• 한국공간정보시스템학회:학술대회논문집
• /
• 2000.06a
• /
• pp.67-76
• /
• 2000

Recently, SAR Interferometry method is actively being studied as a new technic in topographic mapping using satellite imageries. it extract height values using two SAR imageries covering same areas. Unlike when using SPOT imageries, it isn't affected by atmospheric conditions and time. But it is difficult to process radar imageries and the height accuracy is very low where relief displacements are high. In this study, we produced DEM(Digital Elevation Model) using ERS-1, ERS-2 tandem data and analysed the height accuracy over 14 ground control points. The mean error in height was 14.06m. But when using airborne SAR data, it Is expected that we can produce more accurate DEM which will be able to ue used in updating 1/10,000 or 1/25,000 map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.2
• /
• pp.181-188
• /
• 2012

The most recent, Digital photogrammetric camera, Airborne LiDAR and GPS/INS same sensors are used to acquire spatial information of various kinds in the field of aerial survey. In addition, Direct Georeferencing technology has been widely utilized with digital photogrammetric camera and GPS/INS. However, the sensor Calibration to be performed according to the combination of various sensors is followed by problems. Most of all, boresight calibration of integrated sensors is a critical element in the mapping process when using direct georeferencing or using the GPS/INS aerotriangulation. The establishment of a national test-bed in Sejong-si for aerial sensor calibration is absolutely necessary to solve this problem. And accurate calibration with used to integration of GPS/INS by aerotriangulation of aerial imagery was necessary for determination of system parameters, evaluation of systematic errors. Also, an investigation of efficient method for Direct georeferencing to determine the exterior orientation parameters and assessment of geometric accuracy of integrated sensors are performed.

• 한국지형공간정보학회:학술대회논문집
• /
• 2002.11a
• /
• pp.73-80
• /
• 2002

RFM is believed to be universally applicable to any type of the sensor. Most of researches carried out lately are concentrated on terrain-independent method, but the researches about approvement of accuracy by way of terrain-dependent method are required to increase a practical use of satellite imagery in nonprofessional groups. This research focused on a means to improve RFM solution, a matching technique, and a generation of DEM through a correlation analysis, with terrain-dependent solution. The result shows that accuracy problem which is caused by over-parameterization on RFCs was removed through correlation analysis, and it was possible to generate a accurate DEM with terrain-dependent solution. And also, the application of RFM with different satellite images show sensor independent characteristics of RFM

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.5
• /
• pp.28-34
• /
• 2007

A histogram-based road border line extractor is proposed for an efficient road extraction from the high-resolution satellite imagery. The road border lines are extracted from an edge strength map based on the directional histogram difference between the road and the non-road region. The straight and the curved roads are extracted hierarchically from the edge strength map of the original image and the segmented road cluster images, and the road network is constructed based on the connectivity. Unlike the conventional approaches based on the spectral similarity, the proposed road extraction method is more robust to noise because it extracts roads based on the histogram, and is able to extract both the location and the width of roads. In addition, the proposed method can extract roads with various spectral characteristics by identifying the road clusters automatically. Experimental results on IKONOS multi-spectral satellite imagery with high spatial resolution show that the proposed method can extract the straight and the curved roads as well as the accurate road border lines.

• The KIPS Transactions:PartB
• /
• v.15B no.6
• /
• pp.553-560
• /
• 2008

The amount of image data used in medical institution is increasing rapidly with great development of medical technology. Therefore, an automation method that use image processing description, rather than manual macrography of doctors, is required for the analysis large medical data. Specially, medical image registration, which is the process of finding the spatial transform that maps points from one image to the corresponding points in another image, and 3D analysis and visualization skills for a series of 2D images are essential technologies. However, a high establishment cost raise a budget problem, and hence small scaled hospitals hesitate importing these medical visualizing system. In this paper, we propose a visualization system which allows user to manage datasets and manipulates medical images registration using an open source graphics tool - VTK(Visualization Tool Kit). The propose of our research is to get more accurate 3D diagnosis system in less expensive price, compared to existing systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.7
• /
• pp.805-814
• /
• 2010

The Crank-Nicolson isotropic-dispersion finite difference time domain(CN ID-FDTD) scheme is proposed based on isotropic-dispersion finite difference(ID-FD) $equation^{[1],[2]}$. The dispersion relation of CN ID-FDTD is derived for lossy media by solving the eigenvalue problem of iteration matrix in spatial spectral domain, in addition, the weighting factors and scaling factors of the CN ID-FDTD scheme are presented for low dispersion error. The CN ID-FDTD scheme makes the dispersion error drastically reduced and shows accurate numerical results compared to the conventional Crank-Nicolson FDTD method.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1215-1220
• /
• 2003

People's Republic of China is one of the most rapidly developing countries in the world today. There is a great demand on highly actual and accurate spatial information of the whole country, especially of West China which becomes the focus of development of the Chinese government right now and in the next years, but where still not enough topographic maps are available. This raises great challenges to the surveying and mapping community in China. Facing the new challenges the Chinese Academy of Surveying and Mapping (CASM) started its pioneer work early 2002 to explore new techniques and technologies available today toward increasing the map productivity. With import of a CCNS/AEROcontrol system in November 2002 the first DGPS/IMU-based photogrammetric project in China was successfully accomplished jointly by CASM and the Germany-based companies IGI and Techedge. Two photogrammetric blocks of 1:4,000 and 1:20,000 photo scale, respectively, were flown in Anyang, China. Direct georeferencing and integrated sensor orientation were conducted. Results achieved were proven by using ground check points and compared with those of aerial triangulation. Orthophotos generated based on direct georeferencing shows the high efficiency and quality, and thus proved the promise of the new technology. Furthermore several DGPS/IMU-based photogammetric projects was accomplished one by one and a big project of more than 100,000 km2 in the Inner Mongolia will be started in August 2003. The paper presents experiences with DGPS/IMU-based photogrammetry in China. Results achieved in concrete projects are shown and evaluated. Politic and technical specialties in China are discussed. Conclusions outline the potential of DGPS/IMU-based photogrammetric production in China.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_2
• /
• pp.1239-1249
• /
• 2018

Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.3
• /
• pp.1-14
• /
• 2019

North Korea has frequently suffered from extreme agricultural crop droughts, which have led to food shortages, according to the Food and Agriculture Organization (FAO). The increasing frequency of extreme droughts, due to global warming and climate change, has increased the importance of enhancing the national capacity for drought management. Historically, a meteorological drought index based on data collected from weather stations has been widely used. But it has limitations in terms of the distribution of weather stations and the spatial pattern of drought impacts. Satellite-based data can be obtained with the same accuracy and at regular intervals, and is useful for long-term change analysis and environmental monitoring and wide area access in time and space. The Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used to detect drought response as a index of the droughts occurring rapidly over short periods of time. It is more accurate and provides faster analysis of drought conditions compared to the Standardized Precipitation Index (SPI), and the Palmer Drought Severity Index (PDSI). In this study, we analyze drought events during 2015-2017 in North Korea using the ESI satellite-based drought index to determine drought response by comparing with it with the SPI and SPEI drought indices.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.3
• /
• pp.147-157
• /
• 2022

Recently, many studies have been conducted to analyze traffic or object recognition that classifies vehicles through artificial intelligence-based prediction models using CCTV (Closed Circuit TeleVision)or drone images. In order to develop an object recognition deep learning model for accurate traffic estimation, systematic data construction is required, and related standardized guidelines are insufficient. In this study, previous studies were analyzed to derive guidelines for establishing artificial intelligence-based training data for traffic estimation using drone images, and business reports or training data for artificial intelligence and quality management guidelines were referenced. The guidelines for data construction are divided into data acquisition, preprocessing, and validation, and guidelines for notice and evaluation index for each item are presented. The guidelines for data construction aims to provide assistance in the development of a robust and generalized artificial intelligence model in analyzing the estimation of road traffic based on drone image artificial intelligence.