• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.517-523
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• 2019

PM₁₀ concentration is a spatiotemporal phenomenta and capturing data for such continuous phenomena is a difficult task. This study designed a model that enhances spatiotemporal resolution of PM₁₀ concentration levels using satellite imagery, atmospheric and meteorological sensor data, and multiple deep learning models. The designed deep learning model was trained using input data whose factors may affect concentration of PM₁₀ such as meteorological conditions and land-use. Using this model, PM₁₀ images having 15 minute temporal resolution and 30m×30m spatial resolution were produced with only atmospheric and meteorological data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.19-24
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• 1999

This paper addresses a new project being carried out at Satellite Technology Research Center. The purpose of the project is to implement a system which receives, processes and stores 1m resolution satellite image transmitted at over 300Mbps down link data rates. In order to develop such a system, a system operational concept design and a requirements study were being carried out As a result of the operational concept design, system objectives, system context and system functions were defined. The system shall be operated according to the philosophy of maximum automation. rapid processing, reliability, integrity, cost effectiveness, and expandability. The system is divided into twelve independent processes and its behavior is modeled by operational scenario, which are combinations of independent processes. Process information and logs generated by the system shall be stored in databases and data received and generated be automatically archived and managed in a hierarchical storage device. The system shall have redundant components in order to be ready for recovering from sudden system failures. This paper will describe in detail the system operational concept design and the system requirements derived from the operational concept design.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.683-691
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• 2012

High resolution satellite images are now widely used for a variety of mapping applications including photogrammetry, GIS data acquisition and visualization. As the spectral and spatial data size of satellite images increases, a greater processing power is needed to process the images. The solution of these problems is parallel systems. Parallel processing techniques have been developed for improving the performance of image processing along with the development of the computational power. However, conventional CPU-based parallel computing is often not good enough for the demand for computational speed to process the images. The GPU is a good candidate to achieve this goal. Recently GPUs are used in the field of highly complex processing including many loop operations such as mathematical transforms, ray tracing. In this study we proposed a technique for parallel processing of high resolution satellite images using GPU. We implemented a spectral radiometric processing algorithm on Landsat-7 ETM+ imagery using CUDA, a parallel computing architecture developed by NVIDIA for GPU. Also performance of the algorithm on GPU and CPU is compared.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.61-66
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• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1215-1227
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• 2021

Surface reflectance, as a product of the absolute atmospheric correction process of low-orbit satellite imagery, is the basic data required for accurate vegetation analysis. The Commission on Earth Observation Satellite (CEOS) has conducted research and guidance to produce analysis-ready data (ARD) on surface reflectance products for immediate use by users. However, this trend is still in the early stages of research dealing with ARD for high-resolution multispectral images such as KOMPSAT-3A and CAS-500, as it targets medium- to low-resolution satellite images. This study first summarizes the types of distribution of ARD data according to existing cases. The link between Open Data Cube (ODC), the cloud-based satellite image application platforms, and ARD data was also explained. As a result, we present practical ARD deployment steps for high-resolution satellite images and several types of application models in the conceptual level for high-resolution satellite images deployed in ODC and cloud environments. In addition, data pricing policies, accuracy quality issue, platform applicability, cloud environment issues, and international cooperation regarding the proposed implementation and application model were discussed. International organizations related to Earth observation satellites, such as Group on Earth Observations (GEO) and Committee on Earth Observation Satellites (CEOS), are continuing to develop system technologies and standards for the spread of ARD and ODC, and these achievements are expanding to the private sector. Therefore, a satellite-holder country looking for worldwide markets for satellite images must develop a strategy to respond to this international trend.

• Proceedings of the KSRS Conference
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• v.2
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• pp.676-679
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• 2006

Mangrove crowns were delineated using active sensor LIDAR (LIght Detection And Ranging) data by a crown delineating model developed in this study. LIDAR data were acquired from airborne survey by a helicopter for the estuary of Macouria in the northeast coast of French Guiana. The canopy height image was derived from LIDAR vector data by calculating the difference between ground and non-ground data. The mangrove site in the study area was classified to three sectors by the time of mangrove settlement; Mangrove 1986, 2002 and 2003. The estimated crown of Mangrove 1986 was reliable defined for their size, number and volume because of larger crown size and bigger variation of crown height. The tree crown size of Mangrove 2002 and 2003 by the model was overestimated and the number of trees was much underestimated. The estimated crown was not for single crown but a crown group due to homogenous crown height and spatial resolution of LIDAR data. However the canopy height image derived from LIDAR data provided three-dimensional information of mangroves.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.47-55
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• 2002

Remote sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation./sup 1)/ EOC (Electro -Optical Camera) sensor loaded on the KOMPSAT-1 (Korea Multi- Purpose Satellite-1) performs the earth remote sensing operation. EOC can get high-resolution images of ground distance 6.6m during photographing; it is possible to get a tilt image by tilting satellite body up to 45 degrees at maximum. Accordingly, the device developed in this study enables to obtain images by photographing one pair of tilt image for the same point from two different planes. KOMPSAT-1 aims to obtain a Korean map with a scale of 1:25,000 with high resolution. The KOMPSAT-1 developed automated feature extraction system based on stereo satellite image. It overcomes the limitations of sensor and difficulties associated with preprocessing quite effectively. In case of using 6, 7 and 9 ground control points, which are evenly spread in image, with 95% of reliability for horizontal and vertical position, 3-dimensional positioning was available with accuracy of 6.0752m and 9.8274m. Therefore, less than l0m of design accuracy in KOMPSAT-1 was achieved. Also the ground position error of ortho-image, with reliability of 95%, is 17.568m. And elevation error showing 36.82m was enhanced. The reason why elevation accuracy was not good compared with the positioning accuracy used stereo image was analyzed as a problem of image matching system. Ortho-image system is advantageous if accurate altitude and production of digital elevation model are desired. The Korean map drawn on a scale of 1: 25,000 by using the new technique of KOMPSAT-1 EOC image adopted in the present study produces accurate result compared to existing mapping techniques involving high costs with less efficiency.

• Proceedings of the KSRS Conference
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• v.2
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• pp.816-819
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• 2006

One of the most difficult parameters to measure in the sea is current speed and direction. Recently, efforts are being made to estimate the ocean current vectors by utilizing sequential satellite imageries. In this study, we attempted to estimated sea surface current vector (sscv) by using satellite ocean color imageries of SeaWifs around the Korean Peninsula. This ocean color image data has 1-day sampling interval and spatial resolution of 1x1 km. Maximum cross-correlation method is employed which is aimed to detect similar patterns between sequential images. The estimated current vectors are compared to the surface geostrophic current vectors obtained from altimeter of sea level height data. In utilizing the color imagery data, some limitations and drawbacks exist so that in warm water region where phytoplankton concentration is relatively lower than in cold water region, estimation of sscv is poor and unreliable. On the other hand, two current vector fields agree reasonably well in the Korean South Sea region where high concentration of chlorophyll-a and weak tide is observed. In the future, with ocean color images of shorter sampling interval by COMS satellite, the algorithm and methodology developed in the study would be useful in providing the information for the ocean current around Korean Peninsula.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.