• Korean Journal of Remote Sensing
• /
• v.16 no.1
• /
• pp.1-11
• /
• 2000

Multi-temporal data have been used frequently for analyzing dynamic characteristics of ecological environment. Little research, however, shows the characteristics and problems of the analysis of continental- or global-scale, multi-temporal satellite data. This research investigated the characteristics of large-area, multi-temporal data analysis and the problems of phenological difference of ground vegetation and scarcity of training data for a long term period. This research suggested a latitudinal image segmentation method and an invariant pixel method. As an application, the image segmentation and invariant pixel methods were applied to a set of AVHRR data covering most part of Asia from 1982 to 1993. Fuzzy classification results showed the decrease of forests and the increase of croplands at densely populated areas, however an opposite trend was detected at sparsely populated or depopulated areas.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_2
• /
• pp.1803-1818
• /
• 2021

As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.

• Journal of Communications and Networks
• /
• v.15 no.5
• /
• pp.443-456
• /
• 2013

Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much more efficient way than the established Nyquist sampling theorem. CS has recently gained a lot of attention due to its exploitation of signal sparsity. Sparsity, an inherent characteristic of many natural signals, enables the signal to be stored in few samples and subsequently be recovered accurately, courtesy of CS. This article gives a brief background on the origins of this idea, reviews the basic mathematical foundation of the theory and then goes on to highlight different areas of its application with a major emphasis on communications and network domain. Finally, the survey concludes by identifying new areas of research where CS could be beneficial.

• Korean Journal of Remote Sensing
• /
• v.18 no.5
• /
• pp.263-271
• /
• 2002

Recently, spatial information technologies using remotely sensed imagery and functionality of GIS (Geographic Information Systems) have been widely utilized to various types of transportation-related applications. In this study, extraction programs of some practical indices, to be effectively used in transportation reference planning problem, were designed and implemented as prototyped extensions in GIS development environment: traffic flow estimation (TFL/TFB), urban rural index (URI), and accessibility index (AI). In TFL/TFB, user can obtain quantitative results on traffic flow estimation at link/block using high-resolution satellite imagery. Whereas, URI extension provides urban-rural characteristics related to road system, being considered one of important factors in transportation planning. Lastly, AI extension helps to obtain accessibility index between nodes of road segments and surrounding district areas touched or intersected with the road network system, and it also provides useful information for transportation planning problems. This approach is regarded as one of RS-T (Remote Sensing in Transportation), and it is expected to expand as new application of remotely sensed imagery.

• Korean Journal of Remote Sensing
• /
• v.27 no.1
• /
• pp.1-7
• /
• 2011

Satellite imagery information have not been fully utilized due to the low R&D investment in remote sensing application though Korea had succeeded in developing series of earth observing satellites during the last decades. However, another series of earth observing satellites such as KOMPSAT 3, 3-A, 5 are going to be launched in the near future. And recent global warming issues stimulate both private and public sectors to make the most of satellite imagery information. Therefore, it is inevitable to promote the utilization of Korean satellite imagery information. In this study, we analyzed the demand and restrictions in exploitation of satellite imagery information in Korea through the online survey and interview. The results showed that the standardization of pre-processing, service of detailed technical information, fast and reliable image data delivery system are mostly required.

• Korean Journal of Remote Sensing
• /
• v.20 no.6
• /
• pp.369-382
• /
• 2004

The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.9 no.4
• /
• pp.62-70
• /
• 1995

Brushless DC Motor (BDCM) is widely used in the industry such as a variable speed motor in a compressor for room air conditioners, because the motor can be easily controlled and operated over a wide speed range. The system to drive BDCM needs encoder that senses rotor position. Gut in a certain application, the position sensor has to be avoided. In the paper, various position sensorless drive systems for BDCM are investigated and critically evaluated, so that the effective method of sensorless control can be selected. Out of these methods, the freewheeling diode current sensing has many advantages. For example, the simple starting procedure makes it possible to perform sensorless control even in low speed. So the hardware design for this method has been carried out and the system has been implemented using DSP. The experimental results verified that the freewheeling diode current sensing approach has advantages in starting procedure and low speed sensing.

• International Journal of Safety
• /
• v.7 no.2
• /
• pp.17-22
• /
• 2008

Recent developments in contactless, air-coupled sensing of seismic and ultrasonic waves in concrete structures are presented. Contactless sensing allows for rapid, efficient and consistent data collection over a large volume of material. Two inspection applications are discussed: air-coupled impact-echo scanning of concrete structures using seismically generated waves, and air-coupled imaging of internal damages in concrete using ultrasonic tomography. The first application aims to locate and characterize shallow delamination defects within concrete bridge decks. Impact-echo method is applied to scan defected concrete slabs using air coupled sensors. Next, efforts to apply air-coupled ultrasonic tomography to concrete damage imaging are discussed. Preliminary results are presented for air-coupled ultrasonic tomography applied to solid elements to locate internal defects. The results demonstrate that, with continued development, air-coupled ultrasonic tomography may provide improved evaluation of unseen material defects within structures.

• Korean Journal of Remote Sensing
• /
• v.5 no.2
• /
• pp.91-107
• /
• 1989

The purpose of this study is to investigate ways to use Landsat TM data for geological mapping and minieralized area detection. The study was carried out in Kyongju-Pohang area where toseki and bentonite mines are distributed. Rock samples of 18 granites, andesites, toseki, betonites, sedimentary rocks and altered rocks in the study area were collected for the study. The radiometric measurtment of the rock samples were carried out with a radiometer in the laboratory and in the field. The Landsat TM bands 2,3,4,5,7 were used for the measurement. The radiometric characteristics of the sample were mainly processed by the principal component analysis. It was found that the pricipal component analysis of the radiometric characteristics of geologic materials is very useful for the detection of the alteration of rocks and grade of mineral contents. It is expected that the technique can be used in the future for the efficient exploration of minerals in this country and abroad.

• Korean Journal of Remote Sensing
• /
• v.26 no.6
• /
• pp.665-673
• /
• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.