• KIPS Transactions on Computer and Communication Systems
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• v.4 no.2
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• pp.57-64
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• 2015

At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.297-304
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• 2015

The change detection algorithms, based on remotely sensed satellite imagery, can be applied to various applications, such as the hazard/disaster analysis and the land monitoring. However, unchanged areas sometimes detected as the changed areas due to various errors in relief displacements and noise pixels, included in the original multi-temporal dataset at the application of unsupervised change detection algorithm. In this research, the object-based changed detection for the high-spatial resolution satellite images is applied by using the IR-MAD (Iteratively Reweighted- Multivariate Alteration Detection), which is one of those representative change detection algorithms. In additionally, we tried to increase the accuracy of change detection results with using the additional information, based on the cross-sharpening method. In the experiment, we used the KOMPSAT-2 satellite sensor, and resulted in the object-based IR-MAD algorithm, representing higher changed detection accuracy than that by the pixel-based IR-MAD. Also, the object-based IR-MAD, focused on cross-sharpened images, increased in accuracy of changed detection, compared to the original object-based IR-MAD. Through these experiments, we could conclude that the land monitoring and the change detection with the high-spatial-resolution satellite imagery can be accomplished efficiency by using the object-based IR-MAD algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.363-371
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• 2014

Most space-borne optical scanning systems adopt linear arrayconfigurations. The well-knownthree different types of space-borne sensors arealong-track line scanner, across-track linescanner, and three line scanner. To acquire accurate location information of an object on the ground withthose sensors, the exterior and interior orientation parameters are critical factors for both of space-borne and airborne missions. Since the imaging geometry of sensors mightchange time to time due to thermal influence, vibration, and wind, it is very important to analyze the Interior Orientation Parameters (IOP) effects on the ground. The experiments based on synthetic datasets arecarried out while the focal length biases are changing. Also, both high and low altitudes of the imagingsensor were applied. In case with the along-track line scanner, the focal length bias caused errors along the scanline direction. In the other case with the across-track one, the focal length bias caused errors alongthe scan line and vertical directions. Lastly, vertical errors were observed in the case ofthree-line scanner. Those results from this study will be able to provide the guideline for developing new linearsensors, so as for improving the accuracy of laboratory or in-flight sensor calibrations.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.177-184
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• 2010

In these day, many data including sensor, delivery, credit and stock data are generated continuously in massive quantity. It is difficult to learn from these data because they are large in volume and changing fast in their concepts. To handle these problems, learning methods based in sliding window methods over time have been used. But these approaches have a problem of rebuilding models every time new data arrive, which requires a lot of time and cost. Therefore we need very simple incremental learning methods. Bayesian method is an example of these methods but it has a disadvantage which it requries the prior knowledge(probabiltiy) of data. In this study, we propose a learning method based on attribute values. In the proposed method, even though we don't know the prior knowledge(probability) of data, we can apply our new method to data. The main concept of this method is that each attribute value is regarded as an expert learner, summing up the expert learners lead to better results. Experimental results show our learning method learns from data very fast and performs well when compared to current learning methods(decision tree and bayesian).

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.341-369
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• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.213-222
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• 2008

Although hyperspectral sensing data have shown great potential to derive various surface information that is not usually available from conventional multispectral image, the acquisition of proper hyperspectral image data are often limited. To use ground-based hyperspectral camera image for remote sensing studies, radiometric calibration should be prerequisite. The objective of this study is to develop radiometric calibration procedure to convert image digital number (DN) value to surface reflectance for the 120 bands ground-based hyperspectral camera. Hyperspectral image and spectral measurements were simultaneously obtained from the experimental target that includes 22 different surface materials of diverse spectral characteristics at wavelength range between 400 to 900 nm. Calibration coefficients to convert image DN value to at-sensor radiance were initially derived from the regression equations between the sample image and spectral measurements using ASD spectroradiometer. Assuming that there is no atmospheric effects when the image acquisition and spectral measurements were made at very close distance in ground, we were also able to derive calibration coefficients that directly transform DN value to surface reflectance. However, these coefficients for deriving reflectance values should not be applied when the camera is used for aerial image that contains significant effect from atmosphere and further atmospheric correction procedure is required in such case.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.1-1
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• 2016

Many of the world's large ecosystems are severely stressed due to population growth, water quality and quantity problems, vulnerability to flood and drought, and the loss of native species and cultural resources. Consequences of climate change further increase uncertainties about the future. These major societal challenges must be addressed through innovations in governance, policy, and ways of implementing management strategies. Science and engineering play a critical role in helping define possible alternative futures that could be achieved and the possible consequences to economic development, quality of life, and sustainability of ecosystem services. Science has advanced rapidly during the past decade with the emergence of science communities coalescing around 'Grand Challenges' and the maturation of how these communities function has resulted in large interdisciplinary research networks. An example is the River Experiment Center of KICT that engages researchers from throughout Korea and the world. This trend has been complemented by major advances in sensor technologies and data synthesis to accelerate knowledge discovery. These factors combine to allow scientific debate to occur in a more open and transparent manner. The availability of information and improved communication of scientific and engineering issues is raising the level of dialogue at the science-policy interface. However, severe challenges persist since scientific discovery does not occur on the same timeframe as management actions, policy decisions or at the pace sometimes expected by elected officials. Common challenges include the need to make decisions in the face of considerable uncertainty, ensuring research results are actionable and preventing science being used by special interests to delay or obsfucate decisions. These challenges are explored in the context of examples from the United States, including the California Bay-Delta system. California transfers water from the wetter northern part of the state to the drier southern part of the state through the Central Valley Project since 1940 and this was supplemented by the State Water Project in 1973. The scale of these activities is remarkable: approximately two thirds of the population of Californians rely on water from the Delta, these waters also irrigate up to 45% of the fruits & vegetables produced in the US, and about 80% of California's commercial fishery species live in or migrate through the Bay-Delta. This Delta region is a global hotspot for biodiversity that provides habitat for over 700 species, but is also a hotspot for the loss of biodiversity with more than 25 species currently listed by the Endangered Species Act. Understanding the decline of the fragile ecosystem of the Bay-Delta system and the potential consequences to economic growth if water transfers are reduced for the environment, the California State Legislature passed landmark legislation in 2009 (CA Water Code SS 85054) that established "Coequal goals of providing a more reliable water supply for California and protecting, restoring, and enhancing the Delta ecosystem". The legislation also stated that "The coequal goals shall be achieved in a manner that protects and enhances the unique cultural, recreational, natural resource, and agricultural values of the Delta as an evolving place." The challenges of integrating policy, management and scientific research will be described through this and other international examples.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.103-111
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• 2021

The purpose of this study is to study a method for preventing collisions of multiple drones in controlled airspace. As a result of the study, it was proved that it is appropriate as a method to control drone collisions after setting accurate information on the ROI (Region of Interest) area estimated based on the expected drone path and time in the control system as a method to avoid drone collision. As a result of the empirical analysis, the diameter of the flight path of the operating drone should be selected to reduce the risk of collision, and the change in the departure time and operating speed of the operating drone did not act as an influencing factor in the collision. In addition, it has been demonstrated that providing flight priority is one of the appropriate methods as a countermeasure to avoid collisions. For collision avoidance methods, not only drone sensor-based collision avoidance, but also collision avoidance can be doubled by monitoring and predicting collisions in the control system and performing real-time control. This study is meaningful in that it provided an idea for a method for preventing collisions of multiple drones in controlled airspace and conducted practical tests. This helps to solve the problem of collisions that occur when multiple drones of different types are operating based on the control system. This study will contribute to the development of related industries by preventing accidents caused by drone collisions and providing a safe drone operation environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.235-243
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• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.155-166
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• 2021

Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.