas the number concentration after improvement indicate a reasonable variation. After improvement, the number concentration was 706±499 particle/cm³ in the West Sea and 257±80 particle/cm³ in Gangwon-do, and these are similar to the concentration range reported in previous studies. Notably, this is the first attempt to use aerial observation with water-based condensation particle counter to investigate condensation particle number concentration.