The fact that the demands on traffic data collection are imposed by economic and safety considerations raisese the question of the potential for complementing existing traffic data collection programs with satellite data. Evaluating and monitoring traffic characteristics is becoming increasingly important as worsening congestion, declining economic situations, and increasing environmental sensitivies are forcing the government and municipalities to make better use of existing roadway capacities. The present system of using automatic counters at selected points on highways works well from a temporal point of view (i.e., during a specific period of time at one location). However, the present system does not cover the spatial aspects of the entire road system (i.e., for every location during specific periods of time); the counters are employed only at points and only on selected highways. This lack of spatial coverage is due, in part, to the cost of the automatic counters systems (fixed procurement and maintenance costs) and of the personal required to deploy them. The current procedure is believed to work fairly well in the aggregate mode, at the macro level. However, at micro level, the numbers are more suspect. In addition, the statistics only work when assuming a certain homogenity among characteristics of highways in the same class, an assumption that is impossible to test whn little or no data is gathered on many of the highways for a given class. In this paper, a remote sensing system as complement of the existing system is considered and implemented. Since satellite imagery with high resolution is not available, digitized panchromatic imagery acquired from an aircraft platform is utilized for initial test of the feasibility and performance capability of remote sensing data. Different levels of imagery resolutions are evaluated in an attempt to determine what vehicle types could be classified and counted against a background of pavement types, which might be expected in panchromatic satellite imagery. The results of a systematic study with three different levels of resolutions (1m, 2m and 4m) show that the panchromat ic reflectances of vehicles and pavements would be distributed so similarly that it would be difficult to classify systematically and analytically remotely sensing vehicles on pavement within panchromatic range. Anaysis of the aerial photographs show that the shadows of the vehicles could be a cue for vehicle detection.
Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
Korean Journal of Remote Sensing
/
v.36
no.2_2
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pp.249-261
/
2020
Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.
Hye-Kyeong Shin;Jae Yeop Kwon;Pyeong Joong Kim;Tae-Ho Kim
Korean Journal of Remote Sensing
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v.39
no.6_1
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pp.1255-1272
/
2023
Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.
Kim, Hyun-Tae;Zhang, Gui-Ping;Kim, Hyoung-Jin;Joo, Young-Hoon;Ra, In-Ho
Journal of the Korean Institute of Intelligent Systems
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v.16
no.6
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pp.683-690
/
2006
Reducing power consumption to extend network lifetime is one of the most important challenges in designing wireless sensor networks. One promising approach to conserving system energy is to keep only a minimal number of sensors active and put others into low-powered sleep mode, while the active sensors can maintain a connected covet set for the target area. The problem of computing such minimum working sensor set is NP-hard. In this paper, a centralized Voronoi tessellation (CVT) based approximate algorithm is proposed to construct the near optimal cover set. When sensor's communication radius is at least twice of its sensing radius, the covet set is connected at the same time; In case of sensor's communication radius is smaller than twice of its sensing radius, a connection scheme is proposed to calculate the assistant nodes needed for constructing the connectivity of the cover set. Finally, the performance of the proposed algorithm is evaluated through theoretical analysis and extensive numerical experiments. Experimental results show that the proposed algorithm outperforms the greedy algorithm in terms of the runtime and the size of the constructed connected cover set.
Chae Jung Park;Jihoon Cha;Sung Soo Ahn;Hyun Seok Choi;Young Dae Kim;Hyo Suk Nam;Ji Hoe Heo;Seung-Koo Lee
Korean Journal of Radiology
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v.21
no.12
/
pp.1334-1344
/
2020
Objective: Compressed sensing (CS) has gained wide interest since it accelerates MRI acquisition. We aimed to compare the 3D post-contrast T1-weighted volumetric isotropic turbo spin echo acquisition (VISTA) with CS (VISTA-CS) and without CS (VISTA-nonCS) in intracranial vessel wall MRIs (VW-MRI). Materials and Methods: From April 2017 to July 2018, 72 patients who underwent VW-MRI, including both VISTA-CS and VISTA-nonCS, were retrospectively enrolled. Wall and lumen volumes, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured from normal and lesion sites. Two neuroradiologists independently evaluated overall image quality and degree of normal and lesion wall delineation with a four-point scale (scores ≥ 3 defined as acceptable). Results: Scan coverage was increased in VISTA-CS to cover both anterior and posterior circulations with a slightly shorter scan time compared to VISTA-nonCS (approximately 7 minutes vs. 8 minutes). Wall and lumen volumes were not significantly different with VISTA-CS or VISTA-nonCS (interclass correlation coefficient = 0.964-0.997). SNR was or trended towards significantly higher values in VISTA-CS than in VISTA-nonCS. At normal sites, CNR was not significantly different between two sequences (p = 0.907), whereas VISTA-CS provided lower CNR in lesion sites compared with VISTA-nonCS (p = 0.003). Subjective wall delineation was superior with VISTA-nonCS than with VISTA-CS (p = 0.019), although overall image quality did not differ (p = 0.297). The proportions of images with acceptable quality were not significantly different between VISTA-CS (83.3-97.8%) and VISTA-nonCS (75-100%). Conclusion: CS may be useful for intracranial VW-MRI as it allows for larger scan coverage with slightly shorter scan time without compromising image quality.
Kim, Dong-Wook;Jung, Sang-Jin;Kwon, Young-Seok;Kim, Hak-Jin
Proceedings of the Korean Society for Agricultural Machinery Conference
/
2017.04a
/
pp.45-45
/
2017
On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.
A novel optical design for high resolution, large field of view (FOV) and multispectral remote sensing is presented. An f/7.3 Korsch and two f/17.9 Cook three-mirror optical systems are integrated by sharing the primary and secondary mirrors, bias of the FOV, decentering of the apertures and reasonable structure arrangement. The aperture stop of the Korsch system is located on the primary mirror, while those of the Cook systems are on the exit pupils. High resolution image with spectral coverage from visible to near-infrared (NIR) can be acquired through the Korsch system with a focal length of 14 m, while wide-field imaging is accomplished by the two Cook systems whose focal lengths are both 13.24 m. The full FOV is 4°×0.13°, a coverage width of 34.9 km at the altitude of 500 km can then be acquired by push-broom imaging. To facilitate controlling the stray light, the intermediate images and the real exit pupils are spatially available. After optimization, a near diffraction-limited performance and a compact optical package are achieved. The sharing of the on-axis primary and secondary mirrors reduces the cost of fabrication, test, and manufacture effectively. Besides, the two tertiary mirrors of the Cook systems possess the same parameters, further cutting down the cost.
An experimental variable rate nursery sprayer was developed to adjust application rates for canopy volume in real time. The sprayer consisted of two vertical booms integrated with ultrasonic sensors, and variable rate nozzles coupled with pulse width modulation (PMW) based solenoid valves. A custom-designed microcontroller instructed the sensors to detect canopy size and occurrence and then controlled nozzles to achieve variable application rates. A spray delivery system, which consisted of diaphragm pump, pressure regulator and 4-cycle gasoline engine, offered the spray discharge function. Spray delay time, time adjustment in spray trigger for the leading distance of the sensor, was measured with a high-speed camera, and it was from 50 to 140 ms earlier than the desired time (398 ms) at 3.2 km/h under indoor conditions. Consequently, the sprayer triggered 4.5 to 12.5 cm prior to detected targets. Duty cycles of the sprayer were from 20 to 34 ms for senor-to-canopy (STC) distance from 0.30 to 0.76 m. Outdoor test confirmed that the nozzles were triggered from 290 to 380 ms after detecting tree canopy at 3.2 km/h. The spray rate of the new sprayer was 58.4 to 85.2% of the constant application rate (935 L/ha). Spray coverage was collected at four areas of evergreen canopy by water sensitive papers (WSP), and ranged from 1.9 to 41.1% and 1.8 to 34.7% for variable and constant rate applications, respectively. One WSP area had significant (P < 0.05) difference in mean spray coverage between two application conditions.
Kim, June-Kyoung;O, Nam-Geol;Kim, Jae-Joon;Lee, Young-Moo;Kim, Hoon;Jung, Bang-Chul
The Journal of Korean Institute of Communications and Information Sciences
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v.34
no.10B
/
pp.973-980
/
2009
Many studies which have been done for efficient installation and management of wireless sensor networks (WSN) include energy savings, key managements and sensor deployments. Sensor deployment problem is one of the most important and fundamental issues among them in that the topic is directly related with the system cost and performance. In this paper, we suggest a sensor deployment scheme that reduces the system cost of WSN while satisfying the fundamental system requirements of connectivity between sensor nodes and sensing coverage. Using graphical information system(GIS) which contains region-dependent information related with connectivity condition, the initial positions of sensors in the procedure simulated annealing (SA) are determined. The GIS information helps in reducing system cost reduction not only at the initial deployment of SA but also at the final deployment of SA which is shown by computer simulations.
The Journal of Korean Institute of Communications and Information Sciences
/
v.37A
no.9
/
pp.762-771
/
2012
In this paper, we propose an adaptive power control scheme employing a self-optimization concept in femtocell systems, in order to improve system capacity, thereby reducing call-drop probability. In the proposed scheme, each femto base station(FBS) controls individual channel's transmission power base on two parameters; the neighboring cell's transmission power for each individual channel which is delivered from a femto-gateway and the received power strength from neighboring cells which is periodically measured by means of a spectrum sensing. Adaptive adjustment of individual channel's transmission power in accordance with femto mobile station(FMS) mobility features can also reduce undesirable handovers and evenly distribute traffic load over all femtocells. In addition, the manipulative control of channel's transmission power is able to keep the system coverage and the call-drop probability within an acceptable range, regardless of density of femtocells. Computer simulation shows that the proposed scheme outperforms existing schemes in terms of the system coverage and the call-drop probability.
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