• Journal of KIBIM
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• v.7 no.2
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• pp.36-43
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• 2017

Population growth and rapid urbanization has been converting large amounts of rural vegetation into urbanized areas. This human induced change has increased temperature in urban areas in comparison to adjacent rural regions. Various studies regarding to urban heat island have been conducted in different disciplines in order to analyze the environmental issue. Especially, different types of thermal infrared remote sensing data are applied to urban heat island research. This article reviews research focusing on thermal infrared remote sensing for urban heat island and urban planning studies. Seven studies of analyses for the relationships between urban heat island and other dependent indicators in urban planning discipline are reviewed. Despite of different types of thermal infrared remote sensing data, units of analysis, land use and land cover, and other dependent variable, each study results in meaningful outputs which can be implemented in urban planning strategies. As the application of thermal infrared remote sensing data is critical to measure urban heat island, it is important to understand its advantages and disadvantages for better analyses of urban heat island based on this review. Despite of its limitations - spatial resolution, overpass time, and revisiting cycle, it is meaningful to conduct future research on urban heat island with thermal infrared remote sensing data as well as its application to urban planning disciplines. Based on the results from this review, future research with remotely sensed data of urban heat island and urban planning could be modified and better results and mitigation strategies could be developed.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.37-48
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• 1994

In spatial information processing, particularly in non-renewable resource exploration, the spatial data sets, including remote sensing, geophysical and geochemical data, have to be geocoded onto a reference map and integrated for the final analysis and interpretation. Application of a computer based GIS(Geographical Information System of Geological Information System) at some point of the spatial data integration/fusion processing is now a logical and essential step. It should, however, be pointed out that the basic concepts of the GIS based spatial data fusion were developed with insufficient mathematical understanding of spatial characteristics or quantitative modeling framwork of the data. Furthermore many remote sensing and geological data sets, available for many exploration projects, are spatially incomplete in coverage and interduce spatially uneven information distribution. In addition, spectral information of many spatial data sets is often imprecise due to digital rescaling. Direct applications of GIS systems to spatial data fusion can therefore result in seriously erroneous final results. To resolve this problem, some of the important mathematical information representation techniques are briefly reviewed and discussed in this paper with condideration of spatial and spectral characteristics of the common remote sensing and exploration data. They include the basic probabilistic approach, the evidential belief function approach (Dempster-Shafer method) and the fuzzy logic approach. Even though the basic concepts of these three approaches are different, proper application of the techniques and careful interpretation of the final results are expected to yield acceptable conclusions in cach case. Actual tests with real data (Moon, 1990a; An etal., 1991, 1992, 1993) have shown that implementation and application of the methods discussed in this paper consistently provide more accurate final results than most direct applications of GIS techniques.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Information Display
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• v.18 no.3
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• pp.3-12
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• 2017

In the recent years, significant advances have been made in the development of small form-factor, low power, and low cost 3D-sensing devices based on depth-imaging technologies with real-time performance. This has led to the advent of devices and machines that are able to sense and understand the world, navigate in the environment, and interact naturally with their human users. Human-computer interactions based on touch sensing and speech recognition have already become mainstream, and the rapid developments in 3D sensing is paving the path towards the next level of machine intelligence and interactions. This paper discusses the recent developments in real-time 3D sensing technologies and their emerging system application.

• Current Research on Agriculture and Life Sciences
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• v.31 no.2
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• pp.113-123
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• 2013

The carbon-offset mechanism based on forest management has been recognized as a meaningful tool to sequestrate carbons already existing in the atmosphere. Thus, with an emphasis on the forest-originated carbon-offset mechanism, the accurate measurement of the carbon stock in forests has become important, as carbon credits should be issued proportionally with forest carbon stocks. Various remote sensing techniques have already been developed for measuring forest carbon stocks. Yet, despite the efficiency of remote sensing techniques, the final accuracy of their carbon stock estimations is disputable. Therefore, minimizing the uncertainty embedded in the application of remote sensing techniques is important to prevent questions over the carbon stock evaluation for issuing carbon credits. Accordingly, this study reviews the overall procedures of carbon stock evaluation-related remote sensing techniques and identifies the problematic technical issues when measuring the carbon stock. The procedures are sub-divided into four stages: the characteristics of the remote sensing sensor, data preparation, data analysis, and evaluation. Depending on the choice of technique, there are many disputable issues in each stage, resulting in quite different results for the final carbon stock evaluation. Thus, the establishment of detailed standards for each stageis urgently needed. From a policy-making perspective, the top priority should be given to establishinga standard sampling technique and enhancing the statistical analysis tools.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.361-371
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• 2010

In recent, interests regarding open source software for geo-spatial processing are increasing. Open source remote sensing (OSRS) is regarded as one of the progressing and advanced fields in remote sensing. Nevertheless, analyses or application cases regarding OSRS are not enough for general uses or references. In this study, three kinds of OSRS software in consideration of international popularity, types of functionalities, and development environments are taken into account: OSSIM, Opticks, and ORFEO Toolbox (OTB). First, functional comparison with respect to these is carried out on the level of the preliminary survey. According to this investigation, OTB is chosen as the most applicable OSRS software in this study. Running on OTB, NIX format importing module and database connecting module are implemented for widely general uses and further application. As for an example case, airborne image of NIX format is used to region growing segmentation algorithm in OTB, and then the results are stored and retrieved in PostGIS database to test implemented modules. Conclusively, local customization and algorithm development using OSRS software are necessary to build on-demand applications from the developers' viewpoint.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.46-46
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• 2017

We developed a rice simulation model for remote-sensing (SIMRIW-RS, Homma et al., 2007) to evaluate rice production and management on a regional scale. Here, we reports its application trial to estimate rice production in farmers' fields in Sendai, Japan. The remote-sensing data for the application was periodically obtained by multispectral camera (RGB + NIR and RedEdge) attached with unmanned air vehicle (UAV). The airborne images was 8 cm in resolution which was attained by the flight at an altitude of 115 m. The remote-sensing data was relatively corresponded with leaf area index (LAI) of rice and its spatial and temporal variation, although the correspondences had some errors due to locational inaccuracy. Calibration of the simulation model depended on the first two remote-sensing data (obtained around one month after transplanting and panicle initiation) well predicted rice growth evaluated by the third remote-sensing data. The parameters obtained through the calibration may reflect soil fertility, and will be utilized for nutritional management. Although estimation accuracy has still needed to be improved, the rice yield was also well estimated. These results recommended further data accumulation and more accurate locational identification to improve the estimation accuracy.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1268-1271
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• 2003

In the edge detection of RS image, the useful detail losing and the spurious edge often appear. To solve the problem, we use the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, we obtain the RS image of a certain appropriate scale, and figure out the edge data of the plane and the upright directions respectively, then work out the grads vector module of the surface features, at last by tracing them we get the edge data of the object therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of a RS image which obtains an airport, we certificate the feasibility of the application of dyadic wavelet in the object edge detection.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.195-197
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• 2003

Soil moisture is a crucial variable in research works of hydrology, meteorology and plant sciences. Adequate soil moisture is essential for plant growth; excesses and deficits of soil moisture must be considered in agricultural practices. There are already several remote sensing methods used for monitoring soil moisture, such as thermal inertia, vegetation water-supplying index, crop water stress index and multi-factor regression. In this paper, an improved method has been discussed which is based on the thermal inertia. We analyzed the problems of monitoring soil moisture using satellites at first, and then put forward an simplified method which directly uses land surface temperature differences to measure soil moisture. Also we have taken the influence of vegetation into account, and import NDVI into the model. The method was used in the study of soil moisture in Heilongjiang Province, China, and we draw the conclusion by the experiments that the model can evidently increase the precision of monitoring soil moisture.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.9-19
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• 2017

Useful continuous sensing applications are increasingly emerging as a new class of mobile applications. Meanwhile, open, multi-use sensor devices are newly adopted beyond smartphones, and provide huge opportunities to expand potential application categories. In this upcoming environment, uncoordinated use of sensor devices would cause severe imbalance in power consumption of devices, and thus result in early shutdown of some sensing applications depending on power-hungry devices. In this paper, we propose EnergyCordy, a novel inter-device energy use coordination system; with a system-wide holistic view, it coordinates the energy use of concurrent sensing applications over multiple sensor devices. As its key approach, we propose a relaxed sensor association; it decouples the energy use of an application from specific sensor devices leveraging multiple context inference alternatives, allowing flexible energy coordination at runtime. We demonstrated the effectiveness of EnergyCordy by developing multiple example applications over custom-designed wearable senor devices. We show that EnergyCordy effectively coordinates the power usage of concurrent sensing applications over multiple devices and prevent undesired early shutdown of applications.