• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.883-902
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• 2023

Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.95-105
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• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.95-99
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• 1999

We proposed a new retrieval method for aerosol's real part of refractive index, optical thickness, and Angstrom exponent using POLDER's directional reflectance and polarization data. We showed that aerosol's real part of refractive index can be retrieved systematically using multi-directional PR(polarization and reflectance) diagrams in a single infrared band by our algorithm for the first time. We examined the retrieved results, by comparing with the simultaneously measured sky observation data at the study site and we obtained a reasonable agreement between them.

• Proceedings of the Optical Society of Korea Conference
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• 2009.10a
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• pp.74-75
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• 2009

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.90-94
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• 2007

The conventional single-reference station positioning is affected by systematic errors such as ionospheric and tropospheric delay, so that the rover must be located within 10 km from the reference station in order to acquire centimeter-level accuracy. The medium-range real-time kinematic has been proven feasible and can be used for high precision applications. However, the longer of the baseline, the more of the time for resolving the integral ambiguity is required. This is due to the fact that systematic errors can not be eliminated effectively by double-differencing. Recently, network approaches have been proposed to overcome the limitation of the single-reference station positioning. The real-time systematic error modeling can be achieved with the use of GPS network. For expanding the effective range and decreasing the density of the reference stations, Land Survey Bureau, Ministry of the Interior in Taiwan set up a national GPS network. In order to obtain the high precision positioning and provide the multi-goals services, a GPS network including 66 stations already been constructed in Taiwan. The users can download the corrections from the data center via the wireless internet and obtain the centimeter-level accuracy positioning. The service is very useful for surveyors and the high precision coordinates can be obtained real time.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.345-358
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• 2002

DGPS(Differential Global Positioning System) and RTK(Real time Kinematic) are in one of today's most widely used surveying techniques. However surveying with these techniques is restricted by the distance between reference and rover station, and it is difficult to process data in realtime by their own organizational limitation in precise measurement of positioning. To meet these new demands, in this paper, new DGPS and RTK correction data services through the Internet and PSTN(Public Switched Telephony Network) have been proposed. For this purpose, a DGPS and RTK error correction data transmission system is implemented for long-distance using the Internet and PSTN which allows a mobile user at which the rover receiver is located to receive the correction data from the reference in realtime, and analyzed and compared with DGPS and RTK performances by experiments through the Internet and PSTN for the distance and the time.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.418-422
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• 2022

α-pinene is a natural volatile organic compound secreted by coniferous trees to protect themselves from attacks by insects, microorganisms, and viruses. Recently, studies have reported that α-pinene possesses pharmacological effects on various biological reactions such as anxiolytic, sleep-enhancing, anti-nociceptive, and inflammatory activity. Thus, forest bathing has recently received great attention as a novel therapy for treating severe diseases as well as psychological issues. However, appropriate places and timings for effective therapies are still veiled, because on-site monitoring of α-pinene gas in forests is barely possible. Although portable chemosensors could allow real-time analysis of α-pinene gas in forests, the α-pinene sensing properties of chemosensors have never been reported thus far. Herein, we report for the first time, the α-pinene sensing properties of an oxide semiconductor gas sensor based on rhombohedral In₂O₃ (h-In₂O₃) nanoparticles prepared by a microwave-assisted hydrothermal reaction. The h-In₂O₃ nanoparticle sensor showed a high response to α-pinene gas at ppm levels, even under humid conditions (for example, relative humidity of 50 %). The purpose of this research is to identify the potential of oxide semiconductor gas sensors for implementing portable devices that can detect α-pinene gas in forests in real-time.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.322-331
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• 2017

In this paper we present a novel robotic palpation method for the lump shape estimation using contact pressure distribution. Many previous researches about the robotic palpation have used a stiffness map, which is not suitable to obtain geometrical information of a lump. As a result, they require a large data set and long palpation time to estimate the lump shape. Instead of using the stiffness map, the proposed palpation method uses the difference between the normal force direction and the surface normal to detect the lump boundary and estimate its normal. The palpation trajectory is generated by the normal of the lump boundary to track the lump boundary in real-time. The proposed approach requires small data set and short palpation time for the lump shape estimation since the shape can be directly estimated from the optimally generated palpation trajectory. An experiment result shows that our method can find the lump shape accurately in real-time with small data and short time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.68-78
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• 2013

In this paper, we propose an early spectrum sensing(ESS) as an advance preparation for radio-access trial, which enables multi-mode terminals to access the most appropriate radio-access system in a cloud-conceptual base station system where multiple radio access technologies(RATs) coexist. Prior to a random access to one of RATs, a multi-mode terminal conducts a spectrum sensing over entire frequency bands of whole RATs, then select the RAT with the lowest sensing power, that is likely to have the most available spectrum. Thus, an access failure caused by that the selected RAT has no available radio spectrum could be avoidable in advance. In computer simulation, we consider as various RATs as possible. First, circuit and packet systems are taken into consideration. In addition, the packet systems are classified according to the feasibility of carrier aggregation(CA). In case of terminal, three modes are considered with circuit-only, packet-only, and multi-mode. Subsequently, packet traffic is classified into real-time and non-real-time traffic with three different tolerable delay levels. The simulation includes a call process starting with a call generation and ending up with a resource allocation reflecting individual user's QoS requirements and evaluates the proposed scheme in terms of the successful access probability, system access time, system balancing factor and packet loss probability.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.155-158
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• 2008

The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain, and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.