• Journal of Korea Multimedia Society
• /
• v.19 no.4
• /
• pp.725-735
• /
• 2016

High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.

• Journal of the Korean Geographical Society
• /
• v.43 no.5
• /
• pp.761-774
• /
• 2008

Integration of GIS data and human expert knowledge into digital image processing has long been acknowledged as a necessity to improve remote sensing image analysis. We propose inductive machine learning algorithm for GIS data integration and rule-based classification method for land cover classification. Proposed method is tested with a land cover classification of a Landsat ETM+ multispectral image and GIS data layers including elevation, aspect, slope, distance to water bodies, distance to road network, and population density. Decision trees and production rules for land cover classification are generated by C5.0 inductive machine learning algorithm with 350 stratified random point samples. Production rules are used for land cover classification integrated with unsupervised ISODATA classification. Result shows that GIS data layers such as elevation, distance to water bodies and population density can be effectively integrated for rule-based image classification. Intuitive production rules generated by inductive machine learning are easy to understand. Proposed method demonstrates how various GIS data layers can be integrated with remotely sensed imagery in a framework of knowledge base construction to improve land cover classification.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.238-242
• /
• 2007

Today's commercial high resolution satellite imagery such as that provided by IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Digital maps supply the most generally used GIS data probiding topography, road, and building information. Currently, the building information provided by digital maps is incompletely constructed for GIS applications due to planar position error and warped shape. We focus on extracting of the accurate building information including position, shape, and height to update the building information of the digital maps and GIS database. In this paper, we propose a new method of 3D building information extraction with a single high resolution satellite image and digital map. Co-registration between the QuickBird image and the 1:1,000 digital maps was carried out automatically using the RPC adjustment model and the building layer of the digital map was projected onto the image. The building roof boundaries were detected using the building layer from the digital map based on the satellite azimuth. The building shape could be modified using a snake algorithm. Then we measured the building height and traced the building bottom automatically using triangular vector structure (TVS) hypothesis. In order to evaluate the proposed method, we estimated accuracy of the extracted building information using LiDAR DSM.

• Journal of Environmental Impact Assessment
• /
• v.19 no.4
• /
• pp.397-407
• /
• 2010

The increase of the solar reradiation from urban areas relative to suburban due to urbanization heats up the air temperature in urban areas and this is called the urban heat island (UHI) effect. This UHI effect has a positive relationship with the degree of urbanization. Through the studies on UHI using the satellite imagery, the effect of the surface heat radiation was observed by verifying the relationship between the air temperature and the land cover types (surface materials such as urban, vegetation, etc.). In this study, however, the surface temperature distribution was studied in terms of land use types for Seoul. Using land use types, the surface temperature in urban areas such as residential, industrial, and commercial areas in Yeongdeungpo, highly packed with industrial and residential buildings, was maximum $6^{\circ}C$ higher than in the bare ground, which indicated that the surface temperature reflected the pattern of the human-consumed energy on the areas and showed that one of the important causes influencing the air temperature except the surface heat reradiation by the sun is the anthropogenic heat. Also, the effect due to the restoration of the Chunggae stream on UHI was investigated. The average surface temperature for the Chunggae stream was reduced about $0.4^{\circ}C$ after restoration. Considering that each satellite image pixel includes mixture of several materials such as concrete and asphalt, the average surface temperature might be much lower locally reducing UHI near the stream.

• Journal of the Korean Geographical Society
• /
• v.45 no.5
• /
• pp.573-591
• /
• 2010

In this study, trends of heat waves in the populous Seoul metropolitan area over the last 100 years (1908-2007) and spatio-temporal patterns of extreme heat waves and excessive human mortality are examined. In spite of recent global warming, there is no observable increasing or decreasing pattern in the frequency and intensity of heat waves in Seoul due to increases of summer precipitation. Among numerous episodes over the last 100 years in Seoul, 1994 summer is recognized as the unprecedented, most extreme hot episode with long-lasting, intense heat waves Meteorological data observed at the Automatic Weather Stations (AWS) and land surface temperature data derived from Landsat TM satellite imagery in July 1994 reveal that extreme heat waves cause more abnormal increase of elderly mortality in the urbanized areas than in the surroundings covered with more vegetation. This study provides bioclimatological evidences of why urban thermal environments should be seriously considered in the future urban revitalization planning.

• Journal of Korean Society for Geospatial Information Science
• /
• v.16 no.3
• /
• pp.15-20
• /
• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.3 no.4
• /
• pp.33-49
• /
• 2000

This research demonstrates the application of GIS to the selection of the waste landfill site through the case study of a urban area. The estimation factors for the suitability analysis of the waste landfill site were determined. The database was built through collection, input, and transformation of data. The recent land cover classification data and NDVI data which were obtained through processing of satellite imagery were incorporated into GIS data as estimation factors. The relative weights of importance among 2nd category estimation factors were determined by the pairwise comparison method. Also relative weights of 1st category estimation factors which are divided into the social-economical factor and the natural environmental factor were combined with those of 2nd category estimation factors. As the results of this case study, the suitability analysis was conducted in accordance with various estimation criteria. The highest suitability index was obtained in the case where we considered the relative weights of 2nd category estimation factors as different in the viewpoint which regards the social economical factor as important.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.7 no.4
• /
• pp.46-56
• /
• 2004

As economic cooperation and exchanges between North and South Korea have been glowing much more than before, the demand for geographic information on North Korea is recently increasing. In fact, there is no specific method to be provided with geographic information on North Korea. In this regard, the study searched a method to collect geographic information on North Korea by using the high spatial resolution satellite image. In order to produce its best result, the study collected the geographic information on the case study area and ensured the location accuracy. This study produced total 52 items of geographic information on North Korea. Horizontal and vertical errors of stereo image, which are 4.6m and 0.9m respectively, showed high accuracy. In addition, even though the horizontal error of single image is 9m, which is bigger than that of stereo image, there is no doubt that it can be used as basic data for North Korean studies and related projects.

• Spatial Information Research
• /
• v.23 no.2
• /
• pp.31-38
• /
• 2015

Remote sensing data is used to increasing efficiency on benthic cover type survey. Satellite and aerial imagery has variance of reflectance by water column effect even if bottom is consisted with same cover type and condition. This study tried to analyze advances of surveying extent and accuracy through water column correction of CASI-1500 hyperspectral image. Study area is coast of Gangneung city, South Korea where benthic environment is rapidly changing with bleaching of coral reef. Water column correction coefficient was estimated using regression models between water reflectance ($R_W$) and depth for sand bottom then the coefficients were applied to whole image. The results shows that expanded interpretable depth from 6-7m to 15m and decreased variation of reflectance by depth. Additionally, water column corrected reflectance image shows 13%p increased accuracy on benthic cover type classification.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.3
• /
• pp.137-147
• /
• 2012

Recently, floating green algae (FGA) in open oceans and coastal waters have been reported over wide area, yet accurate detection of these using traditional ground based measurement and chemical analysis in the laboratory has been difficult or even impossible due to the lack of spatial resolution, coverage, and revisit frequency. In contrast, spectral reflectance measurement makes it possible to quickly assess the chlorophyll content in green algae. Our objectives are to investigate the spectral reflectance of the FGA observed in the Yellow Sea and to develop a new index to detect FGA from satellite imagery, namely floating green algae index (FGAI), which uses relatively simple reflectance ratio technique. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Ocean Color Imager (GOCI) satellite images at 500m spatial resolution were utilized to produce FGAI which is defined as the ratio between reflectance at 860nm and 660nm bands. Both FGAI results yielded reasonable green algae detection at the regional scale distribution. Especially houly GOCI observations can present more detaield information of FGAI than low-orbit satellite.